Mentally healthy living after pandemic social distancing: a study of older <scp>Canadians</scp> reveals helpful anxiety reduction strategies
Bibliographic record
Abstract
BACKGROUND: Throughout the COVID-19 pandemic, older Canadians were the most at risk of severe physical harm, including death, and their return to post-COVID life was expected to be especially anxiety-provoking. A study was conducted to obtain nationally representative evidence of older Canadians' self-perceived anxiety levels and their strategies to manage or mitigate it as public health restrictions were lifting. MATERIALS AND METHODS: This study had a cross-sectional descriptive design. An e-survey was used to collect data from 1327 Canadians aged 60+ stratified by age, sex, and education to resemble the larger general population. Participants completed the Geriatric Anxiety Scale (GAS-10) and indicated which of the 16 Centre for Addictions and Mental Health's (2022) Coping with Stress and Anxiety strategies they were using to manage or mitigate their anxiety when social distancing was lifting. Descriptive statistics, Pearson correlation, and multiple regression analysis were used to explore the data. RESULTS: While, on average, older Canadians were mildly anxious, nearly one-quarter of responders rated their anxiety as severe. Age, sex, perceived health, were statistically significant correlates of anxiety. Six coping strategies were associated with significantly lower anxiety scores. Moreover, accepting some fear and anxiety as normal, challenging worries and anxious thoughts, and practising relaxation/meditation appeared to increase anxiety. CONCLUSION: Older Canadians used multiple strategies to manage or mitigate their anxiety, and seemingly, with more successful than detrimental tries. Practitioners have much to learn and understand about older people's mental health promotion efforts after social distancing, now and for future pandemics.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".