Socio-Demographic Influences on Perceived Stress and Mental Health During the COVID-19 Pandemic: a Multinational Study
Bibliographic record
Abstract
The present cross-sectional multinational study explores the effect of perceived stress during the COVID-19 pandemic on various socio-demographic factors, including gender, marital status, age groups, work abilities, social activities, and family relationships from Saudi Arabia, Canada, and Pakistan from April to July 2022. This cross-sectional study investigated perceived stress during the COVID-19 pandemic on various socio-demographic factors, work abilities, social activities, and family relationships. Online questionnaires were distributed to participants in Saudi Arabia, Canada, and Pakistan. Mental health indicators were assessed using the Work and Social Adjustment Scale. Spearman’s correlation analysis revealed moderate impairment in working capacity and home management, with a significant effect (r = .565, p < .001). A significant association was observed between gender and engagement in leisure activities such as watching movies, indicating influence on mental well-being (χ2(1, N = 295) = 6.83, p = .009). Analysis of variance (ANOVA) showed significant differences in commitment to home management across four age groups (adolescent, young adult, adult, and mature adult) (F (3, 294) = 3.887, p = .010). Significant variations were also found in maintaining relationships with family members among different age groups (F (3, 294) = 5.506, p = .001). The findings underscore the association between anxiety and impairment in work and home management activities, and disruptions in leisure activities. These insights highlight the importance of targeted interventions to address mental health challenges during current and future healthcare crises. Further prospective studies are warranted to inform comprehensive intervention strategies and enhance resilience in future global challenges.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".