A Scoping Review of Pediatric Healthcare Built Environment Experiences and Preferences Among Children With Disabilities and Their Families
Bibliographic record
Abstract
BACKGROUND: Some children with disabilities (CWD) frequently visit pediatric healthcare settings for appointments. Their age, disability, and regular visits mean that they have unique experiences in healthcare settings. While previous research has explored the clinical experiences of CWD, little is known about their experiences of pediatric healthcare built environments, even though these environments may play an important role in shaping their perceptions of care. Given the significant time that some CWD and chronic illnesses (e.g., cancer) spend in healthcare environments and the impact that these settings can have on their experiences, the knowledge gap concerning how they view, and experience healthcare built environments demands attention. OBJECTIVE: To explore how CWD and their families experience pediatric healthcare built environments. METHODS: A scoping review was conducted by searching five health science and interdisciplinary literature databases using terms related to children, disability, healthcare, and built environment. The search identified 5,397 records that were screened independently by three reviewers. RESULTS: Nineteen studies met inclusion criteria and were considered in the final review. Findings indicate that CWD and their families value healthcare built environment features that support social engagement, patient privacy, and parental presence. Further, the age of a child was highlighted as an important factor that influences the built environment preferences of CWD. CONCLUSIONS: CWD and their families prefer certain healthcare built environment features to optimize their experiences in these settings. Healthcare designers can leverage these findings to advance more inclusive pediatric healthcare spaces to improve care and the quality of life for CWD and their families.
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 | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.024 | 0.030 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".