Measuring Perceived Barriers to Physical Activity in Adolescents
Bibliographic record
Abstract
BACKGROUND: Perceived barriers to moderate-to-vigorous physical activity (PA) may contribute to the low rates of moderate-to-vigorous PA in adolescents. We examined the psychometric properties of scores from the perceived barriers to moderate-to-vigorous PA scale (PB-MVPA) by examining composite reliability and validity evidence based on the internal structure of the PB-MVPA and relations with other variables. METHODS: This study was a cross-sectional analysis of data collected in 2013 from adolescents (N = 507; Mage = 12.40, SD = .62) via self-report scales. RESULTS: Using exploratory and confirmatory factor analyses, we found that perceived barriers were best represented as two factors representing internal (e.g., "I am not interested in physical activity") and external (e.g., "I need equipment I don't have") dimensions. Composite reliability was over .80. Using multiple regression to examine the relationship between perceived barriers and moderate-to-vigorous PA, we found that perceived internal barriers were inversely related to moderate-to-vigorous PA (β = -.32, p < .05). Based on results of the analysis of variances, there were no known-group sex differences for perceived internal and external barriers (p > .26). CONCLUSIONS: The PB-MVPA scale demonstrated evidence of score reliability and validity. To improve the understanding of the impact of perceived barriers on moderate-to- vigorous PA in adolescents, researchers should examine internal and external barriers separately.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".