An online cross‐sectional survey of the health risk behaviours among informal caregivers
Bibliographic record
Abstract
ISSUE ADDRESSED: Informal caregivers may experience unique barriers to engaging in healthy lifestyles, consequently increasing their risk of chronic disease. Among a convenience sample of informal caregivers, this study aimed to: (a) assess the self-reported health risk behaviours of low fruit and vegetable consumption, low physical activity, current smoking and hazardous alcohol consumption; (b) examine the demographic, caree condition and country of residence variables associated with each health risk behaviour; and (c) report the engagement in multiple health risk behaviours. METHODS: An online cross-sectional survey among caregivers in Australia, Canada, New Zealand, the United Kingdom and the United States was conducted. Self-reported health risk behaviours were assessed and compared to key Australian healthy living guidelines. Logistic regression modelling identified participant factors associated with each health risk behaviour. RESULTS: Overall, 384 caregivers were included in the analysis. Hazardous alcohol consumption was the only self-reported health risk behaviour which was much higher than in the general population (60.0%). Caregiver age (P = .018) and country of residence (P = .015) were associated with hazardous alcohol consumption. A majority of caregivers reported engaging in three health risk behaviours (55.0%). CONCLUSIONS: Caregivers are engaging in a range of health risk behaviours; however, rates of hazardous alcohol consumption among the sample were high. Health promotion interventions targeted to address alcohol consumption should consider caregiver age and country of residence. SO WHAT?: This study highlights the health risk behaviours caregivers engage in across a number of countries, and suggests that caregivers require further support to manage alcohol consumption in particular.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".