Parental perspectives on family‐centered care in pediatric neurology: An explanatory sequential mixed‐methods study
Bibliographic record
Abstract
AIM: To explore parents' experiences of family-centered care (FCC) in a pediatric neurology clinic. METHOD: In this explanatory sequential mixed-methods study, parents of children with neurological conditions completed the Measure of Processes of Care (MPOC-20) and the Pediatric Quality of Life (PedsQL) surveys. Linear regression analysis was used to explore associations between MPOC, PedsQL scores, and demographic variables. Through an interpretive description framework, semi-structured interviews were conducted with a subset of parents to develop a deeper understanding of parental experiences and were analyzed using a phronetic iterative approach. RESULTS: Parents rated the MPOC-20 domains 'respectful and supportive care' the highest and 'providing general information' the lowest (n = 69). Child's age and parents' marital status were predictive of lower 'providing general information' and 'specific information' scores; and child's age, area of residence, and the number of additional services were predictive of lower total, emotional, and social PedsQL scores. A conceptual framework highlighting the parents' role in their child's healthcare experiences was developed on the basis of interview findings. INTERPRETATION: This study demonstrates the need to improve FCC (providing general and specific information about the child's condition) and to encourage partnerships between parents and healthcare providers. Involving genetic counsellors in care teams facilitates information sharing, shared decision-making, communication, and the provision of support resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".