Learn more about our study on social media and mental health!


About SOCIAL


The Surveys of Online Cohorts for Internalizing symptoms And Language (SOCIAL) are a collaboration between researchers at Indiana University’s departments of:

The studys represent an interdisciplinary approach to studying mental health that triangulates self-report with data and meta-data obtained from the social media platform Twitter.




We have several SOCIAL studies completed or ongoing:

  • SOCIAL-I: We surveyed a nationally representative sample of 1123 U.S. adults and administered a transdiagnostic battery of symptom assessments that correspond to the Hierarchical Taxonomy of Psychopathology (HiTOP) model. We also obtained their consent to access their Twitter accounts. Individuals were recruited from July 2020 to March 2021 for a study on “social media and mental health.” The sample was selected to approximate the U.S. populations on the intersections of age, gender, and race/ethnicity.

  • SOCIAL-II: All individuals in SOCIAL-I were Twitter users. Accordingly, we could not ascertain the role that being a Twitter user itself has on potential differences between individuals in baseline sociodemographics, social media use, and mental health symptoms. To have a sample of individuals who did not use Twitter as well as to have an additional sample in which to assess the transportability of results from SOCIAL-I, we began the SOCIAL-II study. SOCIAL-II recruited college students from a predominantly White and Asian university in the Midwest. Individuals were compensated for credit in an introductory psychology course. Individuals were recruited from September 2020 to the present. We have over 2,015 participants.

  • SOCIAL-III: This study is scheduled to have an overlapping battery with SOCIALs I and II and will use snowball sampling of Twitter users.

  • SOCIAL-IV: SOCIAL-IV is a bit different in that it is a clinical trial where we also collect social media data! The results of SOCIALs I, II, and III will be used to train classifiers of somatoform, internalizing fear, internalizing distress, and disinhibited externalizing symptoms to track these in SOCIAL-IV participants.

Background


Social media is a relatively recent development. As of 2021, over 75% of adults in the United States are on a social media platform. That alone makes social media an interesting topic to study.

Most relevant to our work, there are reported correlations between social media use and poorer mental health. Many individuals worry that social media use causes poorer mental health, at least in some people. While we do not know if this is true, social media is also interesting from a research perspective because people openly talk about their mental health and some social media behaviors can clue you in to people’s mental health (e.g., when individuals discuss feeling sad). Moreover, we can make inferences about people mental health and emotions based on their behavior. For example, in one study, we looked at the timing of activity on Twitter as an index of a person’s sleep/wake cycle. We found differences between Twitter users who reported being depressed and a random sample suggesting that people who were depressed were more active into the night and less active early in the morning. Watch me talk about this study below (on a social media platform of course):




In another study, we tracked the language of depressed Twitter users vs. a random sample of Twitter users. We specifically looked at the vocabulary of these individuals to try to pinpoint cognitive distortions in their language. Cognitive distortions are a concept from cognitive-behavioral therapy that refer to thinking that is rigid, inflexible, and tends to be unrealistically negative. In that study, we found that depressed Twitter users tended to use more of the language that we identified as cognitive-distorted than a random sample.

What did we measure?


We followed simple principles for choosing measures for this study. First, we wanted to have a good coverage of the symptoms of psychopathology that are represented by the Hierarchical Taxonomy of Psychopathology (HiTOP) model. Second, we wanted to do research that was accessible and could be reproduced by others. Because of this, we focused on freely-available measures, usual the DSM Severity Measures endorsed by the American Psychiatric Association. Below are the measures that we used for all of SOCIALs I and II.

Spectra Construct Measure SOCIAL-I SOCIAL-II SOCIAL-III
Somatoform Pain PHQ-15 Yes Yes Yes
Insomnia ISI Yes Yes Yes
Distress Negative affect PID No Yes Yes
Depression PHQ-9 Yes Yes Yes
Stress MIDUS Yes Yes No
Worry DSM Severity Yes Yes Yes
Social anxiety DSM Severity Yes Yes Yes
Fear Panic DSM Severity Yes Yes Yes
Agoraphobia DSM Severity Partial Partial No
Disinhibition Disinhibition PID No Yes Yes
Alcohol use AUDIT Yes Yes Yes
Substance use DSM Severity Yes Yes Yes
Antagonism Antagonism PID No Yes Yes
Thought disorder Psychoticism PID No Yes Yes
Mania ASRM Partial Partial No
Eating Restrictive intake EDEQ No Yes Yes
Body concerns EDEQ No Yes Yes
Food insecurity USDA No Yes Yes
Detachment Detachment PID No Yes Yes
Social support ESSI No Yes Yes

Results


Analyses are ongoing!