Effects of Open-Loop Feedback on Physical Activity and Television Viewing in Overweight and Obese Children: A Randomized, Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: Television viewing and physical inactivity increase the risk of obesity in youth. Thus, identifying new interventions that increase physical activity and reduce television viewing would be helpful in the prevention and treatment of pediatric obesity. This study evaluated the effects of open-loop feedback plus reinforcement versus open-loop feedback alone on physical activity, targeted sedentary behavior, body composition, and energy intake in youth. METHODS: Thirty overweight or obese 8- to 12-year-old children were randomly assigned to an intervention (n = 14) or control group (n = 16). Participants wore accelerometers every day for 8 weeks and attended biweekly meetings to download the activity monitors. For children in the open-loop feedback plus reinforcement (intervention) group, accumulating 400 counts of physical activity on pedometers earned 1 hour of television/VCR/DVD time, which was controlled by a Token TV electronic device. Open-loop feedback control subjects wore activity monitors but had free access to targeted sedentary behavior. RESULTS: Compared with controls, the open-loop feedback plus reinforcement group demonstrated significantly greater increases in daily physical activity counts (+65% vs +16%) and minutes per day of moderate-to-vigorous physical activity (+9.4 vs +0.3) and greater reductions in minutes per day spent in television viewing (-116.1 vs +14.3). The intervention group also showed more favorable changes in body composition, dietary fat intake, and energy intake from snacks compared with controls. Reductions in sedentary behavior were directly related to reductions in BMI, fat intake, snack intake, and snack intake while watching television. CONCLUSIONS: Providing feedback of physical activity in combination with reinforcing physical activity with sedentary behavior is a simple method of modifying the home environment that may play an important role in treating and preventing child obesity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".