Understanding consumer receptivity towards foods and non‐prescription pills containing phytosterols as a means to offset the risk of cardiovascular disease: an application of protection motivation theory
Bibliographic record
Abstract
Abstract Consumer purchase intention with respect to foods and non‐prescription pills containing phytosterols was investigated through a mall intercept survey ( n = 446) in Ontario, Canada. The study took as its starting point the Protection Motivation Theory (PMT), a social cognition model rooted in research on fear appeal in determining health‐protective behaviour. Structural equation modelling was used to explore whether an adaptation of PMT explains intention to purchase products containing phytosterols as a means to reduce the risk of cardiovascular disease (CVD). The standard form of PMT was adapted to take account of consumer perceptions of the risk of elevated blood cholesterol, reflecting the fact that phytosterols do not directly reduce the risk of CVD but rather help in the management of a single risk factor. Overall, coping appraisal had a positive and significant association with purchase intention, while threat appraisal had no significant effect. Incorporation of cholesterol as a risk factor for CVD significantly improved the measurement strength of the threat appraisal construct. However, the overall predictive power of the model did not change appreciably. The results suggest that the promotion of adaptive behaviours, such as consumption of functional foods and nutraceuticals, needs to focus on perception of response and self‐efficacy rather than individual perceptions of risk.
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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 | 0.001 | 0.001 |
| 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".