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Record W3137477246 · doi:10.2196/24802

An App-Based Parenting Program to Promote Healthy Energy Balance–Related Parenting Practices to Prevent Childhood Obesity: Protocol Using the Intervention Mapping Framework

2021· article· en· W3137477246 on OpenAlexvenueno aff
Levie T Karssen, Jacqueline M. Vink, Carolina de Weerth, Roel C.J. Hermans, Carina P M de Kort, Stef Kremers, Emilie L. M. Ruiter, Junilla K. Larsen

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersJacobs FoundationNederlandse Organisatie voor Wetenschappelijk OnderzoekFonds NutsOhra
KeywordsIntervention mappingIntervention (counseling)Protocol (science)PsychologyScreen timeChildhood obesityEarly childhoodDevelopmental psychologyBehavior changeBalance (ability)GerontologyMedicinePublic healthObesityHealth promotionNursingPhysical activityPhysical therapySocial psychologyAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The family environment plays an important role in the development of children's energy balance-related behaviors. As a result, parents' energy balance-related parenting practices are important targets of preventive childhood obesity programs. Families with a lower socioeconomic position (SEP) may benefit from participating in such programs but are generally less well reached than families with a higher SEP. OBJECTIVE: This paper describes the application of the Intervention Mapping Protocol (IMP) for the development of an app-based preventive intervention program to promote healthy energy balance-related parenting practices among parents of children (aged 0-4 years) with a lower SEP. METHODS: The 6 steps of the IMP were used as a theory- and evidence-based framework to guide the development of an app-based preventive intervention program. RESULTS: In step 1, behavioral outcomes for the app-based program (ie, children have a healthy dietary intake, sufficient sleep, and restricted screen time and sufficient physical activity) and sociocognitive (ie, knowledge, attitudes, and self-efficacy) and automatic (ie, habitual behaviors) determinants of energy balance-related parenting were identified through a needs assessment. In step 2, the behavioral outcomes were translated into performance objectives. To influence these objectives, in step 3, theory-based intervention methods were selected for each of the determinants. In step 4, the knowledge derived from the previous steps allowed for the development of the app-based program Samen Happie! through a process of continuous cocreation with parents and health professionals. In step 5, community health services were identified as potential adopters for the app. Finally, in step 6, 2 randomized controlled trials were designed to evaluate the process and effects of the app among Dutch parents of infants (trial 1) and preschoolers (trial 2). These trials were completed in November 2019 (trial 1) and February 2020 (trial 2). CONCLUSIONS: The IMP allowed for the effective development of the app-based parenting program Samen Happie! to promote healthy energy balance-related parenting practices among parents of infants and preschoolers. Through the integration of theory, empirical evidence, and data from the target population, as well as the process of continued cocreation, the program specifically addresses parents with a lower SEP. This increases the potential of the program to prevent the development of obesity in early childhood among families with a lower SEP. TRIAL REGISTRATION: Netherlands Trial Register NL6727, https://www.trialregister.nl/trial/6727; Netherlands Trial Register NL7371, https://www.trialregister.nl/trial/7371.

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)0.016
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.015
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0250.004

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 head0.127
GPT teacher head0.568
Teacher spread0.440 · 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 designNot applicable
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

Citations10
Published2021
Admission routes1
Has abstractyes

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