L’effet de l’âge, du genre et du statut socioéconomique sur l’utilisation des services de médecine générale pour des symptômes de détresse psychologique
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was, first, to document the psychometric characteristics of a measure of the older adults' socioeconomic status and, secondly, to test the effect of the socioeconomic status on the association between the older adults perceived need to improve their mental health and their use of services in the general medical sector for psychological distress symptoms taking into account the effect of age and gender. METHOD: Data used in this study come from the ESA study (Enquête sur la santé des ainés) on mental health and aging, conducted in 2005-2008 using a probabilistic sample (n=2811) of the older adult population aged 65 years and over living at home in Quebec. RESULTS: Our results showed that a measurement model of the older adults' socioeconomic status including an individual-level (SES_I) and an area/contextual-level dimension of socioeconomic deprivation (SES_C) was plausible. The reliability of the SES index used in the ESA research program was .92. Our results showed that women (b=-.43) and older people (b=-.16) were more at risk to have a disadvantaged socioeconomic status. However, our results did not show evidence of a significant association between the older adults' socioeconomic status, their perception of a need to improve their mental health and the use of medical services for psychological distress symptoms in the general medical sector in the older adult population in Quebec. CONCLUSION: Our results do not support the idea suggested in other studies that socioeconomic status has an effect on the older adults use of services for psychological distress symptoms in the general medical sector and suggest that in a context where medical health services are provided under a public insurance programme context, the socioeconomic status does not influence access to services in the general medical sector in the older adult population.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".