Comparing motivational differences between competitive and recreational weight trainers using Organismic Integration Theory: A replication and extension study
Bibliographic record
Abstract
Objective: Grounded in Organismic Integration Theory (OIT; Deci & Ryan, 2002), the purpose of this study was to examine differences in motives for participation behaviour reported by competitive (CWT) and recreational (RWT) weight trainers. Methods: CWT (n = 177; Mage = 30.86 years; SDage = 11.35 years) and RWT (n = 196; Mage = 21.97 years; SDage = 6.05 years) provided data using a cross-sectional, non-experimental design. Participants completed a multi-section questionnaire that included demographic items, habitual weight training behaviour items, and the Behavioural Regulation in Exercise Questionnaire-2 plus items assessing integrated regulation. Results: The CWT reported more weight training sessions during a typical week (t(367) = 3.58, p < .01, 95%CI = 0.20 – 0.69; Cohen's d = 0.37) and more days of weight training over the past week (t(371) = 3.85, p < .01, 95%CI = 0.23 – 0.70; Cohen's d = 0.40) compared to the RWT. Multivariate differences were evident in the motives for weight training reported by CWT and RWT (F(5, 362) = 43.58, p < .01, Wilks' Lambda = 0.62, ?p2 = 0.38). Follow-up analyses indicated the CWT reported more identified, integrated, and intrinsic regulations for weight training compared to the RWT who reported greater levels of external regulation (?p2 = 0.09 to 0.34; all p's < .05). Discussion: Overall, the results of this study make it apparent that motivational differences within the OIT framework exist between competitive and recreational weight trainers that may be important for understanding participation behaviour in this context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".