Factor Structure and Measurement Invariance of a 10-Item Decisional Balance Scale: Longitudinal and Subgroup Examination Within an Adult Diabetic Sample
Bibliographic record
Abstract
This study explores the longitudinal and subgroup measurement properties of a 10-item, physical activity decisional balance scale, previously published by Plotnikoff, Blanchard, Hotz, and Rhodes (2001 Plotnikoff, R. C., Blanchard, C., Hotz, S. B. and Rhodes, R. 2001. Validation of the decisional balance scales in the exercise domain from the Transtheoretical Model: A longitudinal test. Measurement in Physical Education and Exercise Science, 5: 191–206. [Taylor & Francis Online] , [Google Scholar]), within a diabetic sample of Canadian adults. Results indicated that a three-factor measurement model consistently improved model fit compared to the previously published two-factor model. Evidence of configural, metric, and scalar measurement invariance across time and among subgroups suggests that the 10-item decisional balance scale is appropriate for investigating associative relationships with other constructs and for comparing group means of the pros and cons subscales among a variety of diabetic population subgroups.
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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 | 0.000 |
| 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 | 0.000 |
| 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".