Uncovering survivorship bias in longitudinal mental health surveys during the COVID-19 pandemic

• Published in: Epidemiology and Psychiatric Sciences Vol. 30; p. e45
• Main Authors: Czeisler, Mark É., Wiley, Joshua F., Czeisler, Charles A., Rajaratnam, Shantha M.W., Howard, Mark E.
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 26.05.2021
• Subjects: Anxiety; Bias; Censuses; Coronaviruses; COVID-19; Disease transmission; Estimates; Ethnicity; Gender; Health surveys; Insomnia; Internet; Mental depression; Mental health; Original; Original Article; Pandemics; Participation; Population; Psychiatry; Rape; Research design; Severe acute respiratory syndrome coronavirus 2; Sex crimes; United Kingdom > UK; United States > US; non-random attrition; non-response bias; research design and methods; Epidemiology
• ISSN: 2045-7960; 2045-7979
• DOI: 10.1017/S204579602100038X

Abstract Aims Markedly elevated adverse mental health symptoms were widely observed early in the coronavirus disease-2019 (COVID-19) pandemic. Unlike the U.S., where cross-sectional data indicate anxiety and depression symptoms have remained elevated, such symptoms reportedly declined in the U.K., according to analysis of repeated measures from a large-scale longitudinal study. However, nearly 40% of U.K. respondents (those who did not complete multiple follow-up surveys) were excluded from analysis, suggesting that survivorship bias might partially explain this discrepancy. We therefore sought to assess survivorship bias among participants in our longitudinal survey study as part of The COVID-19 Outbreak Public Evaluation (COPE) Initiative. Methods Survivorship bias was assessed in 4039 U.S. respondents who completed surveys including the assessment of mental health as part of The COPE Initiative in April 2020 and were invited to complete follow-up surveys. Participants completed validated screening instruments for symptoms of anxiety, depression and insomnia. Survivorship bias was assessed for (1) demographic differences in follow-up survey participation, (2) differences in initial adverse mental health symptom prevalence adjusted for demographic factors and (3) differences in follow-up survey participation based on mental health experiences adjusted for demographic factors. Results Adjusting for demographics, individuals who completed only one or two out of four surveys had significantly higher prevalence of anxiety and depression symptoms in April 2020 (e.g. one-survey v . four-survey, anxiety symptoms, adjusted prevalence ratio [aPR]: 1.30, 95% confidence interval [CI]: 1.08–1.55, p = 0.0045; depression symptoms, aPR: 1.43, 95% CI: 1.17–1.75, p = 0.00052). Moreover, individuals who experienced incident anxiety or depression symptoms had significantly higher adjusted odds of not completing follow-up surveys (adjusted odds ratio [aOR]: 1.68, 95% CI: 1.22–2.31, p = 0.0015, aOR: 1.56, 95% CI: 1.15–2.12, p = 0.0046, respectively). Conclusions Our findings reveal significant survivorship bias among longitudinal survey respondents, indicating that restricting analytic samples to only respondents who provide repeated assessments in longitudinal survey studies could lead to overly optimistic interpretations of mental health trends over time. Cross-sectional or planned missing data designs may provide more accurate estimates of population-level adverse mental health symptom prevalence than longitudinal surveys.