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Record W3212279949 · doi:10.1111/hex.13387

Adapting patient and public involvement in patient‐oriented methods research: Reflections in a Canadian setting during COVID‐19

2021· article· en· W3212279949 on OpenAlexaffabout
Jenny Leese, Leana Garraway, Linda Li, Nelly D. Oelke, Martha MacLeod

Bibliographic record

VenueHealth Expectations · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of Northern British ColumbiaUniversity of British ColumbiaOttawa HospitalResearch CanadaUniversity of Ottawa
Fundersnot available
KeywordsContext (archaeology)Coronavirus disease 2019 (COVID-19)PandemicKnowledge translationPsychologyScale (ratio)Quality (philosophy)Public relationsMedicineKnowledge managementPolitical scienceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Processes of the patient and public involvement (PPI) in health research shifted quickly during 2020. Faced with large-scale issues, such as the COVID-19 pandemic, the need to adapt processes of PPI to uphold commitments to nurturing the practice of 'nothing about us without us' in research has been urgent and profound. We describe how processes of PPI in research on patient-oriented methods of knowledge translation and implementation science were adapted by four teams in a Canadian setting. METHODS: As part of an ongoing quality improvement self-study to enhance PPI within these teams, team members shared their experiences of PPI in the context of this pivotal year during interviews and facilitated discussions. Drawing on these experiences, we outline challenges and reflections for adapting processes of PPI in health research on methods in times of urgency, conflict and fast-moving change. DISCUSSION: Our reflections offer insight into common issues encountered across teams that may be amplified during times of rapid change, including handling change and uncertainty, sustaining relationship-building and hearing differing perspectives in processes of PPI. CONCLUSION: These learnings present an opportunity to help others active in or planning patient-oriented methods research to reflect on the changing nature of PPI and how to adapt PPI processes in response to turbulent situations in the future.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.510
GPT teacher head0.573
Teacher spread0.063 · 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.

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

Citations21
Published2021
Admission routes2
Has abstractyes

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