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Record W4411347828 · doi:10.1186/s12966-025-01764-1

Six-month intervention effect of a digital movement behavior intervention on parent- and child intermediary outcomes—results from the Let’s Grow randomized controlled trial

2025· article· en· W4411347828 on OpenAlexaff
Johanna Sandborg, Katherine Downing, Liliana Orellana, Rachael W. Taylor, Lisa M. Barnett, Valerie Carson, Kylie D. Hesketh

Bibliographic record

VenueInternational Journal of Behavioral Nutrition and Physical Activity · 2025
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversity of Alberta
FundersNational Health and Medical Research CouncilHenning och Johan Throne-Holsts stiftelse för främjande av vetenskaplig forskningErik och Edith Fernströms Stiftelse för Medicinsk Forskning
KeywordsIntervention (counseling)Psychological interventionRandomized controlled trialMedicineCognitionMotor skillPsychologyClinical psychologyDevelopmental psychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Parental-focused interventions often aim to improve child health behaviors by changing parenting practices and cognitions and supporting child skill development. These intermediary outcomes serve as milestones that indicate progress towards achieving the ultimate intervention goal; however, the impact on these is rarely reported. The aim of this study was to investigate the effect of a digital intervention, intended to help parents promote healthy movement behaviors in toddlers on these intermediary outcomes. METHODS: This study utilized data from the Let's Grow trial (n = 1165). Participants were recruited Australia-wide and randomized to usual care (routine child healthcare visits) or intervention (usual care plus Let's Grow app) following baseline assessment. Participants with data on at least one intermediary outcome (assessed via an online survey) at baseline and mid-intervention (6-months) were included (usual care, n = 618; intervention, n = 547). These included parental cognitions (knowledge, self-efficacy, confidence) and behaviors (co-participation, role modelling, family rules and routines, screens in child's bedroom), and child developmental skills (motor skills, emotional regulation). Linear regression compared between-group outcomes. We also explored whether changes in the intermediary outcomes were associated with intervention engagement (Web app analytics). RESULTS: The intervention group had higher knowledge of child movement behaviors (mean difference = 0.41, P = 0.002) compared to control. This difference was driven by knowledge in physical activity (mean differences 0.12, P = 0.028) and sleep (mean difference 0.27, P = 0.003) topics. No significant effect was observed for the other intermediary outcomes. Higher engagement was associated with improvements in parental knowledge of child movement behaviors and physical activity, confidence, ease of parenting, family rules for movement behaviors and screen time, and less parental screen time (all P ≤ 0.039). CONCLUSIONS: While Let's Grow positively influenced physical activity and sleep knowledge at the mid-intervention point, our findings suggests that parents might need more time or support to improve cognitions and behaviors related to children's sedentary behavior/screen time and child developmental skills. Further clarity on whether the observed changes translate into differential impacts on child movement behaviors will be reported following trial conclusion. Engagement appears to enhance intervention effects, highlighting the importance of strategies to optimize engagement. TRIAL REGISTRATION: ACTRN12620001280998; U1111-1252-0599.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.014
GPT teacher head0.332
Teacher spread0.318 · 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 designRandomized trial
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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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