Revised Measure of Environmental Qualities of Activity Settings (MEQAS) for youth leisure and life skills activity settings
Bibliographic record
Abstract
PURPOSE: The aim was to create an expanded version of a published observer-rated Measure of Environmental Qualities of Activity Settings (MEQAS-32). METHOD: Testing was conducted using a diverse sample of activity settings. Raters completed the original MEQAS questionnaire (MEQAS-66) for 76 youth leisure and life skills activity settings. Scales for the revised measure (MEQAS-48) were determined using a two-step approach: (a) developing a theoretically-based model based on item-to-item linkages, and (b) confirmatory factor analysis. RESULTS: The analysis revealed a good fitting 9-factor model (CFI= 0.965, RMSEA= 0.049). Five of the six MEQAS-32 scales remained and were validated in an independent dataset. Four additional scales were identified in the MEQAS-48: Comfortable Place-related Qualities, Opportunities for Privacy/Relaxation, Opportunities to Interact with Peers, and Opportunities for Cooperative Group Activity. Opportunities for Choice and Opportunities for Personal Growth were significantly correlated with corresponding youth experiences. Construct validity was demonstrated through predictions for various types of activities. CONCLUSIONS: The MEQAS-48 more completely reflects the original conceptualization of the measure's content than does the MEQAS-32. Findings suggest the increased utility of the measure due to broader coverage of environmental qualities. The MEQAS-48 can be used to assess environmental qualities for research, program design, and clinical practice. Implications for Rehabilitation The MEQAS is the first observer-completed measure of environmental qualities of activity settings. Compared to the MEQAS-32, the MEQAS-48 captures a broader range of important environmental qualities, including comfortable place-related qualities, and opportunities for privacy/relaxation, peer interaction, and cooperative group activity. The MEQAS-48 has clinical utility for use in program design and development, and research utility for understanding environmental qualities.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".