Using Qualitative Geospatial Methods to Explore Physical Activity in Children with Developmental Disabilities: A Feasibility Study
Bibliographic record
Abstract
Children with developmental disabilities (DDs) experience barriers to physical activity (PA) participation. Greater contextual information regarding their PA behaviors is needed for effective PA promotion. We investigated the feasibility of using activity trackers and Global Positioning Systems (GPS) devices with follow-up interviews to explore PA behaviors in children with DDs. Fifteen children with DDs (aged 10 ± 2 years) wore an activity tracker and GPS device for 7 days. Data were time-aligned to measure PA and identify PA locations. Maps were created to guide follow-up semi-structured interviews with the children and their parents/guardians to understand PA contexts and perceptions of daily PA. The children took 8680 ± 4267 steps/day across 6 ± 1 days. The children provided preferences for PA locations and the parents/guardians gave context by expressing how DDs affect PA and identifying environmental factors in PA locations. The children with DDs who lived near parks, participated in PA that leveraged the strengths of their individual skillsets, and had parents/guardians who provided social support had more positive PA experiences. Combining activity tracking and GPS data with follow-up map-based interviews is feasible to explore PA behaviors and the experiences of children with DDs. This methodology may provide novel insight into daily PA in children with DDs, which can inform how future interventions can support them to be more active and have positive experiences while being active.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".