Unpacking the behavioural components and delivery features of early childhood obesity prevention interventions in the TOPCHILD Collaboration: a systematic review and intervention coding protocol
Bibliographic record
Abstract
ABSTRACT Introduction Little is known about how early (e.g., commencing antenatally or in the first 12 months after birth) obesity prevention interventions seek to change behaviour and which components are or are not effective. This study aims to 1) characterise early obesity prevention interventions in terms of target behaviours, delivery features, and behaviour change techniques (BCTs), 2) explore similarities and differences in BCTs used to target behaviours, and 3) explore effectiveness of intervention components in preventing childhood obesity. Methods and analysis Annual comprehensive systematic searches will be performed in Epub Ahead of Print/MEDLINE, Embase, Cochrane (CENTRAL), CINAHL, PsycINFO, as well as clinical trial registries. Eligible randomised controlled trials of behavioural interventions to prevent childhood obesity commencing antenatally or in the first year after birth will be invited to join the TOPCHILD Collaboration. Standard ontologies will be used to code target behaviours, delivery features and BCTs in both published and unpublished intervention materials provided by trialists. Narrative syntheses will be performed to summarise intervention components and compare applied BCTs by types of target behaviours. Exploratory analyses will be undertaken to assess effectiveness of intervention components. Ethics and dissemination The study has been approved by The University of Sydney Human Research Ethics Committee (project no. 2020/273) and Flinders University Social and Behavioural Research Ethics Committee (project no. HREC CIA2133-1). The study’s findings will be disseminated through peer-reviewed publications, conference presentations, and targeted communication with key stakeholders. Discussion Our study will provide an in depth understanding of behavioural components and delivery features used in obesity prevention interventions starting antenatally or in the first 12 months after birth. Understanding common intervention approaches in a systematic way will provide much needed insight to advance the design of early obesity prevention interventions and provide the opportunity to undertake future quantitative predictive modelling. Registration PROSPERO registration no. CRD42020177408 STRENGTHS AND LIMITATIONS OF THIS STUDY This study provides an understanding of behaviours targeted, behaviour change techniques and delivery features used in early childhood obesity prevention trials identified in a systematic review as being eligible for inclusion in the Transforming Obesity Prevention in CHILDren (TOPCHILD) Collaboration. Extends previous methods by coding behaviour change techniques in published and unpublished intervention materials and performing cross validation with trialists through the TOPCHILD Collaboration. Using standardised coding taxonomies will allow for comparisons across studies, and we will pilot test new ontologies from the Human Behaviour Change Project. Explores the complex area of targeting parent and caregivers’ behaviours to impact child outcomes across four key obesity prevention behavioural domains (relating to infant feeding practices, food provision and parent feeding practices, movement practices, sleep health practices). This study will provide preliminary results regarding the examination of intervention components’ effectiveness based on exploratory analysis. Yet, the internationally unique database this project creates will further our understanding of effective intervention components in future research. To date we already have 38 out of 65 eligible trials agreeing to share data, since not all trials may provide unpublished material we may perform sensitivity analyses comparing trials that have shared data to trials that have not shared materials.
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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 | 0.124 | 0.154 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.016 |
| Bibliometrics | 0.043 | 0.033 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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".