Causal Model of Health Literacy in Thai Older Adults with Knee Osteoarthritis
Bibliographic record
Abstract
Knee osteoarthritis is the most common form of arthritis causing disability among older adults. Proper self-care is vital and achievable with health literacy. Thai older adults with knee osteoarthritis have been found to have inadequate health literacy, and poor selfcare behaviors for this condition. The purpose of this descriptive cross-sectional study was to test a causal model of health literacy in Thai older adults with knee osteoarthritis, depicting relationships among provider-patient communication, patient engagement, cognitive function, knowledge of knee osteoarthritis, Internet use, social support, social participation, and health literacy. Participants comprised 318 older adults with knee osteoarthritis, selected using multi-stage random sampling from nine community hospitals in a northern Thai province. Data were collected using a demographic data form, the European Health Literacy Survey Questionnaire, the Provider-patient Communication Scale, the Patient Health Engagement Scale, the Montreal Cognitive Assessment-Basic, the Arthritis Knowledge Scale, the Internet Use Questionnaire, the Social Support Questionnaire, and the Community Participation of the Elderly Questionnaire. Data were analyzed using descriptive statistics, Pearson’s product moment correlation, and structural equation modeling. The final model fitted with empirical data and explained 36% of the variance in health literacy with Internet use as the strongest predictor directly affecting health literacy. Internet use and social participation had positive direct and indirect effects on health literacy via cognitive function. Cognitive function and social support positively directly affected health literacy. Patient engagement negatively affected health literacy indirectly via Internet use. Knowledge of knee osteoarthritis and provider-patient communication did not affect health literacy directly or indirectly. In conclusion, nurses should design interventions to promote health literacy of this population by highlighting Internet use, social participation, cognitive function, social support, and patient engagement, with testing in clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".