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Record W4387305494 · doi:10.1177/16094069231205176

Methodological Approaches to Obtaining Informed Consent when Conducting Research With Individuals With Deafblindness

2023· article· en· W4387305494 on OpenAlexaff
Walter Wittich, Norman Robert Boie, Atul Jaiswal

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2023
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsSanté MontérégieUniversité de MontréalCentre intégré de santé et de services sociaux de la Montérégie-CentreCentre de réadaptation Lethbridge-Layton-MackayCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsInformed consentPsychologyMedical educationSign languageMainstreamInclusion (mineral)Flexibility (engineering)Observational studyBrailleSocial psychologyMedicineComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

Informed consent is essential in research involving people with disabilities to protect their rights and ensure ethical conduct. Individuals with communicative vulnerability, such as those living with deafblindness, face difficulties when the research process is not accessible. Our team has developed methodological expertise where this vulnerable population is concerned. To formalize recommendations that can improve their inclusion, we utilized an observational, retrospective design to address three questions: What are procedures that facilitate recruitment in a lab specializing on working with individuals living with deafblindness? What are optimal procedural adaptations to obtaining informed consent? and What training can best prepare researchers working with individuals living with deafblindness? First, we conducted a textual narrative synthesis of our eight most recent protocols and procedures that required in-person interaction with adults living with deafblindness. Second, we conducted semi-structured discussions among our team members, and third, we engaged in a validation procedure of the synthesized recommendations with our external partners. Procedural adaptations require flexibility in all aspects of recruitment and consent to accommodate communication needs. These include additional time, and accessible formats. Adaptations should consider vision (e.g., large-print, braille) and hearing (e.g., sign language, communication strategies) as well as aspects unique to deafblindness (e.g., intervener support, tactile communication). Consent can be documented in hand-written, electronic, audio or video-recorded format, and may be facilitated by third parties. Team training should include proficiency in plain language, basic knowledge about deafblindness, and awareness of accessibility features for mainstream devices. We present simple steps that can improve inclusion and increase accessibility for participants living with deafblindness, and that can improve the capacity of the research team by developing flexibility, patience, respect, and trust. This information can further inform institutional ethics review boards that are unfamiliar with the logistics of obtaining informed consent when working with participants living with deafblindness.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.055
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.363
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0550.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.989
GPT teacher head0.757
Teacher spread0.232 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Qualitative
DomainMethods
GenreMethods

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

Citations24
Published2023
Admission routes1
Has abstractyes

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