An education intervention to improve health literacy and decision making about supporting self-care among older Australians: a study protocol for a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Older Australians are high consumers of complementary and alternative medicines (CM). To help older people to take an active role in their health, we will develop and evaluate a novel educational intervention to support decision self-efficacy, and improve health literacy skills. METHODS: The primary hypothesis is that participants receiving a web/DVD plus booklet intervention compared with a booklet-only group will demonstrate an increase in decision self-efficacy. This study is a randomised controlled trial. One hundred and sixty-eight people aged 65 years and older will be recruited from community settings comprising retirement villages and community groups, based in Sydney, Australia. Participants will be randomly allocated to either the education intervention delivered by the Internet or a DVD plus booklet versus a control group (booklet only). The primary outcome measure is CM decision self-efficacy. Secondary outcomes are health literacy, knowledge and attitudes, and change in health-seeking behaviour. Participants' views on the ease of using the resources, the length of the modules, the amount of information, and participant understanding of the modules will be assessed. Outcomes will be collected on completion of the intervention at 3 weeks, and at a 2-month follow up from trial entry. DISCUSSION: This trial has the potential to improve CM health literacy in older Australians. There are no educational resources designed to support decision self-efficacy and improve health literacy amongst older people related to CM. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12616000135415 . Registered on 5 February 2016.
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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 | 0.037 | 0.035 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.011 |
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".