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Record W3160000770 · doi:10.1186/s40900-021-00272-3

Co-designing strategies to support patient partners during a scoping review and reflections on the process: a commentary

2021· review· en· W3160000770 on OpenAlexaff
Tamara L. McCarron, Fiona Clement, Jananee Rasiah, Karen A. Moffat, Tracy Wasylak, Maria Santana

Bibliographic record

VenueResearch Involvement and Engagement · 2021
Typereview
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsAlberta Health ServicesCanadian Patient Safety InstituteUniversity of CalgaryUniversity of AlbertaSouth Health Campus
Fundersnot available
KeywordsPsychologyProcess (computing)Patient experienceMedical educationMedicineNursingHealth carePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Patient partners can be described as individuals who assume roles as active members on research teams, indicative of individuals with greater involvement, increased sharing of power, and increased responsibility than traditionally described by patient participants who are primarily studied. A gap still remains in the understanding of how to engage patients. The objective of this commentary is to describe the involvement of four patient partners who worked with researchers during a scoping review. MAIN BODY: We describe approaches to meaningfully engage patient partners in conducting a scoping review. Patient partners were recruited through existing patient networks. Capacity development in the form of the training was provided to these four patient partners. Engagement strategies were co-designed with them to address potential barriers of involvement and acquiring the necessary skills for the successful completion of this scoping review. CONCLUSION: Involving patients partners early in the project established the foundational relationship so patient partners could contribute to their fullest. We witnessed the success of working alongside patient partners as members of the research team with a clear and mutually agreed upon purpose of the engagement in health research activities and how this seemed to contribute to an effective and rewarding experience for both researcher and patient partner.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.781
GPT teacher head0.653
Teacher spread0.128 · 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 designSystematic review
Domainnot available
GenreReview

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 routes1
Has abstractyes

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