Should I post? The relationships among social media use, emotion recognition, and mental health
Abstract
Introduction: While increased time spent on social media can be negatively related to one's overall mental health, social media research often fails to account for what behaviors users are actually engaging in while they are online. The present research helps to address this gap by measuring participants' active and passive social media behavioral styles and investigates whether and how these two social media behavioral styles are related to depression, anxiety, and stress, and the mediating role of emotion recognition ability in this relationship. Methods: A pre-study (N = 128) tested whether various social media behaviors reliably grouped into active and passive behavioral styles, and a main study (N = 139) tested the relationships between social media use style, emotion recognition, and mental health. Results: While we did not find evidence of a mediating relationship between these variables, results supported that more active social media use was related to more severe anxiety and stress as well as poorer emotion recognition skill, while passive social media use was unrelated to these outcomes. Discussion: These findings highlight that, beyond objective time spent on social media, future research must consider how users are spending their time online.
Study specs
- Authors
- E Scarpulla,MD Stosic,AE Weaver
- Institution
- University of San Francisco,University of Southern California,University of Nevada,Las Vegas
- Discipline
- Psychology
- Year
- 2023
- Human Data Platform
- Prolific
- Source
- View Source DOI Google Scholar
Peer Review & Critical Discussion
Potential Selection Bias in 2023 Cohort
The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.
Non-naive Participants Issue
I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.
RLHF Applicability to This Study Design
The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.
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