Child temperament and physical activity in young children
Bibliographic record
Abstract
BACKGROUND: Children's temperament has been noted to influence their physical activity (PA) levels. Therefore, understanding the influence of temperament during the early years may be helpful for developing appropriate PA habits and tailoring interventions to align with different personality traits. OBJECTIVE: The purpose of this study was to examine the relationship between child temperament and objectively-measured PA in preschool-aged children. METHODS: Data were collected as part of the Supporting Physical Activity in the Childcare Environment (SPACE) and SPACE extension studies. Temperament data were collected using the validated Very Short Form of the Children's Behavior Questionnaire, which assessed three dimensions of temperament (i.e., surgency, negative affect and effortful control). Physical activity data were measured during childcare hours over the course of 5 days, using Actical® accelerometers. Total PA was summed, along with light and moderate-to-vigorous PA using age-specific cut-points. Three regression analyses were conducted to evaluate the prediction of PA by the dimensions of temperament. RESULTS: = 3.34 years, SD = 0.63) were retained for analyses, wearing an accelerometer an average of 7.21 h/day. Temperament significantly predicted all three PA levels (P < 0.05), with both negative affect and surgency being significantly associated with PA. CONCLUSION: Surgency is typified by a predisposition towards high activity levels; therefore, it is not surprising that it was the primary predictor of young children's PA. Future research may investigate methods of targeting PA interventions towards children with temperaments that may not predispose them to seeking out increased activity levels.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".