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Record W4394774764 · doi:10.2196/48549

Testing a Biobehavioral Model of Chronic Stress and Weight Gain in Young Children (Family Stress Study): Protocol and Baseline Demographics for a Prospective Observational Study

2024· article· en· W4394774764 on OpenAlexafffundvenueabout
Shannon M Pare, Elizabeth Gunn, Katherine M. Morrison, Alison L. Miller, Alison M. Duncan, Andrea C. Buchholz, David W.L., Paul F. Tremblay, Lori Ann Vallis, Nicola J. Mercer, Jess Haines

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsWestern UniversityGuelph General HospitalMcMaster UniversityUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsObservational studyPreprintMedicineDemographicsStress (linguistics)Clinical psychologyPsychologyInternal medicineDemography

Abstract

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BACKGROUND: Chronic stress is an important risk factor in the development of obesity. While research suggests chronic stress is linked to excess weight gain in children, the biological or behavioral mechanisms are poorly understood. OBJECTIVE: The objectives of the Family Stress Study are to examine behavioral and biological pathways through which chronic stress exposure (including stress from COVID-19) may be associated with adiposity in young children, and to determine if factors such as child sex, caregiver-child relationship quality, caregiver education, and caregiver self-regulation moderate the association between chronic stress and child adiposity. METHODS: The Family Stress Study is a prospective cohort study of families recruited from 2 Canadian sites: the University of Guelph in Guelph, Ontario, and McMaster University in Hamilton, Ontario. Participants will be observed for 2 years and were eligible to participate if they had at least one child (aged 2-6 years) and no plans to move from the area within the next 3 years. Study questionnaires and measures were completed remotely at baseline and will be assessed using the same methods at 1- and 2-year follow-ups. At each time point, caregivers measure and report their child's height, weight, and waist circumference, collect a hair sample for cortisol analysis, and fit their child with an activity monitor to assess the child's physical activity and sleep. Caregivers also complete a web-based health and behaviors survey with questions about family demographics, family stress, their own weight-related behaviors, and their child's mental health, as well as a 1-day dietary assessment for their child. RESULTS: Enrollment for this study was completed in December 2021. The final second-year follow-up was completed in April 2024. This study's sample includes 359 families (359 children, 359 female caregivers, and 179 male caregivers). The children's mean (SD) age is 3.9 years (1.2 years) and 51% (n=182) are female. Approximately 74% (n=263) of children and 80% (n=431) of caregivers identify as White. Approximately 34% (n=184) of caregivers have a college diploma or less and nearly 93% (n=499) are married or cohabiting with a partner. Nearly half (n=172, 47%) of the families have an annual household income ≥CAD $100,000 (an average exchange rate of 1 CAD=0.737626 USD applies). Data cleaning and analysis are ongoing as of manuscript publication. CONCLUSIONS: Despite public health restrictions from COVID-19, the Family Stress Study was successful in recruiting and using remote data collection to successfully engage families in this study. The results from this study will help identify the direction and relative contributions of the biological and behavioral pathways linking chronic stress and adiposity. These findings will aid in the development of effective interventions designed to modify these pathways and reduce obesity risk in children. TRIAL REGISTRATION: ClinicalTrials.gov NCT05534711; https://clinicaltrials.gov/study/NCT05534711. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48549.

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)0.014
metaresearch head score (Gemma)0.008
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.025
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.008
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0190.005

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 head0.398
GPT teacher head0.537
Teacher spread0.139 · 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
GenreProtocol

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

Citations2
Published2024
Admission routes4
Has abstractyes

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