A Scoping Review of Evidence-Informed Recommendations for Designing Inclusive Playgrounds
Bibliographic record
Abstract
Background: Playgrounds provide children with many sensory, motor, and socioemotional experiences that are critical to child development. Unfortunately, playgrounds also represent an environment where children with disabilities experience barriers to accessing play. Structures and materials that are prominently found in almost all playground designs (e.g., swings, slides, sand) can present as obstacles for many children with disabilities to engage in independent play. Aims: This scoping review engaged in the empirical literature to address the research question, “What are the evidence-informed recommendations for designing inclusive playgrounds to enable participation for children with disabilities?” Consideration was given not only to the physical design of playgrounds, but also the playgrounds' surrounding built and social environments. Methods: A systematic search of Medline, PsycINFO, CINAHL, EMBase, ERIC and Scopus was conducted. Only peer-reviewed literature published in English between January 1990 and January 2021, with a primary focus on inclusive playground structure design related to any type of disability were included. Data extraction included the study author(s), year of publication, country of origin, purpose, disability types considered, methods, sample characteristics and key findings. Key findings were synthesized into evidence-informed recommendations, which were later collated, using inductive content analysis, into five broader thematically congruent groups. Results: Thirty-five studies were included using case study (n = 17); observational (n = 6); survey (n = 5); experimental (n = 4); and multiple study (n = 3) designs. Thirteen evidence-based recommendations and one promising practice were categorized into five broad playground elements: entry points; surfacing and paths; features to foster inclusive play; staffing/supervision; and design process. Conclusion: These recommendations build upon previous design-based best-practices that focused exclusively on the physical design of the playground. Our recommendations have implications for how future playgrounds should be designed to maximize usability and inclusiveness and the overall playground experiences for children with disabilities.
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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 | 0.073 | 0.221 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.057 | 0.045 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".