Validation of the Transition Readiness Assessment Questionnaire (TRAQ) 5.0 for use among youth in mental health services
Bibliographic record
Abstract
BACKGROUND: Among youth with psychiatric disorders, the transition from child to adult mental health services is a period of vulnerability to discontinuous care and service disengagement. Regular assessment of transition readiness has been identified as a core component of transition planning, contributing to successful care transitions. The Transition Readiness Assessment Questionnaire (TRAQ) 5.0 is a 20-item questionnaire that measures transition readiness in youth preparing to transition to adult care. Although the TRAQ has been validated and used across many health settings, it has not been validated in youth with primarily mental health concerns. The objective of this study was to validate the TRAQ for use among youth accessing mental health services. METHODS: This study used the Longitudinal Youth in Transition Study baseline cohort, which consists of 237 clinically referred youth (aged 16-18 years) receiving outpatient mental health treatment. Psychometric evaluation of the TRAQ 5.0 included confirmatory factor analysis (CFA), assessment of internal consistency, testing convergent validity using the Dimensions of Emerging Adulthood (IDEAS) and Difficulty in Emotional Regulation (DERS) scales, criterion validity using a question on whether the participant had talked about transition with their clinician and known-group testing based on age. RESULTS: The CFA indicated adequate fit of the five-factor TRAQ structure. The overall scale (=.86) and three of the subscales demonstrated adequate internal consistency. As hypothesized, overall TRAQ scores were higher for youth who had discussed transition and those aged 18. Small correlations were found between the overall TRAQ score and measures of developmental maturity (IDEAS) and emotional awareness (DERS); however, certain subscales did not demonstrate correlation with these constructs. CONCLUSIONS: The TRAQ 5.0 appears to be valid tool to assess the transition readiness of youth in outpatient mental health services. Additional work needs determine whether findings are similar among specific mental health conditions, including substance use disorders and psychotic disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".