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Record W4413375950 · doi:10.1111/1460-6984.70115

Stakeholder Perspectives on the Responsible Innovation in Health Framework for Addressing Stigma‐Based Health Inequalities Among People Who Stutter

2025· article· en· W4413375950 on OpenAlexafffund
Sébastien Finlay, Geneviève Lamoureux, Anne Moïse‐Richard, Lucie Ménard, Ingrid Verduyckt

Bibliographic record

VenueInternational Journal of Language & Communication Disorders · 2025
Typearticle
Languageen
FieldPsychology
TopicStuttering Research and Treatment
Canadian institutionsUniversité du Québec à MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
FundersUniversité de Montréal
KeywordsPsychological interventionStigma (botany)PsychologySustainabilityStakeholderHealth equityFidelityPublic relationsKnowledge managementMedicinePolitical sciencePublic healthComputer scienceNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: People who stutter (PWS) experience stigma-based health inequalities that can negatively impact their quality of life. Yet, few interventions in the literature are explicitly designed to address these systemic disparities. The Responsible Innovation in Health (RIH) framework offers a promising foundation for developing health innovations that are equitable, sustainable and contextually responsive. This study explores how stakeholders interpret and apply the RIH framework to envision interventions that reduce stigma and promote health equity for PWS. METHODS: Using a mixed-methods design, namely the Participative Concept Mapping Approach, stakeholders (PWS, clinicians, health innovators) participated in a workshop to generate, sort and rate ideas based on their importance and feasibility. Concept maps were used to analyse and categorize ideas thematically. RESULTS: Stakeholders generated 94 ideas across six clusters as follows: (1) Digital Technology and Video Media, (2) Collective and Professional Approaches, (3) Cost and Accessibility, (4) Inclusive and Sustainable Intervention Design, (5) Engaging Multi-Modal Approaches and (6) Flexibility. The environmental responsibility value of the RIH framework received limited focus. Discrepancies between the importance and feasibility of ideas highlighted challenges in implementing interventions, while ensuring their sustainability. CONCLUSION: This study demonstrates how stakeholders prioritize values of the RIH framework when envisioning stigma-reducing health innovations for PWS. Findings highlight the need for embedding sustainability within clinical practices and underscore the importance of patient and user feedback to bridge the gap between impactful concepts and practical solutions, ensuring that interventions are meaningful, feasible and grounded in the RIH values. WHAT THIS PAPER ADDS: What is already known on this subject Stuttering is associated with stigma-based health inequalities that extend beyond speech, impacting PWS across multiple domains of life. Research has documented the effects of stigma on quality of life, access to care and communicative participation for PWS. However, frameworks to guide the development of interventions that explicitly address these structural inequities remain limited. What this paper adds to existing knowledge This study is the first to explore how the RIH framework can inform the design of stigma-reducing interventions tailored to stuttering. Through participatory concept mapping with PWS, clinicians and health innovators, it identifies how RIH principles, such as inclusion, sustainability and responsiveness, can shape context-specific, equity-oriented innovations that reflect the lived experiences of PWS. What are the potential or actual clinical implications of this work? Applying the RIH framework to stuttering interventions offers a novel approach for promoting health equity in both clinical and community contexts. This study highlights the importance of co-designing interventions with stakeholders, grounding them in the lived experiences and priorities of people who stutter. It sets the stage for developing sustainable, meaningful and inclusive practices that respond to the complex realities of stigma in stuttering.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.109
GPT teacher head0.459
Teacher spread0.351 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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