Psychometric evaluation of the Participation and Environment Measure for Children and Youth
Bibliographic record
Abstract
AIM: The aim of this study was to examine the psychometric properties (reliability and validity) of the Participation and Environment Measure for Children and Youth (PEM-CY). METHOD: The PEM-CY examines participation frequency, extent of involvement, and desire for change in sets of activities typical for the home, school, or community. Items in the 'Environment' section examine perceived supports and barriers to participation within each setting. Data were collected via an online survey from caregivers of children and young people, aged 5 to 17 years, with and without a range of different disabilities, residing in the USA and Canada. Caregivers were eligible for inclusion if (1) they identified themselves as a parent or legal guardian of the child who was the focus of the survey; (2) they were able to read English; and (3) their child was between 5 and 17 years old at the time of enrolment. RESULTS: Data were obtained from 576 respondents. About half were parents of children with disabilities and a little more than half were from Canada. Child mean age was 11 years (SD 3.1y); 54% were male and 46% were female. Internal consistency was moderate to good (0.59 and above) across the different scales. Test-retest reliability was moderate to good (0.58 and above) across a 1- to 4-week period. There were large and significant differences between the groups with and without disabilities on all participation and environment scales. Although there were some significant age differences, they did not follow a consistent pattern. INTERPRETATION: Results support the use of the PEM-CY for population-level studies to gain a better understanding of the participation of children and young people and the impact of environmental factors on their participation.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".