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Record W2755217893 · doi:10.2196/resprot.8067

Health Information National Trends Survey in American Sign Language (HINTS-ASL): Protocol for the Cultural Adaptation and Linguistic Validation of a National Survey

2017· article· en· W2755217893 on OpenAlexvenueno aff
Poorna Kushalnagar, Raychelle Harris, Raylene Paludneviciene, TraciAnn Hoglind

Bibliographic record

VenueJMIR Research Protocols · 2017
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication DisordersNational Institutes of Health
KeywordsHealth Information National Trends SurveyThe InternetAmerican Sign LanguagePublic healthPopulationSurvey data collectionHealth informationPsychologyGeographySign languageEnvironmental healthComputer scienceMedicineWorld Wide WebPolitical scienceLinguisticsHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The Health Information National Trends Survey (HINTS) collects nationally representative data about the American's public use of health-related information. This survey is available in English and Spanish, but not in American Sign Language (ASL). Thus, the exclusion of ASL users from these national health information survey studies has led to a significant gap in knowledge of Internet usage for health information access in this underserved and understudied population. OBJECTIVE: The objectives of this study are (1) to culturally adapt and linguistically translate the HINTS items to ASL (HINTS-ASL); and (2) to gather information about deaf people's health information seeking behaviors across technology-mediated platforms. METHODS: We modified the standard procedures developed at the US National Center for Health Statistics Cognitive Survey Laboratory to culturally adapt and translate HINTS items to ASL. Cognitive interviews were conducted to assess clarity and delivery of these HINTS-ASL items. Final ASL video items were uploaded to a protected online survey website. The HINTS-ASL online survey has been administered to over 1350 deaf adults (ages 18 to 90 and up) who use ASL. Data collection is ongoing and includes deaf adult signers across the United States. RESULTS: Some items from HINTS item bank required cultural adaptation for use with deaf people who use accessible services or technology. A separate item bank for deaf-related experiences was created, reflecting deaf-specific technology such as sharing health-related ASL videos through social network sites and using video remote interpreting services in health settings. After data collection is complete, we will conduct a series of analyses on deaf people's health information seeking behaviors across technology-mediated platforms. CONCLUSIONS: HINTS-ASL is an accessible health information national trends survey, which includes a culturally appropriate set of items that are relevant to the experiences of deaf people who use ASL. The final HINTS-ASL product will be available for public use upon completion of this study.

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)0.013
metaresearch head score (Gemma)0.004
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.533
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.609
GPT teacher head0.661
Teacher spread0.053 · 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
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

Citations45
Published2017
Admission routes1
Has abstractyes

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