Effects of autonomous motivational priming on motivation and affective responses towards high-intensity interval training
Bibliographic record
Abstract
This study examined the effect of autonomous motivational priming on motivation, attitudes and intentions towards high-intensity interval training (HIT). Participants (N = 42) performed a graded exercise test to determine their peak aerobic power (WPEAK). At a subsequent testing session, participants were randomised to complete either an autonomous or neutral motivational priming task followed by a 10 × 1 HIT exercise protocol, alternating 1-min bouts of hard (70% WPEAK) and light (12.5% WPEAK) exercises for 20 min. Participants primed with autonomous motivation reported greater enjoyment, P = .009, ηp(2) = .16, and perceived competence, P = .005, ηp(2) = .18, post-exercise compared to those in the neutral priming condition. Participants in the autonomous motivational priming condition also reported more positive attitudes, P = .014, ηp(2) = .14, towards HIT; however, there was no difference between the conditions for task motivation during HIT or intentions, P = .53, ηp(2) = .01, to engage in HIT. These findings highlight autonomous motivational priming as a method of enhancing affective and motivational experiences regarding HIT.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".