Age-related patterns in mental health-related complementary and alternative medicine utilization in Canada
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine whether age-related differences in rates of use of complementary and alternative medicine (CAM) specifically for mental health problems parallel well-known age-related differences in use of conventional mental health services and medications. METHODS: A sample of middle-aged (45-64 years; n = 10,762), younger-old (65-74; n = 4,113) and older-old adults (75 years and older; n = 3,623) was drawn from the 2001-2002 Canadian Community Health Survey (CCHS), Cycle 1.2, Mental Health and Wellbeing. Age-related utilization rates of conventional and complementary mental health services and medications/products were calculated. Logistic regression analyses were used to examine the strength of association between age group and utilization of services and medications or products in the context of other important sociodemographic and clinical characteristics. RESULTS: When considered in the context of other sociodemographic and clinical characteristics, older age was positively associated with mental health-related utilization of alternative health products. Older age was not significantly associated with mental health-related consultations with CAM providers. CONCLUSIONS: Overall, age-related patterns in mental health-related use of CAM did not directly correspond to age-related patterns in conventional mental health care utilization, suggesting different sets of predictors involved in seeking each type of care.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".