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Record W4394886685 · doi:10.1002/lrh2.10421

Experiences and lessons learned from a <scp>patient‐engagement</scp> service established by a national research consortium in the U.S. Veterans Health Administration

2024· article· en· W4394886685 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLearning Health Systems · 2024
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsCanadian Institute for Military and Veteran Health Research
FundersCenter for Care Delivery and Outcomes ResearchU.S. Department of Veterans Affairs
KeywordsAttendancePanel discussionCommunity engagementVeterans AffairsService (business)MedicineMedical educationPsychologyNursingPublic relationsPolitical scienceBusinessMarketing

Abstract

fetched live from OpenAlex

Introduction: Meaningful engagement of patients in the research process has increased over the past 20 years. Few accounts are available of engagement infrastructure and processes used by large research organizations. The Pain/Opioid Consortium of Research (Consortium) is a U.S. Department of Veterans Affairs (VA) research network that provides infrastructure to accelerate health research and implementation of evidence-based health care. The Consortium's key activities include facilitating Veteran-engaged research and building community between Veterans and VA researchers. This report sought to describe experiences and lessons learned from the first 3 years of a national research engagement service, featuring a Veteran Engagement (VE) Panel, established by the Consortium. Methods: We gathered authors' experiences to describe development and operation of the Consortium's VE Panel. Engagement staff collected program evaluation data about partners (Veterans and researchers), projects about which the VE Panel consulted, and meeting attendance during operation of the engagement service. Results: We created a 12-member VE Panel; all of whom had lived experience with chronic pain, prescription opioid medication use, or opioid use disorder. Engagement staff and VE Panel members implemented an engagement service operational model designed to continuously learn and adapt. The panel consulted on 48 projects spanning the research process. Seventy-eight percent of panel members, on average, attended each monthly meeting. VE Panel members and participating researchers reported high satisfaction with the quality, ease, and outcomes of their engagement service experiences. Conclusions: This work provides an illustrative example of how a national research consortium facilitated Veteran-engaged research and built community between Veterans and VA researchers by developing and operating an ongoing engagement consulting service, featuring a VE Panel. The service, designed as a learning community, relied on skilled engagement staff to cultivate high quality experiences and outcomes for all partners.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.270
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.141
GPT teacher head0.435
Teacher spread0.294 · 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