I sit because I have fun when I do so! Using self-determination theory to understand sedentary behavior motivation among university students and staff
Bibliographic record
Abstract
Objectives. Evidence exists that independently of physical activity, a dose–response relationship exists between sedentary time and adverse health outcomes. However, little is known about motivations underlying sedentary behavior. The purpose of this study was to (i) examine the factor structure and composition of sedentary-derived autonomous (identified and intrinsic) and controlled (external and introjected) motives within an Organismic Integration Theory (OIT) framework and (ii) determine whether these motivational constructs are related with overall sitting time as well as sitting for work/school and recreation/leisure on weekdays and weekends. Method. University students or staff (n = 571) completed an Internet-based survey within a cross-sectional design. After completing a modified Sedentary Behavior Questionnaire, participants were randomized to one of five groups (general, weekday work/school, weekday recreation/leisure, weekend work/school, weekend recreation/leisure) and completed a sedentary-derived 15-item modified Behavioral Regulation in Exercise Questionnaire. Results. Factor analysis findings support the tenability of a four-factor model for weekday work/school, weekend work/school, and weekend leisure/recreation sedentary behavior and a three-factor model for general and weekday leisure/recreation behavior. Regression analyses showed the motivational constructs explained a significant amount of sedentary behavior variance for weekend work/school (10%), weekend leisure/recreation (9%), weekday work/school (4%), and weekday leisure/recreation (3%). General sedentary behavior was unrelated with the motivational constructs. In general, autonomous motives underlied leisure/recreational sitting while controlled motives were more strongly associated with work/school behavior. Conclusions. Our findings support the hypothesis that motivational constructs grounded in OIT have the potential to further our understanding of sedentary behavior.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| 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".