“Appreciate the Little Things”: A Qualitative Survey of Men’s Coping Strategies and Mental Health Impacts During the COVID-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic has presented a suite of circumstances that will simultaneously affect mental health and mobilize coping strategies in response. Building on a lack of research specifically exploring men’s mental health impacts during the COVID-19 pandemic, this study presents the results of a qualitative survey exploring men’s self-reported aspects of the pandemic giving rise to mental health challenges, alongside their diverse coping strategies applied during this time. The sample comprised 555 men from North America (age M = 38.8 years; SD = 13.5 years), who participated via an online survey with two open-ended qualitative questions assessing, respectively, the aspects of the pandemic affecting their mental health, and the strategies used to manage these challenges. Free-text responses were coded using inductive content analysis. Results pertaining to the mental health impacts of COVID-19 were categorized into two overarching themes: far-reaching ramifications of COVID-19 encompassing consequences for lifestyle, work, and functioning, alongside novel anxieties related to health risks and daily uncertainty. In addition, coping strategies reported were categorized into two broad themes: efforts to avoid, dull or distract oneself from distress, alongside adapting and doing things differently, which encompassed largely approach-oriented efforts to flexibly ameliorate distress. Results signal the far-reaching impacts of COVID-19, alongside profound flexibility and diverse enactments of resilience among men in adapting to unprecedented challenges. Findings have implications for mental health promotion that should aim to leverage men's adaptive coping to encourage opportunities for social connectedness in response to the mental health impacts of the various psychosocial challenges of the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".