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Record W4388871159 · doi:10.1136/bmjopen-2023-073953

Exploring the outcomes of research engagement using the observation method in an online setting

2023· article· en· W4388871159 on OpenAlexafffund
Deborah A. Marshall, Nitya Suryaprakash, Danielle C. Lavallee, Karis L. Barker, Gail MacKean, Sandra Zelinsky, Tamara L. McCarron, Maria Santana, Paul Moayyedi, Stirling Bryan

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsMcMaster UniversityAlberta Health ServicesUniversity of British ColumbiaMichael Smith Health Research BCUniversity of Calgary
FundersCanadian Institutes of Health ResearchCrohn's and Colitis CanadaDalhousie UniversityInstitut de Cardiologie de MontréalAllerganQueen's UniversityMcMaster UniversityResearch ManitobaTakeda Pharmaceutical CompanyUniversity of AlbertaAlberta InnovatesUniversity of Calgary
KeywordsMedicineMedical educationHealth services researchPublic healthFamily medicineData scienceNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to explore the outcomes of research engagement (patient engagement, PE) in the context of qualitative research. DESIGN: We observed engagement in two groups comprised of patients, clinicians and researchers tasked with conducting a qualitative preference exploration project in inflammatory bowel disease. One group was led by a patient research partner (PLG, partner led group) and the other by an academic researcher (RLG, researcher led group). A semistructured guide and a set of critical outcomes of research engagement were used as a framework to ground our analysis. SETTING: The study was conducted online. PARTICIPANTS: Patient research partners (n=5), researchers (n=5) and clinicians (n=4) participated in this study. MAIN OUTCOME MEASURES: Transcripts of meetings, descriptive and reflective observation data of engagement during meetings and email correspondence between group members were analysed to identify the outcomes of PE. RESULTS: Both projects were patient-centred, collaborative, meaningful, rigorous, adaptable, ethical, legitimate, understandable, feasible, timely and sustainable. Patient research partners (PRPs) in both groups wore dual hats as patients and researchers and influenced project decisions wearing both hats. They took on advisory and operational roles. Collaboration seemed easier in the PLG than in the RLG. The RLG PRPs spent more time than their counterparts in the PLG sharing their experience with biologics and helping their group identify a meaningful project question. A formal literature review informed the design, project materials and analysis in the RLG, while the formal review informed the project materials and analysis in the PLG. A PRP in the RLG and the PLG lead leveraged personal connections to facilitate recruitment. The outcomes of both projects were meaningful to all members of the groups. CONCLUSIONS: Our findings show that engagement of PRPs in research has a positive influence on the project design and delivery in the context of qualitative research in both the patient-led and researcher-led group.

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)0.115
metaresearch head score (Gemma)0.176
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.606

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1150.176
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0050.009
Scholarly communication0.0060.007
Open science0.0020.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.978
GPT teacher head0.734
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2023
Admission routes2
Has abstractyes

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