Social Disconnection and Psychological Distress in Canadian Men During the COVID-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic has significantly challenged many men's mental health. Efforts to control the spread of the virus have led to increasing social disconnection, fueling concerns about its long-term effects on men's mental health, and more specifically their experience of psychological distress. Social disconnection, psychological distress, and the relationship between them have yet to be formally explored in a Canadian male sample during the COVID-19 pandemic. The present study examined whether reduced social connection among men was associated with increased anxiety and depressive symptoms (psychological distress) and whether this association was moderated by living alone. The sample consisted of 434 help-seeking Canadian men who completed standardized measures. Analyses controlled for the potentially confounding effects of age and fear of COVID-19. Findings revealed that less social connection was associated with increased psychological distress. This association was not moderated by living alone, nor was living alone directly associated with psychological distress. Younger age and fear of COVID-19 were each independently associated with psychological distress. Socially disconnected men were more likely to experience anxiety and depressive symptoms, suggesting the need for interventions focussed on men's social connectedness, social support, and belongingness to help reduce some COVID-19-induced mental health risks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".