Psychometric properties and parental reported utility of the 19-item ‘About My Child’ (AMC-19) measure
Bibliographic record
Abstract
BACKGROUND: 'About My Child' 19-item version (AMC-19) is a parent-report measure developed to assess the complexity of a child's life due to biological, psychological, social and environmental issues, that can be completed in approximately 5 min. AMC measures two dimensions of complexity: parental concerns and impact on the child. This paper examines the psychometric properties and parent-reported utility of the AMC-19 for children with disabilities or special health care needs. METHOD: Data were gathered from two Canadian studies at CanChild: the 'AMC-19 Pilot' study and the 'Service Utilization and Outcomes (SUO)' study. The AMC-19 Pilot study data allowed us to explore internal consistency and test-retest reliability, as well as parental responses to two open-ended questions on the utility of the AMC-19. The SUO study provided data for analyses of internal consistency and scale property validation with type of diagnosis and service needs. RESULTS: The test-retest ICC was r = 0.83 for concerns and r = 0.87 for impact. Cronbach's alpha across both studies ranged from 0.80 to 0.90. Parents' comments on the AMC-19's utility indicated support for the AMC-19, in particular to identify therapy needs and goals. CONCLUSIONS: The AMC-19 demonstrates strong psychometric properties supporting it as a valuable measure for describing the level of complexity among children with disabilities. We recommend using the AMC-19 in health services research and clinical settings to build dialogue between family and therapists due to its utility reported by parents.
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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 | 0.018 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".