Predicting Walking Intentions and Behaviour among Individuals with Intermittent Claudication: The Role of Pain within the Theory of Planned Behaviour
Bibliographic record
Abstract
This study aimed to improve understanding of walking exercise among individuals with intermittent claudication. Using a prospective design, Ajzen's (1985, 1991) theory of planned behaviour was applied to examine psychosocial determinants of walking exercise. In addition, measures of barrier self-efficacy were explored as determinants of behaviour and perceived pain intensity was examined as a moderator of the intention-behaviour relationship. Ninety-four participants (n = 33 female) completed baseline measures of attitudes, subjective norms, perceived behavioural control, and intentions to engage in walking exercise. Additional measures of pain-related barrier self-efficacy and barrier self-efficacy regarding walking exercise were obtained and the Borg CR1 0 Pain Scale (Borg, 1998) was used to assess perceived pain intensity during walking. Participants were contacted weekly by telephone over four consecutive weeks and asked to recall their walking exercise and associated perceived pain intensity for the preceding seven-day period. Attitudes, subjective norms and perceived behavioural control contributed significantly to a multiple regression model predicting 67% of the variance in walking intentions. Intentions and perceived behavioural control explained 34% of the variance in walking exercise; however, pain-related barrier self-efficacy and barrier self-efficacy did not explain additional variance in behaviour and perceived pain intensity failed to moderate the intention-behaviour relationship. Findings support the theory of planned behaviour for predicting walking intentions and exercise among individuals with intermittent claudication, and suggest that pain cognitions as measured in this study do not play a role in determining walking.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".