Exploring Use Patterns and Racial and Ethnic Differences in Real Time Affective States During Social Media Use Among a Clinical Sample of Adolescents With Depression: Prospective Cohort Study

Author:

Nereim CameronORCID,Bickham DavidORCID,Rich MichaelORCID

Abstract

Background Increasing youth mental health problems over time correlate with increasing rates of social media use (SMU); however, a proposed contributory relationship remains unproven. To better understand how SMU impacts mental health requires a more nuanced understanding of the relationship between different patterns of SMU and specific individual factors. Studies suggest that more active forms of SMU may offer mental health benefits when compared with more passive forms. Furthermore, the literature suggests important differences in patterns of SMU and affective states among those identifying as racial and ethnic minorities. Objective Using ecological momentary assessment (EMA), this study aims to investigate potential differences in affective states during active and passive forms of SMU and whether such differences vary by race and ethnicity. Methods We recruited patients seeking care at a large urban adolescent medicine clinic who exhibited at least mild depressive symptoms based on Patient Health Questionnaire-9 (PHQ-9) scores. Participants completed an enrollment survey and a 7-day EMA protocol, receiving 5 EMA questionnaires per day, which assessed real time SMU behaviors and affective states using the Positive and Negative Affect Schedule–Expanded form subscales. To correct for nonindependent data with EMA responses clustered within individuals, data were analyzed using mixed-effects modeling, allowing for a random intercept at the individual level to examine associations between EMA-reported SMU and affective states while adjusting results for age, gender, race and ethnicity, PHQ-9 score, and EMA response rate. Results A racially and ethnically diverse group of 55 adolescents aged 14 to 19 years provided a total of 976 EMA responses, averaging 17.76 (SD 8.76) responses per participant, with a response rate of 51.15%. Participants reported higher mean levels of negative affect during active SMU (F1,215=3.86; SE 0.05; t1,215=1.96; P=.05) and lower mean levels of positive affect during passive SMU (F1,369=3.90; SE 0.09; t1,369=–1.98; P=.049). However, within different racial and ethnic groups, higher levels of negative affect during moments of active SMU were seen only among Black non-Hispanic participants: F1,81=6.31; SE 0.05; t81=2.51; P=.01). Similarly, lower levels of positive affect during passive SMU were seen only among White non-Hispanic participants (F1,295=10.52; SE 0.13; t295=–3.24; P=.001). Conclusions Although in aggregate, adolescents with depressive symptoms experienced more negative affect during active SMU and less positive affect during passive SMU, these mean outcomes were driven solely by greater negative affect during active SMU by Black non-Hispanic participants and lower positive affect during passive SMU by White non-Hispanic participants. Differences in intentionality, content, context, and expectations of SMU among youths across racial and ethnic groups may result in different affective outcomes. Exploration of the interactions among cultural differences in SMU strategies and characteristics will be critical to furthering our understanding of the impact of SMU on youth mental health.

Publisher

JMIR Publications Inc.

Subject

Computer Science Applications,Health Informatics,Medicine (miscellaneous)

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