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Record W4380576597 · doi:10.2196/45696

Developing a Culturally and Linguistically Congruent Digital Storytelling Intervention in Vietnamese and Korean American Mothers of Human Papillomavirus–Vaccinated Children: Feasibility and Acceptability Study

2023· article· en· W4380576597 on OpenAlexvenueno aff
Sunny Kim, Angela Chia‐Chen Chen, Lihong Ou, Linda Larkey, Michael Todd, Yooro Han

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute on Drug AbuseNational Institutes of HealthOncology Nursing Foundation
KeywordsVietnameseSnowball samplingStorytellingPsychological interventionmHealthIntervention (counseling)MedicineDigital storytellingPsychologyMedical educationFamily medicineNursingPedagogyNarrative

Abstract

fetched live from OpenAlex

BACKGROUND: The high morbidity, mortality, and economic burden attributed to cancer-causing human papillomavirus (HPV) call for researchers to address this public health concern through HPV vaccination. Disparities of HPV-associated cancers in Vietnamese and Korean Americans exist, yet their vaccination rates remain low. Evidence points to the importance of developing culturally and linguistically congruent interventions to improve their HPV vaccination rates. We adopted digital storytelling (DST) that combines oral storytelling with computer-based technology (digital images, audio recording, and music) as a promising approach for facilitating the communication of culturally relevant health messages. OBJECTIVE: This study aimed to (1) assess the feasibility and acceptability of intervention development through DST workshops, (2) conduct an in-depth analysis of the cultural experience that shapes HPV attitudes, and (3) explore aspects of the DST workshop experience that could inform future formative and intervention work. METHODS: Through community partners, social media, and snowball sampling, we recruited 2 Vietnamese American and 6 Korean American mothers (mean age 41.4, SD 5.8 years) who had children vaccinated against HPV. Three virtual DST workshops were conducted between July 2021 and January 2022. Our team supported mothers to develop their own stories. Mothers completed web-based surveys before and after the workshop and provided feedback on each other's story ideas and the workshop experience. We used descriptive statistics to summarize quantitative data and constant comparative analysis to analyze qualitative data collected in the workshop and field notes. RESULTS: Eight digital stories were developed in the DST workshops. They were well accepted, and the mothers showed overall satisfaction and relevant indicators (eg, would recommend it to others, would attend a similar workshop, it was worth their time; mean 4.2-5, range 1-5). Mothers found the process rewarding and appreciated the opportunity to share their stories in group settings and learn from each other. The 6 major themes that emerged from the data reflect the mothers' rich personal experiences, attitudes, and perceptions about their child's HPV vaccination, which included (1) showing parents' love and responsibility; (2) HPV and related knowledge, awareness, and attitudes; (3) factors influencing vaccine decision-making; (4) source of information and information sharing; (5) response to children's being vaccinated; and (6) cultural perspectives on health care and HPV vaccination. CONCLUSIONS: Our findings suggest that a virtual DST workshop is a highly feasible and acceptable approach to engaging Vietnamese American and Korean American immigrant mothers in developing culturally and linguistically congruent DST interventions. Further research is needed to test the efficacy and effectiveness of digital stories as an intervention for Vietnamese American and Korean American mothers of unvaccinated children. This process of developing an easy-to-deliver, culturally and linguistically aligned, and holistic web-based DST intervention can be implemented with other populations in other languages.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.112
GPT teacher head0.498
Teacher spread0.385 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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