Trainer‐exerciser relationship: The congruency effect on exerciser psychological needs using response surface analysis
Bibliographic record
Abstract
Perceptions of fitness trainers' need‐supportive and need‐thwarting behaviors have been shown to impact exercisers' psychological need satisfaction and frustration. Currently, it is unknown whether an agreement or disagreement between exercisers' and fitness trainers' reported perceptions of these behaviors leads to the satisfaction and/or frustration of psychological needs. Based on self‐determination theory, the present study examined the effect of congruency between fitness trainers' and exercisers' perceptions of need‐supportive and need‐thwarting interpersonal behaviors on basic psychological need satisfaction and frustration. A sample of 130 fitness trainers (43 females; Mage = 31.58 ± 7.65) and a total of 640 gym exercisers (350 females; Mage = 34.23 ± 11.59) participated in this study. Findings suggested that the majority of fitness trainers tended to over‐report their use of need‐supportive behavior and under‐report their need‐thwarting behaviors. Results showed that when there was congruency between fitness trainers' reported use and exercisers' perception of interpersonal behaviors, basic need satisfaction tended to increase. This effect was greater for exercisers that rated their respective fitness trainer high on relatedness support. Fitness trainers should be self‐aware of their interpersonal behaviors when engaging with exercisers and interventions based on self‐determination theory could serve as a promising avenue to improve the quality of exercisers' experience.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".