A systematic review of transition readiness and transfer satisfaction measures for adolescents with chronic illness
Bibliographic record
Abstract
BACKGROUND: The transition from pediatric to adult health care can be challenging for adolescents with chronic illnesses. As a result, many adolescents are unable to transfer to adult health care successfully. Adequate measurement of transition readiness and transfer satisfaction with disease management is necessary in order to determine areas to target for intervention towards improving transfer outcomes. OBJECTIVES: This study aims to systematically review and critically appraise research on transition readiness and transfer satisfaction measures for adolescents with chronic illnesses as well as to assess the psychometric quality of these measures. METHODS: Electronic searches were conducted in MEDLINE, EMBASE, CINAHL, PsychINFO, ERIC, and ISI Web of Knowledge for transition readiness and transfer satisfaction measures for adolescents with chronic health conditions. Two reviewers independently selected articles for review and assessed methodological quality. RESULTS: In all, eight readiness and six satisfaction measures met the inclusion criteria, for a total of 14 studies, which were included in the final analysis. None of these measures have well-established evidence of reliability and validity. Most of the measures were developed ad hoc by the study investigators, with minimal to no evidence of reliability and/or validity using the Cohen criteria and COSMIN checklist. CONCLUSION: This research indicates a major gap in our knowledge of transitional care in this population, because there is currently no well-validated questionnaire that measures readiness for transfer to adult health care. Future research must focus on the development of well-validated transition readiness questionnaires, the validation of existing measures, and reaching consensus on outcomes of successful transfer.
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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 | 0.014 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".