Construal levels and self-control of effortful exercise
Bibliographic record
Abstract
An influential theory of self-control suggests that people have a finite store of self-control resources and as these resources are spent, individuals are prone to self-control failure (Baumeister et al., 1998). Self-control over goal attainment is compromised when self-control resources have been depleted (Hagger et al., 2010), but has been shown to be more successful when one has concrete action plans or implementation intentions (Gollwitzer & Sheeran, 2006). In the construal level theory, a concrete (implementation) mindset is associated with means-related (i.e., how to perform a behaviour) details and can be primed using an exemplar task (Trope & Liberman, 2003). The purpose of this study was to investigate if a concrete construal mindset would affect self-controlled performance during an effortful cycling task. Participants (N= 67) were separated into 4 groups in a randomized 2X2 design. Participants first completed either a self-control depleting task (modified Stroop task) or quiet rest control task. They were then given a priming task to induce either a high or low construal mindset. The main outcome measure was the amount of work (watts) generated at 1-minute intervals during a 10-minute cycling task performed at a constant level of perceived exertion (i.e., rating of 15 on Borg’s 6-20 RPE scale). Result showed a significant 3-way (Stroop X construal X time) interaction (p = .014). Analysis of simple effects showed performance deterioration over the course of the cycling trial in the depleted high construal group. In contrast, the depleted low construal group performed consistently over time at the same level as the high construal non-depleted group. Results suggest that concrete action representations support effortful performance when self-control resources are low. Findings have implications for athletic performance and lifestyle exercise behaviours that require self-control. Acknowledgments: This research was supported by the Social Sciences and Humanities Research Council.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".