Effect of Age-Friendly Communities Action Plan on Trajectories of Older Canadians’ Depressive Symptoms Between 2018 and 2020: Multilevel Results From the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
As the COVID-19 pandemic impacted mental health, this longitudinal study examined the effect of age-friendly communities (AFC) action plan on older adults' depressive symptoms. Using the CLSA, the CLSA COVID-19 Questionnaire study, survey of Canadian municipalities, and the census, the depressive symptoms trajectories were modeled with multilevel multinomial regressions. Most respondents (66.1%) had non-depressed trajectories, 28.1% experienced a moderate increase in depressive symptoms, and 5.8% had a depressed trajectory. AFC action plans did not have a protective effect on these trajectories. Being a female, greater loneliness, lower income, ≥2 chronic conditions, inferior social participation, weaker sense of belonging, COVID-19 infection, and pandemic stressors predicted a depressed trajectory. Neighborhood's deprivation had a weak protective effect on the declining trajectory. Although AFC action plans provided no benefits during the pandemic, volunteers facilitating resource access and social interactions could limit any increase in depressive symptoms.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".