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Record W4307689767 · doi:10.2196/39225

Developing a Parenting App to Support Young Children’s Socioemotional and Cognitive Development in Culturally Diverse Low- and Middle-Income Countries: Protocol for a Co-design Study

2022· article· en· W4307689767 on OpenAlexvenueno aff
Haley M LaMonica, Jacob J. Crouse, Yun Ju Christine Song, Mafruha Alam, Mahalakshmi Ekambareshwar, Victoria Loblay, Adam Yoon, Grace Cha, Chloe Wilson, Madelaine Sweeney-Nash, Nathanael Foo, Melissa Teo, Mikael Perhirin, Jakelin Troy, Ian B. Hickie

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersMinderoo FoundationUniversity of Sydney
KeywordsSocioemotional selectivity theoryPsychologyChild developmentDevelopmental psychologyEarly childhood

Abstract

fetched live from OpenAlex

BACKGROUND: Digital technologies are widely recognized for their equalizing effect, improving access to affordable health care regardless of gender, ethnicity, socioeconomic status, or geographic region. The Thrive by Five app is designed to promote positive interactions between children and their parents, extended family, and trusted members of the community to support socioemotional and cognitive development in the first 5 years of life and to strengthen connections to culture and community. OBJECTIVE: This paper aims to describe the iterative co-design process that underpins the development and refinement of Thrive by Five's features, functions, and content. Minderoo Foundation commissioned this work as a quality improvement activity to support an engaging user experience and inform the development of culturally appropriate and relevant content for parents and caregivers in each country where the app is implemented. METHODS: The app content, referred to as Collective Actions, comprises "The Why," that presents scientific principles that underpin socioemotional and cognitive development in early childhood. The scientific information is coupled with childrearing activities for parents, extended family, and members of the community to engage in with the children to support their healthy development and to promote positive connections between parents, families, and communities and these young children. Importantly, the initial content is designed and iteratively refined in collaboration with a subject matter expert group from each country (ie, alpha testing). This content is then configured into the app (either a beta version or localized version) for testing (ie, beta testing) by local parents and caregivers as well as experts who are invited to provide their feedback and suggestions for improvements in app content, features, and functions via a brief web-based survey and a series of co-design workshops. The quantitative survey data will be analyzed using descriptive statistics, whereas the analysis of qualitative data from the workshops will follow established thematic techniques. RESULTS: To date, the co-design protocol has been completed with subject matter experts, parents, and caregivers from 9 countries, with the first results expected to be published by early 2023. The protocol will be implemented serially in the remaining 21 countries. CONCLUSIONS: Mobile technologies are the primary means of internet connection in many countries worldwide, which underscores the potential for mobile health programs to improve access to valuable, evidence-based, and previously unavailable parenting information. However, for maximum impact, it is critically important to ensure that mobile health programs are designed in collaboration with the target audience to support the alignment of content with parents' cultural values and traditions and its relevance to their needs and circumstances. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39225.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.383
GPT teacher head0.610
Teacher spread0.227 · 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 teacher head, not a consensus.

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

Citations24
Published2022
Admission routes1
Has abstractyes

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