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Record W4388720635 · doi:10.1370/afm.22.s1.5447

The Social Organization of Patient Engagement: An Institutional Ethnography (IE) Study

2023· article· en· W4388720635 on OpenAlexaboutno aff
Fiona Webster, Laura Connoy, Craig Dale, Leigha Comer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographySociologyLived experienceSocial exclusionMental healthPovertyChronic painGender studiesPsychologyPolitical sciencePsychiatryPsychotherapistAnthropology

Abstract

fetched live from OpenAlex

Patient engagement (PE) in research is intended to be a “meaningful collaboration” with patients as partners in all aspects of research (CIHR, 2019). The purpose of PE is to engage people with lived experience of a health condition to integrate into research projects what they deem valuable. Through PE, the hope is that subjugated perspectives are being brought forward. However, no universally accepted framework for including voice, perspective, knowledge, and experience in PE exists (Domecq et al., 2014). Indeed, there is significant variation in how PE is defined and practiced, alongside an inadequate representation of systemically and structurally marginalized populations such as migrant populations, those living in poverty, people with mental illnesses, people who use drugs, and racialized groups (Brown Speights et al., 2017; Tremblay et al., 2020). The experiences of many people living with chronic pain in Canada are exemplary of the kinds of marginalization, exclusion, and depoliticization that necessitate effective ParE. Affecting one in four Canadians over the age of 15 (Campbell et al., 2020, p. 5), chronic pain is a stigmatized health condition within medicine due to its subjective nature. We conducted an institutional ethnography (IE) of ParE that began from the standpoint of people with lived experience of chronic pain and marginalization in order to begin identifying the institutional interests underpinning pain research in Canada. In keeping with our commitment to social justice, our core research team was comprised of three senior investigators experienced in IE, two trainees, and two people with lived experience of chronic pain and marginalization. Drawing on our findings, we discuss how a meaningful shift in conceptualization and practice yields a potential to reframe how certain conditions/diseases are normatively understood, thereby leading to the democratization of research and health for the benefit of people living with chronic pain and marginalization. We highlight how equity, diversity, and inclusion can be applied to ParE; the need to revise existing methodologies; and expanding notions of “who counts” in pain research.

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)0.018
metaresearch head score (Gemma)0.024
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 score0.097
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0180.022
Scholarly communication0.0080.006
Open science0.0030.012
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.317
GPT teacher head0.481
Teacher spread0.164 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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