Demographic and psychometric predictors associated with engagement in risk-associated alternative healthcare behaviours
Bibliographic record
Abstract
This paper builds on prior work exploring the use of risk-associated alternative healthcare (RAAH) in Canada. RAAH uptake was surveyed to explore the characteristics of adult RAAH users and the value of established psychometric instruments previously used in alternative healthcare studies in predicting RAAH behaviours: the Control Beliefs Inventory (CBI), the Reward Responsiveness Behavioural Activation System (RBAS) scale, the Positive Attitudes to Science (PAS) scale, the Satisfaction with Orthodox Medicine (SOM) scale, and the brief version of the Susceptibility to Persuasion-II (StP-II-B) scale. Findings suggest RAAH is influenced by gender, age, income, education, employment, chronic illness status, and ethnicity. Engagement in some form of RAAH was common (around 40%) and the most common types of RAAH use reported were physical manipulation and herbal/nutritional supplement use. Other higher-risk AH activities (such as use of toxins and physically invasive procedures) were also reported by about 5% of respondents. The StP-II-B and PAS instruments were predictive of the likelihood of engagement in RAAH behaviours, as illustrated by higher risk tolerance, desire for novelty, positive attitude to advertising and social influence, and positive beliefs about science. The CBI, RBAS, and SOM instruments were not predictive overall. However, the CBI and SOM instruments were predictive of engagement with physical manipulative RAAH activities, while the RBAS was predictive of herbal/nutritional RAAH engagement. These findings can help inform health professionals' understanding of public health-seeking behaviours with respect to risk.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".