Instagram as a Window to Societal Perspective on Mental Health, Gender, and Race: Observational Pilot Study

• Published in: JMIR mental health 2020-10, Vol.7 (10), p.e19171-e19171
• Main Authors: Utter, Kierstin, Waineo, Eva, Bell, Capricia M, Quaal, Harrison L, Levine, Diane L
• Format: Article
• Language: English
• Subjects: African Americans; Anxiety; Attitudes; Chi-square test; COVID-19; Data collection; Females; Gender; Hispanic Americans; Mental depression; Mental disorders; Mental health; Mental health care; Original Paper; Popularity; Race; Social networks; Social research; Stigma; Suicides & suicide attempts; Tagging; Women
• ISSN: 2368-7959; 2368-7959
• DOI: 10.2196/19171

Background: Gender and race are known to impact attitudes toward mental health topics and help-seeking behavior. Men and minorities are more likely to cite stigma as a reason for not seeking help for mental health concerns, which is of particular relevance given the high rate of suicide in men and challenges of historic proportion currently facing minority communities. Instagram provides a platform to discuss mental health, though a lack of male and minority representation may further alienate these populations. Objective: We aimed to investigate whether men and nonwhite individuals are underrepresented in Instagram photos tagged with #mentalhealth (compared to photos tagged with #health) to better understand how gender and race-based representations are manifested on this popular social media platform and discuss the implications. Methods: Three investigators of different genders and racial backgrounds met on nine different days via teleconference to analyze a total of 215 publicly available Instagram photos tagged with #mentalhealth and 215 with #health. These photos were generated using Instagram’s search function, and search results were sorted by most recently published at the time of data collection. For each photo, the three investigators recorded their observations about the gender (male versus female) and race (white versus nonwhite versus racially unclassifiable) of subjects featured in the photo, which they did not discuss with other investigators. Chi-squared analysis was performed on each investigator’s data set to compare the frequency of male versus female and white versus nonwhite subjects identified in each hashtag category. Kappa interrater agreement was calculated for each investigator pair, category (gender or race), and hashtag. Results: All three investigators observed significantly more female as compared to male subjects in photos tagged with #mentalhealth (X2=14.4, P