Coping with fashion for mental health during the COVID-19 pandemic: Part II on motivations and effects
Bibliographic record
Abstract
Understanding clothing’s role in coping and managing daily needs and stressors is critical in understanding its therapeutic possibilities and effects on mental health. Part II of the study involved 576 Canadian emerging adults, exploring their motivations behind clothing engagement whilst navigating the peaks of the pandemic, and how clothing affected their mental health. Individuals reported multiple motivations in their use of clothing, including comfort, self-assurance, individuality, fashion, camouflage, motivation and normalcy. The quantitative analysis found no relationship between the practice of enhancing mood through clothing and mental health. The qualitative analysis revealed several positive and negative effects clothing had on mental health through self-esteem, mood, self-efficacy, distraction, self-congruency and self-empowerment. Findings provide partial evidence that clothing practices and COVID-19’s disruptions to clothing engagement effected perceived mental health. Future research is encouraged to further explore the relationship between clothing and mental health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".