Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

Estimated reading time for CME/CPD: 3 mins

Exploring Social Media Use and Anxiety Symptoms in Health Care Workers During the COVID-19 Pandemic: Cross-Sectional Secondary Data Analysis

AI Summary
  • Higher overall social media use was significantly associated with greater anxiety symptoms among HCWs (OR 1.77, 95% CI 1.15-2.73).
  • Clinically relevant anxiety symptoms affected 29% of HCWs; Facebook was most used, with 54% using it at least once per day.
  • Multifactorial contributors included younger age, prior mental health diagnosis, lower income; calls for longitudinal, mixed methods, and more diverse HCW samples for future research.
Summarise with AI (MRCPsych/FRANZCP)

J Med Internet Res. 2026 Oct 15;28:e102008. doi: 10.2196/102008.

ABSTRACT

BACKGROUND: Health care workers (HCWs) experienced significant mental health challenges, particularly anxiety, during the COVID-19 pandemic. Although social media became a primary source of information and connection, it was also a potential source of stress. The influence of social media on HCWs’ anxiety is not well understood.

OBJECTIVE: This study examined associations between social media use and anxiety symptoms among HCWs during the COVID-19 pandemic.

METHODS: We conducted a secondary, cross-sectional analysis of data from the 2021 UC-COVID study (N=427 HCWs). Anxiety symptoms were assessed using the Generalized Anxiety Disorder-2 (GAD-2). Social media use across multiple platforms (Twitter, Facebook, Instagram, other social media platforms, and other media sources) was evaluated using factor analysis to create a single variable for social media use. Logistic regression models estimated associations between overall social media use and anxiety symptoms, both unadjusted and adjusted for demographic, occupational, and health-related characteristics.

RESULTS: Factor analysis supported a single latent factor representing overall social media use, with all platform indicators loading significantly on the factor (P<.001) and with moderate loadings (0.33-0.59). Of 427 HCWs, the mean age was 44.3 (SD 13.5), and the majority identified as female (n=314, 73.5%) and as working in a hospital location (n=136, 43.6%). Facebook was used the most, with 54% (n=230) of participants using the platform at least once per day. A total of 29% reported clinically relevant anxiety symptoms (GAD-2 ≥3). Using the social media variable from the factor analysis, higher social media use was significantly associated with anxiety symptoms (odds ratio [OR] 1.77, CI 1.15-2.73). Older age was significantly associated with reduced anxiety symptoms (adjusted odds ratio [aOR] 0.97, CI 0.95-0.99). HCWs with a history of mental health diagnoses reported higher levels of anxiety symptoms (aOR 2.33, CI 1.35-4.03). Non-Hispanic Asian HCWs reported fewer anxiety symptoms compared to Non-Hispanic White HCWs (aOR 0.39, CI 0.19-0.80). Participants reporting higher income had significantly lower odds of anxiety symptoms than those in the lower-income group (aOR 0.51, CI 0.30-0.87).

CONCLUSIONS: Study findings highlight the multifactorial nature of anxiety symptoms in HCWs and the need to consider social media use as an important contributor. Integrating HCWs and multiplatform social media use into a single measure offered an innovative lens on digital behavior and anxiety symptoms. The rapidly evolving digital landscape underscores the need for continued research. Future studies should include emerging social media platforms (ie, TikTok, Reddit, YouTube) as usage patterns shift over time. Longitudinal and mixed methods approaches are necessary to understand patterns and methods of social media use over time. Larger and more diverse HCW samples, stronger mental health measures (eg, GAD-7, depression, and burnout scales), and analyses stratified by clinical role and sociodemographic factors will be essential to guide interventions supporting mental health and well-being.

PMID:42879747 | PMC:PMC13671597 | DOI:10.2196/102008

Document this CPD

Share Evidence Blueprint

QR Code

Save to Google Notes

Search Google Scholar

Save as PDF

⭐ My Revision List

close chatgpt icon
ChatGPT

Enter your request.

← →
RAISR4D CME/CPD Evidence Nodes
Swipe to navigate RAISR4D CME/CPD evidence nodes.
CME/CPD