U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

  • Advanced Search
  • Journal List
  • Front Psychol

Effects of Social Media Use on Psychological Well-Being: A Mediated Model

Dragana ostic.

1 School of Finance and Economics, Jiangsu University, Zhenjiang, China

Sikandar Ali Qalati

Belem barbosa.

2 Research Unit of Governance, Competitiveness, and Public Policies (GOVCOPP), Center for Economics and Finance (cef.up), School of Economics and Management, University of Porto, Porto, Portugal

Syed Mir Muhammad Shah

3 Department of Business Administration, Sukkur Institute of Business Administration (IBA) University, Sukkur, Pakistan

Esthela Galvan Vela

4 CETYS Universidad, Tijuana, Mexico

Ahmed Muhammad Herzallah

5 Department of Business Administration, Al-Quds University, Jerusalem, Israel

6 Business School, Shandong University, Weihai, China

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The growth in social media use has given rise to concerns about the impacts it may have on users' psychological well-being. This paper's main objective is to shed light on the effect of social media use on psychological well-being. Building on contributions from various fields in the literature, it provides a more comprehensive study of the phenomenon by considering a set of mediators, including social capital types (i.e., bonding social capital and bridging social capital), social isolation, and smartphone addiction. The paper includes a quantitative study of 940 social media users from Mexico, using structural equation modeling (SEM) to test the proposed hypotheses. The findings point to an overall positive indirect impact of social media usage on psychological well-being, mainly due to the positive effect of bonding and bridging social capital. The empirical model's explanatory power is 45.1%. This paper provides empirical evidence and robust statistical analysis that demonstrates both positive and negative effects coexist, helping to reconcile the inconsistencies found so far in the literature.

Introduction

The use of social media has grown substantially in recent years (Leong et al., 2019 ; Kemp, 2020 ). Social media refers to “the websites and online tools that facilitate interactions between users by providing them opportunities to share information, opinions, and interest” (Swar and Hameed, 2017 , p. 141). Individuals use social media for many reasons, including entertainment, communication, and searching for information. Notably, adolescents and young adults are spending an increasing amount of time on online networking sites, e-games, texting, and other social media (Twenge and Campbell, 2019 ). In fact, some authors (e.g., Dhir et al., 2018 ; Tateno et al., 2019 ) have suggested that social media has altered the forms of group interaction and its users' individual and collective behavior around the world.

Consequently, there are increased concerns regarding the possible negative impacts associated with social media usage addiction (Swar and Hameed, 2017 ; Kircaburun et al., 2020 ), particularly on psychological well-being (Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ). Smartphones sometimes distract their users from relationships and social interaction (Chotpitayasunondh and Douglas, 2016 ; Li et al., 2020a ), and several authors have stressed that the excessive use of social media may lead to smartphone addiction (Swar and Hameed, 2017 ; Leong et al., 2019 ), primarily because of the fear of missing out (Reer et al., 2019 ; Roberts and David, 2020 ). Social media usage has been associated with anxiety, loneliness, and depression (Dhir et al., 2018 ; Reer et al., 2019 ), social isolation (Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ), and “phubbing,” which refers to the extent to which an individual uses, or is distracted by, their smartphone during face-to-face communication with others (Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ).

However, social media use also contributes to building a sense of connectedness with relevant others (Twenge and Campbell, 2019 ), which may reduce social isolation. Indeed, social media provides several ways to interact both with close ties, such as family, friends, and relatives, and weak ties, including coworkers, acquaintances, and strangers (Chen and Li, 2017 ), and plays a key role among people of all ages as they exploit their sense of belonging in different communities (Roberts and David, 2020 ). Consequently, despite the fears regarding the possible negative impacts of social media usage on well-being, there is also an increasing number of studies highlighting social media as a new communication channel (Twenge and Campbell, 2019 ; Barbosa et al., 2020 ), stressing that it can play a crucial role in developing one's presence, identity, and reputation, thus facilitating social interaction, forming and maintaining relationships, and sharing ideas (Carlson et al., 2016 ), which consequently may be significantly correlated to social support (Chen and Li, 2017 ; Holliman et al., 2021 ). Interestingly, recent studies (e.g., David et al., 2018 ; Bano et al., 2019 ; Barbosa et al., 2020 ) have suggested that the impact of smartphone usage on psychological well-being depends on the time spent on each type of application and the activities that users engage in.

Hence, the literature provides contradictory cues regarding the impacts of social media on users' well-being, highlighting both the possible negative impacts and the social enhancement it can potentially provide. In line with views on the need to further investigate social media usage (Karikari et al., 2017 ), particularly regarding its societal implications (Jiao et al., 2017 ), this paper argues that there is an urgent need to further understand the impact of the time spent on social media on users' psychological well-being, namely by considering other variables that mediate and further explain this effect.

One of the relevant perspectives worth considering is that provided by social capital theory, which is adopted in this paper. Social capital theory has previously been used to study how social media usage affects psychological well-being (e.g., Bano et al., 2019 ). However, extant literature has so far presented only partial models of associations that, although statistically acceptable and contributing to the understanding of the scope of social networks, do not provide as comprehensive a vision of the phenomenon as that proposed within this paper. Furthermore, the contradictory views, suggesting both negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Van Den Eijnden et al., 2016 ; Jiao et al., 2017 ; Whaite et al., 2018 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) and positive impacts (Carlson et al., 2016 ; Chen and Li, 2017 ; Twenge and Campbell, 2019 ) of social media on psychological well-being, have not been adequately explored.

Given this research gap, this paper's main objective is to shed light on the effect of social media use on psychological well-being. As explained in detail in the next section, this paper explores the mediating effect of bonding and bridging social capital. To provide a broad view of the phenomenon, it also considers several variables highlighted in the literature as affecting the relationship between social media usage and psychological well-being, namely smartphone addiction, social isolation, and phubbing. The paper utilizes a quantitative study conducted in Mexico, comprising 940 social media users, and uses structural equation modeling (SEM) to test a set of research hypotheses.

This article provides several contributions. First, it adds to existing literature regarding the effect of social media use on psychological well-being and explores the contradictory indications provided by different approaches. Second, it proposes a conceptual model that integrates complementary perspectives on the direct and indirect effects of social media use. Third, it offers empirical evidence and robust statistical analysis that demonstrates that both positive and negative effects coexist, helping resolve the inconsistencies found so far in the literature. Finally, this paper provides insights on how to help reduce the potential negative effects of social media use, as it demonstrates that, through bridging and bonding social capital, social media usage positively impacts psychological well-being. Overall, the article offers valuable insights for academics, practitioners, and society in general.

The remainder of this paper is organized as follows. Section Literature Review presents a literature review focusing on the factors that explain the impact of social media usage on psychological well-being. Based on the literature review, a set of hypotheses are defined, resulting in the proposed conceptual model, which includes both the direct and indirect effects of social media usage on psychological well-being. Section Research Methodology explains the methodological procedures of the research, followed by the presentation and discussion of the study's results in section Results. Section Discussion is dedicated to the conclusions and includes implications, limitations, and suggestions for future research.

Literature Review

Putnam ( 1995 , p. 664–665) defined social capital as “features of social life – networks, norms, and trust – that enable participants to act together more effectively to pursue shared objectives.” Li and Chen ( 2014 , p. 117) further explained that social capital encompasses “resources embedded in one's social network, which can be assessed and used for instrumental or expressive returns such as mutual support, reciprocity, and cooperation.”

Putnam ( 1995 , 2000 ) conceptualized social capital as comprising two dimensions, bridging and bonding, considering the different norms and networks in which they occur. Bridging social capital refers to the inclusive nature of social interaction and occurs when individuals from different origins establish connections through social networks. Hence, bridging social capital is typically provided by heterogeneous weak ties (Li and Chen, 2014 ). This dimension widens individual social horizons and perspectives and provides extended access to resources and information. Bonding social capital refers to the social and emotional support each individual receives from his or her social networks, particularly from close ties (e.g., family and friends).

Overall, social capital is expected to be positively associated with psychological well-being (Bano et al., 2019 ). Indeed, Williams ( 2006 ) stressed that interaction generates affective connections, resulting in positive impacts, such as emotional support. The following sub-sections use the lens of social capital theory to explore further the relationship between the use of social media and psychological well-being.

Social Media Use, Social Capital, and Psychological Well-Being

The effects of social media usage on social capital have gained increasing scholarly attention, and recent studies have highlighted a positive relationship between social media use and social capital (Brown and Michinov, 2019 ; Tefertiller et al., 2020 ). Li and Chen ( 2014 ) hypothesized that the intensity of Facebook use by Chinese international students in the United States was positively related to social capital forms. A longitudinal survey based on the quota sampling approach illustrated the positive effects of social media use on the two social capital dimensions (Chen and Li, 2017 ). Abbas and Mesch ( 2018 ) argued that, as Facebook usage increases, it will also increase users' social capital. Karikari et al. ( 2017 ) also found positive effects of social media use on social capital. Similarly, Pang ( 2018 ) studied Chinese students residing in Germany and found positive effects of social networking sites' use on social capital, which, in turn, was positively associated with psychological well-being. Bano et al. ( 2019 ) analyzed the 266 students' data and found positive effects of WhatsApp use on social capital forms and the positive effect of social capital on psychological well-being, emphasizing the role of social integration in mediating this positive effect.

Kim and Kim ( 2017 ) stressed the importance of having a heterogeneous network of contacts, which ultimately enhances the potential social capital. Overall, the manifest and social relations between people from close social circles (bonding social capital) and from distant social circles (bridging social capital) are strengthened when they promote communication, social support, and the sharing of interests, knowledge, and skills, which are shared with other members. This is linked to positive effects on interactions, such as acceptance, trust, and reciprocity, which are related to the individuals' health and psychological well-being (Bekalu et al., 2019 ), including when social media helps to maintain social capital between social circles that exist outside of virtual communities (Ellison et al., 2007 ).

Grounded on the above literature, this study proposes the following hypotheses:

  • H1a: Social media use is positively associated with bonding social capital.
  • H1b: Bonding social capital is positively associated with psychological well-being.
  • H2a: Social media use is positively associated with bridging social capital.
  • H2b: Bridging social capital is positively associated with psychological well-being.

Social Media Use, Social Isolation, and Psychological Well-Being

Social isolation is defined as “a deficit of personal relationships or being excluded from social networks” (Choi and Noh, 2019 , p. 4). The state that occurs when an individual lacks true engagement with others, a sense of social belonging, and a satisfying relationship is related to increased mortality and morbidity (Primack et al., 2017 ). Those who experience social isolation are deprived of social relationships and lack contact with others or involvement in social activities (Schinka et al., 2012 ). Social media usage has been associated with anxiety, loneliness, and depression (Dhir et al., 2018 ; Reer et al., 2019 ), and social isolation (Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ). However, some recent studies have argued that social media use decreases social isolation (Primack et al., 2017 ; Meshi et al., 2020 ). Indeed, the increased use of social media platforms such as Facebook, WhatsApp, Instagram, and Twitter, among others, may provide opportunities for decreasing social isolation. For instance, the improved interpersonal connectivity achieved via videos and images on social media helps users evidence intimacy, attenuating social isolation (Whaite et al., 2018 ).

Chappell and Badger ( 1989 ) stated that social isolation leads to decreased psychological well-being, while Choi and Noh ( 2019 ) concluded that greater social isolation is linked to increased suicide risk. Schinka et al. ( 2012 ) further argued that, when individuals experience social isolation from siblings, friends, family, or society, their psychological well-being tends to decrease. Thus, based on the literature cited above, this study proposes the following hypotheses:

  • H3a: Social media use is significantly associated with social isolation.
  • H3b: Social isolation is negatively associated with psychological well-being.

Social Media Use, Smartphone Addiction, Phubbing, and Psychological Well-Being

Smartphone addiction refers to “an individuals' excessive use of a smartphone and its negative effects on his/her life as a result of his/her inability to control his behavior” (Gökçearslan et al., 2018 , p. 48). Regardless of its form, smartphone addiction results in social, medical, and psychological harm to people by limiting their ability to make their own choices (Chotpitayasunondh and Douglas, 2016 ). The rapid advancement of information and communication technologies has led to the concept of social media, e-games, and also to smartphone addiction (Chatterjee, 2020 ). The excessive use of smartphones for social media use, entertainment (watching videos, listening to music), and playing e-games is more common amongst people addicted to smartphones (Jeong et al., 2016 ). In fact, previous studies have evidenced the relationship between social use and smartphone addiction (Salehan and Negahban, 2013 ; Jeong et al., 2016 ; Swar and Hameed, 2017 ). In line with this, the following hypotheses are proposed:

  • H4a: Social media use is positively associated with smartphone addiction.
  • H4b: Smartphone addiction is negatively associated with psychological well-being.

While smartphones are bringing individuals closer, they are also, to some extent, pulling people apart (Tonacci et al., 2019 ). For instance, they can lead to individuals ignoring others with whom they have close ties or physical interactions; this situation normally occurs due to extreme smartphone use (i.e., at the dinner table, in meetings, at get-togethers and parties, and in other daily activities). This act of ignoring others is called phubbing and is considered a common phenomenon in communication activities (Guazzini et al., 2019 ; Chatterjee, 2020 ). Phubbing is also referred to as an act of snubbing others (Chatterjee, 2020 ). This term was initially used in May 2012 by an Australian advertising agency to describe the “growing phenomenon of individuals ignoring their families and friends who were called phubbee (a person who is a recipients of phubbing behavior) victim of phubber (a person who start phubbing her or his companion)” (Chotpitayasunondh and Douglas, 2018 ). Smartphone addiction has been found to be a determinant of phubbing (Kim et al., 2018 ). Other recent studies have also evidenced the association between smartphones and phubbing (Chotpitayasunondh and Douglas, 2016 ; Guazzini et al., 2019 ; Tonacci et al., 2019 ; Chatterjee, 2020 ). Vallespín et al. ( 2017 ) argued that phubbing behavior has a negative influence on psychological well-being and satisfaction. Furthermore, smartphone addiction is considered responsible for the development of new technologies. It may also negatively influence individual's psychological proximity (Chatterjee, 2020 ). Therefore, based on the above discussion and calls for the association between phubbing and psychological well-being to be further explored, this study proposes the following hypotheses:

  • H5: Smartphone addiction is positively associated with phubbing.
  • H6: Phubbing is negatively associated with psychological well-being.

Indirect Relationship Between Social Media Use and Psychological Well-Being

Beyond the direct hypotheses proposed above, this study investigates the indirect effects of social media use on psychological well-being mediated by social capital forms, social isolation, and phubbing. As described above, most prior studies have focused on the direct influence of social media use on social capital forms, social isolation, smartphone addiction, and phubbing, as well as the direct impact of social capital forms, social isolation, smartphone addiction, and phubbing on psychological well-being. Very few studies, however, have focused on and evidenced the mediating role of social capital forms, social isolation, smartphone addiction, and phubbing derived from social media use in improving psychological well-being (Chen and Li, 2017 ; Pang, 2018 ; Bano et al., 2019 ; Choi and Noh, 2019 ). Moreover, little is known about smartphone addiction's mediating role between social media use and psychological well-being. Therefore, this study aims to fill this gap in the existing literature by investigating the mediation of social capital forms, social isolation, and smartphone addiction. Further, examining the mediating influence will contribute to a more comprehensive understanding of social media use on psychological well-being via the mediating associations of smartphone addiction and psychological factors. Therefore, based on the above, we propose the following hypotheses (the conceptual model is presented in Figure 1 ):

An external file that holds a picture, illustration, etc.
Object name is fpsyg-12-678766-g0001.jpg

Conceptual model.

  • H7: (a) Bonding social capital; (b) bridging social capital; (c) social isolation; and (d) smartphone addiction mediate the relationship between social media use and psychological well-being.

Research Methodology

Sample procedure and online survey.

This study randomly selected students from universities in Mexico. We chose University students for the following reasons. First, students are considered the most appropriate sample for e-commerce studies, particularly in the social media context (Oghazi et al., 2018 ; Shi et al., 2018 ). Second, University students are considered to be frequent users and addicted to smartphones (Mou et al., 2017 ; Stouthuysen et al., 2018 ). Third, this study ensured that respondents were experienced, well-educated, and possessed sufficient knowledge of the drawbacks of social media and the extreme use of smartphones. A total sample size of 940 University students was ultimately achieved from the 1,500 students contacted, using a convenience random sampling approach, due both to the COVID-19 pandemic and budget and time constraints. Additionally, in order to test the model, a quantitative empirical study was conducted, using an online survey method to collect data. This study used a web-based survey distributed via social media platforms for two reasons: the COVID-19 pandemic; and to reach a large number of respondents (Qalati et al., 2021 ). Furthermore, online surveys are considered a powerful and authenticated tool for new research (Fan et al., 2021 ), while also representing a fast, simple, and less costly approach to collecting data (Dutot and Bergeron, 2016 ).

Data Collection Procedures and Respondent's Information

Data were collected by disseminating a link to the survey by e-mail and social network sites. Before presenting the closed-ended questionnaire, respondents were assured that their participation would remain voluntary, confidential, and anonymous. Data collection occurred from July 2020 to December 2020 (during the pandemic). It should be noted that, because data were collected during the pandemic, this may have had an influence on the results of the study. The reason for choosing a six-month lag time was to mitigate common method bias (CMB) (Li et al., 2020b ). In the present study, 1,500 students were contacted via University e-mail and social applications (Facebook, WhatsApp, and Instagram). We sent a reminder every month for 6 months (a total of six reminders), resulting in 940 valid responses. Thus, 940 (62.6% response rate) responses were used for hypotheses testing.

Table 1 reveals that, of the 940 participants, three-quarters were female (76.4%, n = 719) and nearly one-quarter (23.6%, n = 221) were male. Nearly half of the participants (48.8%, n = 459) were aged between 26 and 35 years, followed by 36 to 35 years (21.9%, n = 206), <26 (20.3%, n = 191), and over 45 (8.9%, n = 84). Approximately two-thirds (65%, n = 611) had a bachelor's degree or above, while one-third had up to 12 years of education. Regarding the daily frequency of using the Internet, nearly half (48.6%, n = 457) of the respondents reported between 5 and 8 h a day, and over one-quarter (27.2%) 9–12 h a day. Regarding the social media platforms used, over 38.5 and 39.6% reported Facebook and WhatsApp, respectively. Of the 940 respondents, only 22.1% reported Instagram (12.8%) and Twitter (9.2%). It should be noted, however, that the sample is predominantly female and well-educated.

Respondents' characteristics.

Measurement Items

The study used five-point Likert scales (1 = “strongly disagree;” 5 = “strongly agree”) to record responses.

Social Media Use

Social media use was assessed using four items adapted from Karikari et al. ( 2017 ). Sample items include “Social media is part of my everyday activity,” “Social media has become part of my daily life,” “I would be sorry if social media shut down,” and “I feel out of touch, when I have not logged onto social media for a while.” The adapted items had robust reliability and validity (CA = 783, CR = 0.857, AVE = 0.600).

Social Capital

Social capital was measured using a total of eight items, representing bonding social capital (four items) and bridging social capital (four items) adapted from Chan ( 2015 ). Sample construct items include: bonging social capital (“I am willing to spend time to support general community activities,” “I interact with people who are quite different from me”) and bridging social capital (“My social media community is a good place to be,” “Interacting with people on social media makes me want to try new things”). The adapted items had robust reliability and validity [bonding social capital (CA = 0.785, CR = 0.861, AVE = 0.608) and bridging social capital (CA = 0.834, CR = 0.883, AVE = 0.601)].

Social Isolation

Social isolation was assessed using three items from Choi and Noh ( 2019 ). Sample items include “I do not have anyone to play with,” “I feel alone from people,” and “I have no one I can trust.” This adapted scale had substantial reliability and validity (CA = 0.890, CR = 0.928, AVE = 0.811).

Smartphone Addiction

Smartphone addiction was assessed using five items taken from Salehan and Negahban ( 2013 ). Sample items include “I am always preoccupied with my mobile,” “Using my mobile phone keeps me relaxed,” and “I am not able to control myself from frequent use of mobile phones.” Again, these adapted items showed substantial reliability and validity (CA = 903, CR = 0.928, AVE = 0.809).

Phubbing was assessed using four items from Chotpitayasunondh and Douglas ( 2018 ). Sample items include: “I have conflicts with others because I am using my phone” and “I would rather pay attention to my phone than talk to others.” This construct also demonstrated significant reliability and validity (CA = 770, CR = 0.894, AVE = 0.809).

Psychological Well-Being

Psychological well-being was assessed using five items from Jiao et al. ( 2017 ). Sample items include “I lead a purposeful and meaningful life with the help of others,” “My social relationships are supportive and rewarding in social media,” and “I am engaged and interested in my daily on social media.” This study evidenced that this adapted scale had substantial reliability and validity (CA = 0.886, CR = 0.917, AVE = 0.688).

Data Analysis

Based on the complexity of the association between the proposed construct and the widespread use and acceptance of SmartPLS 3.0 in several fields (Hair et al., 2019 ), we utilized SEM, using SmartPLS 3.0, to examine the relationships between constructs. Structural equation modeling is a multivariate statistical analysis technique that is used to investigate relationships. Further, it is a combination of factor and multivariate regression analysis, and is employed to explore the relationship between observed and latent constructs.

SmartPLS 3.0 “is a more comprehensive software program with an intuitive graphical user interface to run partial least square SEM analysis, certainly has had a massive impact” (Sarstedt and Cheah, 2019 ). According to Ringle et al. ( 2015 ), this commercial software offers a wide range of algorithmic and modeling options, improved usability, and user-friendly and professional support. Furthermore, Sarstedt and Cheah ( 2019 ) suggested that structural equation models enable the specification of complex interrelationships between observed and latent constructs. Hair et al. ( 2019 ) argued that, in recent years, the number of articles published using partial least squares SEM has increased significantly in contrast to covariance-based SEM. In addition, partial least squares SEM using SmartPLS is more appealing for several scholars as it enables them to predict more complex models with several variables, indicator constructs, and structural paths, instead of imposing distributional assumptions on the data (Hair et al., 2019 ). Therefore, this study utilized the partial least squares SEM approach using SmartPLS 3.0.

Common Method Bias (CMB) Test

This study used the Kaiser–Meyer–Olkin (KMO) test to measure the sampling adequacy and ensure data suitability. The KMO test result was 0.874, which is greater than an acceptable threshold of 0.50 (Ali Qalati et al., 2021 ; Shrestha, 2021 ), and hence considered suitable for explanatory factor analysis. Moreover, Bartlett's test results demonstrated a significance level of 0.001, which is considered good as it is below the accepted threshold of 0.05.

The term CMB is associated with Campbell and Fiske ( 1959 ), who highlighted the importance of CMB and identified that a portion of variance in the research may be due to the methods employed. It occurs when all scales of the study are measured at the same time using a single questionnaire survey (Podsakoff and Organ, 1986 ); subsequently, estimates of the relationship among the variables might be distorted by the impacts of CMB. It is considered a serious issue that has a potential to “jeopardize” the validity of the study findings (Tehseen et al., 2017 ). There are several reasons for CMB: (1) it mainly occurs due to response “tendencies that raters can apply uniformity across the measures;” and (2) it also occurs due to similarities in the wording and structure of the survey items that produce similar results (Jordan and Troth, 2019 ). Harman's single factor test and a full collinearity approach were employed to ensure that the data was free from CMB (Tehseen et al., 2017 ; Jordan and Troth, 2019 ; Ali Qalati et al., 2021 ). Harman's single factor test showed a single factor explained only 22.8% of the total variance, which is far below the 50.0% acceptable threshold (Podsakoff et al., 2003 ).

Additionally, the variance inflation factor (VIF) was used, which is a measure of the amount of multicollinearity in a set of multiple regression constructs and also considered a way of detecting CMB (Hair et al., 2019 ). Hair et al. ( 2019 ) suggested that the acceptable threshold for the VIF is 3.0; as the computed VIFs for the present study ranged from 1.189 to 1.626, CMB is not a key concern (see Table 2 ). Bagozzi et al. ( 1991 ) suggested a correlation-matrix procedure to detect CMB. Common method bias is evident if correlation among the principle constructs is >0.9 (Tehseen et al., 2020 ); however, no values >0.9 were found in this study (see section Assessment of Measurement Model). This study used a two-step approach to evaluate the measurement model and the structural model.

Common method bias (full collinearity VIF).

Assessment of Measurement Model

Before conducting the SEM analysis, the measurement model was assessed to examine individual item reliability, internal consistency, and convergent and discriminant validity. Table 3 exhibits the values of outer loading used to measure an individual item's reliability (Hair et al., 2012 ). Hair et al. ( 2017 ) proposed that the value for each outer loading should be ≥0.7; following this principle, two items of phubbing (PHUB3—I get irritated if others ask me to get off my phone and talk to them; PHUB4—I use my phone even though I know it irritated others) were removed from the analysis Hair et al. ( 2019 ). According to Nunnally ( 1978 ), Cronbach's alpha values should exceed 0.7. The threshold values of constructs in this study ranged from 0.77 to 0.903. Regarding internal consistency, Bagozzi and Yi ( 1988 ) suggested that composite reliability (CR) should be ≥0.7. The coefficient value for CR in this study was between 0.857 and 0.928. Regarding convergent validity, Fornell and Larcker ( 1981 ) suggested that the average variance extracted (AVE) should be ≥0.5. Average variance extracted values in this study were between 0.60 and 0.811. Finally, regarding discriminant validity, according to Fornell and Larcker ( 1981 ), the square root of the AVE for each construct should exceed the inter-correlations of the construct with other model constructs. That was the case in this study, as shown in Table 4 .

Study measures, factor loading, and the constructs' reliability and convergent validity.

Discriminant validity and correlation.

Bold values are the square root of the AVE .

Hence, by analyzing the results of the measurement model, it can be concluded that the data are adequate for structural equation estimation.

Assessment of the Structural Model

This study used the PLS algorithm and a bootstrapping technique with 5,000 bootstraps as proposed by Hair et al. ( 2019 ) to generate the path coefficient values and their level of significance. The coefficient of determination ( R 2 ) is an important measure to assess the structural model and its explanatory power (Henseler et al., 2009 ; Hair et al., 2019 ). Table 5 and Figure 2 reveal that the R 2 value in the present study was 0.451 for psychological well-being, which means that 45.1% of changes in psychological well-being occurred due to social media use, social capital forms (i.e., bonding and bridging), social isolation, smartphone addiction, and phubbing. Cohen ( 1998 ) proposed that R 2 values of 0.60, 0.33, and 0.19 are considered substantial, moderate, and weak. Following Cohen's ( 1998 ) threshold values, this research demonstrates a moderate predicting power for psychological well-being among Mexican respondents ( Table 6 ).

Summary of path coefficients and hypothesis testing.

An external file that holds a picture, illustration, etc.
Object name is fpsyg-12-678766-g0002.jpg

Structural model.

Strength of the model (Predictive relevance, coefficient of determination, and model fit indices).

Goodness of fit → SRMR = 0.063; d_ULS = 1.589; d_G = 0.512; chi-square = 2,910.744 .

Apart from the R 2 measure, the present study also used cross-validated redundancy measures, or effect sizes ( q 2 ), to assess the proposed model and validate the results (Ringle et al., 2012 ). Hair et al. ( 2019 ) suggested that a model exhibiting an effect size q 2 > 0 has predictive relevance ( Table 6 ). This study's results evidenced that it has a 0.15 <0.29 <0.35 (medium) predictive relevance, as 0.02, 0.15, and 0.35 are considered small, medium, and large, respectively (Cohen, 1998 ). Regarding the goodness-of-fit indices, Hair et al. ( 2019 ) suggested the standardized root mean square residual (SRMR) to evaluate the goodness of fit. Standardized root mean square is an absolute measure of fit: a value of zero indicates perfect fit and a value <0.08 is considered good fit (Hair et al., 2019 ). This study exhibits an adequate model fitness level with an SRMR value of 0.063 ( Table 6 ).

Table 5 reveals that all hypotheses of the study were accepted base on the criterion ( p -value < 0.05). H1a (β = 0.332, t = 10.283, p = 0.001) was confirmed, with the second most robust positive and significant relationship (between social media use and bonding social capital). In addition, this study evidenced a positive and significant relationship between bonding social capital and psychological well-being (β = 0.127, t = 4.077, p = 0.001); therefore, H1b was accepted. Regarding social media use and bridging social capital, the present study found the most robust positive and significant impact (β = 0.439, t = 15.543, p = 0.001); therefore, H2a was accepted. The study also evidenced a positive and significant association between bridging social capital and psychological well-being (β = 0.561, t = 20.953, p = 0.001); thus, H2b was accepted. The present study evidenced a significant effect of social media use on social isolation (β = 0.145, t = 4.985, p = 0.001); thus, H3a was accepted. In addition, this study accepted H3b (β = −0.051, t = 2.01, p = 0.044). Furthermore, this study evidenced a positive and significant effect of social media use on smartphone addiction (β = 0.223, t = 6.241, p = 0.001); therefore, H4a was accepted. Furthermore, the present study found that smartphone addiction has a negative significant influence on psychological well-being (β = −0.068, t = 2.387, p = 0.017); therefore, H4b was accepted. Regarding the relationship between smartphone addiction and phubbing, this study found a positive and significant effect of smartphone addiction on phubbing (β = 0.244, t = 7.555, p = 0.001); therefore, H5 was accepted. Furthermore, the present research evidenced a positive and significant influence of phubbing on psychological well-being (β = 0.137, t = 4.938, p = 0.001); therefore, H6 was accepted. Finally, the study provides interesting findings on the indirect effect of social media use on psychological well-being ( t -value > 1.96 and p -value < 0.05); therefore, H7a–d were accepted.

Furthermore, to test the mediating analysis, Preacher and Hayes's ( 2008 ) approach was used. The key characteristic of an indirect relationship is that it involves a third construct, which plays a mediating role in the relationship between the independent and dependent constructs. Logically, the effect of A (independent construct) on C (the dependent construct) is mediated by B (a third variable). Preacher and Hayes ( 2008 ) suggested the following: B is a construct acting as a mediator if A significantly influences B, A significantly accounts for variability in C, B significantly influences C when controlling for A, and the influence of A on C decreases significantly when B is added simultaneously with A as a predictor of C. According to Matthews et al. ( 2018 ), if the indirect effect is significant while the direct insignificant, full mediation has occurred, while if both direct and indirect effects are substantial, partial mediation has occurred. This study evidenced that there is partial mediation in the proposed construct ( Table 5 ). Following Preacher and Hayes ( 2008 ) this study evidenced that there is partial mediation in the proposed construct, because the relationship between independent variable (social media use) and dependent variable (psychological well-being) is significant ( p -value < 0.05) and indirect effect among them after introducing mediator (bonding social capital, bridging social capital, social isolation, and smartphone addiction) is also significant ( p -value < 0.05), therefore it is evidenced that when there is a significant effect both direct and indirect it's called partial mediation.

The present study reveals that the social and psychological impacts of social media use among University students is becoming more complex as there is continuing advancement in technology, offering a range of affordable interaction opportunities. Based on the 940 valid responses collected, all the hypotheses were accepted ( p < 0.05).

H1a finding suggests that social media use is a significant influencing factor of bonding social capital. This implies that, during a pandemic, social media use enables students to continue their close relationships with family members, friends, and those with whom they have close ties. This finding is in line with prior work of Chan ( 2015 ) and Ellison et al. ( 2007 ), who evidenced that social bonding capital is predicted by Facebook use and having a mobile phone. H1b findings suggest that, when individuals believe that social communication can help overcome obstacles to interaction and encourage more virtual self-disclosure, social media use can improve trust and promote the establishment of social associations, thereby enhancing well-being. These findings are in line with those of Gong et al. ( 2021 ), who also witnessed the significant effect of bonding social capital on immigrants' psychological well-being, subsequently calling for the further evidence to confirm the proposed relationship.

The findings of the present study related to H2a suggest that students are more likely to use social media platforms to receive more emotional support, increase their ability to mobilize others, and to build social networks, which leads to social belongingness. Furthermore, the findings suggest that social media platforms enable students to accumulate and maintain bridging social capital; further, online classes can benefit students who feel shy when participating in offline classes. This study supports the previous findings of Chan ( 2015 ) and Karikari et al. ( 2017 ). Notably, the present study is not limited to a single social networking platform, taking instead a holistic view of social media. The H2b findings are consistent with those of Bano et al. ( 2019 ), who also confirmed the link between bonding social capital and psychological well-being among University students using WhatsApp as social media platform, as well as those of Chen and Li ( 2017 ).

The H3a findings suggest that, during the COVID-19 pandemic when most people around the world have had limited offline or face-to-face interaction and have used social media to connect with families, friends, and social communities, they have often been unable to connect with them. This is due to many individuals avoiding using social media because of fake news, financial constraints, and a lack of trust in social media; thus, the lack both of offline and online interaction, coupled with negative experiences on social media use, enhances the level of social isolation (Hajek and König, 2021 ). These findings are consistent with those of Adnan and Anwar ( 2020 ). The H3b suggests that higher levels of social isolation have a negative impact on psychological well-being. These result indicating that, consistent with Choi and Noh ( 2019 ), social isolation is negatively and significantly related to psychological well-being.

The H4a results suggests that substantial use of social media use leads to an increase in smartphone addiction. These findings are in line with those of Jeong et al. ( 2016 ), who stated that the excessive use of smartphones for social media, entertainment (watching videos, listening to music), and playing e-games was more likely to lead to smartphone addiction. These findings also confirm the previous work of Jeong et al. ( 2016 ), Salehan and Negahban ( 2013 ), and Swar and Hameed ( 2017 ). The H4b results revealed that a single unit increase in smartphone addiction results in a 6.8% decrease in psychological well-being. These findings are in line with those of Tangmunkongvorakul et al. ( 2019 ), who showed that students with higher levels of smartphone addiction had lower psychological well-being scores. These findings also support those of Shoukat ( 2019 ), who showed that smartphone addiction inversely influences individuals' mental health.

This suggests that the greater the smartphone addiction, the greater the phubbing. The H5 findings are in line with those of Chatterjee ( 2020 ), Chotpitayasunondh and Douglas ( 2016 ), Guazzini et al. ( 2019 ), and Tonacci et al. ( 2019 ), who also evidenced a significant impact of smartphone addiction and phubbing. Similarly, Chotpitayasunondh and Douglas ( 2018 ) corroborated that smartphone addiction is the main predictor of phubbing behavior. However, these findings are inconsistent with those of Vallespín et al. ( 2017 ), who found a negative influence of phubbing.

The H6 results suggests that phubbing is one of the significant predictors of psychological well-being. Furthermore, these findings suggest that, when phubbers use a cellphone during interaction with someone, especially during the current pandemic, and they are connected with many family members, friends, and relatives; therefore, this kind of action gives them more satisfaction, which simultaneously results in increased relaxation and decreased depression (Chotpitayasunondh and Douglas, 2018 ). These findings support those of Davey et al. ( 2018 ), who evidenced that phubbing has a significant influence on adolescents and social health students in India.

The findings showed a significant and positive effect of social media use on psychological well-being both through bridging and bonding social capital. However, a significant and negative effect of social media use on psychological well-being through smartphone addiction and through social isolation was also found. Hence, this study provides evidence that could shed light on the contradictory contributions in the literature suggesting both positive (e.g., Chen and Li, 2017 ; Twenge and Campbell, 2019 ; Roberts and David, 2020 ) and negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) effects of social media use on psychological well-being. This study concludes that the overall impact is positive, despite some degree of negative indirect impact.

Theoretical Contributions

This study's findings contribute to the current literature, both by providing empirical evidence for the relationships suggested by extant literature and by demonstrating the relevance of adopting a more complex approach that considers, in particular, the indirect effect of social media on psychological well-being. As such, this study constitutes a basis for future research (Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ) aiming to understand the impacts of social media use and to find ways to reduce its possible negative impacts.

In line with Kim and Kim ( 2017 ), who stressed the importance of heterogeneous social networks in improving social capital, this paper suggests that, to positively impact psychological well-being, social media usage should be associated both with strong and weak ties, as both are important in building social capital, and hence associated with its bonding and bridging facets. Interestingly, though, bridging capital was shown as having the greatest impact on psychological well-being. Thus, the importance of wider social horizons, the inclusion in different groups, and establishing new connections (Putnam, 1995 , 2000 ) with heterogeneous weak ties (Li and Chen, 2014 ) are highlighted in this paper.

Practical Contributions

These findings are significant for practitioners, particularly those interested in dealing with the possible negative impacts of social media use on psychological well-being. Although social media use is associated with factors that negatively impact psychological well-being, particularly smartphone addiction and social isolation, these negative impacts can be lessened if the connections with both strong and weak ties are facilitated and featured by social media. Indeed, social media platforms offer several features, from facilitating communication with family, friends, and acquaintances, to identifying and offering access to other people with shared interests. However, it is important to access heterogeneous weak ties (Li and Chen, 2014 ) so that social media offers access to wider sources of information and new resources, hence enhancing bridging social capital.

Limitations and Directions for Future Studies

This study is not without limitations. For example, this study used a convenience sampling approach to reach to a large number of respondents. Further, this study was conducted in Mexico only, limiting the generalizability of the results; future research should therefore use a cross-cultural approach to investigate the impacts of social media use on psychological well-being and the mediating role of proposed constructs (e.g., bonding and bridging social capital, social isolation, and smartphone addiction). The sample distribution may also be regarded as a limitation of the study because respondents were mainly well-educated and female. Moreover, although Internet channels represent a particularly suitable way to approach social media users, the fact that this study adopted an online survey does not guarantee a representative sample of the population. Hence, extrapolating the results requires caution, and study replication is recommended, particularly with social media users from other countries and cultures. The present study was conducted in the context of mainly University students, primarily well-educated females, via an online survey on in Mexico; therefore, the findings represent a snapshot at a particular time. Notably, however, the effect of social media use is increasing due to COVID-19 around the globe and is volatile over time.

Two of the proposed hypotheses of this study, namely the expected negative impacts of social media use on social isolation and of phubbing on psychological well-being, should be further explored. One possible approach is to consider the type of connections (i.e., weak and strong ties) to explain further the impact of social media usage on social isolation. Apparently, the prevalence of weak ties, although facilitating bridging social capital, may have an adverse impact in terms of social isolation. Regarding phubbing, the fact that the findings point to a possible positive impact on psychological well-being should be carefully addressed, specifically by psychology theorists and scholars, in order to identify factors that may help further understand this phenomenon. Other suggestions for future research include using mixed-method approaches, as qualitative studies could help further validate the results and provide complementary perspectives on the relationships between the considered variables.

Data Availability Statement

Ethics statement.

The studies involving human participants were reviewed and approved by Jiangsu University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. This study is supported by the National Statistics Research Project of China (2016LY96).

  • Abbas R., Mesch G. (2018). Do rich teens get richer? Facebook use and the link between offline and online social capital among Palestinian youth in Israel . Inf. Commun. Soc. 21 , 63–79. 10.1080/1369118X.2016.1261168 [ CrossRef ] [ Google Scholar ]
  • Adnan M., Anwar K. (2020). Online learning amid the COVID-19 pandemic: students' perspectives . J. Pedagog. Sociol. Psychol. 2 , 45–51. 10.33902/JPSP.2020261309 [ CrossRef ] [ Google Scholar ]
  • Ali Qalati S., Li W., Ahmed N., Ali Mirani M., Khan A. (2021). Examining the factors affecting SME performance: the mediating role of social media adoption . Sustainability 13 :75. 10.3390/su13010075 [ CrossRef ] [ Google Scholar ]
  • Bagozzi R. P., Yi Y. (1988). On the evaluation of structural equation models . J. Acad. Mark. Sci. 16 , 74–94. 10.1007/BF02723327 [ CrossRef ] [ Google Scholar ]
  • Bagozzi R. P., Yi Y., Phillips L. W. (1991). Assessing construct validity in organizational research . Admin. Sci. Q. 36 , 421–458. 10.2307/2393203 [ CrossRef ] [ Google Scholar ]
  • Bano S., Cisheng W., Khan A. N., Khan N. A. (2019). WhatsApp use and student's psychological well-being: role of social capital and social integration . Child. Youth Serv. Rev. 103 , 200–208. 10.1016/j.childyouth.2019.06.002 [ CrossRef ] [ Google Scholar ]
  • Barbosa B., Chkoniya V., Simoes D., Filipe S., Santos C. A. (2020). Always connected: generation Y smartphone use and social capital . Rev. Ibérica Sist. Tecnol. Inf. E 35 , 152–166. [ Google Scholar ]
  • Bekalu M. A., McCloud R. F., Viswanath K. (2019). Association of social media use with social well-being, positive mental health, and self-rated health: disentangling routine use from emotional connection to use . Health Educ. Behav. 46(2 Suppl), 69S−80S. 10.1177/1090198119863768 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brown G., Michinov N. (2019). Measuring latent ties on Facebook: a novel approach to studying their prevalence and relationship with bridging social capital . Technol. Soc. 59 :101176. 10.1016/j.techsoc.2019.101176 [ CrossRef ] [ Google Scholar ]
  • Campbell D. T., Fiske D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix . Psychol. Bull. 56 , 81–105. 10.1037/h0046016 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Carlson J. R., Zivnuska S., Harris R. B., Harris K. J., Carlson D. S. (2016). Social media use in the workplace: a study of dual effects . J. Org. End User Comput. 28 , 15–31. 10.4018/JOEUC.2016010102 [ CrossRef ] [ Google Scholar ]
  • Chan M. (2015). Mobile phones and the good life: examining the relationships among mobile use, social capital and subjective well-being . New Media Soc. 17 , 96–113. 10.1177/1461444813516836 [ CrossRef ] [ Google Scholar ]
  • Chappell N. L., Badger M. (1989). Social isolation and well-being . J. Gerontol. 44 , S169–S176. 10.1093/geronj/44.5.s169 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Chatterjee S. (2020). Antecedents of phubbing: from technological and psychological perspectives . J. Syst. Inf. Technol. 22 , 161–118. 10.1108/JSIT-05-2019-0089 [ CrossRef ] [ Google Scholar ]
  • Chen H.-T., Li X. (2017). The contribution of mobile social media to social capital and psychological well-being: examining the role of communicative use, friending and self-disclosure . Comput. Hum. Behav. 75 , 958–965. 10.1016/j.chb.2017.06.011 [ CrossRef ] [ Google Scholar ]
  • Choi D.-H., Noh G.-Y. (2019). The influence of social media use on attitude toward suicide through psychological well-being, social isolation, and social support . Inf. Commun. Soc. 23 , 1–17. 10.1080/1369118X.2019.1574860 [ CrossRef ] [ Google Scholar ]
  • Chotpitayasunondh V., Douglas K. M. (2016). How phubbing becomes the norm: the antecedents and consequences of snubbing via smartphone . Comput. Hum. Behav. 63 , 9–18. 10.1016/j.chb.2016.05.018 [ CrossRef ] [ Google Scholar ]
  • Chotpitayasunondh V., Douglas K. M. (2018). The effects of phubbing on social interaction . J. Appl. Soc. Psychol. 48 , 304–316. 10.1111/jasp.12506 [ CrossRef ] [ Google Scholar ]
  • Cohen J. (1998). Statistical Power Analysis for the Behavioural Sciences . Hillsdale, NJ: Lawrence Erlbaum Associates. [ Google Scholar ]
  • Davey S., Davey A., Raghav S. K., Singh J. V., Singh N., Blachnio A., et al.. (2018). Predictors and consequences of phubbing among adolescents and youth in India: an impact evaluation study . J. Fam. Community Med. 25 , 35–42. 10.4103/jfcm.JFCM_71_17 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • David M. E., Roberts J. A., Christenson B. (2018). Too much of a good thing: investigating the association between actual smartphone use and individual well-being . Int. J. Hum. Comput. Interact. 34 , 265–275. 10.1080/10447318.2017.1349250 [ CrossRef ] [ Google Scholar ]
  • Dhir A., Yossatorn Y., Kaur P., Chen S. (2018). Online social media fatigue and psychological wellbeing—a study of compulsive use, fear of missing out, fatigue, anxiety and depression . Int. J. Inf. Manag. 40 , 141–152. 10.1016/j.ijinfomgt.2018.01.012 [ CrossRef ] [ Google Scholar ]
  • Dutot V., Bergeron F. (2016). From strategic orientation to social media orientation: improving SMEs' performance on social media . J. Small Bus. Enterp. Dev. 23 , 1165–1190. 10.1108/JSBED-11-2015-0160 [ CrossRef ] [ Google Scholar ]
  • Ellison N. B., Steinfield C., Lampe C. (2007). The benefits of Facebook friends: Social capital and college students' use of online social network sites . J. Comput. Mediat. Commun. 12 , 1143–1168. 10.1111/j.1083-6101.2007.00367.x [ CrossRef ] [ Google Scholar ]
  • Fan M., Huang Y., Qalati S. A., Shah S. M. M., Ostic D., Pu Z. (2021). Effects of information overload, communication overload, and inequality on digital distrust: a cyber-violence behavior mechanism . Front. Psychol. 12 :643981. 10.3389/fpsyg.2021.643981 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Fornell C., Larcker D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error . J. Market. Res. 18 , 39–50. 10.1177/002224378101800104 [ CrossRef ] [ Google Scholar ]
  • Gökçearslan S., Uluyol Ç., Sahin S. (2018). Smartphone addiction, cyberloafing, stress and social support among University students: a path analysis . Child. Youth Serv. Rev. 91 , 47–54. 10.1016/j.childyouth.2018.05.036 [ CrossRef ] [ Google Scholar ]
  • Gong S., Xu P., Wang S. (2021). Social capital and psychological well-being of Chinese immigrants in Japan . Int. J. Environ. Res. Public Health 18 :547. 10.3390/ijerph18020547 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Guazzini A., Duradoni M., Capelli A., Meringolo P. (2019). An explorative model to assess individuals' phubbing risk . Fut. Internet 11 :21. 10.3390/fi11010021 [ CrossRef ] [ Google Scholar ]
  • Hair J. F., Risher J. J., Sarstedt M., Ringle C. M. (2019). When to use and how to report the results of PLS-SEM . Eur. Bus. Rev. 31 , 2–24. 10.1108/EBR-11-2018-0203 [ CrossRef ] [ Google Scholar ]
  • Hair J. F., Sarstedt M., Pieper T. M., Ringle C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications . Long Range Plann. 45 , 320–340. 10.1016/j.lrp.2012.09.008 [ CrossRef ] [ Google Scholar ]
  • Hair J. F., Sarstedt M., Ringle C. M., Gudergan S. P. (2017). Advanced Issues in Partial Least Squares Structural Equation Modeling. Thousand Oaks, CA: Sage. [ Google Scholar ]
  • Hajek A., König H.-H. (2021). Social isolation and loneliness of older adults in times of the CoViD-19 pandemic: can use of online social media sites and video chats assist in mitigating social isolation and loneliness? Gerontology 67 , 121–123. 10.1159/000512793 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Henseler J., Ringle C. M., Sinkovics R. R. (2009). The use of partial least squares path modeling in international marketing, in New Challenges to International Marketing , Vol. 20, eds R.R. Sinkovics and P.N. Ghauri (Bigley: Emerald; ), 277–319. [ Google Scholar ]
  • Holliman A. J., Waldeck D., Jay B., Murphy S., Atkinson E., Collie R. J., et al.. (2021). Adaptability and social support: examining links with psychological wellbeing among UK students and non-students . Fron. Psychol. 12 :636520. 10.3389/fpsyg.2021.636520 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Jeong S.-H., Kim H., Yum J.-Y., Hwang Y. (2016). What type of content are smartphone users addicted to? SNS vs. games . Comput. Hum. Behav. 54 , 10–17. 10.1016/j.chb.2015.07.035 [ CrossRef ] [ Google Scholar ]
  • Jiao Y., Jo M.-S., Sarigöllü E. (2017). Social value and content value in social media: two paths to psychological well-being . J. Org. Comput. Electr. Commer. 27 , 3–24. 10.1080/10919392.2016.1264762 [ CrossRef ] [ Google Scholar ]
  • Jordan P. J., Troth A. C. (2019). Common method bias in applied settings: the dilemma of researching in organizations . Austr. J. Manag. 45 , 3–14. 10.1177/0312896219871976 [ CrossRef ] [ Google Scholar ]
  • Karikari S., Osei-Frimpong K., Owusu-Frimpong N. (2017). Evaluating individual level antecedents and consequences of social media use in Ghana . Technol. Forecast. Soc. Change 123 , 68–79. 10.1016/j.techfore.2017.06.023 [ CrossRef ] [ Google Scholar ]
  • Kemp S. (January 30, 2020). Digital 2020: 3.8 billion people use social media. We Are Social . Available online at: https://wearesocial.com/blog/2020/01/digital-2020-3-8-billion-people-use-social-media .
  • Kim B., Kim Y. (2017). College students' social media use and communication network heterogeneity: implications for social capital and subjective well-being . Comput. Hum. Behav. 73 , 620–628. 10.1016/j.chb.2017.03.033 [ CrossRef ] [ Google Scholar ]
  • Kim K., Milne G. R., Bahl S. (2018). Smart phone addiction and mindfulness: an intergenerational comparison . Int. J. Pharmaceut. Healthcare Market. 12 , 25–43. 10.1108/IJPHM-08-2016-0044 [ CrossRef ] [ Google Scholar ]
  • Kircaburun K., Alhabash S., Tosuntaş S. B., Griffiths M. D. (2020). Uses and gratifications of problematic social media use among University students: a simultaneous examination of the big five of personality traits, social media platforms, and social media use motives . Int. J. Mental Health Addict. 18 , 525–547. 10.1007/s11469-018-9940-6 [ CrossRef ] [ Google Scholar ]
  • Leong L.-Y., Hew T.-S., Ooi K.-B., Lee V.-H., Hew J.-J. (2019). A hybrid SEM-neural network analysis of social media addiction . Expert Syst. Appl. 133 , 296–316. 10.1016/j.eswa.2019.05.024 [ CrossRef ] [ Google Scholar ]
  • Li L., Griffiths M. D., Mei S., Niu Z. (2020a). Fear of missing out and smartphone addiction mediates the relationship between positive and negative affect and sleep quality among Chinese University students . Front. Psychiatr. 11 :877. 10.3389/fpsyt.2020.00877 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Li W., Qalati S. A., Khan M. A. S., Kwabena G. Y., Erusalkina D., Anwar F. (2020b). Value co-creation and growth of social enterprises in developing countries: moderating role of environmental dynamics . Entrep. Res. J. 2020 :20190359. 10.1515/erj-2019-0359 [ CrossRef ] [ Google Scholar ]
  • Li X., Chen W. (2014). Facebook or Renren? A comparative study of social networking site use and social capital among Chinese international students in the United States . Comput. Hum. Behav . 35 , 116–123. 10.1016/j.chb.2014.02.012 [ CrossRef ] [ Google Scholar ]
  • Matthews L., Hair J. F., Matthews R. (2018). PLS-SEM: the holy grail for advanced analysis . Mark. Manag. J. 28 , 1–13. [ Google Scholar ]
  • Meshi D., Cotten S. R., Bender A. R. (2020). Problematic social media use and perceived social isolation in older adults: a cross-sectional study . Gerontology 66 , 160–168. 10.1159/000502577 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Mou J., Shin D.-H., Cohen J. (2017). Understanding trust and perceived usefulness in the consumer acceptance of an e-service: a longitudinal investigation . Behav. Inf. Technol. 36 , 125–139. 10.1080/0144929X.2016.1203024 [ CrossRef ] [ Google Scholar ]
  • Nunnally J. (1978). Psychometric Methods . New York, NY: McGraw-Hill. [ Google Scholar ]
  • Oghazi P., Karlsson S., Hellström D., Hjort K. (2018). Online purchase return policy leniency and purchase decision: mediating role of consumer trust . J. Retail. Consumer Serv. 41 , 190–200. [ Google Scholar ]
  • Pang H. (2018). Exploring the beneficial effects of social networking site use on Chinese students' perceptions of social capital and psychological well-being in Germany . Int. J. Intercult. Relat. 67 , 1–11. 10.1016/j.ijintrel.2018.08.002 [ CrossRef ] [ Google Scholar ]
  • Podsakoff P. M., MacKenzie S. B., Lee J.-Y., Podsakoff N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies . J. Appl. Psychol. 88 , 879–903. 10.1037/0021-9010.88.5.879 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Podsakoff P. M., Organ D. W. (1986). Self-reports in organizational research: problems and prospects . J. Manag. 12 , 531–544. 10.1177/014920638601200408 [ CrossRef ] [ Google Scholar ]
  • Preacher K. J., Hayes A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models . Behav Res. Methods 40 , 879–891. 10.3758/brm.40.3.879 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Primack B. A., Shensa A., Sidani J. E., Whaite E. O., yi Lin L., Rosen D., et al.. (2017). Social media use and perceived social isolation among young adults in the US . Am. J. Prev. Med. 53 , 1–8. 10.1016/j.amepre.2017.01.010 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Putnam R. D. (1995). Tuning in, tuning out: the strange disappearance of social capital in America . Polit. Sci. Polit. 28 , 664–684. 10.2307/420517 [ CrossRef ] [ Google Scholar ]
  • Putnam R. D. (2000). Bowling Alone: The Collapse and Revival of American Community . New York, NY: Simon and Schuster. [ Google Scholar ]
  • Qalati S. A., Ostic D., Fan M., Dakhan S. A., Vela E. G., Zufar Z., et al.. (2021). The general public knowledge, attitude, and practices regarding COVID-19 during the lockdown in Asian developing countries . Int. Q. Commun. Health Educ. 2021 :272684X211004945. 10.1177/0272684X211004945 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Reer F., Tang W. Y., Quandt T. (2019). Psychosocial well-being and social media engagement: the mediating roles of social comparison orientation and fear of missing out . New Media Soc. 21 , 1486–1505. 10.1177/1461444818823719 [ CrossRef ] [ Google Scholar ]
  • Ringle C., Wende S., Becker J. (2015). SmartPLS 3 [software] . Bönningstedt: SmartPLS. [ Google Scholar ]
  • Ringle C. M., Sarstedt M., Straub D. (2012). A critical look at the use of PLS-SEM in MIS Quarterly. MIS Q . 36, iii–xiv. 10.2307/41410402 [ CrossRef ] [ Google Scholar ]
  • Roberts J. A., David M. E. (2020). The social media party: fear of missing out (FoMO), social media intensity, connection, and well-being . Int. J. Hum. Comput. Interact. 36 , 386–392. 10.1080/10447318.2019.1646517 [ CrossRef ] [ Google Scholar ]
  • Salehan M., Negahban A. (2013). Social networking on smartphones: when mobile phones become addictive . Comput. Hum. Behav. 29 , 2632–2639. 10.1016/j.chb.2013.07.003 [ CrossRef ] [ Google Scholar ]
  • Sarstedt M., Cheah J.-H. (2019). Partial least squares structural equation modeling using SmartPLS: a software review . J. Mark. Anal. 7 , 196–202. 10.1057/s41270-019-00058-3 [ CrossRef ] [ Google Scholar ]
  • Schinka K. C., VanDulmen M. H., Bossarte R., Swahn M. (2012). Association between loneliness and suicidality during middle childhood and adolescence: longitudinal effects and the role of demographic characteristics . J. Psychol. Interdiscipl. Appl. 146 , 105–118. 10.1080/00223980.2011.584084 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Shi S., Mu R., Lin L., Chen Y., Kou G., Chen X.-J. (2018). The impact of perceived online service quality on swift guanxi . Internet Res. 28 , 432–455. 10.1108/IntR-12-2016-0389 [ CrossRef ] [ Google Scholar ]
  • Shoukat S. (2019). Cell phone addiction and psychological and physiological health in adolescents . EXCLI J. 18 , 47–50. 10.17179/excli2018-2006 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Shrestha N. (2021). Factor analysis as a tool for survey analysis . Am. J. Appl. Math. Stat. 9 , 4–11. 10.12691/ajams-9-1-2 [ CrossRef ] [ Google Scholar ]
  • Stouthuysen K., Teunis I., Reusen E., Slabbinck H. (2018). Initial trust and intentions to buy: The effect of vendor-specific guarantees, customer reviews and the role of online shopping experience . Electr. Commer. Res. Appl. 27 , 23–38. 10.1016/j.elerap.2017.11.002 [ CrossRef ] [ Google Scholar ]
  • Swar B., Hameed T. (2017). Fear of missing out, social media engagement, smartphone addiction and distraction: moderating role of self-help mobile apps-based interventions in the youth , Paper presented at the 10th International Conference on Health Informatics (Porto). [ Google Scholar ]
  • Tangmunkongvorakul A., Musumari P. M., Thongpibul K., Srithanaviboonchai K., Techasrivichien T., Suguimoto S. P., et al.. (2019). Association of excessive smartphone use with psychological well-being among University students in Chiang Mai, Thailand . PLoS ONE 14 :e0210294. 10.1371/journal.pone.0210294 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Tateno M., Teo A. R., Ukai W., Kanazawa J., Katsuki R., Kubo H., et al.. (2019). Internet addiction, smartphone addiction, and hikikomori trait in Japanese young adult: social isolation and social network . Front. Psychiatry 10 :455. 10.3389/fpsyt.2019.00455 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Tefertiller A. C., Maxwell L. C., Morris D. L. (2020). Social media goes to the movies: fear of missing out, social capital, and social motivations of cinema attendance . Mass Commun. Soc. 23 , 378–399. 10.1080/15205436.2019.1653468 [ CrossRef ] [ Google Scholar ]
  • Tehseen S., Qureshi Z. H., Johara F., Ramayah T. (2020). Assessing dimensions of entrepreneurial competencies: a type II (reflective-formative) measurement approach using PLS-SEM . J. Sustain. Sci. Manage. 15 , 108–145. [ Google Scholar ]
  • Tehseen S., Ramayah T., Sajilan S. (2017). Testing and controlling for common method variance: a review of available methods . J. Manag. Sci. 4 , 146–165. 10.20547/jms.2014.1704202 [ CrossRef ] [ Google Scholar ]
  • Tonacci A., Billeci L., Sansone F., Masci A., Pala A. P., Domenici C., et al.. (2019). An innovative, unobtrusive approach to investigate smartphone interaction in nonaddicted subjects based on wearable sensors: a pilot study . Medicina (Kaunas) 55 :37. 10.3390/medicina55020037 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Twenge J. M., Campbell W. K. (2019). Media use is linked to lower psychological well-being: evidence from three datasets . Psychiatr. Q. 90 , 311–331. 10.1007/s11126-019-09630-7 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Vallespín M., Molinillo S., Muñoz-Leiva F. (2017). Segmentation and explanation of smartphone use for travel planning based on socio-demographic and behavioral variables . Ind. Manag. Data Syst. 117 , 605–619. 10.1108/IMDS-03-2016-0089 [ CrossRef ] [ Google Scholar ]
  • Van Den Eijnden R. J., Lemmens J. S., Valkenburg P. M. (2016). The social media disorder scale . Comput. Hum. Behav. 61 , 478–487. 10.1016/j.chb.2016.03.038 [ CrossRef ] [ Google Scholar ]
  • Whaite E. O., Shensa A., Sidani J. E., Colditz J. B., Primack B. A. (2018). Social media use, personality characteristics, and social isolation among young adults in the United States . Pers. Indiv. Differ. 124 , 45–50. 10.1016/j.paid.2017.10.030 [ CrossRef ] [ Google Scholar ]
  • Williams D. (2006). On and off the'net: scales for social capital in an online era . J. Comput. Mediat. Commun. 11 , 593–628. 10.1016/j.1083-6101.2006.00029.x [ CrossRef ] [ Google Scholar ]
  • Open access
  • Published: 24 September 2021

Social media use and social connectedness among adolescents in the United Kingdom: a qualitative exploration of displacement and stimulation

  • Lizzy Winstone 1 ,
  • Becky Mars 1 , 2 ,
  • Claire M. A. Haworth 2 , 3 , 4 &
  • Judi Kidger 1  

BMC Public Health volume  21 , Article number:  1736 ( 2021 ) Cite this article

40k Accesses

24 Citations

51 Altmetric

Metrics details

Connectedness to family and peers is a key determinant of adolescent mental health. Existing research examining associations between social media use and social connectedness has been largely quantitative and has focused primarily on loneliness, or on specific aspects of peer relationships. In this qualitative study we use the displacement hypothesis and the stimulation hypothesis as competing theoretical lenses through which we examine the complex relationship between social media use and feelings of connectedness to family and peers.

In-depth paired and individual interviews were conducted with twenty-four 13–14-year-olds in two inner-city English secondary schools. Interviews were transcribed verbatim, coded and thematically analysed.

Analysis identified four themes: (i) ‘Displacement of face-to-face socialising’ (ii) ‘Social obligations’ (iii) ‘(Mis)Trust’ and (iv) ‘Personal and group identity’. Results indicated stronger support for the stimulation hypothesis than the displacement hypothesis. We found evidence of a complex set of reciprocal and circular relationships between social media use and connectedness consistent with a ‘rich-get-richer’ and a ‘poor-get-poorer’ effect for family and peer connectedness – and a ‘poor-get-richer’ effect in peer connectedness for those who find face-to-face interactions difficult.

Our findings suggest that parents should take a measured approach to social media use, providing clear guidance, promoting trust and responsible time management, and acknowledging the role of social media in making connections. Understanding and sharing in online experiences is likely to promote social connectedness. Supporting young people to negotiate breathing space in online interactions and prioritising trust over availability in peer relationships may optimise the role of social media in promoting peer connectedness.

Peer Review reports

Introduction

Social connectedness is defined as feelings of belonging and closeness to others, as well as satisfaction with relationships and perceived support and opportunities for self-disclosure of personal information. It comprises different domains (peer, school, family and community/ neighbourhood) and is a key social determinant of adolescent mental health and well-being [ 1 , 2 , 3 ]. Family connectedness in particular has been found to buffer the negative effects of bullying and to be related to lower risk for suicide-related outcomes and depressive symptoms [ 3 , 4 ].

Social media use (SMU) is thought to have both positive and negative influences on the lives of young people, for whom it has become an integral part of daily life [ 5 ]. In 2018, 80% of 14-year-olds in the United Kingdom (UK) had a profile on a social media or messaging app [ 6 ]. For the purposes of this study, we include within social media social network sites as defined by boyd and Ellison [ 7 ], in addition to web-based messaging and microblogging services (such as WhatsApp and Tumblr) and social video platforms (such as YouTube). SMU has various functions, with users typically seeking entertainment, communication, inspiration and information. The use of social media to engage with others, either through direct communication or through the publication or consumption of content and its associated feedback, makes it an inherently social part of adolescence [ 8 ]. As such, SMU may have important implications for increasing connectedness with individuals and groups [ 9 ]. However, concerns have been raised by parents about screen-time interfering with other activities that may also be beneficial to connectedness [ 10 ], such as schoolwork, extra-curricular activities and engaging with others face-to-face. Through these competing processes of stimulation and displacement, SMU may simultaneously enhance and undermine social connectedness in adolescence [ 9 ].

The displacement and stimulation hypotheses

The displacement hypothesis was formulated on the basis of internet use rather than social media specifically [ 11 ]. The theory of displacement is two-fold, regarding both time displacement and displacement of strong social ties with weak ones. Use of the internet for entertainment purposes – as a solitary, socially disengaged activity comparable to passive consumption of social media content without active engagement – is thought to displace time spent socialising with others offline, subsequently undermining social connectedness [ 11 , 12 ]. Where used for communication purposes, online engagement and expansion of social networks were thought to be primarily with weak ties rather than with close family and friends, and as such, of little benefit to psychosocial well-being [ 11 , 13 ].

In line with this hypothesis, previous research has found that SMU is associated with increases in bridging but not bonding social capital, whereby vast expansion of social networks made possible through SMU enhances the number of weak social ties rather than improving relationships with close friends and family [ 5 ]. SMU may also displace time spent on other activities beneficial to well-being, including physical exercise and sleep [ 14 , 15 ]. With regards to family connectedness, an intensive longitudinal experience sampling study found little evidence that time spent using digital technology displaced time spent engaging offline with parents or resulted in problematic parent-adolescent offline interactions [ 16 ].

Evidence also exists in support of an opposing theory, the stimulation hypothesis, whereby SMU enhances the user’s existing social resources through increased contact and maintenance of relationships [ 17 , 18 ]. In direct contradiction to the displacement hypothesis (whereby strong social ties are displaced with weak ones) it has been suggested that adolescents are increasingly using social media to enhance the quality of existing friendships rather than seeking out new connections, leading to beneficial impacts on social connectedness and social and emotional support [ 17 ].

One study directly compared the two competing hypotheses and found that, rather than displacing time spent offline with friends, use of instant messenger was positively related to face-to-face socialising, in turn predicting better friendship quality and well-being [ 19 ]. This effect was specific to using instant messenger to communicate with friends and did not apply to use of chat rooms (primarily with strangers). The authors suggested that features of online communication – including asynchronous responding and absence of nonverbal cues or responses –could lower social inhibition and encourage sharing of personal information. These intimate self-disclosures can be beneficial to well-being and peer connectedness through enhancing feelings of support and trust [ 20 , 21 ].

Using experience sampling methodology, researchers have explored fluctuations in adolescents’ use of Instagram, Snapchat and WhatsApp with and without close friends [ 8 ]. Findings illustrated the complexity of the relationship between SMU and friendship closeness, with substantial differences at the within- and between-person level. Those who used Instagram or WhatsApp in the previous hour (whether with or without close friends) reported feeling slightly less close to close friends, however, those with a higher average frequency across a three-week period felt closer to their friends than those with less frequent use. Snapchat use was not found to be related to friendship closeness at either the within or between person level [ 8 ]. These findings were echoed in a study showing evidence for the displacement hypothesis at the within-person level – with increases in smartphone communication on a particular day reducing face-to-face interaction for a given individual – but not the between-person level – with no discernible difference in the level of face-to-face interaction for more or less prolific online communicators [ 22 ].

There is also evidence to suggest the relationship with SMU may be curvilinear, with only excessive levels of SMU found to be associated with lower levels of social capital [ 20 , 23 ] or poorer psychosocial functioning [ 24 ]. In a longitudinal study of adolescents in Belgium [ 23 ], Wang et al. found that low to moderate levels of active public Facebook use (that is broadcasting content publicly but not direct messaging with others) were associated with decreased loneliness over time, supporting the stimulation hypothesis. However, higher levels of broadcasting were associated with increased loneliness over time, indicating support for the displacement hypothesis. This indicates that rather than being mutually exclusive theories, both the stimulation and displacement hypotheses may be possible, depending on both the amount and type of SMU [ 17 ].

Objectives of the current study

Most existing research examining the displacement and stimulation hypotheses has been quantitative and has focused primarily on peer connectedness. Qualitative research, and research exploring the relationship between adolescent SMU and family connectedness is scarce. This qualitative study aimed to examine the relationship between SMU and social connectedness (encompassing peers and family) through the experiences and perspectives of a sample of 13–14-year-olds in south-west England.

Participants

Thirteen interviews were conducted with 24 Year 9 students aged 13–14 years (19 girls and five boys) in February–March 2020. Interviews took place at two English secondary schools in inner-city locations. One was in a particularly deprived area with an ethnically diverse and lower socio-economic status student population (measured by the proportion of students eligible for free school meals). The other was a single sex girls’ school with a higher-than-average socio-economic status population. Heads of Year 9 in each school were asked to advertise the study to all classes in the year group, with participant information sheets provided. The information sheets encouraged students with a range of social media experiences to take part, including those who considered themselves to be non-users. Two participants presented themselves as non-users of social media, describing their use of YouTube solely for entertainment purposes. Students volunteered to take part and all volunteers were selected for interview providing they returned signed parental consent forms by a cut-off date. In advance of the interviews, participants indicated on consent forms their preference for participation in an individual or paired interview with a friend (Table  1 ). Participants received a £10 Amazon voucher by way of thanks.

Design and procedure

Interviews were all conducted face-to-face by LW. LW is a female PhD student with some previous experience of conducting in-depth interviews with adults, and is trained in qualitative data analysis and conducting research with young people. JK oversaw the process and is a female academic with extensive qualitative research experience. The interviews were audio recorded, took place at school during lesson time and lasted between 45 min and an hour. A topic guide (available in Additional file  1 ) was used to ensure consistency in covering a number of core areas for discussion, including typical apps and activities used, family and school rules regarding SMU, online interactions with peers, family or strangers and SMU in those experiencing poor mental health. The guide was developed following consultation with a young people’s advisory board – a group of 11–18-year-olds with experience in advising on the design of health-related research materials. The group provided input into issues they felt most important relating to SMU and mental health. Flexibility in the topic guide allowed interview participants to take the conversation in any direction they felt to be relevant to the broad issue of social media and mental health, reflecting on their own SMU as well as that of their peers. This flexibility was felt to be important in mitigating the impact of the adult researchers’ preconceptions about adolescent SMU, social connectedness and mental health, enabling openness to experiences recognised as meaningful by participants themselves.

Data analysis

An inductive, reflexive approach to thematic analysis was used from a critical realist (contextualist) perspective [ 25 ]. SMU is so intertwined with one’s experience and perceptions of interpersonal and intergroup relationships that it would not make sense to refer to there being an authentic truth or reality. However, as researchers aspiring to improve public mental health through recommendations to stakeholders, we need to acknowledge young people’s experiences and feelings as an external reality, whilst recognising the prisms through which these are encountered by young people and interpreted by ourselves [ 25 ]. We interpreted the data as adults who experienced adolescence in a time before social media existed and we reflected on this throughout the analytic process.

Notes were taken during and after each interview. These were not coded but used in reflection during analysis. The interviews were transcribed verbatim and imported into NVivo version 12 for coding by LW. Analysis was conducted primarily by LW, from the perspective of an adult using social media for direct communication with existing friends and family. LW acknowledges that her own experiences – both positive and negative – of SMU will unavoidably frame her interpretation of the data.

A systematic and inclusive coding process was adopted, with coding applied flexibly to include unexpected data [ 25 ]. Codes were both descriptive (e.g., ‘nothing to do’) and interpretative (e.g., ‘privacy concerns’). Following coding of the complete dataset, initial themes were constructed and reviewed iteratively when examined against each interview, with thematic boundaries altered as necessary. Further amendments were made where appropriate following group discussion between the authors to review both codes and themes. During the review process codes considered irrelevant to the research question (e.g., ‘apps’) were discarded or included within other codes where appropriate (e.g., ‘memories’ was encapsulated within ‘friendships’). Two previously separate themes – ‘keeping in touch’ and ‘time displacement’ were merged into ‘displacement of face-to-face socialising’. Once themes were developed, they were examined in relation to the displacement and stimulation hypotheses to see whether findings confirmed, contradicted, or developed these theories. Participants were not asked to provide feedback on the findings.

Four themes were identified through analysis of the qualitative interview data with regard to SMU and social connectedness. Table  2 provides an overview of these themes and sub-themes with key illustrative data extracts. Each sub-theme is discussed in turn, along with implications for displacement and stimulation theories. There were no systematic differences in opinions and experiences between participants from the two different schools or those interviewed individually compared to with others, so comparisons are not presented here.

Displacement of face-to-face socialising

Elements of both displacement and stimulation were interwoven in discussions of online and offline socialising. Participants’ own SMU was sometimes felt to displace face-to-face social activities that promote feelings of connectedness. However, online peer interactions frequently took place when in-person socialising was not possible, helping to alleviate feelings of boredom and loneliness. Social network expansion was also highlighted as a key benefit of SMU, meeting new people, and maintaining contact with old friends outside of school and family members abroad.

Socialising with family

Several participants suggested that time spent socialising with family members would likely increase if they were to reduce their social media screen-time. Participant F5 spoke about recently breaking her phone and noted the positive impact it had on increasing time spent with her family.

Those participants who appeared to be minimal social media users reflected most on the importance of not ‘missing out’ on time with family (M3). Being with and ‘helping’ (M2) family was highlighted as a priority for these participants, with M2 suggesting that ‘talking to your family… is safer than talking on social media’. The strong family connectedness depicted by these participants appeared to have a protective effect against SMU displacing time spent together.

More frequently however, references to family connectedness and screen-time suggested increased SMU was a result rather than a cause of poor connectedness. Several participants alluded to their SMU at home as a means of reducing boredom or loneliness, because family members were not available to share meals or converse (F1, F2, M4, F6, F7, F12, F16). Some participants described family situations where disruption to home life, unsocial family dynamics or parents’ work patterns created time where they were left alone and turned to SMU because there was ‘nothing else to do’ (F1, F18, F19). F7 described sitting alone to eat dinner while using her phone and noted ‘…we just don’t do things as a family. It’s not social media, it’s just like, we just don’t do things.’

Consistent with the stimulation hypothesis, participants explained the benefits of communicating via social media to stay connected to family members who did not live close by, enhancing family connectedness beyond the nuclear family unit. This was felt to be particularly beneficial to those who would otherwise find the cost of overseas communication prohibitive. For some, this applied to one-to-one relationships with cousins of a similar age (F8). For others, group chats on social media enabled geographically disparate family members to come together as one to catch up or celebrate special occasions (F3).

Rather than displacing time spent socialising face-to-face with family, these comments showed how SMU was an important means of maintaining social interaction when in-person contact was not possible.

Socialising with friends

Across the sample, there were diverging opinions as to whether there was a difference between online and face-to-face socialising. In line with the displacement hypothesis, some found socialising through social media to be less rewarding than face-to-face, pointing particularly to the more genuine feel to in-person interactions where ‘you’ll see how they really are in person’ (F4) and can ‘gauge more’ (F6). Others gave opinions more aligned with the stimulation hypothesis, whereby online socialising facilitated offline interaction when they felt their own personalities to be ‘shy’ or socially ‘awkward’ (F6) – a social compensation effect [ 26 ]. As participant F10 put it, ‘I’m better friends with people because I’ve spoken to them more online and therefore in real life, we’re better friends. I wouldn’t say it’s different, no’.

As with family interactions, some participants pointed to the possibility of excessive SMU displacing time spent socialising in person with friends, leading some young people to ‘distance themselves from family and friends’ (M5). Some participants expressed a desire to reduce their own SMU to spend more time ‘meeting up with those people’ they were communicating with online (F5).

However, those who were more frequent users again indicated that online interactions generally replaced face-to-face out of necessity. Friends who were unable to socialise in person due to geographical constraints turned to social media to maintain peer-to-peer interaction. This applied to ‘long-distance friendships’ (F16), keeping in touch with friends at other schools, and those who did not live within walking distance to their close friends (F18).

Yes, that’s one of the reasons I use social media so much, it’s because all of my friends live so far away. I think my closest friend lives a 20-minute drive from me. So, I use social media to stay in contact with everyone, because that’s the only way you can really talk to people. (F19)

SMU was thus felt to strengthen or maintain peer connectedness for those with reduced opportunities for offline socialising, providing a protective effect from the risks of poor peer connectedness or loneliness.

SMU also promoted continuity of social networks, enabling young people to stay ‘connected’ (F12) with old friends from primary school, those who have moved away from the area, and friendships formed from extracurricular activities (F10). Without social media, there was a perceived risk that such ‘friendship[s] would just die’ (F16). Rather than ‘weak ties’ of vast online networks suggested by the displacement hypothesis [ 11 ], these were presented as close friendships whose enduring existence was stimulated by SMU in the absence of opportunities for offline interaction.

What social media is used for may influence whether it is perceived by the user to be displacing time spent with peers. Participant M1 pointed to the difference between playing PlayStation with a headset on, ‘talking to your friends… you are playing but also talking, so I feel more social, more talkative’ and ‘when you are using social media [passively], you feel isolated. You are just on your phone’ (M1). Whereas passive or excessive SMU may be perceived to displace face-to-face interaction, using social media explicitly for socialising may fulfil more of a stimulation function – enabling friends to ‘hang out’ (M4, M5) online when doing so in person is not possible.

In addition to maintaining stability within their social circle, SMU was also often credited with expansion of participants’ social circle through making new friends online, both by offering opportunities for new introductions, such as through a ‘mutual friend’ (F5), and by facilitating the development of friendships through initial online communication, which felt less intimidating than new face-to-face socialising (M4). Supporting the online enhanced self-disclosure or social compensation hypothesis [ 26 ] this was found to be particularly helpful to F6, who described herself as ‘shy’.

I feel like it’s easier for me because I feel like… if I’d just met someone, like, if someone just came to school now and we had to be friends, I feel like it would take me a while to, like, be able to talk to them without feeling… It depends. I think sometimes I’m really shy, and I think sometimes I’d rather just get to know someone online first… (F6)

As such, SMU was determined to be an important – and in some cases, critical – means of maintaining and expanding the size of young people’s social networks. SMU was explicitly credited by some participants for network expansion over and above friendship closeness. The network enhancing benefits they ascribed to SMU may be aligned to some extent with the ‘weak ties’ suggested by the displacement hypothesis, bringing limited psychosocial reward [ 11 , 13 ]. However, many young people in our sample referred to most of their online interactions and relationship maintenance being with existing close friends, illustrative of a stimulation effect. The importance of network size for well-being may vary across individuals, and a discussion between participants F6 and F7 noted the distinction between small numbers of ‘deep’ friendships (F6) that traverse online and offline worlds, and the tendency for some young people (including themselves at an earlier age) to place importance on having ‘loads of followers’ (F6) who were ‘fake friends’ (F7).

Social obligations

Whilst SMU enhanced feelings of connectedness through enabling participants to keep in touch with others, this was frequently accompanied by demanding expectations amongst peers. Participants reported feeling obliged – in line with social norms – to respond promptly to messages from peers and to provide positive feedback on peers’ social media posts. This was sometimes accompanied by feeling overwhelmed by multiple messages or group chats, guilt associated with making excuses for unavailability or outright peer conflict if expectations were not met. Rather than displacement or stimulation, we suggest this represents a situation of ‘over-stimulation’.

Obligation to be available

Most participants reflecting on their own active use of social media made implicit reference to a social media etiquette developed by their generation, to which they either adhered or chose to ignore. Participants felt they were expected to respond immediately to social media messages. Being available to take part in multiple online conversations simultaneously was felt to be ‘stressful’ and ‘a mess in my mind’ (M4), with ending conversations causing difficulty for several participants.

For me, it is actually hard, because I don’t have a way to end the conversation. I just go on another application and then after an hour or two, I check what they actually wrote and then they’re like, ‘Oh, you came back,’ and then I have to tell them a random explanation. I was like, ‘Oh, I went do something,’ or something, because I don’t want to tell them, ‘Oh, I couldn't be bothered to talk to you anymore,’ because that’s, kind of, a harsh way. (M4)

Participants often discussed their online communication in obligation-related terms as a means of avoiding conflict with peers, or as a chore necessary to adhere to social norms.

People don’t assume, “Oh, they're busy.” If my friend didn’t reply to me for a day, I’d instantly think, “Oh, have I done something wrong?” because I feel like a day is quite a long time to go without social media for us, so I’d just be like, “Oh, are they annoyed at me?” (F12)

This narrative of obligation or duty was underlined by terminology used by participants who reflected on the need to provide peers with an ‘excuse’ (F12, F15) to end online conversations or not to respond immediately to messages, with one participant ‘panicking’ (F14) when her phone was broken in case friends took offense to her lack of contact.

This aligns with neither the displacement nor stimulation hypothesis. These participants seemed to reveal a sense of ‘over-stimulation’ or ‘hyper-connectedness’ with peers, whereby perceived excessive or duty-bound online communication no longer enhanced friendship quality but became a burden attached to friendships.

Obligation to provide positive feedback

Several participants explained their motivation for commenting on a friend’s post as an act of altruism to boost others’ self-esteem, stimulating peer connectedness through provision of emotional support and mutual respect (F4, F5, F10). However, others conveyed a weight of expectation to do so to avoid negative consequences to the friendship. Failure to like or comment on pictures posted by friends was usually met with confusion (‘because it’s the normal thing to do’ (F11)), a need for justification, or conflict (M4).

While many participants accepted this etiquette as part of everyday peer relationships, others described it as time-consuming and ‘overwhelming’ (F15), with some feeling ‘forced’ (M4) to like or comment on a friend’s post. This emotive language seemed to convey a sense of excessive peer connectedness or over-stimulation emerging from unrealistic but increasingly normalised expectations of friendship.

Participant F12 described the process of commenting and liking on others’ posts as ‘trading’ to boost perceived popularity for enhanced peer status. This understanding that provision of positive feedback is expected rather than based on genuine positive evaluation of content may undermine the validating effect of receiving positive feedback oneself, leading some young people to view likes or comments received on their own content as a superficial form of popularity and undermining benefits to self-esteem.

In addition to extending the positive stimulation effect of online communication into negative feelings of oppressiveness, the concept of displacement is exemplified here through young people’s defining of friendship in the normative obligation to exchange likes and positive comments. These more potentially hollow popularity-based aspects of friendships are indicative of ‘weak’ ties – a superficial type of peer support compared to the deeper benefits of strong affective ties defined by close emotional, tangible support, mutual respect and trust [ 11 ]. However, peer popularity is a key aspect of identity development and sense of self in adolescence, and receipt of feedback to social media content may therefore still be an important contributor to well-being and peer connectedness for this age group [ 27 ].

The theme of (mis)trust encapsulated both positive and negative aspects of the role of SMU in social relationships. The dominant narrative presented social media as a vehicle through which participants’ parents could demonstrate their trust that they would behave safely and responsibly. This was generally reciprocated by participants, several whom trusted their parents or other family members to follow their social media accounts as a form of protection. One exception to this provided an example of a more complicated relationship with parents and felt a lack of trust to be left in charge of their own SMU, with implications for responding to adverse online experiences.

Where close friends were felt to be trustworthy, social media provided opportunities for self-disclosure, fostering intimacy in the relationship, and improving peer connectedness in a virtuous cycle. However, the fear of data misappropriation, such as screenshotting within broader peer networks, appeared to have led to widespread underlying feelings of mistrust, undermining peer connectedness. Rather than a linear effect of displacement or stimulation, displacement or undermining of social connectedness seemed to present in a poor-get-poorer effect, whereas good quality relationships were further stimulated by SMU in a rich-get-richer effect.

Opportunities for adults to demonstrate trust

With adolescents in control of their own online profiles and content, social media was felt by some to provide opportunities for adults in their lives to demonstrate they trust young people to be responsible online, nurturing their independence. Within the sample, there were positive examples of trusting parental relationships, in which parents had provided guidance and established boundaries, then let young people use social media without excessive interference (M1, F8, F10).

Several participants spoke of their parents or other family members following their social media accounts to keep an eye on them. This was generally framed positively as overseeing participants’ SMU for their protection, either in terms of giving advice about data privacy or inappropriate posts (F17), or in more practical terms, whereby geographical tags can help parents locate young people if they are unable to contact them (M4). Participant M4 also went on to discuss the barriers introduced by social media to prevent lying to his parents about his whereabouts. This was also framed positively as preventing potential damage to the relationship. The dominant narratives of mutual trust developing and being played out through parents’ navigation of young people’s SMU demonstrated the potential for stimulation of family connectedness.

However, one participant stood out in their portrayal of parents with strict attitudes to SMU, whereby access to certain apps or activities had been banned, describing a paternal relationship defined by restrictions and lies.

My mum gave [snapchat]to me when I was 10, and then my dad said I wasn’t allowed to have it. I kind of deleted it for a while, and then I discovered I could just hide it, so I had it on my phone. Then whenever he asked to use my phone, I’d delete it, and then download it again and put it back in when I got my phone back… (F1)

This participant also spoke of her parents looking over her shoulder as she used social media or taking her phone out of her hands to check what she was doing.

Those participants with parents who had demonstrated their trust reported feeling able to discuss and ask for advice on difficult issues encountered on social media, whereas those with less trusting parents felt reluctant to approach their parents for fear of repercussions. This is evident in contrasting comments from F14, who was comfortable approaching their mother for help with online peer relationships, and F1, who felt that her parents’ dogmatic approach to social media prevented her reporting online sexual harassment in case she was no longer allowed to use certain apps.

I mean she [mum] knows that you’re going to get follow requests from people you don’t necessarily know and she said, “You can accept them but just make sure you know what you’re getting into.” She’s like, “If anything gets too bad tell me because we’re not going to tell you off or anything. We want to understand and even if you’re in the wrong we’ll try to help you”. (F14)
But I wouldn’t tell my parents [about strangers’ sexual harassment online] because they wouldn’t let me have it any more, and I’m not really meant to have it anyway. (F1)

Participants who had established a sense of mutual trust with parents also noted an appreciation for constructive guidance and boundaries to SMU. This appeared particularly pertinent to night-time SMU and its potential to disrupt participants’ sleep patterns, where rules set by parents about SMU in bed were quickly found to be beneficial by participants F4 and F5. In this sense, an authoritative approach to setting sensible SMU boundaries – seemingly reflective of good family connectedness – seemed to be acceptable to young people. Family connectedness therefore has the potential to mitigate well-documented negative effects of night-time SMU on sleep [ 14 ].

Self-disclosure and fear of screenshotting (‘I don’t trust you’)

We found some evidence of online enhanced self-disclosure in our sample – in line with the stimulation hypothesis – whereby features of online communication facilitate sharing of intimate information, leading to better quality relationships [ 28 ]. Those participants who demonstrated online enhanced self-disclosure appeared to do so specifically because of perceived poor social skills. Participant F6 described herself as particularly lacking in social confidence and noted a preference for sharing sensitive disclosures via social media rather than at school where ‘everyone is always there’ (F6). In this case, the perceived privacy of direct messaging via social media with trusted close friends was felt to stimulate online self-disclosure and deepen the participant’s friendships. M1 also noted difficulties approaching friends face-to-face with a problem, but an ability to be ‘direct’ in doing so online. One participant gave a specific example of preferring online rather than face-to-face interaction in the case of a close bereavement, where giving condolences online would avoid an uncomfortable display of emotion (M4).

However, a more common perspective amongst our sample was a preference for face-to-face sharing when it came to sensitive or personal information. Reasons included the increased effort involved in typing long messages online (F5), ease of conversation and avoiding misunderstandings when able to gauge behavioural or vocal cues (F4, F7, F10, F11, F12, F14, F15, F18, F19), knowing who else is present and increased privacy offline (F2, M2, M3, M5, F8, F16, F17), and face-to-face as a less superficial and therefore more appropriate context for discussing serious problems (F9).

For many participants the risk of screenshots being taken and shared presented a substantial barrier to online self-disclosure (Fig.  1 ), with some saying they would not trust even close friends with sensitive information sent over social media. Others reserved any content sharing only for trusted close friends, and only using certain apps such as Snapchat where users are notified if someone has taken a screenshot. Fears included screenshots being used as ‘evidence’ (F13) or ‘proof’ (F15) within an argument, or to spread ‘rumours’ (F6), but also images being manipulated and used to ‘make fun’ of the subject (M3). Other participants blamed screenshotting for exacerbating peer conflict and for the potential ‘break[down]’ (M5) of friendships. For two participants (M2, M3), the risk of screenshotting and potential misappropriation of content put them off using any social media at all. In restricting online self-disclosure, this fear and mistrust of social media audiences represent a limit to online peer connectedness, aligned to the displacement of good quality face-to-face social interactions with less intimate ones online.

figure 1

Implications of social media screenshotting for trust and poor peer connectedness

Concerns about deception and privacy issues appeared to be at the forefront of most participants’ minds as a result of their own or peers’ experiences, or anxieties raised by parents. These worries ranged from trusting (or not) their friends to sensitively handle content shared privately, feeling ‘suspicious’ (F8) when contacted by strangers as to their identity and intentions, to a general undercurrent of mistrust of social media audiences not to ‘hack’ (M4) their accounts, ‘steal’ (F18, F19) their data or identity or engage in other ‘scary’ (F2) behaviour.

Probably if I had to think of something off the top of mind, I would probably say the most important thing on social media is, don’t talk to someone you don’t know, because you don’t know what they’re capable of. (M4)

The young people in our sample were thus acutely aware of the risks of identity theft and of engaging online with potentially dangerous strangers. Combined with a general discomfort with online self-disclosure or fear of screenshotting among peers, this mistrust can simultaneously be perceived as a challenge to quality in peer relationships and interpreted as a constructive strategy for mitigating risk.

Personal and group identity

Social identity development and expression can be facilitated through SMU. Using social media to share experiences – messaging, viewing online content together with friends and family, and co-producing content such as TikTok videos – appeared to foster feelings of connectedness through stimulation of a sense of belonging. Participants described careful curation of their online profiles to construct and express their identity. Online social networking and microblogging enabled those with specific interests (such as art or music) or experiences (including mental health conditions) to find like-minded others and join communities without geographical constraints, thus enhancing peer connectedness.

In terms of family connectedness, frustrations with adults’ lack of understanding of young people’s SMU and overemphasis on online harms led to a perceived disconnect between generations. Rather than displacement weakening family connectedness here, an adult discourse of SMU displacing activities they perceived to be healthier had negative implications for highlighting differences between generational groups and reducing feelings of mutual respect and understanding.

Sense of belonging

SMU stimulated feelings of social connectedness via enhancing feelings of belonging and group membership. For some participants, this was achieved simply through inclusion in a group chat (F3, M4).

In other cases, appearing on Instagram stories, ‘slip stories’, or private stories of their friends – whether as actors within the content or as privileged audiences of this restricted content – helped to cement participants’ position as a trusted member of the peer group (M4) and was generally perceived to symbolise a close friendship (F1, F2, M4, F9, F11). In such cases, privacy settings became markers of group membership.

In line with the stimulation hypothesis, SMU enabled and made salient shared experiences with existing friends and family, an important part of social group membership. Several participants highlighted the shared enjoyment of passively consuming social media content in the presence of others. This included watching YouTube videos together with family members (M3), sharing funny memes with parents (M1, F8), and using content related to special shared interests (such as football) to enrich interactions with siblings and improve the closeness of the relationship (F6). In addition, active co-production of visual content with others was presented as an important part of friendship for some (F9) and a way to ‘make memories’ with friends (F5). This co-production could improve peer connectedness through collaboratively working to achieve a common creative goal and sharing in a sense of accomplishment.

For some participants (F18, F19, F2), social media represented an opportunity to express their opinions and share creative projects with like-minded others outside their immediate friendship groups, with whom they would otherwise be unlikely to interact because of differences in age or location. Using social media in this way gave them access to communities in which they could receive support in shaping their artistic identities as well as becoming active and supportive community members. Identity development and expression was thus supported by SMU, simultaneously stimulating connectedness to a wider peer network.

Generational disconnect

Many participants expressed a sense of frustration with what they perceived to be an adult obsession with screen-time and the negative effects of SMU, which seemed to impact negatively on family identity and connectedness. Growing up in a vastly different environment to their elders – largely but not exclusively related to the advent of social media – was felt to have led to a disconnect between generations, whereby adults were perceived as unable ‘to relate’ (F10, F14, F15). As such, there was a sense that adults fail to fully appreciate the significance of the online world for this generation, imposing arbitrary screen-time limitations rather than taking time to understand the positive and negative aspects of SMU.

Older generations were felt to overestimate the negative impacts of SMU (‘adults think it’s bad but it’s not that bad…’ (F13)) with too much importance placed on social media as a cause of bullying or harm, when the relationship as experienced by young people, is more complex.

I think the biggest problem with social media is adults say, “It’s evil, you shouldn’t do it,” but the thing is- and they’re like, “It creates argument, you bully each other.” It doesn’t. The thing is the arguments are going to happen anyway, it just doesn’t help you resolving it really. People are like, “Oh it creates arguments. It turns people into bullies. You’re vulnerable on there.” It isn’t really. That’s the thing. (F13)

Several participants relayed experiences whereby their parents or other family members had been critical of their SMU, with a general negative ‘stigma’ attached to social media (F10). While this was sometimes perceived as a justifiable concern around online harms (F4, M4), those who were told to simply ‘get off your phone’ (F12) felt misunderstood and some found this irritating or upsetting (F2, F10, F11, F12, F14, F15). Participant F14 described her mother’s dismissive attitude towards social media. Her mother suggested that her SMU displaced time better spent on healthier activities such as exercise and face-to-face socialising, but was felt to underestimate the social importance of SMU and the diverging priorities between generations. With social media often used strategically at times when such activities are logistically more difficult (as discussed under ‘displacement of face-to-face socialising’), this perceived inappropriate emphasis on displacement and screen-time restrictions appeared to underlie the sense of disconnect between young people and older generations. These age-related group differences – accentuated by divergent attitudes to SMU – have the potential to increase inter-generational discord, harming family connectedness through diminished feelings of mutual understanding and respect.

This qualitative study contributes to a growing literature on the psychosocial impacts of SMU in adolescence. We explored in depth the role of SMU in the broader social environment from the perspectives of adolescents themselves, examining both peer and family connectedness. Four themes were identified: i) ‘Displacement of face-to-face socialising’ (ii) ‘Social obligations’ (iii) ‘(Mis)Trust’ and (iv) ‘Personal and group identity’.

Findings in relation to displacement and stimulation hypotheses

We found some limited evidence in favour of the displacement hypothesis [ 11 ], whereby time spent using social media was felt by some participants to displace time spent socialising with family or friends face-to-face. However, it was often the case that online peer interactions took place mainly when in person socialising was not possible, providing opportunities to socialise and maintain peer relationships online in the absence of offline opportunities. Those experiencing increased SMU in place of family socialising tended to relay lower levels of family connectedness that preceded the SMU, with SMU used strategically to overcome feelings of loneliness in the home. This supports a ‘poor-get-poorer’ or ‘social deterioration’ effect, whereby those who feel less connected to their family are likely to rely more on SMU for social interactions or to alleviate boredom at home, further compounding a lack of connectedness within the household. Considering peer and family connectedness together, this is also illustrative of a ‘poor-get-richer’ or ‘social compensation’ effect, whereby poor family connectedness leads to increased online socialising with friends and subsequent improved peer connectedness. SMU may therefore serve as a protective tool in some circumstances to mitigate psychological risks associated with poor family connectedness or reduced face-to-face socialising. It is worth noting that these interviews took place before the COVID-19 pandemic led to school closures and lockdown, and SMU is likely to have served a particularly important function in this regard over the course of the pandemic.

One of few studies examining SMU and family connectedness, a cross-sectional survey of Canadian adolescents [ 29 ] found that heavy SMU (3 or more hours per day) was associated with greater odds of negative reported relationships between mothers and daughters, fathers and daughters and fathers and sons, but not mothers and sons. The authors explain their results as indicative of SMU displacing time spent engaging face-to-face with parents, with negative consequences for family relationships, However, our findings indicate that adolescents may also be motivated to turn to social media as a result of existing poor family connectedness.

Our study provides more evidence for the stimulation hypothesis, whereby SMU enhances the user’s existing social resources through increased contact and maintenance of relationships. Perceived benefits of SMU that emerged in this sample included the expansion of social networks, the ability to keep in touch with friends and family (including those for whom geographical constraints prevent offline socialising), enhanced self-disclosure for socially awkward young people or among very close friends, and supporting identity development and feelings of belonging. Consistent with a ‘poor-get-richer’ effect, those with reduced social resources offline – not only due to social awkwardness or anxiety but also loneliness or geographical barriers to offline interaction – find online support particularly beneficial [ 17 ,  27 ].

Where close friends were felt to be trustworthy, social media provided opportunities for self-disclosure, fostering intimacy in the relationship and improving peer connectedness in a ‘rich-get-richer’ or ‘social enhancement’ effect (Fig.  2 ). This is in line with previous research finding that adolescents’ time spent on instant messaging services enhances time spent face-to-face with friends, and subsequent quality of friendships [ 20 ]. SMU also provides opportunities for young people to construct, express, and develop identity in relation to their social world [ 30 ]. Young people in our sample reported using social media to share experiences, such as passively watching entertaining content together with friends and family members, as well as actively co-producing content, with privacy settings used to demarcate friendship group boundaries to different degrees of closeness (Fig. 2 ). This may foster feelings of connectedness and belonging, in line with the stimulation hypothesis.

figure 2

Social enhancement (rich-get-richer) effect of social media in connectedness within close friendships

In addition to the positive aspects of SMU, young people reported feeling pressures of expectation around providing feedback on friends’ online posts and being constantly available for communication. For these young people, social media had created a normative environment of ‘over-stimulation’, which fostered feelings of stress. It may be that SMU for direct peer communication may stimulate connectedness and subsequent well-being to a point, whereas excessive communication and the associated expectations to respond might undermine these benefits. This aligns to the 'digital Goldilocks hypothesis' [ 24 ] and other evidence of a curvilinear relationship between SMU and psychosocial adjustment [ 23 ], whereby moderate SMU is beneficial to well-being (compared to no use at all) but excessive use is associated with negative outcomes. In addition, the fear of data misappropriation such as screenshotting within broader peer networks appeared to have led to widespread underlying feelings of mistrust, thus undermining peer connectedness, and lending weight to the suggestion that broader SMU may discourage development of ‘strong ties’. Screenshotting is a currently understudied aspect of SMU. Our findings suggest the role of screenshotting within relationships between SMU and psychosocial outcomes – including social connectedness – warrants further attention.

Parental understanding of social media use in young people

Where a family environment of mutual respect had been established and consideration had been given to understanding the indispensable role of social media in young people’s lives, with positive aspects acknowledged in addition to traditional e-safety concerns, young people were more accepting of advice and clear boundaries regarding healthy SMU. Young people felt they were trusted to behave responsibly online and in turn trusted authority figures to provide guidance regarding challenges encountered without fear of access to social media being removed or restricted. Risks to peer connectedness encountered online, such as cyber-ostracism or screenshotting, may thus be mitigated by strong family connectedness. With this supportive environment, young people are able to navigate online difficulties but also feel encouraged to share positive social media content with family members, promoting shared interests and family identity. A ‘rich-get-richer’ [ 19 ] effect appears to develop, with social media promoting further trust and family connectedness (Fig.  3 ).

figure 3

Social enhancement (rich-get-richer) effect of social media in family connectedness

Conversely, an existing lack of trust in relationships between young people and their parents may underpin a rejection of screen-time restrictions and a reluctance to report exposure to online harms, adding further to a sense of social distance and further undermining connectedness, consistent with a ‘poor-get-poorer’ effect (Fig.  4 ). Future research might explore whether these findings can be generalised to the wider population of young people, and test the relationship between parental attitudes to social media and young people’s resilience or vulnerability to online harm.

figure 4

Social deterioration (poor-get-poorer) effect of social media in family connectedness

Limitations

This study has some important limitations. Our sample size was somewhat smaller than planned due to the emergence of COVID-19, with boys in particular under-represented. However, a broad range of views and experiences were captured in the sample, which were sufficient to enable rich themes to be generated [ 31 ]. While our sample was diverse in their experiences of social media, they were not selected on the basis of how much they used SMU or for what reasons, therefore it is possible that some additional patterns of SMU may exist in this age group that were not captured. All participants were aged 13–14-years and attended inner-city secondary schools in one area of the country. Different offline experiences and circumstances are likely to be accompanied by different online experiences, and caution should therefore be exercised in generalising findings from this study to other populations.

Implications

The separation of the social environment offline and on social media is not clear cut. Focusing on developing trusting, attentive relationships with peers and parents offline is likely to optimise the potential for social media to further benefit social connectedness. Feeling understood and respected by adults should encourage young people to accept and appreciate healthy boundaries established regarding their digital activities. A balance must be sought between teaching young people about the risks to well-being that engaging with social media may lead to, without being alarmist and creating a culture in which confidence in others is discouraged. Healthy peer relationships in which there is trust, respect, and space to ignore digital notifications and messages are likely to benefit most from SMU that enables enhanced self-disclosure and increased closeness without feeling oppressive. Young people should be supported to re-prioritise trustworthiness over availability in defining meaningful and fulfilling friendships. If, as our evidence suggests, the online social environment is an extension of relationships in the real world, fostering healthy connectedness with others offline is likely to maximise the social benefits and minimise the potential harms of social media for young people.

Conclusions

Rather than a clear, unidirectional relationship in which SMU harms – through a process of displacement – or enhances – through stimulation – overall social connectedness in adolescence, we suggest a complex set of reciprocal and circular relationships in which social media can play both a beneficial role in reinforcing existing positive connections to peers and family, and a deleterious role in exacerbating an already poor social environment through the propagation of mistrust. The relationship between SMU and social connectedness cannot be viewed as independent of either content or context. In addition to quality of existing offline social resources, the different activities and ways in which adolescents use social media will partially determine the direction and valence of effects. Passive SMU, devoid of social interaction, is unlikely to confer the same social benefits as SMU for direct communication with friends. However, parents and other adults supporting young people should also take account of individual differences in how social media may benefit or undermine connectedness, supporting individuals to find ways to interact with social media that best supports their well-being.

Availability of data and materials

The qualitative datasets generated and analysed during the current study are not publicly available due to the data containing information that could compromise research participant privacy but are available from the corresponding author on reasonable request.

Abbreviations

Social media use

Viner RM, Ozer EM, Denny S, Marmot M, Resnick M, Fatusi A, et al. Adolescence and the social determinants of health. Lancet. 2012 Apr 28;379(9826):1641–52. https://doi.org/10.1016/S0140-6736(12)60149-4 .

Article   PubMed   Google Scholar  

Jose PE, Ryan N, Pryor J. Does social connectedness promote a greater sense of well-being in adolescence over time? J Res Adolesc. 2012 Jun;22(2):235–51. https://doi.org/10.1111/j.1532-7795.2012.00783.x .

Article   Google Scholar  

McLoughlin LT, Spears BA, Taddeo CM, Hermens DF. Remaining connected in the face of cyberbullying: why social connectedness is important for mental health. Psychol Sch. 2019;56(6):945–58. https://doi.org/10.1002/pits.22232 .

Foster CE, Horwitz A, Thomas A, Opperman K, Gipson P, Burnside A, et al. Connectedness to family, school, peers, and community in socially vulnerable adolescents. Child Youth Serv Rev. 2017 Oct 1;81:321–31. https://doi.org/10.1016/j.childyouth.2017.08.011 .

Article   PubMed   PubMed Central   Google Scholar  

Ryan T, Allen KA, Gray DL, McInerney DM. How social are social media? A review of online social behaviour and connectedness. J Relationships Res. 2017;8. https://doi.org/10.1017/jrr.2017.13 .

Ofcom. Online Nation 2019 data. https://www.ofcom.org.uk/research-and-data/internet-and-on-demand-research/online-nation. 2019 . Accessed 2 August 2021.

Boyd DM, Ellison NB. Social network sites: definition, history, and scholarship. J Comput-Mediat Commun. 2007 Oct;13(1):210–30. https://doi.org/10.1111/j.1083-6101.2007.00393.x .

Pouwels JL, Valkenburg PM, Beyens I, van Driel II, Keijsers L. Social media use and friendship closeness in adolescents’ daily lives: an experience sampling study. Dev Psychol. 2021 Feb;57(2):309–23. https://doi.org/10.1037/dev0001148 .

Allen KA, Ryan T, Gray DL, McInerney DM, Waters L. Social media use and social connectedness in adolescents: the positives and the potential pitfalls. The Educational and Developmental Psychologist. 2014 Jul;31(1):18–31. https://doi.org/10.1017/edp.2014.2 .

Ofcom. Children and parents: Media use and attitudes report 2019. July 2019. https://www.ofcom.org.uk/research-and-data/media-literacy-research/childrens . Accessed 2 August 2021.

Kraut R, Patterson M, Lundmark V, Kiesler S, Mukophadhyay T, Scherlis W. Internet paradox: a social technology that reduces social involvement and psychological well-being? Am Psychol. 1998 Sep;53(9):1017–31. https://doi.org/10.1037/0003-066X.53.9.1017 .

Article   CAS   PubMed   Google Scholar  

Bessière K, Kiesler S, Kraut R, Boneva BS. Effects of internet use and social resources on changes in depression. Information, Community & Society. 2008 Feb 1;11(1):47–70. https://doi.org/10.1080/13691180701858851 .

Turkle S. Alone together: why we expect more from technology and less from each other. Hachette UK; 2017.

Google Scholar  

Scott H, Woods HC. Understanding links between social media use, sleep and mental health: recent progress and current challenges. Current Sleep Medicine Reports. 2019 Sep;5(3):141–9. https://doi.org/10.1007/s40675-019-00148-9 .

Viner RM, Gireesh A, Stiglic N, Hudson LD, Goddings AL, Ward JL, et al. Roles of cyberbullying, sleep, and physical activity in mediating the effects of social media use on mental health and wellbeing among young people in England: a secondary analysis of longitudinal data. The Lancet Child & Adolescent Health. 2019 Oct 1;3(10):685–96. https://doi.org/10.1016/S2352-4642(19)30186-5 .

Jensen M, George MJ, Russell MA, Lippold MA, Odgers CL. Does adolescent digital technology use detract from the parent–adolescent relationship? J Res Adolesc. 2021 Jun;31(2):469–81. https://doi.org/10.1111/jora.12618 .

Nowland R, Necka EA, Cacioppo JT. Loneliness and social internet use: pathways to reconnection in a digital world? Perspect Psychol Sci. 2018 Jan;13(1):70–87. https://doi.org/10.1177/1745691617713052 .

Best P, Taylor B, Manktelow R. I’ve 500 friends, but who are my mates? Investigating the influence of online friend networks on adolescent wellbeing. Journal of Public Mental Health. 2015 .

Valkenburg PM, Peter J. Online communication and adolescent well-being: testing the stimulation versus the displacement hypothesis. J Comput-Mediat Commun. 2007 Jul 1;12(4):1169–82. https://doi.org/10.1111/j.1083-6101.2007.00368.x .

Bohn A, Buchta C, Hornik K, Mair P. Making friends and communicating on Facebook: implications for the access to social capital. Soc Networks. 2014 May 1;37:29–41. https://doi.org/10.1016/j.socnet.2013.11.003 .

Desjarlais M, Gilmour J, Sinclair J, Howell KB, West A. Predictors and social consequences of online interactive self-disclosure: a literature review from 2002 to 2014. Cyberpsychol Behav Soc Netw. 2015 Dec 1;18(12):718–25. https://doi.org/10.1089/cyber.2015.0109 .

Verduyn P, Schulte-Strathaus JC, Kross E, Hülsheger UR. When do smartphones displace face-to-face interactions and what to do about it? Comput Hum Behav. 2021;114:106550. https://doi.org/10.1016/j.chb.2020.106550 .

Wang K, Frison E, Eggermont S, Vandenbosch L. Active public Facebook use and adolescents' feelings of loneliness: evidence for a curvilinear relationship. J Adolesc. 2018;67:35–44. https://doi.org/10.1016/j.adolescence.2018.05.008 .

Przybylski AK, Orben A, Weinstein N. How much is too much? Examining the relationship between digital screen engagement and psychosocial functioning in a confirmatory cohort study. J Am Acad Child Adolesc Psychiatry. 2020;59(9):1080–8. https://doi.org/10.1016/j.jaac.2019.06.017 .

Braun V, Clarke V. One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qual Res Psychol. 2020;14:1–25.

Valkenburg PM, Peter J. Social consequences of the internet for adolescents: a decade of research. Curr Dir Psychol Sci. 2009;18(1):1–5. https://doi.org/10.1111/j.1467-8721.2009.01595.x .

Nesi J, Choukas-Bradley S, Prinstein MJ. Transformation of adolescent peer relations in the social media context: part 1—a theoretical framework and application to dyadic peer relationships. Clin Child Fam Psychol Rev. 2018;21(3):267–94. https://doi.org/10.1007/s10567-018-0261-x .

Desjarlais M, Joseph JJ. Socially interactive and passive technologies enhance friendship quality: an investigation of the mediating roles of online and offline self-disclosure. Cyberpsychol Behav Soc Netw. 2017;20(5):286–91. https://doi.org/10.1089/cyber.2016.0363 .

Sampasa-Kanyinga H, Goldfield GS, Kingsbury M, Clayborne Z, Colman I. Social media use and parent–child relationship: a cross-sectional study of adolescents. J Community Psychology. 2020;48(3):793–803. https://doi.org/10.1002/jcop.22293 .

Davis K. Young people’s digital lives: the impact of interpersonal relationships and digital media use on adolescents’ sense of identity. Comput Hum Behav. 2013;29(6):2281–93. https://doi.org/10.1016/j.chb.2013.05.022 .

Braun V, Clarke V. To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales. Qualitative research in sport, exercise and health. 2021;13(2):201–16. https://doi.org/10.1080/2159676X.2019.1704846 .

Download references

Acknowledgements

We are extremely grateful to the young people who spoke to us about their experiences of adolescence in the age of social media, and to the teaching staff who took time to organise the interviews.

This study is funded by the National Institute for Health Research (NIHR) School for Public Health Research (SPHR) (Grant Reference Number PD-SPH-2015). CMAH is supported by a Philip Leverhulme Prize. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funders had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Author information

Authors and affiliations.

Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK

Lizzy Winstone, Becky Mars & Judi Kidger

NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, BS8 2BN, UK

Becky Mars & Claire M. A. Haworth

School of Psychological Science, University of Bristol, Bristol, BS8 1TU, UK

Claire M. A. Haworth

The Alan Turing Institute, British Library, London, NW1 2DB, UK

You can also search for this author in PubMed   Google Scholar

Contributions

LW coordinated the study, carried out the interviews and drafted the manuscript; All authors conceived of the study, and participated in its design and in interpretation of the data. BM, CMAH, and JK critiqued the output for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Lizzy Winstone .

Ethics declarations

Ethics approval and consent to participate.

The study was approved by and carried out in accordance with the University of Bristol Faculty of Health Sciences Ethics Committee (Ref: 84883). Informed consent was obtained by parents or legal guardians of participants involved in the study as well as participants themselves.

Consent for publication

Not applicable.

Competing interests

We have no known competing interests to declare.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1..

Social media use and social connectedness: interview topic guide.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Winstone, L., Mars, B., Haworth, C.M.A. et al. Social media use and social connectedness among adolescents in the United Kingdom: a qualitative exploration of displacement and stimulation. BMC Public Health 21 , 1736 (2021). https://doi.org/10.1186/s12889-021-11802-9

Download citation

Received : 17 June 2021

Accepted : 13 September 2021

Published : 24 September 2021

DOI : https://doi.org/10.1186/s12889-021-11802-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Social media
  • Social connectedness
  • Adolescence
  • Peer relationships
  • Family relationships

BMC Public Health

ISSN: 1471-2458

qualitative research paper about social media

Conceptualising and measuring social media engagement: A systematic literature review

  • Review Article
  • Open access
  • Published: 11 August 2021
  • Volume 2021 , pages 267–292, ( 2021 )

Cite this article

You have full access to this open access article

qualitative research paper about social media

  • Mariapina Trunfio 1 &
  • Simona Rossi   ORCID: orcid.org/0000-0003-4384-0002 1  

30k Accesses

35 Citations

Explore all metrics

The spread of social media platforms enhanced academic and professional debate on social media engagement that attempted to better understand its theoretical foundations and measurements. This paper aims to systematically contribute to this academic debate by analysing, discussing, and synthesising social media engagement literature in the perspective of social media metrics. Adopting a systematic literature review, the research provides an overarching picture of what has already been investigated and the existing gaps that need further research. The paper confirms the polysemic and multidimensional nature of social media engagement. It identifies the behavioural dimension as the most used proxy for users' level of engagement suggesting the COBRA model as a conceptual tool to classify and interpret the construct. Four categories of metrics emerged: quantitative metrics, normalised indexes, set of indexes, qualitative metrics. It also offers insights and guidance to practitioners on modelling and managing social media engagement.

Similar content being viewed by others

qualitative research paper about social media

An Alternative Media Experience: LiveLeak

qualitative research paper about social media

What is Qualitative in Qualitative Research

The future of social media in marketing.

Avoid common mistakes on your manuscript.

1 Introduction

Over the last decade, customer engagement has received increasing attention in academic and professional debate (Hollebeek, 2019 ; Kumar et al., 2019 ; Marketing Science Institute, 2020 ; Peltier et al., 2020 ; Rather et al., 2019 ; Rossmann et al., 2016 ). It can be considered a “consumer’s positively brand-related cognitive, emotional and behavioural activity during, or related to, focal consumer/brand interactions” (Hollebeek, 2014 , p.149). Engaged customers display greater brand loyalty and satisfaction (Bowden, 2009 ; Jaakkola & Alexander, 2014 ) and are more likely to contribute to new product development (Haumann et al., 2015 ), service innovation (Kumar et al., 2010 ), and viral marketing activity spread by word of mouth (Wu et al., 2018 ). Customer engagement can also be linked with important brand performance indicators, including sales growth, feedback, and referrals (Van Doorn et al., 2010 ).

Acknowledging the potential of ICTs, scholars and practitioners are experimenting with new ways to capitalise on customer engagement and adapt to the new challenges of digital platforms (Barger et al., 2016 ; Peltier et al., 2020 ). Social media platforms reshaped the dyadic interaction between customers and organisations, creating spaces for digital sharing and engagement. By enabling users to comment, review, create, and share content across online networks, social media provide direct access to brands and allow co-creation processes. As such, the pervasive character of social media with its potential for engaging with customers and building relationships generated much interest in the concept of social media engagement (Barger et al., 2016 ; Hallock et al., 2019 ; Oviedo-García et al., 2014 ; Peltier et al., 2020 ; Schivinski et al., 2016 ). Engaging with customers in real-time and managing many incoming customers’ big data interested academic investigation and opened opportunities for marketers to enhance social media marketing success (Liu et al., 2019 ).

Understanding, monitoring, and measuring social media engagement are key aspects that interest scholars and practitioners who proposed diverse conceptualisations, several indicators and KPIs. With the spread of social media analytics, social networking platforms, digital service providers, marketers, and freelancers developed their metrics to measure engagement with brand-related social media contents and advertising campaigns. At the same time, scholars have pointed out various metrics and procedures that contribute to evaluating social media engagement in different fields (Mariani et al., 2018 ; Muñoz-Expósito et al., 2017 ; Trunfio & Della Lucia, 2019 ). Nevertheless, many of these studies offer a partial perspective of analysis that does not allow the phenomenon to be represented in diverse aspects (Oviedo-García et al., 2014 ). As a result, social media engagement remains an enigma wrapped in a riddle for many executives (McKinsey, 2012 ). How communities across an ever-growing variety of platforms, new forms of customer-brand interactions, different dimensions and cultural differences impact social media engagement measurement represents one of the main challenges (Peltier et al., 2020 ).

Although social media engagement represented a key topic in marketing research (Barger et al., 2016 ; Peltier et al., 2020 ), an overarching perspective of the existing knowledge can drive the investigation of the state of the field, including the study of the research streams, and the analysis of the measurement tools. This paper aims to systematically contribute to the academic debate by analysing, discussing, and synthesising social media engagement literature from the social media metrics perspective. A systematic literature review approach provides an overarching picture of what has already been investigated and the existing gaps that need further research. It contributes towards a systematic advancement of knowledge in the field and offers insights and guidance to practitioners on modelling and managing social media engagement (Tranfield et al., 2003 ).

The remainder of the paper is structured as follows. Section  2 presents the theoretical background of the study on customer engagement and social media engagement. Section  3 describes the methodology used for conducting the systematic literature review (Pickering & Byrne, 2014 ; Tranfield et al., 2003 ). Section  4 presents the bibliometric analysis results, including the year in which research began, the journals that publish most research, and the most relevant authors with publications on the topic. Then, Sect.  5 classifies these studies in terms of four macro-themes, conceptualisations, platforms, measurement, and behaviours and describes the key results available in the literature. Section  6 provides a critical discussion of the findings from the literature review and highlights its key contributions. Lastly, Sect.  7 concludes the study by highlighting its limitations and proposing directions for future research.

2 Theoretical background

2.1 customer engagement.

Although customer engagement research has increased theoretical and managerial relevance (Brodie et al., 2011 ; Hollebeek et al., 2016 , 2019 ; Kumar et al., 2019 ; Vivek et al., 2012 ), to date, there is still no consensus on its definition due to its multidimensional, multidisciplinary and polysemic nature.

Several customer engagement conceptualisations have been proposed in the literature, drawing on various theoretical backgrounds, particularly service-dominant logic, and relationship marketing. From a psychological perspective, one of the first definitions of customer engagement is the one of Bowden ( 2009 ) that conceptualises it as a psychological process that drives customer loyalty. Similarly, Brodie et al. ( 2011 ) define customer engagement as a psychological state that occurs by interactive, co-creative customer experiences with a focal object. Later, focusing on the behavioural aspects, it has been described as the intensity of an individual’s participation in an organisation’s offerings or organisational activities (Vivek et al., 2012 ). More recently, from a value-based perspective, customer engagement has been defined as the mechanics that customers use to add value to the firm (Kumar et al., 2019 ).

Although the perspectives may vary, common elements can be identified in various conceptualisations. Literature generally understands customer engagement as a highly experiential, subjective, and context-dependent construct (Brodie et al., 2011 ) based on customer-brand interactions (Hollebeek, 2018 ). Moreover, scholars agree on its multidimensional nature (Brodie et al., 2013 ; Hollebeek et al., 2016 ; So et al., 2016 ; Vivek et al., 2012 ) encompassing cognitive (customer focus and interest in a brand), emotional (feelings of inspiration or pride caused by a brand), and behavioural (customer effort and energy necessary for interaction with a brand) dimensions. Also, researchers have proposed that customer engagement affects different marketing constructs (Brodie et al., 2011 ; Van Doorn et al., 2010 ). For example, in Bowden’s research (2009), there is evidence to support that customer engagement is a predictor of loyalty. Brodie et al. ( 2011 ) explore its effects on customer satisfaction, empowerment, trust, and affective commitment towards the members of a community. Van Doorn et al. ( 2010 ) propose customer-based drivers, including attitudinal factors such as satisfaction, brand commitment and trust, as well as customer goals, resources, and value perceptions.

2.2 Social media engagement: The academic perspective

Social media engagement has also been investigated as brand-user interaction on social media platforms (Barger et al., 2016 ; De Vries & Carlson, 2014 ; Hallock et al., 2019 ; Oviedo-García et al., 2014 ; Peltier et al., 2020 ; Schivinski et al., 2016 ). However, while conceptual discussions appear to dominate the existing customer engagement literature, research results fragmented when moving to the online context. Scholars agree that social media engagement is a context-specific occurrence of customer engagement (Brodie et al., 2013 ) that reflects customers’ individual positive dispositions towards the community or a focal brand (Dessart, 2017 ). Social media engagement can emerge with respect to different objects: the community, representing other customers in the network, and the brand (Dessart, 2017 ). Furthermore, antecedents and consequences of social media engagement have been identified to understand why customers interact on social media and the possible outcomes (Barger et al., 2016 ), such as loyalty, satisfaction, trust, and commitment (Van Doorn et al., 2010 ).

In continuity with literature on customer engagement, also social media engagement can be traced back to affective, cognitive, and behavioural dimensions (Van Doorn et al., 2010 ). Most of the literature focuses on the behavioural dimension as it can be expressed through actions such as liking, commenting, sharing, and viewing contents from a brand (Barger et al., 2016 ; Muntinga et al., 2011 ; Oh et al., 2017 ; Oviedo-García et al., 2014 ; Peltier et al., 2020 ; Rietveld et al., 2020 ; Schivinski et al., 2016 ). It is worth pointing out that not all these actions determine the same level of engagement. Schivinski et al. ( 2016 ) in the COBRA (Consumer Online Brand Related Activities) Model differentiate between three levels of social media engagement: consumption, contribution, and creation. Consumption constitutes the minimum level of engagement and is the most common brand-related activity among customers (e.g., viewing brand-related audio, video, or pictures). Contribution denotes the response in peer-to-peer interactions related to brands (e.g., liking, sharing, commenting on brand-related contents). Creation is the most substantial level of the online brand-related activities that occur when customers spontaneously participate in customising the brand experiences (e.g., publishing brand-related content, uploading brand-related video, pictures, audio or writing brand-related articles). Starting from these social media actions, scholars attempted to measure social media engagement in several ways developing scales, indexes, and metrics (Harrigan et al., 2017 ; Oviedo-García et al., 2014 ; Schivinski et al., 2016 ; Trunfio & Della Lucia, 2019 ). Nevertheless, many of these studies offer a partial perspective of analysis that does not allow the phenomenon to be represented in its diverse aspects (Oviedo-García et al., 2014 ). Researchers have also examined emotional and cognitive dimensions (Dessart, 2017 ) as essential components of social media engagement that lead to positive brand outcomes (Loureiro et al., 2017 ).

2.3 Social media engagement: The practitioners’ perspective

In business practice, the concept of customer engagement appeared for the first time in 2006 when the Advertising Research Foundation (ARF), in conjunction with the American Association of Advertising Agencies and the Association of National Advertisers, defined it as a turning on a prospect to a brand idea enhanced by the surrounding context (ARF, 2006 ) . Later, several consulting firms tried to give their definition emphasising different aspects and perspectives. For example, in 2008, Forrester Consulting, an American market research company, defined customer engagement as a way to create ‘deep connections with customers that drive purchase decisions, interaction, and participation over time’ (Forrester Consulting, 2008 , p.4). Gallup Consulting identified four levels of customer engagement and defined it as an emotional connection between customers and companies (Gallup Consulting, 2009 ). Similarly, the famous American software provider Hubspot ( 2014 ) identified social media engagement as ‘ the ongoing interactions between company and customer, offered by the company, chosen by the customer’ (Hubspot, 2014 , p.1).

With the increasing spread of social networks and their exploitation as an important marketing tool, practitioners recognised a clear linkage between customer engagement and the metrics to assess digital strategy success. Over time, social networking platforms such as Facebook, LinkedIn, and YouTube, developed their metrics to measure engagement with brand-related social media contents and advertising campaigns (Table 1 ).

With the spread of social media analytics, platforms and digital service providers developed dashboards and analytical indicators to assess, measure and monitor the engagement generated by social media marketing activities (Table 2 ). At the same time, many bloggers, marketers, and freelancers have weighed in on the topic, enriching the debate with new contributions.

As a result, while scholars still have to agree upon a shared definition of social media engagement, marketers have recognised it as one of the most important online outcome companies need to deliver with social media and a key metric to assess social media strategy success . Despite the growing interest in business practice and its solid traditional theoretical roots, most of the existing literature on social media engagement offers only conceptual guidelines (Barger et al., 2016 ; Peltier et al., 2020 ). The measurement of engagement in social media and its financial impact remains an enigma wrapped in a riddle for many executives (McKinsey, 2012 ) and requires further investigations. Mainly, how new and emerging platforms, new forms of customer-brand interactions, different dimensions, and cultural differences impact social media engagement measurement remains an understudied phenomenon (Peltier et al., 2020 ).

3 Methodology

The literature review is one of the most appropriate research methods, which aims to map the relevant literature identifying the potential research gaps that need further research to contribute towards a systematic advancement of new knowledge in the field (Tranfield et al., 2003 ). This research is built upon the rigorous, transparent, and reproducible protocol of the systematic literature review as a scientific and transparent process that reduces the selection bias through an exhaustive literature search (Pencarelli & Mele, 2019 ; Pickering & Byrne, 2014 ; Tranfield et al., 2003 ). Building on recent studies (Inamdar et al., 2020 ; Linnenluecke et al., 2020 ; Phulwani et al., 2020 ), in addition to the systematic literature review, a bibliometric analysis (Li et al., 2017 ) was also performed to provide greater comprehensions into the field's current state and highlight the future research directions.

3.1 Database, keywords, inclusion, and exclusion criteria

To conduct a literature review, quality journals are considered the basis for selecting quality publications (Wallace & Wray, 2016 ). Therefore, the database Scopus, run by Elsevier Publishing, was considered to search for relevant literature, being the most significant abstract and citation source database used in recent reviews.

When conducting a literature review, a fundamental issue is determining the keywords that allow identifying the papers (Aveyard, 2007 ). To address it, the most frequently used keywords in peer-reviewed literature have been under investigation. As such, the following research chain was used: “Social media” “Engagement” AND “metric*”, searching under title, abstract, and keywords.

The systematic literature review protocol (Fig.  1 ) has been conducted on the 26 th of March 2020. The study considers an open starting time to trace back to the origin of social media engagement metrics research up to late March 2020. The initial search attempts identified 259 documents.

figure 1

The systematic literature review protocol

After the articles’ identification, criteria for inclusion and exclusion were adopted. First, the 259 articles were screened, considering English-language articles published in peer-reviewed academic journals to safeguard the quality and effectiveness of the review. Due to variability in the peer-review process and their limited availability, book reviews, editorials, and papers from conference proceedings were excluded from this research. After the screening, a sample of 157 papers was obtained.

Afterwards, the full text of these papers was reviewed to assess eligible articles. As a result, 116 articles were excluded because their subject matter was not closely related to the topic of social media engagement metrics. In detail, papers were excluded when: 1) they mainly focused on social media engagement but superficially touched the metrics or 2) they mainly focused on metrics but superficially touched on social media engagement. In the end, 41 eligible articles were identified.

3.2 Analysis tools

The relevant data of the 41 documents in the final sample were saved and organised in a Microsoft Excel spreadsheet to include all the essential paper information such as paper title, authors’ names, and affiliations, abstract, keywords and references. Then, adopting the bibliometrics analysis method (Aria & Cuccurullo, 2017 ), the R-Tool ‘Biblioshiny for Bibliometrix’ was used to perform a comprehensive bibliometric analysis. Bibliometrix is a recent R-package that facilitates a more complete bibliometric analysis, employing specific tools for both bibliometric and scientometric quantitative research (Aria & Cuccurullo, 2017 ; Dervis, 2019 ; Jalal, 2019 ).

4 An overview of social media engagement metrics research.

The bibliometric analysis provided information on the 41 articles, allowing to highlight the significance of the topic.

4.1 Publication trend

The number of annual publications shows a rollercoaster trend (Fig.  2 ). Although the first relevant paper was published in 2013, only since 2016 publications begun to increase significantly with a slight decrease in 2018. This renders social media engagement metrics a relatively young research field.

figure 2

Timeline of the studies (January 2013- March 2020)

It is worth pointing out that the articles extraction was done in March 2020: this explains the low number of articles published in 2020.

4.2 Most relevant sources

When looking at the Journal sources overview, the analysis revealed 34 journals covering different fields, including marketing, management, economics, tourism and hospitality, engineering, communication, and technology. As shown in Fig.  3 , only four journals have more than two publications: Internet Research , Journal of Engineering and Applied Sciences , International Journal of Sports Marketing and Sponsorship. and Online Information Review .

figure 3

Most relevant sources

4.3 Seminal papers

Interesting findings emerged considering the most global cited documents that allow identifying the seminal articles in according to the timeliness, utility and quality, expressed by the scientific community (Okubo, 1997 ). The number of citations an article receives, and the studies cited in an article are two of the most popular bibliometric indicators used to determine the popularity of a publication.

Figure  4 shows the number of author citations for each article, identifying as seminal works: Malthouse’s (2013) paper ‘ Managing Customer Relationships in the Social Media Era: Introducing the Social CRM House’ with 278 global citations; Sabate’s (2014) paper ‘Factors influencing popularity of branded content in Facebook fan pages’ with 145 global citations; Mariani’s (2016) paper ‘ Facebook as a destination marketing tool: Evidence from Italian regional Destination Management Organizations ’ with 104 global citations; Oh’s (2017) paper ‘ Beyond likes and tweets: Consumer engagement behavior and movie box office in social media ’ with 54 global citations; Colicev’s (2018)’ Improving consumer mindset metrics and shareholder value through social media: The different roles of owned and earned media ’ with 39 global citations; Rossmann’s (2016) ‘ Drivers of user engagement in eWoM communication ’ with 35 global citations; Oviedo-Garcia’s (2014) ‘ Metric proposal for customer engagement in Facebook’ with 33 global citations .

figure 4

Most cited articles

The analysis of the papers reviewed revealed that the theme of social media engagement metrics turns out to be a hot topic and a newly emerging stream of research.

5 Social media engagement: areas of investigation

In recent years social media engagement has gained relevance in academic research, and many scholars have questioned its measurement, intensifying the academic debate with ever new contributions. Following previous studies, a comprehensive analysis allows framing the following categories of broad research subjects, used to conduct the subsequent systematic literature review (Fig.  5 ): (1) conceptualisation, (2) platforms, (3) measurement and (4) behaviours. All 41 articles were analysed according to the proposed scheme.

figure 5

Areas of investigation

5.1 Investigating social media engagement

What emerges from the analysis of the 41 papers is that scholars used different approaches and methodologies to conceptualise and measure engagement in the digital context of social media.

As shown in Fig.  6 , most studies (66%) employ quantitative methodologies. For instance, Yoon et al. ( 2018 ) explored the relationship between digital engagement metrics and financial performance in terms of company revenue, confirming that customer engagement on a company’s Facebook fan page can influence revenue. Colicev et al. ( 2018 ) developed three social media metrics, including engagement, to study the effects of earned social media and owned social media on brand awareness, purchase intention, and customer satisfaction. In comparison, Wang and Kubickova ( 2017 ) examined factors affecting the engagement metrics of Facebook fan pages in the Northeast America hotel industry, factors such as time-of-day, day-of-week, age, gender and distance between the hotel and users’ origin of residence. They also analysed the impact of Facebook engagement on electronic word-of-mouth (eWOM), to better understand the importance of the engagement metrics within the hospitality context.

figure 6

Classification of the 41 articles based on the methodology applied

From a qualitative point of view (17% of the papers), Hallock et al. ( 2019 ) used a case study approach to understand the firm perspective on social media engagement metrics, shedding light on how companies view engagement with social media as measurable metrics of customer interactions with the platform. Conversely, Michopoulou and Moisa ( 2019 ) used the same approach to investigate the use of social media marketing metrics and practices in the U.K. hotel industry.

Only a small part of the studies analysed (10% of the papers) explores social media engagement from a purely conceptual perspective. In this sense, Oviedo-Garcìa et al. ( 2014 ) and Muñoz-Expósito et al. ( 2017 ) directly identified social media engagement metrics for Facebook and Twitter, providing fascinating insights for scholars and practitioners.

Finally, among the papers analysed, only three studies (7% of the papers) use mixed methodologies to explore the phenomenon from qualitative and quantitative perspectives.

5.2 Defining social media engagement

Researchers identified 30 unique definitions of engagement applied to the social media context. Multiple definitions used several terms when defining engagement on social media. They were not singular and straightforward but were interspersed with various key terms and overlapping concepts, as presented in Table 3 .

The presence of synonymous terms directly addresses the lack of a standard definition and the challenges that this presents to researchers and practitioners in the field (Table 4 ).

As a relevant result, most authors focus on its behavioural manifestation (22% of the studies) resulting from motivational drivers when defining social media engagement. It is considered as the active behavioural efforts that both existing and potential customers exert toward online brand-related content (Yoon et al., 2018 ). It involves various activities that range from consuming content, participating in discussions, and interacting with other customers to digital buying (Oh et al., 2017 ; Yoon et al., 2018 ). Similarly, in addition to the behavioural manifestations, other scholars (12%) focus on the emotional connection expressed through the intensity of interactions and their implications, toward the offers and activities of a brand, product, or firm, regardless of whether it is initiated by the individual or by the firm (Muñoz-Expósito et al., 2017 ).

Shifting the observation lens from the customers to the firms, another group of scholars (10% of the studies) define social media engagement as the non-monetary return that derives from the online marketing strategies of brands (Khan, 2017 ; Medjani et al., 2019 ; Michopoulou & Moisa, 2019 ). In this case, engagement is viewed exclusively as a non-financial metric and as a measure of the performance of social media marketing activities.

Lastly, a small percentage of studies (10% of the studies) considers engagement as the number of people who acknowledge agreement or preference for content, who participate in creating, sharing and using content (Colicev et al., 2018 ; Li et al., 2019 ; Rahman et al., 2017 ).

5.3 Social Media Platforms

In a total of 41 articles reviewed, 85% of studies mention the platforms analysed, as shown in Table 5 . Facebook is the most popular platform analysed, followed by Twitter, YouTube, LinkedIn, and Instagram. These results were rather expected, given the fact that Facebook, with 2.6 billion monthly active users (Facebook, May 2020), is the most popular social media platform worldwide.

An interesting finding is that there are several articles (15% of the studies) which do not refer to a specific platform or that consider all the platforms together, when measuring social media engagement (e.g., Hallock et al., 2019 ; Medjani et al., 2019 ). This is interesting, given that each social network has different features that make the engagement measurement unique and not replicable.

5.4 Measuring social media engagement

The systematic literature review confirms that there is no theoretical certainty or solid consensus among scholars about measuring engagement on social media.

As can be seen from Table 6 , studies on social media engagement metrics can be grouped and classified into four macro-categories. The first group of studies, namely ‘quantitative metrics’, which is also the most numerous (66% of the studies), attempts to propose a simplistic assessment of the impact of social media engagement, based on the number of comments, likes, shares, followers etc. (Khan et al., 2019 ; Medjani et al., 2019 ; Yoon et al., 2018 ).

The second group of studies (17% of the studies), namely ‘normalised indexes’, provide a quantitative evaluation of the engagement a content generates in relation to the number of people to whom that content has been displayed. In this way, it is possible to obtain an average measure of the users’ engagement, dividing the total actions of interest by the total number of posts (Osokin, 2019 ; Zanini et al., 2019 ), the number of followers (Vlachvei & Kyparissi, 2017 ) or the number of people reached by a post (Muñoz-Expósito et al., 2017 ; Rossmann et al., 2016 ).

In a more complex and detailed way, studies from the third group (10% of the studies) identify social media engagement metrics developing ‘set of indexes’. For example, Li et al. ( 2019 ) use three social media metrics to measure engagement in the casual-dining restaurant setting: rates of conversation, amplification, and applause. In detail, conversation rate measures the number of comments or reviews in response to a post, amplification rate measures how much online content is shared, and applause rate measures the number of positive reactions on posts. Similarly, drawing from previous literature, Mariani et al. ( 2018 ) develop three social media metrics, namely generic engagement, brand engagement, and user engagement. Authors calculated these metrics by assessing different weights to different interaction actions, to emphasise the degree of users’ involvement implied by the underlying activities of respectively liking, sharing, or commenting.

Despite their great diffusion among academics and practitioners, some scholars (7% of the studies) argue that quantitative metrics are not enough to appreciate the real value of customer engagement on social media, and a qualitative approach is more suitable. For example, Abuljadail and Ha ( 2019 ) conducted an online survey of 576 Facebook users in Saudi Arabia to examine customer engagement on Facebook. Rogers ( 2018 ) critiques contemporary social media metrics considered ‘vanity metrics’ and repurpose alt metrics scores and other engagement measures for social research—namely dominant voice, concern, commitment, positioning, and alignment—to measure the ‘otherwise engaged’.

5.5 Social media engagement brand-related activities

When measuring social media engagement, scholars dealt with different social media actions that can be classified (Table 7 ) according to the three dimensions of the COBRA model (Consumer Online Brand Related Activities): consumption, contribution, or creation (Schivinski et al., 2016 ).

In a total of 41 articles reviewed, the most investigated dimension by researchers is contribution, i.e. when a customer comments, shares, likes a form of pre-existing brand content (e.g., Buffard et al., 2020 ; Khan et al., 2019 ). Its popularity among the studies may be due to its interactive nature of “liking” and “commenting”, which can be said to be the most common behaviour exhibited across social media platforms and often one of the most manageable interactions to obtain data. Additionally, studies that include creation in the measurement of social media engagement consider posting/publishing brand-related content, uploading brand-related video, pictures, audio or writing brand-related articles (e.g., Zanini et al., 2019 ). Among the sampled papers, the least investigated dimension of the COBRA model is consumption, considered by only seven studies (e.g., Colicev et al., 2018 ; Oh et al., 2017 ). It considers viewing brand-related audio, video, and pictures, following threads on online brand community forums or downloading branded widgets.

Dimensions have been investigated individually, for example, just considering the number of likes or comments (Khan et al., 2019 ; Yoon et al., 2018 ), or jointly using composite indicators, as in the case of Oviedo-Oviedo-García et al., 2014 ).

6 Discussion

This research presents fresh knowledge in the academic debate by providing an overarching picture of social media engagement, framing the phenomenon conceptually and offering a lens to interpret platforms and measuring tools. Conceptual and empirical studies tried to define, conceptualise, and measure social media engagement in diverse ways from different fields of research. They increased the gap between academia and managerial practice, where the topic of social media engagement metrics seems to be much more consolidated. The paper contributes to the academic debate on social media engagement, presenting continuity and discontinuity elements between different fields of enquiry. It also offers avenues for future research that both academics and marketers should explore. It also provides insights and guidance to practitioners on modelling and managing social media engagement.

6.1 Theoretical contribution

The article offers some theoretical contributions to this relatively young research field through the systematic literature review approach.

Firstly, the paper confirms the multidimensional and polysemic nature of engagement, even in the specific context of social media platforms, in continuity with the academic customer engagement research (Brodie et al., 2013 ; Hollebeek et al., 2016 ; So et al., 2016 ; Vivek et al., 2012 ). The concept of social media engagement can be traced back to three dimensions of analysis (Van Doorn, 2010 )—affective, cognitive, and behavioural—and some empirical studies measure it as such (Dessart, 2017 ; Vivek et al., 2014 ). However, the behavioural dimension is still the most used proxy to measure users’ level of engagement. Similarly, marketers and social media platforms have focused on behavioural interactions associated with likes, comments and sharing when reporting engagement metric (Peltier et al., 2020 ). What is worth pointing out is that emotional and cognitive dimensions are also essential components of social media engagement and should be adequately addressed by future research.

Secondly, strictly related to the first point, the paper suggests the COBRA model (Schivinski, 2016 ) as a conceptual tool to classify and interpret social media engagement from the behavioural perspective. Social media engagement can be manifested symbolically through actions (Barger et al., 2016 ; Oh et al., 2017 ; Van Doorn et al., 2010 ) that can be traced back to the three dimensions of consumption, contribution and creation (Schivinski et al., 2016 ). However, it is worth pointing out that not all these actions determine the same level of engagement. When measuring social media engagement, researchers should pay attention not only to ‘contribution’ but also to ‘consumption’ and ‘creation’, which are important indicators of the attention a post receives (Oviedo-Garcìa, 2014 ; Schivinski et al., 2016 ), giving them a different weight. It becomes even more important if considering that the same social networks provide different weights to users' actions. For example, in several countries, Instagram has tested removing the like feature on content posted by others, although users can still see the number of likes on their posts. YouTube has also decided to stop showing precise subscriber counts and Facebook is experimenting with hiding like counts, similar to Instagram.

Thirdly, the paper presents some of the key metrics used to evaluate social media engagement identifying quantitative metrics, normalised indexes, set of indexes and qualitative metrics. Although all indicators are based on the interaction between the user and the brand, as the literature suggests (Barger et al., 2016 ; Oviedo-Garcìa, 2014 ; Vivek et al., 2014 ), the paper argues that different metrics measure diverse aspects of social media engagement and should be used carefully by researchers. Despite the conceptual and qualitative research on the topic, even the most recent metrics offer measurements that do not allow engagement to be widely represented in its multidimensional and polysemic nature (Oviedo-García et al., 2014 ; Peltier et al., 2020 ). To get a deeper understanding of the construct, researchers should also consider some of the most recent advances in business practice. As an example, more and more practitioners have the chance to measure engagement by tracking the time spent on content and web pages to blend the different types of material, such as pictures, text, or even videos. Also, cursor movements, which are known to correlate with visual attention, and eye-tracking, can provide insights into the within-content engagement.

6.2 Managerial implications

Even if the topic of social media engagement seems to be more consolidated in business practice, this study also provides valuable implications for practitioners. Particularly, the findings shed light on the nature of social media engagement construct and on how metrics can be an extremely useful tool to evaluate, monitor, and interpret the effectiveness of social media strategies and campaigns.

This research offers a strategic-operational guide to the measurement of social media engagement, helping marketers understand what engagement is and choose the most effective and suitable KPIs to assess the performance and success of their marketing efforts. In this sense, marketers should accompany traditional metrics, such as likes, comments and shares, with new metrics capable of better capturing user behaviours.

Marketers also need to realise that engagement is a complex construct that goes beyond the simple behavioural dimension, encompassing cognitive and emotional traits. As a result, in some cases, the so-called “vanity metrics” could fail in fully representing all the aspects of social media engagement. In these cases, it should be accompanied by qualitative insights to analyse what users like to share or talk about and not merely look at likes, comments, and shares counts.

7 Limitations and future research

This research is not without limitations. First, the systematic literature review only includes English articles published in Journals. As social media engagement and engagement metrics are emerging research topics, conference proceedings and book chapters could also be included to deepen the understanding of the subject. Second, this research was conducted on the database Scopus of Elsevier for the keywords “social media engagement metrics”. Researchers could use a combination of different databases and keywords to search for new contributions and insights. Third, although the paper is based on a systematic literature review, this methodology reveals the subjectivity in the social sciences.

As this is a relatively young field of research, a further academic investigation is needed to overcome the limitations of the study and outline new scenarios and directions for future research. In addition, considering the growing importance of social media, there is value in broadening the analysis through additional studies. Future marketing research could use mixed approaches to integrate the three dimensions of social media engagement, linking qualitative and quantitative data. Advanced sentiment web mining techniques could be applied to allow researchers to analyse what users like to share or talk about and not merely look at likes, comments, and shares as the only metrics (Peltier et al., 2020 ).

Although Facebook and Twitter are the most used social network by brands, and the most significant part of the literature focuses on these two platforms, researchers should not forget that there are new and emerging social media in different countries (e.g., TikTok, Clubhouse). They already represent a hot topic for practitioners and are calling scholars to define new metrics to measure engagement. Additionally, as the use of social media increased during the COVID-19 pandemic, future research should take this into account to better understand social media engagement across different social media platforms.

Abuljadail, M., & Ha, L. (2019). Engagement and brand loyalty through social capital in social media. International Journal of Internet Marketing and Advertising, 13 (3), 197–217. https://doi.org/10.1504/IJIMA.2019.102557

Article   Google Scholar  

Advertising Research Foundation. (2006). Engagement: Definitions and Anatomy . ARF White Paper. https://thearf.org/ . Retrieved 5 May 2021

Aggrawal, N., & Arora, A. (2019). Behaviour of viewers: YouTube videos viewership analysis. International Journal of Business Innovation and Research, 20 (1), 106–128. https://doi.org/10.1504/IJBIR.2019.101692

Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11 (4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007

Aswani, R., Ghrera, S. P., Kar, A. K., & Chandra, S. (2017). Identifying buzz in social media: A hybrid approach using artificial bee colony and k-nearest neighbors for outlier detection. Social Network Analysis and Mining, 7 (1), 1–10. https://doi.org/10.1007/s13278-017-0461-2

Aveyard, H. (2007). Doing a Literature Review in Health and Social Care: A practical guide . Pennsylvania Plaza New York: McGrow Hill.

Google Scholar  

Barger, V., Peltier, J. W., & Schultz, D. E. (2016). Social media and consumer engagement: A review and research agenda. Journal of Research in Interactive Marketing, 10 (4), 268–287. https://doi.org/10.1108/JRIM-06-2016-0065

Bowden, J. (2009). The process of customer engagement: A conceptual framework. Journal of Marketing Theory and Practice, 17 (1), 63–74.

Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of Service Research, 14 (3), 252–271. https://doi.org/10.2753/MTP1069-6679170105

Brodie, R. J., Ilic, A., Juric, B., & Hollebeek, L. (2013). Consumer engagement in a virtual brand community: An exploratory analysis. Journal of Business Research, 66 (1), 105–114. https://doi.org/10.1016/j.jbusres.2011.07.029

Buffard, J., & Papasava, A. (2020). A quantitative study on the impact of emotion on social media engagement and conversion. Journal of Digital and Social Media Marketing, 7 (4), 355–375.

Colicev, A., Malshe, A., Pauwels, K., & O’Connor, P. (2018). Improving consumer mindset metrics and shareholder value through social media: The different roles of owned and earned media. Journal of Marketing, 82 (1), 37–56. https://doi.org/10.1509/jm.16.0055

De Vries, N. J., & Carlson, J. (2014). Examining the drivers and brand performance implications of customer engagement with brands in the social media environment. Journal of Brand Management, 21 (6), 495–515. https://doi.org/10.1057/bm.2014.18

Dervis, H. (2019). Bibliometric analysis using bibliometrix an R package. Journal of Scientometric Research, 8 (3), 156–160. https://doi.org/10.5530/jscires.8.3.32

Dessart, L. (2017). Social media engagement: A model of antecedents and relational outcomes. Journal of Marketing Management, 33 (5–6), 375–399. https://doi.org/10.1080/0267257X.2017.1302975

Dolan, R., Conduit, J., Fahy, J., & Goodman, S. (2017). Social media: Communication strategies, engagement and future research directions. International Journal of Wine Business Research, 29 (1), 2–19. https://doi.org/10.1108/IJWBR-04-2016-0013

Forrester Consulting. (2008). How engaged are your customers? . Forrester Consuting. http://docplayer.net/9663683-How-engaged-are-your-customers.html . Retrieved 5 May 2021

Gallup Consulting. (2009). Customer engagement: What’s your engagement ratio? . Gallup Consulting. https://strengthszone.com/wp-content/uploads/2016/01/Customer-Engagement-Ratio-Brochure.pdf . Retrieved 5 May 2021

Gruner, R. L., & Power, D. (2018). To integrate or not to integrate? Understanding B2B social media communications. Online Information Review, 42 (1), 73–92. https://doi.org/10.1108/OIR-04-2016-0116

Guidry, J. P. D., Waters, R. D., & Saxton, G. D. (2014). Moving social marketing beyond personal change to social change: Strategically using Twitter to mobilize supporters into vocal advocates. Journal of Social Marketing, 4 (3), 240–260. https://doi.org/10.1108/JSOCM-02-2014-0014

Hallock, W., Roggeveen, A. L., & Crittenden, V. (2019). Firm-level perspectives on social media engagement: An exploratory study. Qualitative Market Research, 22 (2), 217–226. https://doi.org/10.1108/QMR-01-2017-0025

Harrigan, P., Evers, U., Miles, M., & Daly, T. (2017). Customer engagement with tourism social media brands. Tourism Management, 59 , 597–609. https://doi.org/10.1016/j.tourman.2016.09.015

Haumann, T., Güntürkün, P., & Schons, L. M. (2015). Engaging customers in coproduction processes: How value-enhancing and intensity-reducing communication strategies mitigate the negative effects of coproduction intensity. Journal of Marketing, 79 (6), 17–33. https://doi.org/10.1509/jm.14.0357

Hollebeek, L. D. (2018). Individual-level cultural consumer engagement styles: Conceptualization, propositions and implications. International Marketing Review , 35 , 42–71.

Hollebeek, L. D. (2019). Developing business customer engagement through social media engagement-platforms: An integrative S-D logic/RBV-informed model. Industrial Marketing Management, 81 , 89–98. https://doi.org/10.1016/j.indmarman.2017.11.016

Hollebeek, L. D., Conduit, J., & Brodie, R. J. (2016). Strategic drivers, anticipated and unanticipated outcomes of customer engagement. Journal of Marketing Management, 32 (5–6), 393–398. https://doi.org/10.1080/0267257X.2016.1144360

Hollebeek, L. D., Glynn, M. S., & Brodie, R. J. (2014). Consumer brand engagement in social media: Conceptualization, scale development and validation. Journal of Interactive Marketing, 28 (2), 149–165. https://doi.org/10.1016/j.intmar.2013.12.002

Hollebeek, L. D., Srivastava, R. K., & Chen, T. (2019). S-D logic–informed customer engagement: Integrative framework, revised fundamental propositions, and application to CRM. Journal of the Academy of Marketing Science, 47 (1), 161–185. https://doi.org/10.1007/s11747-016-0494-5

Hubspot. (2014). CRM expert Paul Greenberg defines customer engagement . Hubspot. https://blog.hubspot.com/sales/paul-greenberg-defines-customer-engagement . Retrieved 5 May 2021

Inamdar, Z., Raut, R., Narwane, V. S., Gardas, B., Narkhede, B., & Sagnak, M. (2020). A systematic literature review with bibliometric analysis of big data analytics adoption from period 2014 to 2018. Journal of Enterprise Information Management, 34 (1), 101–139. https://doi.org/10.1108/JEIM-09-2019-0267

Jaakkola, E., & Alexander, M. (2014). The role of customer engagement behavior in value co-creation: A service system perspective. Journal of Service Research, 17 (3), 247–261. https://doi.org/10.1177/1094670514529187

Jalal, S. K. (2019). Co-authorship and co-occurrences analysis using bibliometrix r-package: A case study of india and bangladesh. Annals of Library and Information Studies, 66 (2), 57–64.

Kalinić, Č, & Vujičić, M. (2019). A subnational assessment of hotel social media metrics - The case of Serbia. Geographica Pannonica, 23 (2), 87–101.

Khan, G., Mohaisen, M., & Trier, M. (2019). The network ROI: Concept, metrics, and measurement of social media returns (a Facebook experiment). Internet Research, 30 (2), 631–652. https://doi.org/10.1108/INTR-07-2018-0346

Khan, I., Dongping, H., & Wahab, A. (2016). Does culture matter in effectiveness of social media marketing strategy? An investigation of brand fan pages. Aslib Journal of Information Management, 68 (6), 694–715. https://doi.org/10.1108/AJIM-03-2016-0035

Khan, M. L. (2017). Social media engagement: What motivates user participation and consumption on YouTube? Computers in Human Behavior, 66 , 236–247. https://doi.org/10.1016/j.chb.2016.09.024

Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T., & Tillmanns, S. (2010). Undervalued or overvalued customers: Capturing total customer engagement value. Journal of Service Research, 13 (3), 297–310. https://doi.org/10.1177/1094670510375602

Kumar, V., Rajan, B., Gupta, S., & Dalla Pozza, I. (2019). Customer engagement in service. Journal of the Academy of Marketing Science, 47 (1), 138–160. https://doi.org/10.1007/s11747-017-0565-2

Le, T. D. (2018). Influence of WOM and content type on online engagement in consumption communities : The information flow from discussion forums to Facebook. Online Information Review, 42 (2), 161–175. https://doi.org/10.1108/OIR-09-2016-0246

Li, J., Kim, W. G., & Choi, H. M. (2019). Effectiveness of social media marketing on enhancing performance: Evidence from a casual-dining restaurant setting. Tourism Economics, 20 (10), 1–20. https://doi.org/10.1177/1354816619867807

Li, X., Wu, P., Shen, G. Q., Wang, X., & Teng, Y. (2017). Mapping the knowledge domains of building information modeling (BIM): A bibliometric approach. Automation in Construction, 84 , 195–206. https://doi.org/10.1016/j.autcon.2017.09.011

Linnenluecke, M. K., Marrone, M., & Singh, A. K. (2020). Conducting systematic literature reviews and bibliometric analyses. Australian Journal of Management, 45 (2), 175–194. https://doi.org/10.1177/0312896219877678

Liu, X., Shin, H., & Burns, A. C. (2019). Examining the impact of luxury brand’s social media marketing on customer engagement: Using big data analytics and natural language processing. Journal of Business Research . https://doi.org/10.1016/j.jbusres.2019.04.042

Loureiro, S. M. C., Gorgus, T., & Kaufmann, H. R. (2017). Antecedents and outcomes of online brand engagement: The role of brand love on enhancing electronic-word-of-mouth. Online Information Review, 41 (7), 985–1005. https://doi.org/10.1108/OIR-08-2016-0236

Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E., & Zhang, M. (2013). Managing customer relationships in the social media era: Introducing the social CRM house. Journal of Interactive Marketing, 27 (4), 270–280. https://doi.org/10.1016/j.intmar.2013.09.008

Mariani, M. M., Di Felice, M., & Mura, M. (2016). Facebook as a destination marketing tool: Evidence from Italian regional destination management organizations. Tourism Management, 54 , 321–343. https://doi.org/10.1016/j.tourman.2015.12.008

Mariani, M. M., Mura, M., & Di Felice, M. (2018). The determinants of Facebook social engagement for national tourism organizations’ Facebook pages: A quantitative approach. Journal of Destination Marketing and Management, 8 , 312–325. https://doi.org/10.1016/j.jdmm.2017.06.003

Marketing Science Institute. (2020). Research priorities 2020–2022 . Marketing Science Institute. https://www.msi.org/wp-content/uploads/2020/06/MSI_RP20-22.pdf . Retrieved 5 May 2021

McCoy, C. G., Nelson, M. L., & Weigle, M. C. (2018). Mining the Web to approximate university rankings. Information Discovery and Delivery, 46 (3), 173–183. https://doi.org/10.1108/IDD-05-2018-0014

McKinsey. (2012). Demystifyng social media . McKinsey. https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/demystifying-social-media . Retrieved 5 May 2021

Medjani, F., Rutter, R., & Nadeau, J. (2019). Social media management, objectification and measurement in an emerging market. Business and Emerging Markets, 11 (3), 288–311. https://doi.org/10.1504/IJBEM.2019.102654

Michopoulou, E., & Moisa, D. G. (2019). Hotel social media metrics: The ROI dilemma. International Journal of Hospitality Management, 76 , 308–315. https://doi.org/10.1016/j.ijhm.2018.05.019

Muñoz-Expósito, M., Oviedo-García, M. Á., & Castellanos-Verdugo, M. (2017). How to measure engagement in Twitter: Advancing a metric. Internet Research, 27 (5), 1122–1148. https://doi.org/10.1108/IntR-06-2016-0170

Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30 (1), 13–46. https://doi.org/10.2501/IJA-30-1-013-046

Oh, C., Roumani, Y., Nwankpa, J. K., & Hu, H. F. (2017). Beyond likes and tweets: Consumer engagement behavior and movie box office in social media. Information and Management, 54 (1), 25–37. https://doi.org/10.1016/j.im.2016.03.004

Okubo, Y. (1997). Bibliometric indicators and analysis of research systems: methods and examples . Paris: OECD Publishing.

Osokin, N. (2019). User engagement and gratifications of NSO supporters on Facebook: Evidence from European football. International Journal of Sports Marketing and Sponsorship, 20 (1), 61–80. https://doi.org/10.1108/IJSMS-11-2017-0115

Oviedo-García, M. Á., Muñoz-Expósito, M., Castellanos-Verdugo, M., & Sancho-Mejías, M. (2014). Metric proposal for customer engagement in Facebook. Journal of Research in Interactive Marketing, 8 (4), 327–344. https://doi.org/10.1108/JRIM-05-2014-0028

Peltier, J., Dahl, A. J., & VanderShee, B. A. (2020). Antecedent consumer factors, consequential branding outcomes and measures of online consumer engagement: Current research and future directions. Journal of Research in Interactive Marketing, 14 (2), 239–268. https://doi.org/10.1108/JRIM-01-2020-0010

Pencarelli, T., & Mele, G. (2019). A systematic literature review on social media metrics. Mercati & Competitività, 1 , 1–24.

Phulwani, P. R., Kumar, D., & Goyal, P. (2020). A Systematic Literature Review and Bibliometric Analysis of Recycling Behavior. Journal of Global Marketing, 33 (5), 354–376. https://doi.org/10.1080/08911762.2020.1765444

Pickering, C., & Byrne, J. (2014). The benefits of publishing systematic quantitative literature reviews for PhD candidates and other early-career researchers. Higher Education Research & Development,  33 (3), 534–548

Popp, N., McEvoy, C., & Watanabe, N. (2017). Do college athletics marketers convert social media growth into ticket sales? International Journal of Sports Marketing and Sponsorship, 18 (2), 212–227. https://doi.org/10.1108/IJSMS-05-2017-090

Rahman, Z., Suberamanian, K., Zanuddin, H., Moghavvemi, S., & Bin MdNasir, M. H. N. (2016). SNS metrics analysis “A study on fanpage interactive contents.” International Journal of Applied Business and Economic Research, 14 (2), 1405–1415.

Rahman, Z., Suberamanian, K., Zanuddin, H., Moghavvemi, S., & Nasir, M. H. N. M. (2017). Fanpage viral metrics analysis “study on frequently posted contents.” Journal of Engineering and Applied Sciences, 12 (16), 4039–4046.

Rather, R. A., Hollebeek, L. D., & Islam, J. U. (2019). Tourism-based customer engagement: The construct, antecedents, and consequences. The Service Industries Journal, 39 (7–8), 519–540. https://doi.org/10.1080/02642069.2019.1570154

Rietveld, R., Van Dolen, W., Mazloom, M., & Worring, M. (2020). What you feel, is what you like influence of message appeals on customer engagement on Instagram. Journal of Interactive Marketing, 49 , 20–53. https://doi.org/10.1016/j.intmar.2019.06.003

Rogers, R. (2018). Digital traces in context| Otherwise engaged: Social media from vanity metrics to critical analytics. International Journal of Communication, 12 (23), 450–472.

Rossmann, A., Ranjan, K. R., & Sugathan, P. (2016). Drivers of user engagement in eWoM communication. Journal of Services Marketing, 30 (5), 541–553. https://doi.org/10.1108/JSM-01-2015-0013

Sabate, F., Berbegal-Mirabent, J., Cañabate, A., & Lebherz, P. R. (2014). Factors influencing popularity of branded content in Facebook fan pages. European Management Journal, 32 (6), 1001–1011. https://doi.org/10.1016/j.emj.2014.05.001

Schivinski, B., Christodoulides, G., & Dabrowski, D. (2016). Measuring consumers’ engagement with brand-related social-media content: Development and validation of a scale that identifies levels of social-media engagement with brands. Journal of Advertising Research, 56 (1), 64–80. https://doi.org/10.2501/JAR-2016-004

Segijn, C. M., Maslowska, E., Araujo, T., & Viswanathan, V. (2019). Engaging with TV events on Twitter: The interrelations between TV consumption, engagement actors, and engagement content. Internet Research, 30 (2), 381–401. https://doi.org/10.1108/INTR-08-2018-0389

Sitta, D., Faulkner, M., & Stern, P. (2018). What can the brand manager expect from Facebook? Australasian Marketing Journal, 26 (1), 17–22. https://doi.org/10.1016/j.ausmj.2018.01.001

So, K. K. F., King, C., Sparks, B. A., & Wang, Y. (2016). Enhancing customer relationships with retail service brands: The role of customer engagement. Journal of Service Management, 27 (2), 170–193. https://doi.org/10.1108/JOSM-05-2015-0176

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14 (3), 207–222. https://doi.org/10.1111/1467-8551.00375

Trunfio, M., & Della Lucia, M. (2019). Engaging destination stakeholders in the digital era: The best practice of italian regional DMOs. Journal of Hospitality and Tourism Research, 43 (3), 349–373. https://doi.org/10.1177/1096348018807293

Van Doorn, J., Lemon, K. N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P. C. (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, 13 (3), 253–266. https://doi.org/10.1177/1094670510375599

Vivek, S. D., Beatty, S. E., Dalela, V., & Morgan, R. M. (2014). A generalized multidimensional scale for measuring customer engagement. Journal of Marketing Theory and Practice , 22 (4), 401–420.

Vivek, S. D., Beatty, S. E., & Morgan, R. M. (2012). Customer engagement: Exploring customer relationships beyond purchase. Journal of Marketing Theory and Practice, 20 (2), 122–146. https://doi.org/10.2753/MTP1069-6679200201

Vlachvei, A., & Kyparissis, A. (2017). Museums on Facebook wall: A case staudy of Thessaloniki’s museums. Tourismos, 12 (3), 75–96.

Vrettos, K., & Gouscos, D. (2019). Evaluating the presence of Greek tourism-related public sector entities in online social networks. International Journal of Public Administration in the Digital Age, 6 (1), 15–40.

Wallace, M., & Wray, A. (2016). Critical reading and writing for postgraduates . Sage.

Wang, C., & Kubickova, M. (2017). The impact of engaged users on eWOM of hotel Facebook page. Journal of Hospitality and Tourism Technology, 8 (2), 190–204. https://doi.org/10.1108/JHTT-09-2016-0056

Wu, J., Fan, S., & Zhao, J. L. (2018). Community engagement and online word of mouth: An empirical investigation. Information & Management, 55 (2), 258–270. https://doi.org/10.1016/j.im.2017.07.002Get

Yoon, G., Li, C., Ji, Y., North, M., Hong, C., & Liu, J. (2018). Attracting comments: digital engagement metrics on facebook and financial performance. Journal of Advertising, 47 (1), 24–37. https://doi.org/10.1080/00913367.2017.1405753

Zanini, M. T., Carbone de Moraes, F., Lima, V., Migueles, C., Lourenco, C., & Reis Irigaray, H. A. (2019). Soccer and twitter: Virtual brand community engagement practices. Marketing Intelligence and Planning, 37 (7), 791–805. https://doi.org/10.1108/MIP-08-2018-0371

Download references

Open access funding provided by Università Parthenope di Napoli within the CRUI-CARE Agreement.

Author information

Authors and affiliations.

Department of Management and Quantitative Studies, University of Naples “Parthenope”, Naples, Italy

Mariapina Trunfio & Simona Rossi

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Simona Rossi .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Trunfio, M., Rossi, S. Conceptualising and measuring social media engagement: A systematic literature review. Ital. J. Mark. 2021 , 267–292 (2021). https://doi.org/10.1007/s43039-021-00035-8

Download citation

Received : 12 November 2020

Accepted : 29 July 2021

Published : 11 August 2021

Issue Date : September 2021

DOI : https://doi.org/10.1007/s43039-021-00035-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Customer engagement
  • Social media engagement
  • Social media platforms
  • Qualitative metrics
  • Quantitative metrics
  • Social media metrics
  • COBRA model
  • Find a journal
  • Publish with us
  • Track your research

To read this content please select one of the options below:

Please note you do not have access to teaching notes, the power of qualitative research in the era of social media.

Qualitative Market Research

ISSN : 1352-2752

Article publication date: 6 September 2011

The electronic social media such as Twitter, Facebook, MySpace, etc. have become a major form of communication, and the expression of attitudes and opinions, for the general public. Recently, they have also become a source of data for market researchers. This paper aims to provide a critical look at the advantages and limitations of such an approach to understanding brand perceptions and attitudes in the market place. Although the social media provide a wealth of data for automated content analyses, this review questions the validity and reliability of this research approach, and concludes that social media monitoring (SMM) is a poor substitute for in‐depth qualitative research which has many advantages and benefits.

Design/methodology/approach

The paper presents a detailed, systematic comparison of various research approaches. These include well‐established methods and recent inventions which are in use to explore and understand consumer behaviour and attitudes. Particular attention is given to the analysis of spontaneous consumer attitudes as expressed through the social media and also in qualitative research interviews.

This analysis concludes that there are three critical features which differentiate qualitative research (as practised in IDIs and group discussions) from SMM. These are: the direct, interactive dialogue or conversation between consumers and researchers; the facility to “listen” and attend to the (sometimes unspoken) underlying narrative which connects consumers' needs and aspirations, personal goals and driving forces to behaviour and brand choice; and the dynamic, interactive characteristics of the interview that achieve a meeting of minds to produce a shared understanding. Philosophically, it is this “conversation” that gives qualitative research its validity and authenticity which makes it superior to SMM.

Originality/value

This review questions the validity and reliability of the SMM, and concludes that it is a poor substitute for in‐depth qualitative research which has many advantages and benefits.

  • Social media monitoring
  • Qualitative research
  • Research methods
  • Automated content analysis
  • Social media

Branthwaite, A. and Patterson, S. (2011), "The power of qualitative research in the era of social media", Qualitative Market Research , Vol. 14 No. 4, pp. 430-440. https://doi.org/10.1108/13522751111163245

Emerald Group Publishing Limited

Copyright © 2011, Emerald Group Publishing Limited

Related articles

We’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

  • Open access
  • Published: 13 May 2024

What are the strengths and limitations to utilising creative methods in public and patient involvement in health and social care research? A qualitative systematic review

  • Olivia R. Phillips 1 , 2   na1 ,
  • Cerian Harries 2 , 3   na1 ,
  • Jo Leonardi-Bee 1 , 2 , 4   na1 ,
  • Holly Knight 1 , 2 ,
  • Lauren B. Sherar 2 , 3 ,
  • Veronica Varela-Mato 2 , 3 &
  • Joanne R. Morling 1 , 2 , 5  

Research Involvement and Engagement volume  10 , Article number:  48 ( 2024 ) Cite this article

226 Accesses

2 Altmetric

Metrics details

There is increasing interest in using patient and public involvement (PPI) in research to improve the quality of healthcare. Ordinarily, traditional methods have been used such as interviews or focus groups. However, these methods tend to engage a similar demographic of people. Thus, creative methods are being developed to involve patients for whom traditional methods are inaccessible or non-engaging.

To determine the strengths and limitations to using creative PPI methods in health and social care research.

Electronic searches were conducted over five databases on 14th April 2023 (Web of Science, PubMed, ASSIA, CINAHL, Cochrane Library). Studies that involved traditional, non-creative PPI methods were excluded. Creative PPI methods were used to engage with people as research advisors, rather than study participants. Only primary data published in English from 2009 were accepted. Title, abstract and full text screening was undertaken by two independent reviewers before inductive thematic analysis was used to generate themes.

Twelve papers met the inclusion criteria. The creative methods used included songs, poems, drawings, photograph elicitation, drama performance, visualisations, social media, photography, prototype development, cultural animation, card sorting and persona development. Analysis identified four limitations and five strengths to the creative approaches. Limitations included the time and resource intensive nature of creative PPI, the lack of generalisation to wider populations and ethical issues. External factors, such as the lack of infrastructure to support creative PPI, also affected their implementation. Strengths included the disruption of power hierarchies and the creation of a safe space for people to express mundane or “taboo” topics. Creative methods are also engaging, inclusive of people who struggle to participate in traditional PPI and can also be cost and time efficient.

‘Creative PPI’ is an umbrella term encapsulating many different methods of engagement and there are strengths and limitations to each. The choice of which should be determined by the aims and requirements of the research, as well as the characteristics of the PPI group and practical limitations. Creative PPI can be advantageous over more traditional methods, however a hybrid approach could be considered to reap the benefits of both. Creative PPI methods are not widely used; however, this could change over time as PPI becomes embedded even more into research.

Plain English Summary

It is important that patients and public are included in the research process from initial brainstorming, through design to delivery. This is known as public and patient involvement (PPI). Their input means that research closely aligns with their wants and needs. Traditionally to get this input, interviews and group discussions are held, but this can exclude people who find these activities non-engaging or inaccessible, for example those with language challenges, learning disabilities or memory issues. Creative methods of PPI can overcome this. This is a broad term describing different (non-traditional) ways of engaging patients and public in research, such as through the use or art, animation or performance. This review investigated the reasons why creative approaches to PPI could be difficult (limitations) or helpful (strengths) in health and social care research. After searching 5 online databases, 12 studies were included in the review. PPI groups included adults, children and people with language and memory impairments. Creative methods included songs, poems, drawings, the use of photos and drama, visualisations, Facebook, creating prototypes, personas and card sorting. Limitations included the time, cost and effort associated with creative methods, the lack of application to other populations, ethical issues and buy-in from the wider research community. Strengths included the feeling of equality between academics and the public, creation of a safe space for people to express themselves, inclusivity, and that creative PPI can be cost and time efficient. Overall, this review suggests that creative PPI is worthwhile, however each method has its own strengths and limitations and the choice of which will depend on the research project, PPI group characteristics and other practical limitations, such as time and financial constraints.

Peer Review reports

Introduction

Patient and public involvement (PPI) is the term used to describe the partnership between patients (including caregivers, potential patients, healthcare users etc.) or the public (a community member with no known interest in the topic) with researchers. It describes research that is done “‘with’ or ‘by’ the public, rather than ‘to,’ ‘about’ or ‘for’ them” [ 1 ]. In 2009, it became a legislative requirement for certain health and social care organisations to include patients, families, carers and communities in not only the planning of health and social care services, but the commissioning, delivery and evaluation of them too [ 2 ]. For example, funding applications for the National Institute of Health and Care Research (NIHR), a UK funding body, mandates a demonstration of how researchers plan to include patients/service users, the public and carers at each stage of the project [ 3 ]. However, this should not simply be a tokenistic, tick-box exercise. PPI should help formulate initial ideas and should be an instrumental, continuous part of the research process. Input from PPI can provide unique insights not yet considered and can ensure that research and health services are closely aligned to the needs and requirements of service users PPI also generally makes research more relevant with clearer outcomes and impacts [ 4 ]. Although this review refers to both patients and the public using the umbrella term ‘PPI’, it is important to acknowledge that these are two different groups with different motivations, needs and interests when it comes to health research and service delivery [ 5 ].

Despite continuing recognition of the need of PPI to improve quality of healthcare, researchers have also recognised that there is no ‘one size fits all’ method for involving patients [ 4 ]. Traditionally, PPI methods invite people to take part in interviews or focus groups to facilitate discussion, or surveys and questionnaires. However, these can sometimes be inaccessible or non-engaging for certain populations. For example, someone with communication difficulties may find it difficult to engage in focus groups or interviews. If individuals lack the appropriate skills to interact in these types of scenarios, they cannot take advantage of the participation opportunities it can provide [ 6 ]. Creative methods, however, aim to resolve these issues. These are a relatively new concept whereby researchers use creative methods (e.g., artwork, animations, Lego), to make PPI more accessible and engaging for those whose voices would otherwise go unheard. They ensure that all populations can engage in research, regardless of their background or skills. Seminal work has previously been conducted in this area, which brought to light the use of creative methodologies in research. Leavy (2008) [ 7 ] discussed how traditional interviews had limits on what could be expressed due to their sterile, jargon-filled and formulaic structure, read by only a few specialised academics. It was this that called for more creative approaches, which included narrative enquiry, fiction-based research, poetry, music, dance, art, theatre, film and visual art. These practices, which can be used in any stage of the research cycle, supported greater empathy, self-reflection and longer-lasting learning experiences compared to interviews [ 7 ]. They also pushed traditional academic boundaries, which made the research accessible not only to researchers, but the public too. Leavy explains that there are similarities between arts-based approaches and scientific approaches: both attempts to investigate what it means to be human through exploration, and used together, these complimentary approaches can progress our understanding of the human experience [ 7 ]. Further, it is important to acknowledge the parallels and nuances between creative and inclusive methods of PPI. Although creative methods aim to be inclusive (this should underlie any PPI activity, whether creative or not), they do not incorporate all types of accessible, inclusive methodologies e.g., using sign language for people with hearing impairments or audio recordings for people who cannot read. Given that there was not enough scope to include an evaluation of all possible inclusive methodologies, this review will focus on creative methods of PPI only.

We aimed to conduct a qualitative systematic review to highlight the strengths of creative PPI in health and social care research, as well as the limitations, which might act as a barrier to their implementation. A qualitative systematic review “brings together research on a topic, systematically searching for research evidence from primary qualitative studies and drawing the findings together” [ 8 ]. This review can then advise researchers of the best practices when designing PPI.

Public involvement

The PHIRST-LIGHT Public Advisory Group (PAG) consists of a team of experienced public contributors with a diverse range of characteristics from across the UK. The PAG was involved in the initial question setting and study design for this review.

Search strategy

For the purpose of this review, the JBI approach for conducting qualitative systematic reviews was followed [ 9 ]. The search terms were (“creativ*” OR “innovat*” OR “authentic” OR “original” OR “inclu*”) AND (“public and patient involvement” OR “patient and public involvement” OR “public and patient involvement and engagement” OR “patient and public involvement and engagement” OR “PPI” OR “PPIE” OR “co-produc*” OR “co-creat*” OR “co-design*” OR “cooperat*” OR “co-operat*”). This search string was modified according to the requirements of each database. Papers were filtered by title, abstract and keywords (see Additional file 1 for search strings). The databases searched included Web of Science (WoS), PubMed, ASSIA and CINAHL. The Cochrane Library was also searched to identify relevant reviews which could lead to the identification of primary research. The search was conducted on 14/04/23. As our aim was to report on the use of creative PPI in research, rather than more generic public engagement, we used electronic databases of scholarly peer-reviewed literature, which represent a wide range of recognised databases. These identified studies published in general international journals (WoS, PubMed), those in social sciences journals (ASSIA), those in nursing and allied health journals (CINAHL), and trials of interventions (Cochrane Library).

Inclusion criteria

Only full-text, English language, primary research papers from 2009 to 2023 were included. This was the chosen timeframe as in 2009 the Health and Social Reform Act made it mandatory for certain Health and Social Care organisations to involve the public and patients in planning, delivering, and evaluating services [ 2 ]. Only creative methods of PPI were accepted, rather than traditional methods, such as interviews or focus groups. For the purposes of this paper, creative PPI included creative art or arts-based approaches (e.g., e.g. stories, songs, drama, drawing, painting, poetry, photography) to enhance engagement. Titles were related to health and social care and the creative PPI was used to engage with people as research advisors, not as study participants. Meta-analyses, conference abstracts, book chapters, commentaries and reviews were excluded. There were no limits concerning study location or the demographic characteristics of the PPI groups. Only qualitative data were accepted.

Quality appraisal

Quality appraisal using the Critical Appraisal Skills Programme (CASP) checklist [ 10 ] was conducted by the primary authors (ORP and CH). This was done independently, and discrepancies were discussed and resolved. If a consensus could not be reached, a third independent reviewer was consulted (JRM). The full list of quality appraisal questions can be found in Additional file 2 .

Data extraction

ORP extracted the study characteristics and a subset of these were checked by CH. Discrepancies were discussed and amendments made. Extracted data included author, title, location, year of publication, year study was carried out, research question/aim, creative methods used, number of participants, mean age, gender, ethnicity of participants, setting, limitations and strengths of creative PPI and main findings.

Data analysis

The included studies were analysed using inductive thematic analysis [ 11 ], where themes were determined by the data. The familiarisation stage took place during full-text reading of the included articles. Anything identified as a strength or limitation to creative PPI methods was extracted verbatim as an initial code and inputted into the data extraction Excel sheet. Similar codes were sorted into broader themes, either under ‘strengths’ or ‘limitations’ and reviewed. Themes were then assigned a name according to the codes.

The search yielded 9978 titles across the 5 databases: Web of Science (1480 results), PubMed (94 results), ASSIA (2454 results), CINAHL (5948 results) and Cochrane Library (2 results), resulting in 8553 different studies after deduplication. ORP and CH independently screened their titles and abstracts, excluding those that did not meet the criteria. After assessment, 12 studies were included (see Fig.  1 ).

figure 1

PRISMA flowchart of the study selection process

Study characteristics

The included studies were published between 2018 and 2022. Seven were conducted in the UK [ 12 , 14 , 15 , 17 , 18 , 19 , 23 ], two in Canada [ 21 , 22 ], one in Australia [ 13 ], one in Norway [ 16 ] and one in Ireland [ 20 ]. The PPI activities occurred across various settings, including a school [ 12 ], social club [ 12 ], hospital [ 17 ], university [ 22 ], theatre [ 19 ], hotel [ 20 ], or online [ 15 , 21 ], however this information was omitted in 5 studies [ 13 , 14 , 16 , 18 , 23 ]. The number of people attending the PPI sessions varied, ranging from 6 to 289, however the majority (ten studies) had less than 70 participants [ 13 , 14 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Seven studies did not provide information on the age or gender of the PPI groups. Of those that did, ages ranged from 8 to 76 and were mostly female. The ethnicities of the PPI group members were also rarely recorded (see Additional file 3 for data extraction table).

Types of creative methods

The type of creative methods used to engage the PPI groups were varied. These included songs, poems, drawings, photograph elicitation, drama performance, visualisations, Facebook, photography, prototype development, cultural animation, card sorting and creating personas (see Table  1 ). These were sometimes accompanied by traditional methods of PPI such as interviews and focus group discussions.

The 12 included studies were all deemed to be of good methodological quality, with scores ranging from 6/10 to 10/10 with the CASP critical appraisal tool [ 10 ] (Table  2 ).

Thematic analysis

Analysis identified four limitations and five strengths to creative PPI (see Fig.  2 ). Limitations included the time and resource intensity of creative PPI methods, its lack of generalisation, ethical issues and external factors. Strengths included the disruption of power hierarchies, the engaging and inclusive nature of the methods and their long-term cost and time efficiency. Creative PPI methods also allowed mundane and “taboo” topics to be discussed within a safe space.

figure 2

Theme map of strengths and limitations

Limitations of creative PPI

Creative ppi methods are time and resource intensive.

The time and resource intensive nature of creative PPI methods is a limitation, most notably for the persona-scenario methodology. Valaitis et al. [ 22 ] used 14 persona-scenario workshops with 70 participants to co-design a healthcare intervention, which aimed to promote optimal aging in Canada. Using the persona method, pairs composed of patients, healthcare providers, community service providers and volunteers developed a fictional character which they believed represented an ‘end-user’ of the healthcare intervention. Due to the depth and richness of the data produced the authors reported that it was time consuming to analyse. Further, they commented that the amount of information was difficult to disseminate to scientific leads and present at team meetings. Additionally, to ensure the production of high-quality data, to probe for details and lead group discussion there was a need for highly skilled facilitators. The resource intensive nature of the creative co-production was also noted in a study using the persona scenario and creative worksheets to develop a prototype decision support tool for individuals with malignant pleural effusion [ 17 ]. With approximately 50 people, this was also likely to yield a high volume of data to consider.

To prepare materials for populations who cannot engage in traditional methods of PPI was also timely. Kearns et al. [ 18 ] developed a feedback questionnaire for people with aphasia to evaluate ICT-delivered rehabilitation. To ensure people could participate effectively, the resources used during the workshops, such as PowerPoints, online images and photographs, had to be aphasia-accessible, which was labour and time intensive. The author warned that this time commitment should not be underestimated.

There are further practical limitations to implementing creative PPI, such as the costs of materials for activities as well as hiring a space for workshops. For example, the included studies in this review utilised pens, paper, worksheets, laptops, arts and craft supplies and magazines and took place in venues such as universities, a social club, and a hotel. Further, although not limited to creative PPI methods exclusively but rather most studies involving the public, a financial incentive was often offered for participation, as well as food, parking, transport and accommodation [ 21 , 22 ].

Creative PPI lacks generalisation

Another barrier to the use of creative PPI methods in health and social care research was the individual nature of its output. Those who participate, usually small in number, produce unique creative outputs specific to their own experiences, opinions and location. Craven et al. [ 13 ], used arts-based visualisations to develop a toolbox for adults with mental health difficulties. They commented, “such an approach might still not be worthwhile”, as the visualisations were individualised and highly personal. This indicates that the output may fail to meet the needs of its end-users. Further, these creative PPI groups were based in certain geographical regions such as Stoke-on-Trent [ 19 ] Sheffield [ 23 ], South Wales [ 12 ] or Ireland [ 20 ], which limits the extent the findings can be applied to wider populations, even within the same area due to individual nuances. Further, the study by Galler et al. [ 16 ], is specific to the Norwegian context and even then, maybe only a sub-group of the Norwegian population as the sample used was of higher socioeconomic status.

However, Grindell et al. [ 17 ], who used persona scenarios, creative worksheets and prototype development, pointed out that the purpose of this type of research is to improve a certain place, rather than apply findings across other populations and locations. Individualised output may, therefore, only be a limitation to research wanting to conduct PPI on a large scale.

If, however, greater generalisation within PPI is deemed necessary, then social media may offer a resolution. Fedorowicz et al. [ 15 ], used Facebook to gain feedback from the public on the use of video-recording methodology for an upcoming project. This had the benefit of including a more diverse range of people (289 people joined the closed group), who were spread geographically around the UK, as well as seven people from overseas.

Creative PPI has ethical issues

As with other research, ethical issues must be taken into consideration. Due to the nature of creative approaches, as well as the personal effort put into them, people often want to be recognised for their work. However, this compromises principles so heavily instilled in research such as anonymity and confidentiality. With the aim of exploring issues related to health and well-being in a town in South Wales, Byrne et al. [ 12 ], asked year 4/5 and year 10 pupils to create poems, songs, drawings and photographs. Community members also created a performance, mainly of monologues, to explore how poverty and inequalities are dealt with. Byrne noted the risks of these arts-based approaches, that being the possibility of over-disclosure and consequent emotional distress, as well as people’s desire to be named for their work. On one hand, the anonymity reduces the sense of ownership of the output as it does not portray a particular individual’s lived experience anymore. On the other hand, however, it could promote a more honest account of lived experience. Supporting this, Webber et al. [ 23 ], who used the persona method to co-design a back pain educational resource prototype, claimed that the anonymity provided by this creative technique allowed individuals to externalise and anonymise their own personal experience, thus creating a more authentic and genuine resource for future users. This implies that anonymity can be both a limitation and strength here.

The use of creative PPI methods is impeded by external factors

Despite the above limitations influencing the implementation of creative PPI techniques, perhaps the most influential is that creative methodologies are simply not mainstream [ 19 ]. This could be linked to the issues above, like time and resource intensity, generalisation and ethical issues but it is also likely to involve more systemic factors within the research community. Micsinszki et al. [ 21 ], who co-designed a hub for the health and well-being of vulnerable populations, commented that there is insufficient infrastructure to conduct meaningful co-design as well as a dominant medical model. Through a more holistic lens, there are “sociopolitical environments that privilege individualism over collectivism, self-sufficiency over collaboration, and scientific expertise over other ways of knowing based on lived experience” [ 21 ]. This, it could be suggested, renders creative co-design methodologies, which are based on the foundations of collectivism, collaboration and imagination an invalid technique in the research field, which is heavily dominated by more scientific methods offering reproducibility, objectivity and reliability.

Although we acknowledge that creative PPI techniques are not always appropriate, it may be that their main limitation is the lack of awareness of these methods or lack of willingness to use them. Further, there is always the risk that PPI, despite being a mandatory part of research, is used in a tokenistic or tick-box fashion [ 20 ], without considering the contribution that meaningful PPI could make to enhancing the research. It may be that PPI, let alone creative PPI, is not at the forefront of researchers’ minds when planning research.

Strengths of creative PPI

Creative ppi disrupts power hierarchies.

One of the main strengths of creative PPI techniques, cited most frequently in the included literature, was that they disrupt traditional power hierarchies [ 12 , 13 , 17 , 19 , 23 ]. For example, the use of theatre performance blurred the lines between professional and lay roles between the community and policy makers [ 12 ]. Individuals created a monologue to portray how poverty and inequality impact daily life and presented this to representatives of the National Assembly of Wales, Welsh Government, the Local Authority, Arts Council and Westminster. Byrne et al. [ 12 ], states how this medium allowed the community to engage with the people who make decisions about their lives in an environment of respect and understanding, where the hierarchies are not as visible as in other settings, e.g., political surgeries. Creative PPI methods have also removed traditional power hierarchies between researchers and adolescents. Cook et al. [ 13 ], used arts-based approaches to explore adolescents’ ideas about the “perfect” condom. They utilised the “Life Happens” resource, where adolescents drew and then decorated a person with their thoughts about sexual relationships, not too dissimilar from the persona-scenario method. This was then combined with hypothetical scenarios about sexuality. A condom-mapping exercise was then implemented, where groups shared the characteristics that make a condom “perfect” on large pieces of paper. Cook et al. [ 13 ], noted that usually power imbalances make it difficult to elicit information from adolescents, however these power imbalances were reduced due to the use of creative co-design techniques.

The same reduction in power hierarchies was noted by Grindell et al. [ 17 ], who used the person-scenario method and creative worksheets with individuals with malignant pleural effusion. This was with the aim of developing a prototype of a decision support tool for patients to help with treatment options. Although this process involved a variety of stakeholders, such as patients, carers and healthcare professionals, creative co-design was cited as a mechanism that worked to reduce power imbalances – a limitation of more traditional methods of research. Creative co-design blurred boundaries between end-users and clinical staff and enabled the sharing of ideas from multiple, valuable perspectives, meaning the prototype was able to suit user needs whilst addressing clinical problems.

Similarly, a specific creative method named cultural animation was also cited to dissolve hierarchies and encourage equal contributions from participants. Within this arts-based approach, Keleman et al. [ 19 ], explored the concept of “good health” with individuals from Stoke-on Trent. Members of the group created art installations using ribbons, buttons, cardboard and straws to depict their idea of a “healthy community”, which was accompanied by a poem. They also created a 3D Facebook page and produced another poem or song addressing the government to communicate their version of a “picture of health”. Public participants said that they found the process empowering, honest, democratic, valuable and practical.

This dissolving of hierarchies and levelling of power is beneficial as it increases the sense of ownership experienced by the creators/producers of the output [ 12 , 17 , 23 ]. This is advantageous as it has been suggested to improve its quality [ 23 ].

Creative PPI allows the unsayable to be said

Creative PPI fosters a safe space for mundane or taboo topics to be shared, which may be difficult to communicate using traditional methods of PPI. For example, the hypothetical nature of condom mapping and persona-scenarios meant that adolescents could discuss a personal topic without fear of discrimination, judgement or personal disclosure [ 13 ]. The safe space allowed a greater volume of ideas to be generated amongst peers where they might not have otherwise. Similarly, Webber et al. [ 23 ], , who used the persona method to co-design the prototype back pain educational resource, also noted how this method creates anonymity whilst allowing people the opportunity to externalise personal experiences, thoughts and feelings. Other creative methods were also used, such as drawing, collaging, role play and creating mood boards. A cardboard cube (labelled a “magic box”) was used to symbolise a physical representation of their final prototype. These creative methods levelled the playing field and made personal experiences accessible in a safe, open environment that fostered trust, as well as understanding from the researchers.

It is not only sensitive subjects that were made easier to articulate through creative PPI. The communication of mundane everyday experiences were also facilitated, which were deemed typically ‘unsayable’. This was specifically given in the context of describing intangible aspects of everyday health and wellbeing [ 11 ]. Graphic designers can also be used to visually represent the outputs of creative PPI. These captured the movement and fluidity of people and well as the relationships between them - things that cannot be spoken but can be depicted [ 21 ].

Creative PPI methods are inclusive

Another strength of creative PPI was that it is inclusive and accessible [ 17 , 19 , 21 ]. The safe space it fosters, as well as the dismantling of hierarchies, welcomed people from a diverse range of backgrounds and provided equal opportunities [ 21 ], especially for those with communication and memory difficulties who might be otherwise excluded from PPI. Kelemen et al. [ 19 ], who used creative methods to explore health and well-being in Stoke-on-Trent, discussed how people from different backgrounds came together and connected, discussed and reached a consensus over a topic which evoked strong emotions, that they all have in common. Individuals said that the techniques used “sets people to open up as they are not overwhelmed by words”. Similarly, creative activities, such as the persona method, have been stated to allow people to express themselves in an inclusive environment using a common language. Kearns et al. [ 18 ], who used aphasia-accessible material to develop a questionnaire with aphasic individuals, described how they felt comfortable in contributing to workshops (although this material was time-consuming to make, see ‘Limitations of creative PPI’ ).

Despite the general inclusivity of creative PPI, it can also be exclusive, particularly if online mediums are used. Fedorowicz et al. [ 15 ], used Facebook to create a PPI group, and although this may rectify previous drawbacks about lack of generalisation of creative methods (as Facebook can reach a greater number of people, globally), it excluded those who are not digitally active or have limited internet access or knowledge of technology. Online methods have other issues too. Maintaining the online group was cited as challenging and the volume of responses required researchers to interact outside of their working hours. Despite this, online methods like Facebook are very accessible for people who are physically disabled.

Creative PPI methods are engaging

The process of creative PPI is typically more engaging and produces more colourful data than traditional methods [ 13 ]. Individuals are permitted and encouraged to explore a creative self [ 19 ], which can lead to the exploration of new ideas and an overall increased enjoyment of the process. This increased engagement is particularly beneficial for younger PPI groups. For example, to involve children in the development of health food products, Galler et al. [ 16 ] asked 9-12-year-olds to take photos of their food and present it to other children in a “show and tell” fashion. They then created a newspaper article describing a new healthy snack. In this creative focus group, children were given lab coats to further their identity as inventors. Galler et al. [ 16 ], notes that the methods were highly engaging and facilitated teamwork and group learning. This collaborative nature of problem-solving was also observed in adults who used personas and creative worksheets to develop the resource for lower back pain [ 23 ]. Dementia patients too have been reported to enjoy the creative and informal approach to idea generation [ 20 ].

The use of cultural animation allowed people to connect with each other in a way that traditional methods do not [ 19 , 21 ]. These connections were held in place by boundary objects, such as ribbons, buttons, fabric and picture frames, which symbolised a shared meaning between people and an exchange of knowledge and emotion. Asking groups to create an art installation using these objects further fostered teamwork and collaboration, both at an individual and collective level. The exploration of a creative self increased energy levels and encouraged productive discussions and problem-solving [ 19 ]. Objects also encouraged a solution-focused approach and permitted people to think beyond their usual everyday scope [ 17 ]. They also allowed facilitators to probe deeper about the greater meanings carried by the object, which acted as a metaphor [ 21 ].

From the researcher’s point of view, co-creative methods gave rise to ideas they might not have initially considered. Valaitis et al. [ 22 ], found that over 40% of the creative outputs were novel ideas brought to light by patients, healthcare providers/community care providers, community service providers and volunteers. One researcher commented, “It [the creative methods] took me on a journey, in a way that when we do other pieces of research it can feel disconnected” [ 23 ]. Another researcher also stated they could not return to the way they used to do research, as they have learnt so much about their own health and community and how they are perceived [ 19 ]. This demonstrates that creative processes not only benefit the project outcomes and the PPI group, but also facilitators and researchers. However, although engaging, creative methods have been criticised for not demonstrating academic rigour [ 17 ]. Moreover, creative PPI may also be exclusive to people who do not like or enjoy creative activities.

Creative PPI methods are cost and time efficient

Creative PPI workshops can often produce output that is visible and tangible. This can save time and money in the long run as the output is either ready to be implemented in a healthcare setting or a first iteration has already been developed. This may also offset the time and costs it takes to implement creative PPI. For example, the prototype of the decision support tool for people with malignant pleural effusion was developed using personas and creative worksheets. The end result was two tangible prototypes to drive the initial idea forward as something to be used in practice [ 17 ]. The use of creative co-design in this case saved clinician time as well as the time it would take to develop this product without the help of its end-users. In the development of this particular prototype, analysis was iterative and informed the next stage of development, which again saved time. The same applies for the feedback questionnaire for the assessment of ICT delivered aphasia rehabilitation. The co-created questionnaire, designed with people with aphasia, was ready to be used in practice [ 18 ]. This suggests that to overcome time and resource barriers to creative PPI, researchers should aim for it to be engaging whilst also producing output.

That useable products are generated during creative workshops signals to participating patients and public members that they have been listened to and their thoughts and opinions acted upon [ 23 ]. For example, the development of the back pain resource based on patient experiences implies that their suggestions were valid and valuable. Further, those who participated in the cultural animation workshop reported that the process visualises change, and that it already feels as though the process of change has started [ 19 ].

The most cost and time efficient method of creative PPI in this review is most likely the use of Facebook to gather feedback on project methodology [ 15 ]. Although there were drawbacks to this, researchers could involve more people from a range of geographical areas at little to no cost. Feedback was instantaneous and no training was required. From the perspective of the PPI group, they could interact however much or little they wish with no time commitment.

This systematic review identified four limitations and five strengths to the use of creative PPI in health and social care research. Creative PPI is time and resource intensive, can raise ethical issues and lacks generalisability. It is also not accepted by the mainstream. These factors may act as barriers to the implementation of creative PPI. However, creative PPI disrupts traditional power hierarchies and creates a safe space for taboo or mundane topics. It is also engaging, inclusive and can be time and cost efficient in the long term.

Something that became apparent during data analysis was that these are not blanket strengths and limitations of creative PPI as a whole. The umbrella term ‘creative PPI’ is broad and encapsulates a wide range of activities, ranging from music and poems to prototype development and persona-scenarios, to more simplistic things like the use of sticky notes and ordering cards. Many different activities can be deemed ‘creative’ and the strengths and limitations of one does not necessarily apply to another. For example, cultural animation takes greater effort to prepare than the use of sticky notes and sorting cards, and the use of Facebook is cheaper and wider reaching than persona development. Researchers should use their discretion and weigh up the benefits and drawbacks of each method to decide on a technique which suits the project. What might be a limitation to creative PPI in one project may not be in another. In some cases, creative PPI may not be suitable at all.

Furthermore, the choice of creative PPI method also depends on the needs and characteristics of the PPI group. Children, adults and people living with dementia or language difficulties all have different engagement needs and capabilities. This indicates that creative PPI is not one size fits all and that the most appropriate method will change depending on the composition of the group. The choice of method will also be determined by the constraints of the research project, namely time, money and the research aim. For example, if there are time constraints, then a method which yields a lot of data and requires a lot of preparation may not be appropriate. If generalisation is important, then an online method is more suitable. Together this indicates that the choice of creative PPI method is highly individualised and dependent on multiple factors.

Although the limitations discussed in this review apply to creative PPI, they are not exclusive to creative PPI. Ethical issues are a consideration within general PPI research, especially when working with more vulnerable populations, such as children or adults living with a disability. It can also be the case that traditional PPI methods lack generalisability, as people who volunteer to be part of such a group are more likely be older, middle class and retired [ 24 ]. Most research is vulnerable to this type of bias, however, it is worth noting that generalisation is not always a goal and research remains valid and meaningful in its absence. Although online methods may somewhat combat issues related to generalisability, these methods still exclude people who do not have access to the internet/technology or who choose not to use it, implying that online PPI methods may not be wholly representative of the general population. Saying this, however, the accessibility of creative PPI techniques differs from person to person, and for some, online mediums may be more accessible (for example for those with a physical disability), and for others, this might be face-to-face. To combat this, a range of methods should be implemented. Planning multiple focus group and interviews for traditional PPI is also time and resource intensive, however the extra resources required to make this creative may be even greater. Although, the rich data provided may be worth the preparation and analysis time, which is also likely to depend on the number of participants and workshop sessions required. PPI, not just creative PPI, often requires the provision of a financial incentive, refreshments, parking and accommodation, which increase costs. These, however, are imperative and non-negotiable, as they increase the accessibility of research, especially to minority and lower-income groups less likely to participate. Adequate funding is also important for co-design studies where repeated engagement is required. One barrier to implementation, which appears to be exclusive to creative methods, however, is that creative methods are not mainstream. This cannot be said for traditional PPI as this is often a mandatory part of research applications.

Regarding the strengths of creative PPI, it could be argued that most appear to be exclusive to creative methodologies. These are inclusive by nature as multiple approaches can be taken to evoke ideas from different populations - approaches that do not necessarily rely on verbal or written communication like interviews and focus groups do. Given the anonymity provided by some creative methods, such as personas, people may be more likely to discuss their personal experiences under the guise of a general end-user, which might be more difficult to maintain when an interviewer is asking an individual questions directly. Additionally, creative methods are by nature more engaging and interactive than traditional methods, although this is a blanket statement and there may be people who find the question-and-answer/group discussion format more engaging. Creative methods have also been cited to eliminate power imbalances which exist in traditional research [ 12 , 13 , 17 , 19 , 23 ]. These imbalances exist between researchers and policy makers and adolescents, adults and the community. Lastly, although this may occur to a greater extent in creative methods like prototype development, it could be suggested that PPI in general – regardless of whether it is creative - is more time and cost efficient in the long-term than not using any PPI to guide or refine the research process. It must be noted that these are observations based on the literature. To be certain these differences exist between creative and traditional methods of PPI, direct empirical evaluation of both should be conducted.

To the best of our knowledge, this is the first review to identify the strengths and limitations to creative PPI, however, similar literature has identified barriers and facilitators to PPI in general. In the context of clinical trials, recruitment difficulties were cited as a barrier, as well as finding public contributors who were free during work/school hours. Trial managers reported finding group dynamics difficult to manage and the academic environment also made some public contributors feel nervous and lacking confidence to speak. Facilitators, however, included the shared ownership of the research – something that has been identified in the current review too. In addition, planning and the provision of knowledge, information and communication were also identified as facilitators [ 25 ]. Other research on the barriers to meaningful PPI in trial oversight committees included trialist confusion or scepticism over the PPI role and the difficulties in finding PPI members who had a basic understanding of research [ 26 ]. However, it could be argued that this is not representative of the average patient or public member. The formality of oversight meetings and the technical language used also acted as a barrier, which may imply that the informal nature of creative methods and its lack of dependency on literacy skills could overcome this. Further, a review of 42 reviews on PPI in health and social care identified financial compensation, resources, training and general support as necessary to conduct PPI, much like in the current review where the resource intensiveness of creative PPI was identified as a limitation. However, others were identified too, such as recruitment and representativeness of public contributors [ 27 ]. Like in the current review, power imbalances were also noted, however this was included as both a barrier and facilitator. Collaboration seemed to diminish hierarchies but not always, as sometimes these imbalances remained between public contributors and healthcare staff, described as a ‘them and us’ culture [ 27 ]. Although these studies compliment the findings of the current review, a direct comparison cannot be made as they do not concern creative methods. However, it does suggest that some strengths and weaknesses are shared between creative and traditional methods of PPI.

Strengths and limitations of this review

Although a general definition of creative PPI exists, it was up to our discretion to decide exactly which activities were deemed as such for this review. For example, we included sorting cards, the use of interactive whiteboards and sticky notes. Other researchers may have a more or less stringent criteria. However, two reviewers were involved in this decision which aids the reliability of the included articles. Further, it may be that some of the strengths and limitations cannot fully be attributed to the creative nature of the PPI process, but rather their co-created nature, however this is hard to disentangle as the included papers involved both these aspects.

During screening, it was difficult to decide whether the article was utilising creative qualitative methodology or creative PPI , as it was often not explicitly labelled as such. Regardless, both approaches involved the public/patients refining a healthcare product/service. This implies that if this review were to be replicated, others may do it differently. This may call for greater standardisation in the reporting of the public’s involvement in research. For example, the NIHR outlines different approaches to PPI, namely “consultation”, “collaboration”, “co-production” and “user-controlled”, which each signify an increased level of public power and influence [ 28 ]. Papers with elements of PPI could use these labels to clarify the extent of public involvement, or even explicitly state that there was no PPI. Further, given our decision to include only scholarly peer-reviewed literature, it is possible that data were missed within the grey literature. Similarly, the literature search will not have identified all papers relating to different types of accessible inclusion. However, the intent of the review was to focus solely on those within the definition of creative.

This review fills a gap in the literature and helps circulate and promote the concept of creative PPI. Each stage of this review, namely screening and quality appraisal, was conducted by two independent reviewers. However, four full texts could not be accessed during the full text reading stage, meaning there are missing data that could have altered or contributed to the findings of this review.

Research recommendations

Given that creative PPI can require effort to prepare, perform and analyse, sufficient time and funding should be allocated in the research protocol to enable meaningful and continuous PPI. This is worthwhile as PPI can significantly change the research output so that it aligns closely with the needs of the group it is to benefit. Researchers should also consider prototype development as a creative PPI activity as this might reduce future time/resource constraints. Shifting from a top-down approach within research to a bottom-up can be advantageous to all stakeholders and can help move creative PPI towards the mainstream. This, however, is the collective responsibility of funding bodies, universities and researchers, as well as committees who approve research bids.

A few of the included studies used creative techniques alongside traditional methods, such as interviews, which could also be used as a hybrid method of PPI, perhaps by researchers who are unfamiliar with creative techniques or to those who wish to reap the benefits of both. Often the characteristics of the PPI group were not included, including age, gender and ethnicity. It would be useful to include such information to assess how representative the PPI group is of the population of interest.

Creative PPI is a relatively novel approach of engaging the public and patients in research and it has both advantages and disadvantages compared to more traditional methods. There are many approaches to implementing creative PPI and the choice of technique will be unique to each piece of research and is reliant on several factors. These include the age and ability of the PPI group as well as the resource limitations of the project. Each method has benefits and drawbacks, which should be considered at the protocol-writing stage. However, given adequate funding, time and planning, creative PPI is a worthwhile and engaging method of generating ideas with end-users of research – ideas which may not be otherwise generated using traditional methods.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Critical Appraisal Skills Programme

The Joanna Briggs Institute

National Institute of Health and Care Research

Public Advisory Group

Public and Patient Involvement

Web of Science

National Institute for Health and Care Research. What Is Patient and Public Involvement and Public Engagement? https://www.spcr.nihr.ac.uk/PPI/what-is-patient-and-public-involvement-and-engagement Accessed 01 Sept 2023.

Department of Health. Personal and Public Involvement (PPI) https://www.health-ni.gov.uk/topics/safety-and-quality-standards/personal-and-public-involvement-ppi#:~:text=The Health and Social Care Reform Act (NI) 2009 placed,delivery and evaluation of services . Accessed 01 Sept 2023.

National Institute for Health and Care Research. Policy Research Programme – Guidance for Stage 1 Applications https://www.nihr.ac.uk/documents/policy-research-programme-guidance-for-stage-1-applications-updated/26398 Accessed 01 Sept 2023.

Greenhalgh T, Hinton L, Finlay T, Macfarlane A, Fahy N, Clyde B, Chant A. Frameworks for supporting patient and public involvement in research: systematic review and co-design pilot. Health Expect. 2019. https://doi.org/10.1111/hex.12888

Article   PubMed   PubMed Central   Google Scholar  

Street JM, Stafinski T, Lopes E, Menon D. Defining the role of the public in health technology assessment (HTA) and HTA-informed decision-making processes. Int J Technol Assess Health Care. 2020. https://doi.org/10.1017/S0266462320000094

Article   PubMed   Google Scholar  

Morrison C, Dearden A. Beyond tokenistic participation: using representational artefacts to enable meaningful public participation in health service design. Health Policy. 2013. https://doi.org/10.1016/j.healthpol.2013.05.008

Leavy P. Method meets art: arts-Based Research Practice. New York: Guilford; 2020.

Google Scholar  

Seers K. Qualitative systematic reviews: their importance for our understanding of research relevant to pain. Br J Pain. 2015. https://doi.org/10.1177/2049463714549777

Lockwood C, Porritt K, Munn Z, Rittenmeyer L, Salmond S, Bjerrum M, Loveday H, Carrier J, Stannard D. Chapter 2: Systematic reviews of qualitative evidence. Aromataris E, Munn Z, editors. JBI Manual for Evidence Synthesis JBI. 2020. https://synthesismanual.jbi.global . https://doi.org/10.46658/JBIMES-20-03

CASP. CASP Checklists https://casp-uk.net/images/checklist/documents/CASP-Qualitative-Studies-Checklist/CASP-Qualitative-Checklist-2018_fillable_form.pdf (2022).

Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006. https://doi.org/10.1191/1478088706qp063oa

Article   Google Scholar  

Byrne E, Elliott E, Saltus R, Angharad J. The creative turn in evidence for public health: community and arts-based methodologies. J Public Health. 2018. https://doi.org/10.1093/pubmed/fdx151

Cook S, Grozdanovski L, Renda G, Santoso D, Gorkin R, Senior K. Can you design the perfect condom? Engaging young people to inform safe sexual health practice and innovation. Sex Educ. 2022. https://doi.org/10.1080/14681811.2021.1891040

Craven MP, Goodwin R, Rawsthorne M, Butler D, Waddingham P, Brown S, Jamieson M. Try to see it my way: exploring the co-design of visual presentations of wellbeing through a workshop process. Perspect Public Health. 2019. https://doi.org/10.1177/1757913919835231

Fedorowicz S, Riley V, Cowap L, Ellis NJ, Chambers R, Grogan S, Crone D, Cottrell E, Clark-Carter D, Roberts L, Gidlow CJ. Using social media for patient and public involvement and engagement in health research: the process and impact of a closed Facebook group. Health Expect. 2022. https://doi.org/10.1111/hex.13515

Galler M, Myhrer K, Ares G, Varela P. Listening to children voices in early stages of new product development through co-creation – creative focus group and online platform. Food Res Int. 2022. https://doi.org/10.1016/j.foodres.2022.111000

Grindell C, Tod A, Bec R, Wolstenholme D, Bhatnagar R, Sivakumar P, Morley A, Holme J, Lyons J, Ahmed M, Jackson S, Wallace D, Noorzad F, Kamalanathan M, Ahmed L, Evison M. Using creative co-design to develop a decision support tool for people with malignant pleural effusion. BMC Med Inf Decis Mak. 2020. https://doi.org/10.1186/s12911-020-01200-3

Kearns Á, Kelly H, Pitt I. Rating experience of ICT-delivered aphasia rehabilitation: co-design of a feedback questionnaire. Aphasiology. 2020. https://doi.org/10.1080/02687038.2019.1649913

Kelemen M, Surman E, Dikomitis L. Cultural animation in health research: an innovative methodology for patient and public involvement and engagement. Health Expect. 2018. https://doi.org/10.1111/hex.12677

Keogh F, Carney P, O’Shea E. Innovative methods for involving people with dementia and carers in the policymaking process. Health Expect. 2021. https://doi.org/10.1111/hex.13213

Micsinszki SK, Buettgen A, Mulvale G, Moll S, Wyndham-West M, Bruce E, Rogerson K, Murray-Leung L, Fleisig R, Park S, Phoenix M. Creative processes in co-designing a co-design hub: towards system change in health and social services in collaboration with structurally vulnerable populations. Evid Policy. 2022. https://doi.org/10.1332/174426421X16366319768599

Valaitis R, Longaphy J, Ploeg J, Agarwal G, Oliver D, Nair K, Kastner M, Avilla E, Dolovich L. Health TAPESTRY: co-designing interprofessional primary care programs for older adults using the persona-scenario method. BMC Fam Pract. 2019. https://doi.org/10.1186/s12875-019-1013-9

Webber R, Partridge R, Grindell C. The creative co-design of low back pain education resources. Evid Policy. 2022. https://doi.org/10.1332/174426421X16437342906266

National Institute for Health and Care Research. A Researcher’s Guide to Patient and Public Involvement. https://oxfordbrc.nihr.ac.uk/wp-content/uploads/2017/03/A-Researchers-Guide-to-PPI.pdf Accessed 01 Nov 2023.

Selman L, Clement C, Douglas M, Douglas K, Taylor J, Metcalfe C, Lane J, Horwood J. Patient and public involvement in randomised clinical trials: a mixed-methods study of a clinical trials unit to identify good practice, barriers and facilitators. Trials. 2021 https://doi.org/10.1186/s13063-021-05701-y

Coulman K, Nicholson A, Shaw A, Daykin A, Selman L, Macefield R, Shorter G, Cramer H, Sydes M, Gamble C, Pick M, Taylor G, Lane J. Understanding and optimising patient and public involvement in trial oversight: an ethnographic study of eight clinical trials. Trials. 2020. https://doi.org/10.1186/s13063-020-04495-9

Ocloo J, Garfield S, Franklin B, Dawson S. Exploring the theory, barriers and enablers for patient and public involvement across health, social care and patient safety: a systematic review of reviews. Health Res Policy Sys. 2021. https://doi.org/10.1186/s12961-020-00644-3

National Institute for Health and Care Research. Briefing notes for researchers - public involvement in NHS, health and social care research. https://www.nihr.ac.uk/documents/briefing-notes-for-researchers-public-involvement-in-nhs-health-and-social-care-research/27371 Accessed 01 Nov 2023.

Download references

Acknowledgements

With thanks to the PHIRST-LIGHT public advisory group and consortium for their thoughts and contributions to the design of this work.

The research team is supported by a National Institute for Health and Care Research grant (PHIRST-LIGHT Reference NIHR 135190).

Author information

Olivia R. Phillips and Cerian Harries share joint first authorship.

Authors and Affiliations

Nottingham Centre for Public Health and Epidemiology, Lifespan and Population Health, School of Medicine, University of Nottingham, Clinical Sciences Building, City Hospital Campus, Hucknall Road, Nottingham, NG5 1PB, UK

Olivia R. Phillips, Jo Leonardi-Bee, Holly Knight & Joanne R. Morling

National Institute for Health and Care Research (NIHR) PHIRST-LIGHT, Nottingham, UK

Olivia R. Phillips, Cerian Harries, Jo Leonardi-Bee, Holly Knight, Lauren B. Sherar, Veronica Varela-Mato & Joanne R. Morling

School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Loughborough, Leicestershire, LE11 3TU, UK

Cerian Harries, Lauren B. Sherar & Veronica Varela-Mato

Nottingham Centre for Evidence Based Healthcare, School of Medicine, University of Nottingham, Nottingham, UK

Jo Leonardi-Bee

NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, NG7 2UH, UK

Joanne R. Morling

You can also search for this author in PubMed   Google Scholar

Contributions

Author contributions: study design: ORP, CH, JRM, JLB, HK, LBS, VVM, literature searching and screening: ORP, CH, JRM, data curation: ORP, CH, analysis: ORP, CH, JRM, manuscript draft: ORP, CH, JRM, Plain English Summary: ORP, manuscript critical review and editing: ORP, CH, JRM, JLB, HK, LBS, VVM.

Corresponding author

Correspondence to Olivia R. Phillips .

Ethics declarations

Ethics approval and consent to participate.

The Ethics Committee of the Faculty of Medicine and Health Sciences, University of Nottingham advised that approval from the ethics committee and consent to participate was not required for systematic review studies.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

40900_2024_580_MOESM1_ESM.docx

Additional file 1: Search strings: Description of data: the search strings and filters used in each of the 5 databases in this review

Additional file 2: Quality appraisal questions: Description of data: CASP quality appraisal questions

40900_2024_580_moesm3_esm.docx.

Additional file 3: Table 1: Description of data: elements of the data extraction table that are not in the main manuscript

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Phillips, O.R., Harries, C., Leonardi-Bee, J. et al. What are the strengths and limitations to utilising creative methods in public and patient involvement in health and social care research? A qualitative systematic review. Res Involv Engagem 10 , 48 (2024). https://doi.org/10.1186/s40900-024-00580-4

Download citation

Received : 28 November 2023

Accepted : 25 April 2024

Published : 13 May 2024

DOI : https://doi.org/10.1186/s40900-024-00580-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Public and patient involvement
  • Creative PPI
  • Qualitative systematic review

Research Involvement and Engagement

ISSN: 2056-7529

qualitative research paper about social media

IMAGES

  1. Research Paper on Social Media

    qualitative research paper about social media

  2. 005 Largepreview Essay Example On Impact Of Social Media Our ~ Thatsnotus

    qualitative research paper about social media

  3. Research paper on social media slideshare

    qualitative research paper about social media

  4. research paper sample pdf about social media

    qualitative research paper about social media

  5. Qualitative Research Using Social Media

    qualitative research paper about social media

  6. Social Media Qualitative Research Title Examples For Students : The

    qualitative research paper about social media

VIDEO

  1. The Impact of social media on the academic performance of social science students at UWI T&T

  2. Research paper- social media

  3. Social media study by Rice University finds high levels of distraction among younger users

  4. Kurator Citations

  5. Qualitative Research Paper 3

  6. Qualitative Data Analysis with ChatGPT (extremely time-saving) 🤖 🔥

COMMENTS

  1. Why people are becoming addicted to social media: A qualitative study

    Today, social media (SM) (e.g., WhatsApp, Instagram, Facebook, etc.) have enjoyed such rapidly-growing popularity that around 2.67 billion users of social networks have been estimated worldwide. After ... This study is a qualitative research which builds on conventional content analysis. To gain a deeper understanding of SMA, researchers have ...

  2. PDF Qualitative Research on Youths' Social Media Use: A review of the

    Schmeichel, Mardi; Hughes, Hilary E.; and Kutner, Mel (2018) "Qualitative Research on Youths' Social Media Use: A review of the literature," Middle Grades Review: Vol. 4 : Iss. 2 , Article 4. This Research is brought to you for free and open access by the College of Education and Social Services at ScholarWorks @ UVM.

  3. Social media in qualitative research: Challenges and ...

    The challenges of using social media in qualitative research are many. These challenges are related to the large volume of data, the nature of digital texts, visual cues, and types of behaviour on social media sites, the authenticity of the data, the level of access obtained, and the digital divide in some situations.

  4. Effects of Social Media Use on Psychological Well-Being: A Mediated

    Social media usage has been associated with anxiety, loneliness, and depression ... Given this research gap, this paper's main objective is to shed light on the effect of social media use on psychological well-being. ... as qualitative studies could help further validate the results and provide complementary perspectives on the relationships ...

  5. Qualitative and Mixed Methods Social Media Research:

    This article presents a descriptive methodological analysis of qualitative and mixed methods approaches for social media research. It is based on a systematic review of 229 qualitative or mixed methods research articles published from 2007 through 2013 where social media played a central role.

  6. PDF Qualitative Research on Social Media Addictions of Psychological

    Psychological counselor, social media addiction, qualitative research, focus group interview 1. Introduction Depending on the intensive use of the Internet in our lives, communication technology tools have developed, and one of these tools, social media, has started to be used more frequently. Social media is defined as an

  7. Adolescent Social Media Use and Well-Being: A Systematic ...

    Qualitative research into adolescents' experiences of social media use and well-being has the potential to offer rich, nuanced insights, but has yet to be systematically reviewed. The current systematic review identified 19 qualitative studies in which adolescents shared their views and experiences of social media and well-being. A critical appraisal showed that overall study quality was ...

  8. The Impact of Social Media on Mental Health: a Mixed-methods Research

    heightened use of social media on mental health. Qualitative and quantitative data were collected from 95 mental health practitioners (N = 95) via Qualtrics. ... I would like to dedicate this research paper to my family, friends, and loved ones. A special acknowledgment to my significant other, Donnie, for

  9. A systematic review: the influence of social media on depression

    Social media. The term 'social media' refers to the various internet-based networks that enable users to interact with others, verbally and visually (Carr & Hayes, Citation 2015).According to the Pew Research Centre (Citation 2015), at least 92% of teenagers are active on social media.Lenhart, Smith, Anderson, Duggan, and Perrin (Citation 2015) identified the 13-17 age group as ...

  10. Social media use and social connectedness among adolescents in the

    Connectedness to family and peers is a key determinant of adolescent mental health. Existing research examining associations between social media use and social connectedness has been largely quantitative and has focused primarily on loneliness, or on specific aspects of peer relationships. In this qualitative study we use the displacement hypothesis and the stimulation hypothesis as competing ...

  11. Analyzing social media data: A mixed-methods framework ...

    To qualitative researchers, social media offers a novel opportunity to harvest a massive and diverse range of content without the need for intrusive or intensive data collection procedures. However, performing a qualitative analysis across a massive social media data set is cumbersome and impractical. Instead, researchers often extract a subset of content to analyze, but a framework to ...

  12. [PDF] Social media in qualitative research: Challenges and

    This paper argues that many of the challenges concerned with social media settings, by nature, are emergent and linked to their virtual and contextual features, and uses the Klein and Myers (1999) framework for traditional interpretive field studies as a vehicle for unpacking these challenges. Expand. 12. PDF.

  13. Rethinking social media for qualitative research: The use of Facebook

    SUBMIT PAPER. The Sociological Review. Impact Factor: 2.5 / 5-Year Impact Factor: 3.3 . JOURNAL HOMEPAGE ... First published online July 4, 2019. Rethinking social media for qualitative research: The use of Facebook Activity Logs and Search History in interview settings. Justine Gangneux [email protected] View all authors and affiliations ...

  14. (PDF) A Narrative Research Approach: The Experiences of Social Media

    The aim of this study is to create a framework to narrate positive and n egative ex-. periences of two higher education faculty members in using social media; pros and. cons of using social media ...

  15. Social media in qualitative research: Challenges and recommendations

    The emergence of social media provides an opportunity for IS researchers to examine new phenomena in new ways. This paper looks at the potential use of social media in qualitative research in information systems. This paper suggests how qualitative IS researchers can design their studies to capitalize on social media data. This paper makes ...

  16. Social Media in Qualitative Research: Challenges and Recommendations

    The emergence of social media on the Internet provides an opportunity for information systems researchers to examine new phenomena in new ways. However, for various reasons qualitative researchers in IS have not fully embraced this opportunity. This paper looks at the potential use of social media in qualitative research in information systems.

  17. Methodologies in Social Media Research: Where We Are and Where We Still

    The data from social media are often used in oncology research, including content analysis using qualitative and/or quantitative methods. Content analysis of social media data has provided a valuable source of information on public perceptions and unmet needs of patients with cancer and their families.

  18. Conceptualising and measuring social media engagement: A ...

    This paper aims to systematically contribute to this academic debate by analysing, discussing, and synthesising social media engagement literature in the perspective of social media metrics. Adopting a systematic literature review, the research provides an overarching picture of what has already been investigated and the existing gaps that need ...

  19. The power of qualitative research in the era of social media

    Although the social media provide a wealth of data for automated content analyses, this review questions the validity and reliability of this research approach, and concludes that social media monitoring (SMM) is a poor substitute for in‐depth qualitative research which has many advantages and benefits., - The paper presents a detailed ...

  20. A Qualitative Study to Explore the Impact of Social Media on ...

    Social media is very helpful in educational fields, and it has some flaws too. As due to excessive media usage people are have weaker relationships with their loved ones. Individuals are facing several mental and physical issues. Results of the study can also be helpful for creating new strategies to limit social media use in daily life.

  21. Optimizing Recruitment for Qualitative Research: A Comparison of Social

    Optimizing Recruitment for Qualitative Research: A Comparison of Social Media, Emails, and Offline Methods. Nana Sledzieski https ... Chamberlain C., Halpin D. (2018). mHealth resources for asthma and pregnancy care: Methodological issues and social media recruitment. A discussion paper. Journal of Advanced Nursing, 74(10), 2442-2449. https ...

  22. Reporting of Ethical Considerations in Qualitative Research Utilizing

    Background: The internet community has become a significant source for researchers to conduct qualitative studies analyzing users' views, attitudes, and experiences about public health. However, few studies have assessed the ethical issues in qualitative research using social media data. Objective: This study aims to review the reportage of ethical considerations in qualitative research ...

  23. PDF Social Media and Qualitative Research

    paper looks at the potential use of social media in qualitative research in information systems. It discusses some of the challenges of using social media and suggests how qualitative IS researchers can design their studies to capitalize on social media data. After discussing an illustrative qualitative study, the paper makes recommendations for

  24. Su1864 #IBDTOK: A CROSS-SECTIONAL QUALITATIVE ANALYSIS OF SOCIAL MEDIA

    DOI: 10.1016/s0016-5085(24)02428-4 Corpus ID: 269599320; Su1864 #IBDTOK: A CROSS-SECTIONAL QUALITATIVE ANALYSIS OF SOCIAL MEDIA VIDEOS ABOUT INFLAMMATORY BOWEL DISEASE @article{Monti2024Su1864A, title={Su1864 \#IBDTOK: A CROSS-SECTIONAL QUALITATIVE ANALYSIS OF SOCIAL MEDIA VIDEOS ABOUT INFLAMMATORY BOWEL DISEASE}, author={Gabriel Monti and Marissa M. Song Mayeda and Jenna Anderson and Jessica ...

  25. What are the strengths and limitations to utilising creative methods in

    Background There is increasing interest in using patient and public involvement (PPI) in research to improve the quality of healthcare. Ordinarily, traditional methods have been used such as interviews or focus groups. However, these methods tend to engage a similar demographic of people. Thus, creative methods are being developed to involve patients for whom traditional methods are ...