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Record W4416706541 · doi:10.1371/journal.pone.0336245

Patient and public involvement in developing and validating an instrument for assessing the scaling potential of innovations in health and social services: A consensus study

2025· article· en· W4416706541 on OpenAlexafffundabout
Roberta de Carvalho Corôa, Ali Ben Charif, Claude Bernard Uwizeye, Florence Lizotte, Amédé Gogovor, Robert K. D. McLean, Andrew Milat, Léonel Philibert, Louisa Blair, Kathy Kastner, Jean-Sébastien Renaud, France Légaré

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsFrancophone University AssociationCanadian Patient Safety InstituteInternational Development Research CentreInstitut National de Santé Publique du QuébecUniversité Laval
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsPublic involvementMEDLINEPublic healthScale (ratio)ScalabilityPsychometricsScalingResearch design

Abstract

fetched live from OpenAlex

BACKGROUND: Before proven health innovations are scaled, an assessment of their scaling potential can save resources and assure quality at scale. Involving the beneficiaries of scaling is necessary for it to be effective and relevant. We aimed to develop, with patient and public involvement (PPI), an instrument for assessing the scalability of innovations in health and social services and to establish content validity. METHODS: We conducted a multiphase study based on the Integrated Knowledge Translation approach and the Montreal Model for PPI. A steering committee provided feedback throughout the project. Informed by a systematic review, the research team and steering committee selected promising items for inclusion in the instrument. In a two-round online Delphi process, patients and public representatives and other expert panellists reached consensus on the relevance, clarity and necessity of each item. Finally, with a patient partner and two scaling teams we developed the instrument and a manual. RESULTS: The steering committee consisted of a patient partner, an expert in health measures and two policymakers who were experts in scaling. Based on the systematic review, we retained 43 items covering 12 domains. Two new items related to PPI and sex- and gender-sensitive scaling were validated by the committee. A 24-member Delphi panel assessed the resulting 45 items for content validity. Patients and public representatives constituted 29.1% of the panel and researchers 25%. Fourteen items were excluded for not reaching content validity thresholds. The final selection included three items added by panellists (consideration of national and local legislation, disadvantages of not scaling, and equity). Despite a low score, an item on sex and gender was retained as being essential for redressing consequences of inequities in health research. CONCLUSION: The final tool, the Innovation Scalability Self-administered Questionnaire (ISSaQ 4.0), includes 37 items across 12 domains and is available in French and English.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.570
metaresearch head score (Gemma)0.527
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5700.527
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0120.009
Science and technology studies0.0040.008
Scholarly communication0.0070.011
Open science0.0060.017
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.335
GPT teacher head0.433
Teacher spread0.098 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations1
Published2025
Admission routes3
Has abstractyes

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