Care Coordination for Children with Neurodevelopmental Disorders and Medical Complexity: Is Child Behavioral Health a Key Mediator of Caregiver Stress?
Bibliographic record
Abstract
INTRODUCTION: Children with neurodevelopmental disorders and medical complexity experience care that is fragmented, costly, and ineffective, causing health disparities and harm. The Neurodevelopmental Disorders Care Coordination (NDD-CC) program addresses these issues by connecting families with support across medical and social services. While NDD-CC has improved outcomes in several areas, many families continue to experience challenges. OBJECTIVE: Using data from a longitudinal study, we investigated patterns of change across child health and behavior and caregiver stress during care coordination (CC). METHODS: We performed an exploratory analysis of prospectively collected data from 67 caregivers of children with a neurodevelopmental disorder aged 2 to 17 years referred for CC. We examined changes in child health states (EQ-5D-Y), care-related quality of life (CarerQoL), and parenting stress (Parental Stress Index-Short Form) to assess impacts of CC over time and within subgroups. RESULTS: Most caregivers who reported CarerQoL scores in the bottom half of the distribution at baseline saw improvements at 3 (89%) and 12 months (71%). Gains were strongly associated with improvements in mental health at both time points. Similarly, child health states in the bottom half of the distribution improved the most. The difficult child domain of the parenting stress index was the key contributor to clinically significant stress scores, and changes in the difficult child score were negatively associated with changes in CarerQoL, explaining 36% of the variance. CONCLUSION: Findings show that CC has the most impact on those with the greatest need; yet clinically significant child behavior may prevent sustained improvements if left unaddressed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".