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Record W3158733299 · doi:10.2196/27542

Self-Care Needs and Technology Preferences Among Parents in Marginalized Communities: Participatory Design Study

2021· article· en· W3158733299 on OpenAlexvenueno aff
Weichao Yuwen, Miriana C. Duran, Minghui Tan, Teresa M. Ward, Sunny Chieh Cheng, Magaly Ramirez

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersNational Institute of Nursing ResearchUniversity of Washington
KeywordsParticipatory designCitizen journalismParticipatory action researchSociologyPsychologyComputer scienceEngineeringWorld Wide WebAnthropology

Abstract

fetched live from OpenAlex

BACKGROUND: Ten million parents provide unpaid care to children living with chronic conditions, such as asthma, and a high percentage of these parents are in marginalized communities, including racial and ethnic minority and low-income families. There is an urgent need to develop technology-enabled tailored solutions to support the self-care needs of these parents. OBJECTIVE: This study aimed to use a participatory design approach to describe and compare Latino and non-Latino parents' current self-care practices, needs, and technology preferences when caring for children with asthma in marginalized communities. METHODS: The participatory design approach was used to actively engage intended users in the design process and empower them to identify needs and generate design ideas to meet those needs. RESULTS: Thirteen stakeholders participated in three design sessions. We described Latino and non-Latino parents' similarities in self-care practices and cultural-specific preferences. When coming up with ideas of technologies for self-care, non-Latino parents focused on improving caregiving stress through journaling, daily affirmations, and tracking feelings, while Latino parents focused more on relaxation and entertainment. CONCLUSIONS: Considerations need to be taken beyond language differences when developing technology-enabled interventions for diverse populations. The community partnership approach strengthened the study's inclusive design.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.114
GPT teacher head0.417
Teacher spread0.303 · 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 designObservational
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

Citations10
Published2021
Admission routes1
Has abstractyes

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