Testing the utility of three social‐cognitive models for predicting objective and self‐report physical activity in adults with type 2 diabetes
Bibliographic record
Abstract
OBJECTIVE: Theory-based interventions to promote physical activity (PA) are more effective than atheoretical approaches; however, the comparative utility of theoretical models is rarely tested in longitudinal designs with multiple time points. Further, there is limited research that has simultaneously tested social-cognitive models with self-report and objective PA measures. The primary aim of this study was to test the predictive ability of three theoretical models (social cognitive theory, theory of planned behaviour, and protection motivation theory) in explaining PA behaviour. METHODS: Participants were adults with type 2 diabetes (n = 287, 53.8% males, mean age = 61.6 ± 11.8 years). Theoretical constructs across the three theories were tested to prospectively predict PA behaviour (objective and self-report) across three 6-month time intervals (baseline-6, 6-12, 12-18 months) using structural equation modelling. PA outcomes were steps/3 days (objective) and minutes of MET-weighted PA/week (self-report). RESULTS: The mean proportion of variance in PA explained by these models was 6.5% for objective PA and 8.8% for self-report PA. Direct pathways to PA outcomes were stronger for self-report compared with objective PA. CONCLUSIONS: These theories explained a small proportion of the variance in longitudinal PA studies. Theory development to guide interventions for increasing and maintaining PA in adults with type 2 diabetes requires further research with objective measures. Theory integration across social-cognitive models and the inclusion of ecological levels are recommended to further explain PA behaviour change in this population. Statement of contribution What is already known on this subject? Social-cognitive theories are able to explain partial variance for physical activity (PA) behaviour. What does this study add? The testing of three theories in a longitudinal design over 3, 6-month time intervals. The parallel use and comparison of both objective and self-report PA measures in testing these theories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".