Motivational profiles for physical activity among adults with type 2 diabetes and their relationships with physical activity behavior
Bibliographic record
Abstract
Using self-determination theory, the aim of this study was to examine motivational profiles toward physical activity among adults with type 2 diabetes and how these profiles predict physical activity. In total, 381 adults with type 2 diabetes (188 or 49.3% women, M age = 61.39, SD = 7.29) completed a questionnaire assessing their physical activity motivation and behavior. First, results of a multiple regression analysis showed that intrinsic and identified motives were positively associated with leisure-time physical activity over the past three months while results of a multivariate analysis of covariance revealed that higher levels of intrinsic and identified motives were associated with observing physical activity recommendations for type 2 diabetes (i.e. practicing 150 min of moderate to vigorous physical activity per week). Then, results of a cluster analysis distinguished four distinct motivational profiles: self-determined, controlled, moderate, and non-self-determined. Participants reporting the highest physical activity participation level and observing physical activity recommendations were more likely to present a self-determined profile. The present study highlights the benefits of using both a variable-centered and a motivational profile approach. They also highlight the importance of examining the type of motivation associated with physical activity practice among adults with type 2 diabetes since autonomous forms of motivation positively influence both the frequency of leisure-time physical activity and the observance of physical activity recommendations for type 2 diabetes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".