Men’s goal-oriented motives, physical activity experiences and body-related perceptions: a latent profile analysis
Bibliographic record
Abstract
Goal-oriented exercise motives are important predictors of men’s physical activity behaviours and experiences, and body-related perceptions. To date, men’s exercise goal motives have been studied predominantly in isolation, and person-centred approaches that identify distinct goal motive profiles and their correlates have been limited. To address this gap, 322 men (mean age = 34.15, SD = 11.53) were recruited to participate in an online multi-national cross-sectional survey, and latent profile analysis was used to identify profiles based on an adapted version of the Reasons for Exercising Inventory. Comparisons were made for levels of LTPA, physical activity enjoyment, body surveillance, and body attitudes between the profiles. Five profiles were identified, with three profiles having low, average, and high levels of all forms of goal-oriented motives, respectively. Additionally, one profile was characterised mainly by appearance goals and one profile by weight loss goals. Participants in the low overall goal-oriented motivation profile participated in less LTPA than the other profiles, and the participants in the weight loss and appearance profiles reported significantly less exercise enjoyment than the high overall goal-oriented motivation profile. As expected, participants in the profile motivated by appearance reported greater body surveillance and more negative body attitudes. Leveraging a person-centred approach, these results advance previous literature on men’s exercise goal-oriented motives, and the ways in which distinct goal-oriented motive profiles are associated with physical activity experiences and body-related perceptions. Interventions targeting different forms of goal-oriented motivation may have the potential to enhance men’s physical activity experiences and body-related perceptions.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".