UC Davis

With advances in natural language processing and machine learning, researchers are leveraging social media as a low-cost, low-burden method for measuring various psychosocial factors. However, it is unclear whether information derived from social media is generalizable to broader populations, especially middle-aged and older adults. Using data on women aged 53-70 years from Nurses Health Study II (2017-2018; n = 49,045), we assessed differences in sociodemographic characteristics, health conditions, behaviors, and psychosocial factors between regular and nonregular users of Facebook (Facebook, Inc., Menlo Park, California). We evaluated effect sizes with phi (φ) coefficients (categorical data) or Cohens d (continuous data) and calculated odds ratios with 95% confidence intervals. While most comparisons between regular and nonregular users achieved statistical significance in this large sample, effect sizes were mostly very small (conventionally defined as φ or d <0.01) (e.g., optimism score: meanregular users = 19 vs. meannonregular users = 19 (d = -0.03); physical activity: meanregular users = 24 metabolic equivalent of task (MET)-hours/week vs. meannonregular users = 24 MET-hours/week (d = 0.01)). Some factors had slightly larger differences for regular users versus nonregular users (e.g., depression: 28% vs. 23% (φ = 0.05); odds ratio = 1.27 (95% confidence interval: 1.22, 1.33); obesity: 34% vs. 26% (φ = 0.07); odds ratio = 1.42 (95% confidence interval: 1.36, 1.48)). Results suggest that regular Facebook users were similar to nonregular users across sociodemographic and psychosocial factors, with modestly worse health regarding obesity and depressive symptoms. In future research, investigators should evaluate other demographic groups.