Experiencing variety in exercise from a Self-Determination Theory perspective: Prospective effects in relation to motivation quality in exercise settings
Bibliographic record
Abstract
Beyond the three basic psychological needs (competence, autonomy and relatedness) embedded within Self-Determination Theory (SDT; Deci & Ryan, 2000), additional psychosocial experiences may exist and should be explored to better understand motivation. Experiencing variety has been found to be intrinsically motivating (Kahn & Ratner, 2005) and may be particularly salient in exercise contexts as expectations of task variety have been found to be conducive to intrinsic motivation (Dimmock et al., 2012). In this study, we used a prospective observational design to examine the extent to which competence, autonomy, relatedness, and variety predict the quality of internal and external behavioural regulations in exercise. Participants (N = 365) completed an online questionnaire at two time points, six weeks apart. Ratings of competence, autonomy, relatedness, and variety were found to positively predict intrinsic (R2 = .41), integrated (R2 = .32), and identified (R2 = .36) regulation, and negatively predicted external regulation (R2 = .14) and amotivation (R2 = .07). In addition to the basic psychological needs, variety was found to be a unique predictor of intrinsic (B = .13, p < .001), integrated (B = .13, p = .002), identified (B = .11, p < .001) and external (B = -.09, p = .025) regulation. Theoretical implications regarding the basic psychological needs and the experience of variety in exercise settings are discussed along with how variety may supplement our understanding of motivation.Acknowledgments: Funding for this project was provided by the Social Sciences and Humanities Research Council of Canada
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".