Evidence map›Paper›PMID 42376369›Full record

ArticleInternational journal of clinical and health psychology : IJCHP

Accelerometer-derived movement phenotypes and adolescent mental health in pediatric obesity: A causal machine-learning study.

Siyu Pan, Peng Wang, Fabian Herold, Matthew Heath, Edmund Wei Jian Lee, Effie Lai-Chong Law, Cassandra J Lowe, André Werneck, Markus Gerber, David Moreau and 5 more

Abstract read
In one paragraph

Article in International journal of clinical and health psychology : IJCHP. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Siyu PanSchool of psychology, Wuhan Sports University, Wuhan, China.
Peng WangSchool of psychology, Wuhan Sports University, Wuhan, China.
Fabian HeroldDepartment of Physiology, Faculty of Medicine, HMU Health and Medical University Erfurt, Erfurt, Thuringia 99089, Germany.
Matthew HeathSchool of Kinesiology, Faculty of Health Sciences, University of Western Ontario, 1151 Richmond St, London, ON N6A 3K7, Canada.
Edmund Wei Jian LeeDepartment of Media and Communication, College of Liberal Arts and Social Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China.
Effie Lai-Chong LawDepartment of Computer Science (Human-Computer Interaction Group), Durham University, Durham, UK.
Cassandra J LoweDepartment of Psychology, University of Exeter, UK.
André WerneckCenter for Epidemiological Research in Nutrition and Health, Department of Nutrition, School of Public Health, Universidade de São Paulo, São Paulo, Brazil.
Markus GerberDepartment of Sport, Exercise and Health, Faculty of Medicine, University of Basel, Grosse Allee 6, Basel 4052, Switzerland.
David MoreauSchool of Psychology and Centre for Brain Research, University of Auckland, Auckland 1030 New Zealand.
Myrto MavilidiFaculty of Education, Southern Cross University, Lismore, Australia.
Fred PaasDepartment of Psychology, Education, and Child Studies, Erasmus University Rotterdam, Rotterdam, P.O. Box 1738, the Netherlands.
Mats HallgrenDepartment of Public Health Sciences, Karolinska Institutet, Nobels väg 12A, Stockholm 17177, Sweden.
Xia XuSchool of psychology, Wuhan Sports University, Wuhan, China.
Liye ZouSchool of psychology, Wuhan Sports University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Children with overweight or obesity are at elevated risk for later-life mental health challenges, but the role of accelerometer-derived waking movement behaviors remains uncertain. Thus, we examined longitudinal associations of sedentary behavior (SB), light-intensity physical activity (LPA), and moderate-to-vigorous-intensity physical activity (MVPA) at age 7 with later-life internalizing and externalizing problems. Method: We used data from the UK Millennium Cohort Study, focusing on children with overweight or obesity at age 7 who had valid accelerometer data and a complete set of predefined analytic variables (N = 858). Exposures were average daily minutes of SB, LPA, and MVPA. Outcomes were parent-reported Strengths and Difficulties Questionnaire-based internalizing and externalizing problems scores at ages 11 and 14. A generalized random forests approach was used to estimate average treatment effects (ATEs) and conditional average treatment effects (CATEs), adjusted for relevant demographic, socioeconomic, body mass index, parental distress, baseline mental health, and co-occurring movement intensities; day-of-week activity-pattern variables were used as exploratory candidate moderators. Results: Estimated ATEs were small. After applying the Benjamini-Hochberg false-discovery-rate (FDR) correction across the 12 primary exposure-outcome tests, only the association between higher SB and lower internalizing problems at age 11 remained statistically significant (ATE = -0.013 SDQ points per additional min/day; 95% CI, -0.019 to -0.007; q < 0.001). No other pathway survived FDR correction, and other nominal or directionally suggestive estimates were interpreted as exploratory. CATE summaries and calibration tests provided limited evidence of reproducible heterogeneity. Conclusions: Accelerometer-derived waking movement behaviors at age 7 were associated with later SDQ problems scores in small and outcome-specific ways among children with overweight or obesity. Since the study is based on observational data and relies on measured-confounder assumptions, the findings should be interpreted cautiously, and as model-based estimates rather than definitive causal evidence.

Indexed as

AccelerometryCausal machine learningDigital phenotypingMental healthPediatric obesityWearable sensors

Identifiers

PMID42376369
PMCPMC13312474

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.