Vested interest increases long-term engagement in exercise:effects on intentions and marathon performance through self-efficacy
Bibliographic record
Abstract
To helping address the global pandemics of obesity and chronic diseases further research should be conducted on understanding why people (e.g., regular exercisers) participate in and maintain regular exercise over the long term. Past research has shown that vested interest — the perceived hedonic relevance of an attitude object — can promote behaviour change. Critically though, no research to date has explored the role of vested interest in exercise. Thus, we examined the relationship between attitudes, vested interest and exercise intentions and behaviour by exploring the effect of vested interest on exercise engagement (intentions and marathon performance) through self-efficacy. Two studies (N1 = 145; N2 = 53) show that: a) individuals holding high levels of vested interest would exercise even if their attitude toward exercising is negative; b) the effect of vested interest on exercise intentions occurs both directly and indirectly via self-efficacy; and c) the effect of vested interest on exercise engagement and maintenance (marathon performance) occurs indirectly via self-efficacy. According to our novel findings, vested interest represents an overlooked social-psychological dimension that could play an important role in promoting healthier lifestyles and should be investigated more consistently to better understand the psychological, social and behavioural aspects of sport and exercise. Indeed, interventions could target inactive and active people alike by focusing on increasing perceptions of the vested implications of exercising, hence stakeholders might consider using the findings of this research to design and implement prevention campaigns and behaviour change interventions that could target communities’ cardiorespiratory and metabolic fitness, health and wellbeing.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".