The relationship between health literacy and quality of life among frequent users of health care services: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Although health literacy and quality of life are important concepts in health care, the link between them is unclear, especially for a population of frequent users of health care services with chronic diseases. Low health literacy is a common problem that has been linked to several negative health outcomes. Quality of life is an important health outcome in patient-centered care. Frequent users of health care services are a vulnerable population that deserves attention due to high costs and negative outcomes such as lower quality of life and higher mortality. The objective of this study was to examine the relationship between health literacy and the physical and mental components of quality of life among frequent users of health care services with chronic diseases. METHODS: This study presents the cross-sectional analysis of data collected through the V1SAGES project, a randomized controlled trial on the effectiveness of a case management intervention in primary care in Quebec, Canada. Participants (n = 247) were frequent users of health care services presenting at least one chronic condition. Health literacy was measured by the Newest Vital Sign (NVS), and the physical and mental components of quality of life were evaluated by the Short Form Health Survey Version 2 (SF-12v2). The association between health literacy (independent variable) and the physical and mental components of quality of life was examined using biserial correlation. RESULTS: No association was found between health literacy and quality of life (physical component: r = 0.108, ρ = 0.11; mental component: r = 0.147, ρ = 0.15). CONCLUSION: This study suggests that there is no relationship between health literacy and the physical and mental components of quality of life among frequent users of health care services. TRIAL REGISTRATION: NCT01719991 . Registered October 25, 2012.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".