The reliability and validity of a child and adolescent participation in decision‐making questionnaire
Bibliographic record
Abstract
BACKGROUND: There is a growing impetus across the research, policy and practice communities for children and young people to participate in decisions that affect their lives. Furthermore, there is a dearth of general instruments that measure children and young people's views on their participation in decision-making. This paper presents the reliability and validity of the Child and Adolescent Participation in Decision-Making Questionnaire (CAP-DMQ) and specifically looks at a population of looked-after children, where a lack of participation in decision-making is an acute issue. METHODS: The participants were 151 looked after children and adolescents between 10-23 years of age who completed the 10 item CAP-DMQ. Of the participants 113 were in receipt of an advocacy service that had an aim of increasing participation in decision-making with the remaining participants not having received this service. RESULTS: The results showed that the CAP-DMQ had good reliability (Cronbach's alpha = 0.94) and showed promising uni-dimensional construct validity through an exploratory factor analysis. The items in the CAP-DMQ also demonstrated good content validity by overlapping with prominent models of child and adolescent participation (Lundy 2007) and decision-making (Halpern 2014). A regression analysis showed that age and gender were not significant predictors of CAP-DMQ scores but receipt of advocacy was a significant predictor of scores (effect size d = 0.88), thus showing appropriate discriminant criterion validity. CONCLUSION: Overall, the CAP-DMQ showed good reliability and validity. Therefore, the measure has excellent promise for theoretical investigation in the area of child and adolescent participation in decision-making and equally shows empirical promise for use as a measure in evaluating services, which have increasing the participation of children and adolescents in decision-making as an intended outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".