Effects of an affective mental contrasting intervention on physical activity behaviour
Bibliographic record
Abstract
University is a vulnerable period for discontinuing regular physical activity, which can have implications for individuals' physical and psychological health (Bray & Born, 2010). Accordingly, it is imperative to develop and implement cost and time-effective interventions to mitigate the consequences of this transition. Mental contrasting is a self-regulatory strategy that involves imagining the greatest outcome associated with achieving a desired goal while also considering the most critical obstacle for attaining that same goal (Oettingen & Gollwitzer, 2010). Intervention research has shown that mental contrasting can be taught in a cost- and time-effective way, affecting numerous health behaviours including physical activity (Oettingen, 2012). Drawing from diverse theoretical perspectives, recent meta-analytic evidence suggests that affective judgements (e.g., enjoyable-unenjoyable) exert greater influence on physical activity behaviours than instrumental judgements (e.g., useful-useless; Rhodes, Fiala, & Conner, 2009). The present study utilized mental contrasting as a means of targeting affective judgements, through intervention, in order to bolster physical activity promotion efforts. 110 inactive, female, university students were randomly assigned to an affective, instrumental or standard mental contrasting intervention. Assessments were conducted at baseline, and 4-weeks post intervention. After controlling for baseline levels, participants in the affective mental contrasting condition displayed higher moderate-to-vigorous physical activity (MVPA) than those in the instrumental or standard comparison conditions, F(2, 90) = 3.14, p < .05, ηp2 = 0.065. Overall, affective mental contrasting may help inactive, female students increase activity or attenuate declining levels of MVPA that typically occurs during university.Acknowledgments: This research was supported by a graduate scholarship awarded to Geralyn Ruissen by the Canadian Institute of Health Research.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".