Women's health priorities and perceptions of care: a survey to identify opportunities for improving preventative health care delivery for older women
Bibliographic record
Abstract
BACKGROUND: women live longer than men but consistently report poorer health status and health-related quality of life. Information is scarce on what components of care women desire to help them meet the challenges of their later years. OBJECTIVES: to identify older women"s priorities for maintaining physical, emotional and social well-being in later years and to measure the extent to which women perceive that these priorities are being met by the health care system. METHODS: a cross-sectional survey of community-dwelling women aged 55-93 years old (n = 609, mean age 70). Women attendees of outpatient medical clinics were invited to fill out a written questionnaire on health priorities and perceptions of care. Mismatches between the care that women desired and the care they perceived to be receiving were identified. Predictors of unmet priorities were evaluated. SETTING: the Greater Montreal Area in Quebec, Canada. RESULTS: in general, respondents were more concerned about preventing disability than with developing certain diseases later in life. Women prioritised feeling validated in the health care relationship and having their health care provider see them as a whole person. Deficiencies in addressing memory loss, preserving mobility and function and treating urinary incontinence were highlighted. Women aged 75 years and older were less likely to perceive that their priorities were unmet compared to women aged 55-74 years (OR 0.571; 95% confidence interval 0.404-0.808), when adjusting for other socio-demographic and health variables. CONCLUSIONS: Opportunities exist to improve the preventive health care that women are receiving to promote healthy ageing. Women aged 55-74 should especially be targeted for interventions to prevent disability in later life.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".