Exploring the benefits of children's active play imagery
Bibliographic record
Abstract
The first purpose of the current study was to examine the relationship between children's active play imagery and two developmental outcomes, personal/social skills and cognitive skills. The second purpose was to examine the relationship between children's active play imagery and self-confidence in active play. A total of 105 male and female children (Mage = 9.84, SD = 1.41) were recruited from various summer programs, and completed inventories that assessed their active play imagery (i.e., capability, social, and fun), positive personal development (i.e., personal/social skills and cognitive skills), and self-confidence. Examination of the scales' psychometric properties indicated poor reliability for the cognitive skills subscale; therefore it was excluded from further analysis. Multiple regression analysis revealed that all three active play imagery types (capability, social, fun) were positively and significantly related to personal/social skills, accounting for 26% of the variance. Specifically, capability imagery and social imagery emerged as the strongest individual predictors of personal/social skills. Further, regression analysis showed that both capability imagery and fun imagery were positively and significantly associated with self-confidence, accounting for 18% of the variance. In particular, fun imagery was found to be the strongest individual predictor of self-confidence. This study highlights the usefulness of imagery in fostering important developmental outcomes and self-confidence among children. To this end, child practitioners should consider implementing imagery workshops in school, clinical, and community settings.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".