Assessing readiness for transition from paediatric to adult health care: Revision and psychometric evaluation of the Am I <scp>ON TRAC</scp> for Adult Care questionnaire
Bibliographic record
Abstract
AIM: To refine and psychometrically test the Am I ON TRAC for Adult Care questionnaire. BACKGROUND: Inadequate transition to adult care for adolescents with special healthcare needs has been associated with greater risk of treatment non-adherence, lack of medical follow-up, increased morbidity and mortality. Presently, there are no well-validated measures assessing adolescents' readiness to transition from paediatric to adult medical care. DESIGN: Descriptive cross-sectional study. METHODS: The Am I ON TRAC for Adult Care questionnaire was refined to improve the instrument's methodological soundness. A literature review informed the revisions. A convenience sample of 200 adolescents, 12-19 years, was recruited from four outpatient clinics at a paediatric hospital in Western Canada between April-June 2012. Construct validity was evaluated by Exploratory Factory Analysis; concurrent validity was assessed using the Psychosocial Maturity Index. Internal consistency was evaluated by computing Cronbach's alpha estimates. RESULTS: Factor analysis of the knowledge items identified a 14-item unidimensional scale. Knowledge and behaviour sub-scale scores increased with age, with a stronger relationship between knowledge and age. Psychosocial maturity correlated with both sub-scale scores, but had a stronger association with behaviour. Psychosocial maturity and age had a weak but significant correlation suggesting age is a loose proxy for maturity. Only 27% of 17-year olds, but 62% 18-year olds, scored above the behaviour cut-off for transition readiness. CONCLUSION: The revised Am I ON TRAC for Adult Care questionnaire is a psychometrically sound measure that has potential to be used as a readiness assessment tool in both clinical practice and research.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".