MétaCan
Menu
Back to cohort
Record W4404479778 · doi:10.2196/59283

An Online Resource for Monitoring 24-Hour Activity in Children and Adolescents: Observational Analysis

2024· article· en· W4404479778 on OpenAlexvenueno aff
Benny Kai Guo Loo, Siao Hui Toh, Fadzlynn Fadzully, Mohammad Ashik Zainuddin, Mimi Azliha Abu Bakar, Joanne Shumin Gao, Jing Chun Teo, Jie Kai Ethel Lim, Beron Wei Zhong Tan, Michael Chia, Terence Buan Kiong Chua, Kok Hian Tan

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersNational Medical Research CouncilMedical Research Council
KeywordsMcNemar's testDescriptive statisticsLikert scaleMedicineObservational studyWilcoxon signed-rank testPhysical activitySedentary behaviorPhysical therapyScreen timePsychologyMann–Whitney U testDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

Background: The Singapore integrated 24-hour activity guide for children and adolescents was introduced to promote healthy lifestyle behaviors, including physical activity, sedentary behavior, sleep, and diet, to enhance metabolic health and prevent noncommunicable diseases. To support the dissemination and implementation of these recommendations, a user-friendly online resource was created to help children and adolescents adopt these behaviors in Singapore. Objective: This study aimed to assess the acceptability of the online resource in the adoption of healthier lifestyle behaviors, and the change in the users' behaviors with the use of this online resource. Methods: Participants aged 7-17 years were required to log their activity levels of the past 7 days at the beginning and at the end of a 3-month period using the browser-based online resource, including information on the duration and frequency of moderate- to vigorous-intensity physical activity (MVPA), length of sedentary behavior, duration and regularity of sleep, and food portions. User satisfaction, on the length, ease of use, and relevance of the online resource, was also recorded using a 10-point Likert scale. Descriptive statistics and statistical analyses, including the Wilcoxon signed rank test and McNemar test, were carried out at baseline and at the end of 3 months. Results: A total of 46 participants were included for analysis. For physical activity, the number of days of MVPA increased from a median of 3 (IQR 2-5) days to 4 (IQR 2-5) days (P=.01). For sedentary behavior, the median daily average screen time decreased from 106 (IQR 60-142.5) minutes to 90 (IQR 60-185) minutes. For sleep, 10% (5/46) more participants met the recommended duration, and the number of days with regular sleep increased from a median of 6 (IQR 5-7) days to 7 (IQR 5-7) days (P=.03). For diet, there was a decrease in the portion of carbohydrates consumed from a median of 42% (IQR 30-50) to 40% (IQR 30-48.5; P=.03), and the number of days of water and unsweetened beverage consumption remained stable at a median of 5 days but with a higher IQR of 4-7 days (P=.04). About 90% (39-41/46) of the participants reported that the online resource was relevant and easy to use, and the rating for user satisfaction remained favorable at a median of 8 with a higher IQR of 7-9 (P=.005). Conclusions: The findings support the development of a dedicated online resource to assist the implementation of healthy lifestyle behaviors based on the Singapore integrated 24-hour activity guide for children and adolescents. This resource received favorable ratings and its use showed the adoption of healthier behaviors, including increased physical activity and sleep, as well as decreased sedentary time and carbohydrate consumption, at the end of a 3-month period.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.050
GPT teacher head0.336
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Pediatrics and ParentingSame topicChild Development and Digital TechnologyFrench-language works237,207