Health literacy mediates the relationships of cognitive and physical functions with health-related quality of life in older adults
Bibliographic record
Abstract
Background Declining cognitive function (CF) and physical function (PF) relate to poorer health-related quality of life (HRQoL) in older adults. As health literacy (HL) facilitates health information utilization, it may mediate links between functionality and HRQoL appraisals. This study examined HL as an intermediary between joint CF and PF contributions and HRQoL in Hong Kong older adults. Methods 490 older adults aged 50–80 years completed assessments from March to July 2021. Health Literacy Survey Questionnaire Short Form 12 questions (HLS-SF12), Montreal Cognitive Assessment (MoCA), Senior Fitness Test (SFT) and 12-Item Short-Form Health Survey version 2 (SF-12v2) were used to assess HL, CF, PF and HRQoL, respectively. Path analysis tested a model with HL mediating CF/PF predictors and HRQoL outcome. Results Results for direct effects indicated that CF significantly associated with PF (β = 0.115, SE = 0.012, p < 0.001), PF significantly connected to HL (β = 0.101, SE = 0.022, p < 0.001), and HL significantly related to HRQoL (β = 0.457, SE = 0.049, p < 0.001). Meanwhile, PF significantly linked to HRQoL directly (β = 0.156, SE = 0.025, p < 0.001) as well as indirectly (β = 0.046, 95% CI [0.028, 0.067]). Significant mediating effect of HL was found on the relationship of PF and HRQoL. Conclusion Findings confirm CF and PF joint impacts on HL and HRQoL in older adults, elucidating HL’s mediating role in translating functionality levels into HRQoL. Fostering enduring health knowledge access may thus buffer effects of age-related declines on well-being. Results can inform interventions leveraging this pathway to promote resilient trajectories.
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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 | 0.007 |
| 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 | 0.000 | 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".