Reliability and Validity of Physical Activity Instruments Used in Children and Youth with Physical Disabilities: A Systematic Review
Bibliographic record
Abstract
Research often characterizes children and youth with physical disabilities as less physically active than their typically developing peers. To inform the development and evaluation of future interventions, it is important to identify the most accurate methods for assessing physical activity behavior in this population. The objectives of this review were 1) to identify the self-report and objective instruments used to examine habitual physical activity behavior within this population and 2) to determine the reliability and validity of these instruments. Following a standardized protocol, a systematic review was conducted using six electronic databases and a range of search terms. Fifty studies (N = 2,613; Mage = 11.3 ± 2.6 years; 53% male) were included. Seven disability groups were examined, with the majority of studies focused on cerebral palsy (64%) and juvenile arthritis (20%). Poor to good reliability and weak validity were found among the self-report instruments such as questionnaires and activity diaries. Good to excellent reliability and validity were established for the objective instruments such as activity monitors (e.g., accelerometers, pedometers). Further research is warranted among physical disability groups other than cerebral palsy, and in establishing reliability and validity of self-report physical activity instruments specific to these target groups.
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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 | 0.012 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".