Feasibility and Effect of the Exergame BOOSTH Introduced to Improve Physical Activity and Health in Children: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Despite the well-known beneficial health effects of physical activity (PA), the majority of Dutch primary school children do not meet the recommended PA guidelines. Although there is growing evidence on the effectiveness of exergames for PA in children, there is limited evidence on their effect on health outcomes, such as cardiovascular health and health-related quality of life (HRQOL), and on factors influencing their effectiveness and feasibility. The exergame BOOSTH uses a wrist-worn activity tracker to measure steps per day. As a reward for the performed PA, children can unlock levels in the online BOOSTH game. In addition, "BOOSTH battle" enables competition between groups. OBJECTIVE: This protocol describes a cluster randomized controlled trial in 16 primary schools in the Netherlands investigating the effect of BOOSTH on moderate-to-vigorous PA (MVPA) using accelerometry. Secondary aims are to investigate the feasibility of BOOSTH (mixed methods: questionnaires and focus group interviews) and its effect on cardiovascular risk factors (anthropometrics, blood pressure, and retinal microvasculature) and HRQOL. METHODS: Stratification variables and relevant variables related to outcomes (such as BMI [z-score], sex, age, and parenting style) and/or missingness will be taken into account. Measurements will be performed at baseline and after 3, 6, and 12 months. RESULTS: The study has received funding from Province Limburg (SAS-2015-04956) and received ethical approval from the Medical Ethics Committee of Maastricht University Medical Centre (METC172043/NL64324.068.17). The results of the analyses are expected to be published in 2021. CONCLUSIONS: With this study, the ability of the exergame BOOSTH to increase PA and improve health in children of primary school age will be investigated. The insights into effectiveness and feasibility will result in scientific and societal recommendations, which could potentially contribute to widespread implementation of exergames for children. TRIAL REGISTRATION: ClinicalTrials.gov NCT03440580; https://clinicaltrials.gov/ct2/show/NCT03440580. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24035.
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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 | 0.043 | 0.039 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.089 | 0.015 |
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".