Valkenburg, P.M., Meier, A., & Beyens, I. (2022). Social media use and its impact on adolescent mental health

Question 1

association between SMU and illness

Answer 1

• associations of general use of social network sites (SNS use) with higher levels of adolescent ill-being that ranged from very small to moderate
• As for well-being, one meta-analysis found that SNS use was weakly associated with higher levels of wellbeing, whereas another found that it was weakly related to lower levels of well-being
• When this meta-analysis analyzed happiness, life satisfaction, and depression separately, it found that SNS use was associated with both higher levels of well-being and illbeing

-> a result that suggests that ill-being is
not simply the flip-side of well-being and vice versa, and that both outcomes should be investigated in their own right

Question 2

gaps in literature

Answer 2

• evidence is mainly cross-sectional, no causality
• lack of attention to mediators
• lack of attention to risk and protective factors
• over-reliance on self-report measures (we need more objective measures)
• small and homogenous samples
• lack o fattention to the content
• inconsistent definition of predictors and outcomes

Question 3

future research should….

Answer 3

• define predictors and outcomes consistently
• move away from self report, use eg. log-based measures of time spent with SM (However, although log-based measures are often seen as the gold standard, they have their own validity threats, such as
  technical errors and the erroneous tracing of SM apps running in the background when the screen is turned off. Also, still measures the time spent, just as self-report).
• adopt measures that capture adolescents’ responses to specific content or qualities of SM interactions

Question 4

What has often been ignored in such debates is that the effect sizes are just what they are: statistics observed at the aggregate level. Such statistics are typically derived from heterogeneous samples of adolescents who may differ greatly in their susceptibilities to the effects of environmental influences in general [53] and media influences in particular [54]. After all, each adolescent is subject to unique dispositional, social-context, and situational factors that guide their SMU and moderate its effects [55]. Such person-specific antecedents and effects of SMU cannot be captured by the aggregatelevel statistics that have been reported in the majority of empirical studies and reviews, including the current one.

Answer 4

oke

Question 5

conclusie

Answer 5

If we accept the propositions of media-specific susceptibility theories, it is plausible to assume that both optimistic and pessimistic conclusions about the effects of SMU are valid, they just refer to different adolescents.

N=1 studies have found that a small group of adolescents experienced negative effects of SMU on wellbeing (around 10e15%) and another small group experienced positive effects (also around 10%e15%). Reassuringly though, most adolescents experienced no or negligible effects.

A person-specific approach to media effects requires a large number of respondents and a large number of withinperson observations per respondent. Indeed, statistical power is expensive. However, due to rapidly advancing technological (e.g. phone-based experience sampling methods) and methodological developments (e.g. N = 1 time series analyses), such approaches are increasingly within everyone’s reach, especially when researchers pool resources in interdisciplinary teams.