A Structured Discharge Education Intervention for Parents of Newly Diagnosed Pediatric Oncology Patients
Bibliographic record
Abstract
Background: Parents of children newly diagnosed with cancer require specialized knowledge and skills in order to safely care for their children at home. The Children's Oncology Group (COG) developed expert consensus recommendations to guide new diagnosis education; however, these recommendations have not been empirically tested. Methods: We used a sequential two-cohort study design to test a nurse-led Structured Discharge Teaching Intervention (SDTI) that operationalizes the COG expert recommendations in the setting of a tertiary children's hospital. Outcomes included parent Readiness for Hospital Discharge Scale (RHDS); Quality of Discharge Teaching Scale (QDTS); Post-Discharge Coping Difficulty (PDCD); Nurse Satisfaction; and post-discharge unplanned healthcare utilization. Results: The process for discharge education changed significantly before and after implementation of the SDTI, with significantly fewer instances of one-day discharge teaching, and higher involvement of staff nurses in teaching. Overall, parental RHDS, QDTS, and PDCD scores were similar in the unintervened and intervened cohorts. Almost 60% of patients had unplanned healthcare encounters during the first 30 days following their initial hospital discharge. Overall nurse satisfaction with the quality and process of discharge education significantly increased post-intervention. Discussion: Although the structure for and process of delivering discharge education changed significantly with implementation of the SDTI, parent RHDS and QDTS scores remained uniformly high and PDCD scores and non-preventable unplanned healthcare utilization remained similar, while nurse satisfaction with the quality and process of discharge education significantly improved, suggesting that further testing of the SDTI across diverse pediatric oncology settings is warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".