Abstract: Social networking sites (SNS) are frequently criticized as a driving force behind rising depression rates. Yet empirical studies exploring the associations between SNS use and well-being have been predominantly cross-sectional, while the few existing longitudinal studies provided mixed results. We examined prospective associations between SNS use and multiple indicators of well-being in a nationally representative sample of Dutch adults (N ∼ 10,000), comprising six waves of annual measures of SNS use and well-being. We used an analytic method that estimated prospective effects of SNS use and well-being while also estimating time-invariant between-person associations between these variables. Between individuals, SNS use was associated with lower well-being. However, within individuals, year-to-year changes in SNS use were not prospectively associated with changes in well-being (or vice versa). Overall, our analyses suggest that the conclusions about the causal impact of social media on rising mental health problems in the population might be premature.
Keywords: social media, social networking sites, life satisfaction, emotions, loneliness, self-esteem, longitudinal methods, between- and within-person effects
Social media are often criticized as a driving force behind the current depression epidemics (Twenge et al., 2018). Yet the empirical evidence supporting the harmful effect of social media use on individuals has been based on predominantly cross-sectional data, while the few existing longitudinal studies provided mixed results. Herein, we used a large nationally representative panel of Dutch adults who contributed to a maximum of six yearly assessments of both SNS use and various indicators of well-being. Importantly, in contrast to many previous longitudinal studies, we relied on advanced statistical methods that are able to disentangle between- from within-person effects. Given policy makers’ recent interest in interventions aimed at curbing the suspected harmful consequences of social media use (UK Commons Select Committees, 2019), assessing whether SNS use is indeed associated with poorer well-being over time at a within-person level is particularly important.
Our results showed that, on average, more heavy SNS users indeed tended to consistently report slightly lower well-being—even though, consistent with recent large-scale cross-sectional studies (Orben & Przybylski, 2019a, 2019b), these effects were small. Importantly, despite the presence of between-person associations, within-individual changes in SNS use were not associated with within-individual changes in well-being (and vice versa). Importantly, our sample size would have allowed us to detect even tiny effects at an α level .05 (N = 10,000 gives a 99% power to detect a correlation of .04), suggesting that these null effects are unlikely to be explained by a lack of power.
How can we reconcile the presence of negative associations between SNS use and well-being at the between-person level with the absence of the prospective effects in either direction? One rather mundane explanation is that between-person associations might be driven by confounding with some third variables. For example, emotionally unstable and introverted individuals might be more likely to use social media (Liu & Campbell, 2017) and to report lower well-being (Diener et al., 2003). As a result, interindividual differences in personality traits, such as neuroticism or introversion, might be responsible for both higher SNS use and lower well-being. Relatedly, the negative between-person associations between SNS use and well-being could be (at least partially) driven by common method variance (Orben & Lakens, 2019). Future research should investigate these possibilities.
Alternatively, SNS use and well-being might affect each other, but on a shorter timescale, such as hours, days, or weeks (rather than years). Hence, assessing SNS use and well-being with shorter time intervals, for example, using daily diary or experience sampling methods would shed some light on this question. Nevertheless, it is important to note that even if SNS use affects daily fluctuations in well-being, the fact that these short-term associations do not translate into longer term effects, as indicated by our results, is worth further investigations.
The presence of between-person associations combined with the lack of within-person prospective effects in our findings might have implications that go beyond the field of social media effects. Specifically, it adds to the literature on the importance of separating effects at different levels of analysis more generally (Curran et al., 2014). The associations between the variables at one level of analysis (e.g., individuals) do not necessarily mirror the associations between these variables at another level (e.g., groups), and using the relations at one level to make inferences about the relations at another level represents an error of inference (ecological fallacy; Robinson, 1950). This has been common knowledge in other social science disciplines, such as sociology or education research, for decades (Raudenbush & Willms, 1995; Robinson, 1950). As psychologists have recently been showing increasing interest in exploring psychological phenomena across different levels of analysis too (e.g., within-person vs. between-person), using methods that allow for a proper differentiation of between- from within-person effects is essential (Usami et al., 2019).
It is important to note this study’s limitations. While the data set we used allowed us to include a broad range of well-being indicators, it did not offer a differentiated selection of SNS use measures. Specifically, the available variables mainly reflected a quantitative aspect of use, such as frequency and intensity. However, the mere number of hours spent on SNS might matter less that the content one is exposed to and the type of activities one is engaged in. For example, researchers have recently started differentiating between passive (browsing other people’s profiles) and active (posting messages and status updates) SNS use, showing that only the former (but not the latter) was associated with lower well-being (Verduyn et al., 2015). In addition, SNS use might have different consequences depending on what motives individuals pursue, with using social media for making new friends (vs. for social skills compensation) having positive (vs. negative) correlates (Teppers et al., 2014). Ultimately, while this study used self-report measures of SNS use, we hope that future studies will rely on objective measures, such as obtained from smartphone screen time applications (Ellis et al., 2018). In addition, our attempt to include as many diverse measures of well-being as possible resulted in varying time lags between SNS use and different measures of well-being. Although our additional analyses (see Supplementary Materials) showed that the length of time lag had no consistent effect on the associations between SNS use and well-being, we hope that data sets will become available with even more regular and fine-grained assessments than LISS.
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