A Brief Report on Sex-Specific Differences in Persistent Depression, Anxiety, and Loneliness Among Canadian Veterans During the COVID-19 Pandemic
Bibliographic record
Abstract
INTRODUCTION: Older adults are at increased risk of severe illness and mortality from Coronavirus disease of 2019 (COVID-19) infection. However, public health strategies aimed at reducing spread of COVID-19 may have resulted in increased mental health symptoms, particularly among older adults. Currently, little is known about whether older Veterans were more likely to experience persistent mental health symptoms during the COVID-19 pandemic than non-Veterans. The objectives of the current study were to (1) compare differences in persistent symptoms of anxiety, depression, and loneliness among a sample of Canadian Armed Forces Veterans and non-Veterans ≥55 years of age and (2) to evaluate potential sex-specific differences in persistent mental health symptoms. MATERIAL AND METHODS: The data for this study are drawn from a longitudinal survey of Canadian adults (55 years and older) during the COVID-19 pandemic. Ethical approval was received from the Women's College Hospital Research Ethics Board. Participants completed a baseline survey of sociodemographic, mental health-related, and COVID-19-related variables in May 2020 and 8 follow-up surveys monthly between May 2020 and January 2021. Modified Poisson regression models with robust standard errors were used to estimate risk of persistent symptoms of anxiety, depression, and loneliness. RESULTS: Eight hundred twenty-nine participants (13.7% [n = 114] Veterans) were included in the analysis of persistent depressive symptoms, 859 participants (14.0% [n = 120] Veterans) were included in the analysis of persistent anxiety symptoms, and 862 (13.9% [n = 120] Veterans) were included in the analysis of persistent symptoms of loneliness. When comparing male Veterans and non-Veterans, there were small but statistically insignificant differences in persistent symptoms of anxiety (adjusted relative risk [aRR], 0.59; 95% confidence interval [CI], 0.24-1.46), depression (aRR, 1.54; 95% CI, 0.63-3.77), or loneliness (aRR, 0.79; 95% CI, 0.36-1.75); similar small but statistically insignificant differences were observed in persistent symptoms of anxiety (aRR, 1.26; 95% CI, 0.51-3.09), depression (aRR, 1.16; 95% CI, 0.49-2.73), and loneliness (aRR, 1.33; 95% CI, 0.61-2.90) when comparing female Veterans to female non-Veterans. CONCLUSIONS: Qualitative, but statistically nonsignificant sex-specific differences in persistent symptoms of anxiety, depression, and loneliness during the early months of the COVID-19 pandemic were observed in this study comparing Veterans and non-Veterans. Additional sex-stratified analyses using larger samples or qualitative interviews may be useful in understanding the unique mental health experiences of older men, women, and gender diverse Veterans during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".