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Record W3015497915 · doi:10.2196/15647

Gamifying Parenting Education Using an App Developed for Pacific and Other New Zealand Families (Play Kindly): Qualitative Study

2020· article· en· W3015497915 on OpenAlexvenueno aff
Rebecca Mairs, Marthinus Johannes Bekker, Tony Patolo, Sarah Hopkins, Esther Cowley‐Malcolm, Lana Perese, Gerhard Sundborn, Sally Merry

Bibliographic record

VenueJMIR Serious Games · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersCure Kids
KeywordsFocus groupEthnic groupContext (archaeology)PsychologyQualitative researchUsabilityPsychological interventionPopulationMedical educationDevelopmental psychologyMedicineSociologySocial scienceGeographyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Play Kindly is a gamified animated app designed to address common behavioral problems in childhood. The interface is designed to appeal to Pacific people, a population group with a higher risk of developing clinically significant behavioral problems than most other ethnic groups in New Zealand. OBJECTIVE: The aim of this study is to explore the opinions of parents and professionals about the acceptability, usability, and content of Play Kindly. METHODS: We used qualitative and Pacific and Māori research methodologies. A total of five focus groups with 45 parents and 12 individual interviews with professionals were conducted. The five focus groups consisted of 2 pan-Pacific groups, 1 Māori group, 1 open group, and 1 group of young Pacific adults or prospective parents. The professionals were from a range of disciplines, and the majority had expertise in early childhood, parenting interventions, or research in this field. RESULTS: Play Kindly appealed to both parents and professionals. Participants related to the scenarios, which were created in collaboration with a playwright and animator. Although most participants liked the Pacific feel, there was some disagreement about how culturally specific the app should be. A range of issues with usability and gamification techniques were highlighted, likely attributed to the low budget and lack of initial co-design with parents as well as professionals with specific expertise in parenting. A number of parents and professionals felt that the parenting strategies were overly simplified and did not take into account the context in which the behavior occurred. Professionals suggested narrowing the focus of the app to deliver two important parenting messages: playing with your child and positively reinforcing desired behaviors. CONCLUSIONS: Play Kindly is the first culturally adapted parenting app of its kind designed for Pacific parents and other New Zealanders with children 2-5 years of age. This app has potential in Pacific communities where there are limited culturally specific parenting resources. The results of this study will guide improvements of the app prior to testing it in an open trial.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.079
GPT teacher head0.398
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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