Transition readiness of youth with co‐occurring chronic health and mental health conditions: A mixed methods study
Bibliographic record
Abstract
BACKGROUND: A large proportion of youth with chronic conditions have mental health comorbidities. However, the effect of these comorbidities on paediatric-adult transition readiness, and the relevance of widely used tools for measuring transition readiness, are unknown. OBJECTIVE: The objectives of this study were to describe and explore the transition readiness of youth with co-occurring chronic health and mental health conditions using a combination of quantitative data obtained from participants completing the Transition Readiness Assessment Questionnaire (TRAQ) and qualitative data. DESIGN AND PARTICIPANTS: A three-phase sequential explanatory mixed methods design was employed, with the qualitative strand taking priority. First, the TRAQ scores (range 1-5) of youth with co-occurring conditions (n = 61) enroled in a multisite randomized controlled trial were measured, followed by qualitative interviews with a sample of youth (n = 9) to explain the quantitative results. Results from both strands were then integrated, yielding comprehensive insights. RESULTS: Median TRAQ scores ranged from 2.86 on the appointment keeping subscale to 5.00 on the talking with providers subscale. The qualitative results uncovered the complexities faced by this group concerning the impact of a mental health comorbidity on transition readiness and self-management skills across TRAQ domains. The integrated findings identified a diverse and highly individualized set of strengths and challenges amongst this group that did not align with overarching patterns as measured by the TRAQ. CONCLUSIONS: This mixed methods study generated novel understandings about how youth with co-occurring conditions develop competencies related to self-care, self-advocacy and self-management in preparation for paediatric-adult service transitions. Results demonstrated the assessment of transition readiness using a generic scale does not address the nuanced and complex needs of youth with co-occurring chronic health and mental health conditions. Our findings suggest tailoring transition readiness practices for this group based on youths' own goals, symptoms, coping mechanisms and resources. PATIENT OR PUBLIC INVOLVEMENT: This study was conducted in collaboration with five young adult research partners (YARP) with lived experience transitioning from paediatric to adult health/mental health services. The YARP's contributions across study phases ensured the perspectives of young people were centred throughout data collection, analysis, interpretation and presentation of findings. All five YARP co-authored this manuscript.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".