Understanding physical activity and sedentary behaviour among preschool-aged children in Singapore: a mixed-methods approach
Bibliographic record
Abstract
OBJECTIVES: This study investigated physical activity (PA) and sedentary behaviour (SB) among preschool-aged children in Singapore and potential correlates at multiple levels of the socioecological model from in-school and out-of-school settings. DESIGN: A cross-sectional study using a mixed-methods approach. PARTICIPANTS: Parent-child dyads from six preschools in Singapore. METHODS: PA and SB of children (n=72) were quantified using wrist-worn accelerometers for seven consecutive days. Three focus group discussions (FGDs) among 12 teachers explored diverse influences on children's activities, and System for Observing Play and Leisure Activity in Youth (SOPLAY) assessed PA environment and children's activity levels at preschools. Seventy-three parents completed questionnaires on home and neighbourhood factors influencing children's PA and SB. Descriptive analyses of quantitative data and thematic analysis of FGDs were performed. RESULTS: Based on accelerometry, children (4.4±1.1 years) spent a median of 7.8 (IQR 6.4-9.0) hours/day in SB, and 0.5 (0.3-0.8) hours/day in moderate-to-vigorous physical activity (MVPA). MVPA was similar throughout the week, and SB was slightly higher on non-school days. In preschools, SOPLAY showed more children engaging in MVPA outdoors (34.0%) than indoors (7.7%), and absence of portable active play equipment. FGDs revealed issues that could restrict active time at preschool, including academic requirements of the central curriculum and its local implementation. The teachers had varying knowledge about PA guidelines and perceived that the children were sufficiently active. In out-of-school settings, parents reported that their children rarely used outdoor facilities for active play and spent little time in active travel. Few children (23.5%) participated in extracurricular sports, but most (94.5%) reported watching screens for 1.5 (0.5-3.0) hours/day. CONCLUSION: MVPA was low and SB was high in preschool-aged children in an urban Asian setting. We identified diverse in-school and out-of-school correlates of PA and SB that should be taken into account in health promotion strategies.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".