Development and validation of the Decisional Balance Scale for Physical Activity in Female Survivors of Violence (DBSPA-FSV)
Bibliographic record
Abstract
Introduction: Due to the trauma they have experienced, women who are survivors of violence struggle to engage in regular physical activity despite its numerous benefits. Identifying the factors that facilitate or hinder engagement in physical activity within this population is therefore essential. However, no valid tool currently exists specifically for this purpose. This study, based on the concept of decisional balance drawn from the transtheoretical model of behavior change, aimed to develop and validate the Decisional Balance Scale for Physical Activity in Female Survivors of Violence (DBSPA-FSV). Methods: Three hundred one volunteers participated in three complementary steps which followed established validation procedures. In step 1, a preliminary version of the items was developed based on the existing literature. In step 2, the dimensionality and convergent validity of the scale were examined. In step 3, the reliability of the scale was tested. Results: In step 1, a preliminary version of 32 items was developed. The scale was refined to 22 items, grouped into two factors (facilitators and barriers) and six sub-dimensions (physical, psychological, and socio-environmental). In step 2, bi-factor confirmatory models with a global construct and six or two correlated factors demonstrated satisfactory fit indexes. Convergent validity was confirmed by significant correlations between DBSPA- FSV constructs and the concept of self-determined motivation in the expected directions. In step 3, the internal and test-retest reliability of the scale were confirmed. Discussion: The DBSPA-FSV scale exhibits satisfactory psychometric properties and will contribute to research on the engagement in physical activity of women survivors of violence.
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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".