A literature review of children's active play
Bibliographic record
Abstract
Active play takes place during a child's free time (Brockman et al., 2011), and has been shown to enhance children's physical, social, emotional and cognitive development (Burdette & Whitaker, 2005). Despite the noted benefits, there has been a significant decline in children's active play over the past 50 years (Gray, 2011). Therefore, it is important to further our understanding of children's active play to help facilitate physical activity participation. The purpose of this study was to conduct a literature review on children's active play. More specifically, we sought to answer three research questions: 1) How active play is defined; 2) How active play is measured; and 3) What are the facilitators and barriers to active play. Searches were conducted using computerized databases (e.g. SPORTDiscus, PsychInfo) between January and April of 2014. A total of 27 studies spanning from 2006-2014 were analyzed. Several definitions of active play were proposed across studies, suggesting the need for an operational definition. Common measures of active play included accelerometers and questionnaires. Facilitators to active play included gender, play location (backyard vs. neighborhood), type of play and playmate choice. Environments that were autonomy-supportive, unstructured, natural and close to home were positively associated with active play, while high levels of sedentary time were associated with decreased levels of active play. Barriers to children's active play included parental constraints, safety concerns, weather conditions and technology. Recommendations for future research and strategies to promote active play are provided.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".