Quality of transitional care of children with chronic diseases: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: To analyze which factors may be associated with the quality-of-care transition of children with chronic diseases from the hospital to their home. METHOD: A cross-sectional, quantitative study, carried out in two hospitals in Southern Brazil, from February to September 2019. Participants included 167 family members of children with chronic disease. Data collection took place through a demographic questionnaire, and the use of the Brazilian version of the Care Transitions Measure (CTM-15). RESULTS: The average score for the quality of care transition was 90.1 (sd = 19.5) (0-100). Factor 1, "Health management preparation", was the one with the highest self-perceived average, 92.3 (sd = 11.6), while Factor 4, "Care plan", had the lowest average, 86.3 (sd = 21.3). The quality of care transition was higher for patients living in municipalities belonging to health regions other than the hospital's. CONCLUSION: The quality of care transition for children with chronic diseases, perceived by the children's family members, in the discharge process from the hospital to home, was considered high. Living in a health region other than the hospital's region was associated with better perception of the quality of care transition.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".