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Record W4400453593 · doi:10.1136/bmjebm-2024-sdc.144

145 Meaningful engagement is attainable: evaluation of co-production used for the cochrane review of patient decision aids

2024· article· en· W4400453593 on OpenAlexaff
Krystina B. Lewis, Maureen Smith, Dawn Stacey, Meg Carley, Ian D. Graham

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsCochraneOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsProduction (economics)Computer scienceProcess engineeringMedicineEngineeringEconomics

Abstract

fetched live from OpenAlex

Introduction Since its first publication, the Cochrane Review of Patient Decision Aids team has been committed to collaborating with knowledge users (e.g. patients/health consumers, caregivers) as research team members. Little is known about knowledge users’ involvement in the conduct of systematic reviews. During its most recent update, we evaluated team members’ degree of meaningful engagement. Methods We surveyed team members pre and post review. In the pre-survey, team members indicated their preferred level of involvement for each review step. In the post-survey, they reported on their degree of satisfaction with their actual level of involvement and provided open-ended responses about their partnering experiences in this co-produced review. Using the Patient Engagement In Research Scale (PEIRS-22), we measured the degree of meaningful engagement/involvement throughout review procedures. We analyzed quantitative data descriptively and qualitative data using content analysis, with triangulation. Results Twenty of 21(95%) team members completed the pre-survey; 17 of 20(85.0%) completed the post. Preferred levels of involvement in the review steps varied from search grey literature n=3(15%) to provide feedback on manuscript n=20(100%). Sixteen (94.1%) participants were totally or very satisfied with the extent to which they were involved throughout. All agreed the review was co-produced. PEIRS- 22 scores revealed high (n=15,88.2%) levels of meaningful engagement. Participants qualitatively reported there was authentic engagement, diverse perspectives were incorporated, which, in their view resulted in better/more relevant outputs. Challenges included time, resources, and logistics of collaborating with a large international team. Discussion It is possible to meaningfully engage knowledge users in reviews. The PEIRS-22 was useful, yet, given it was originally developed to measure patient/family partners’ engagement, it required minor edits to be used with all team members. Conclusion Using a co-production approach, team members reported high levels of meaningful engagement. These results support ways in which systematic reviews can be successfully co-produced.

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
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.458
metaresearch head score (Gemma)0.735
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.668

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4580.735
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.015
Bibliometrics0.0180.021
Science and technology studies0.0050.006
Scholarly communication0.0170.014
Open science0.0040.019
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.113
GPT teacher head0.545
Teacher spread0.432 · 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 designObservational · Qualitative
DomainMethods
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

Citations0
Published2024
Admission routes1
Has abstractyes

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