M Czeisler1,2,3, J Wiley1, C Czeisler1,4,5, S Rajaratnam1,2,4,5, M Howard1,2,6. 1. Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia. 2. Institute for Breathing and Sleep, Austin Health, Melbourne, Victoria, Australia. 3. Department of Psychiatry, Brigham & Women's Hospital, Boston, Massachusetts, United States. 4. Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham & Women's Hospital, Boston, Massachusetts, United States. 5. Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, United States. 6. Division of Medicine, University of Melbourne, Melbourne, Victoria, Australia.
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 largescale 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 4,039 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 prevalences 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 higher prevalences of anxiety and depression symptoms in April 2020 (e.g., one-survey versus 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 higher 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 revealed 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 prevalences than longitudinal surveys.
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 largescale 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 4,039 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 prevalences 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 higher prevalences of anxiety and depression symptoms in April 2020 (e.g., one-survey versus 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 higher 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 revealed 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 prevalences than longitudinal surveys.
Entities:
Keywords:
Mental Health; Population Survey; Research Design and Methods; Survival Analysis
Authors: Kieran Ayling; Ru Jia; Carol Coupland; Trudie Chalder; Adam Massey; Elizabeth Broadbent; Kavita Vedhara Journal: Ann Behav Med Date: 2022-05-18
Authors: Flávia L Osório; Antonio Waldo Zuardi; Isabella L M Silveira; José Alexandre S Crippa; Jaime Eduardo Cecílio Hallak; Karina Pereira-Lima; Sonia R Loureiro Journal: Front Psychiatry Date: 2022-04-08 Impact factor: 5.435