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Record W4323295502 · doi:10.2196/46951

Digital Storytelling Intervention to Promote Human Papillomavirus Vaccination Among At-Risk Asian Immigrant Populations: Pilot Intervention Study

2023· article· en· W4323295502 on OpenAlexvenueno aff
Angela Chia‐Chen Chen, Sunny Kim, Lihong Ou, Michael Todd, Linda Larkey

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 Institutes of HealthOncology Nursing Foundation
KeywordsVietnameseMcNemar's testPsychological interventionMedicineEthnic groupVaccinationIntervention (counseling)DemographyGerontologyFamily medicinePsychologyNursingSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The high morbidity, mortality, and economic burden attributed to cancer-causing human papillomavirus (HPV) calls for researchers to address this public health concern through HPV vaccination. Despite disparities in HPV-associated cancers in Korean Americans and Vietnamese Americans, their vaccination rates remain low. Evidence points to the importance of developing culturally and linguistically congruent interventions to improve HPV vaccination rates. Digital storytelling (a specific form of cultural narrative) shows promise as an effective culture-centric health promotion strategy. OBJECTIVE: The aim of this quasi-experimental single-group study was to assess the feasibility, acceptability, and preliminary effects of a culturally and linguistically congruent digital storytelling intervention on Korean American and Vietnamese American mothers' attitudes and intention in vaccinating their children against HPV. We also examined if the association between attitudes and intention differed by their child's sex (boy vs girl) and by ethnicity (Korean American vs Vietnamese American). METHODS: Participants were recruited via multiple avenues (eg, ethnic minority community organizations, social media, and flyers posted in local Asian supermarkets and nail salons). Web-based, valid, and reliable measures were administered to collect data preintervention and postintervention. Descriptive statistics, paired and independent sample t tests, the chi-square test, and the McNemar test were used to describe the distributions of variables and to examine the differences between subgroups and changes in key variables over time. Logistic regression models were used to examine associations of mothers' HPV- and vaccine-related attitudes with vaccination intention and to explore if the association between attitudes and vaccination intention differed by the target children's sex or ethnicity. RESULTS: =18.38, P<.001). The measure of mothers' negative attitudes toward HPV and the vaccine was significantly associated with higher vaccination intention (odds ratio 0.27, 95% CI 0.14-0.51; P<.001), adjusting for background variables (sociodemographic characteristics) and other HPV-related variables (family cancer history, prior HPV education, and HPV communication with health care providers). Findings did not suggest that a child's sex or ethnicity moderated the association between attitudes and vaccination intention. CONCLUSIONS: This remotely delivered intervention using digital stories was feasible and acceptable, and showed preliminary effects on promoting Korean American and Vietnamese American mothers' intention to vaccinate their children against HPV. Future research that uses a randomized controlled trial design with a larger and more diverse sample and includes children's vaccination status will help understand the effect of the intervention.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.005

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 head0.169
GPT teacher head0.513
Teacher spread0.344 · 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
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

Citations14
Published2023
Admission routes1
Has abstractyes

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