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Record W2117757460 · doi:10.1186/2046-4053-4-11

User-centered design and the development of patient decision aids: protocol for a systematic review

2015· review· en· W2117757460 on OpenAlexafffund
Holly O. Witteman, Selma Chipenda Dansokho, Heather Colquhoun, Angela Coulter, Michèle Dugas, Angela Fagerlin, Anik Giguère, Sholom Glouberman, Lynne Haslett, Aubri Hoffman, Noah Ivers, France Légaré, Jean Légaré, Carrie A. Levin, Karli Lopez, Víctor M. Montori, Thierry Provencher, Jean-Sébastien Renaud, Kerri Sparling, Dawn Stacey, Gratianne Vaisson, Robert J. Volk, William Witteman

Bibliographic record

VenueSystematic Reviews · 2015
Typereview
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsCentre hospitalier universitaire de QuébecOttawa HospitalUniversity of OttawaCanadian Arthritis Patient AllianceHôpital Saint-François d'AssiseUniversity of TorontoRegent Park Community Health CentreToronto Rehabilitation InstituteHôpital du Saint-SacrementWomen's College HospitalUniversité Laval
FundersDepartment of Family and Community Medicine, University of TorontoUniversity of TorontoCanadian Institutes of Health ResearchUniversity of OttawaNational Institute on AgingPatient-Centered Outcomes Research Institute
KeywordsDecision aidsMedicineProtocol (science)Systematic reviewMEDLINECochrane LibraryGrey literatureKnowledge managementMedical educationComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Providing patient-centered care requires that patients partner in their personal health-care decisions to the full extent desired. Patient decision aids facilitate processes of shared decision-making between patients and their clinicians by presenting relevant scientific information in balanced, understandable ways, helping clarify patients' goals, and guiding decision-making processes. Although international standards stipulate that patients and clinicians should be involved in decision aid development, little is known about how such involvement currently occurs, let alone best practices. This systematic review consisting of three interlinked subreviews seeks to describe current practices of user involvement in the development of patient decision aids, compare these to practices of user-centered design, and identify promising strategies. METHODS/DESIGN: A research team that includes patient and clinician representatives, decision aid developers, and systematic review method experts will guide this review according to the Cochrane Handbook and PRISMA reporting guidelines. A medical librarian will hand search key references and use a peer-reviewed search strategy to search MEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, the ACM library, IEEE Xplore, and Google Scholar. We will identify articles across all languages and years describing the development or evaluation of a patient decision aid, or the application of user-centered design or human-centered design to tools intended for patient use. Two independent reviewers will assess article eligibility and extract data into a matrix using a structured pilot-tested form based on a conceptual framework of user-centered design. We will synthesize evidence to describe how research teams have included users in their development process and compare these practices to user-centered design methods. If data permit, we will develop a measure of the user-centeredness of development processes and identify practices that are likely to be optimal. DISCUSSION: This systematic review will provide evidence of current practices to inform approaches for involving patients and other stakeholders in the development of patient decision aids. We anticipate that the results will help move towards the establishment of best practices for the development of patient-centered tools and, in turn, help improve the experiences of people who face difficult health decisions. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42014013241.

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)0.125
metaresearch head score (Gemma)0.184
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.125
Threshold uncertainty score0.663

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1250.184
Meta-epidemiology (narrow)0.0070.007
Meta-epidemiology (broad)0.0170.015
Bibliometrics0.0160.016
Science and technology studies0.0050.007
Scholarly communication0.0090.010
Open science0.0050.006
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0800.012

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 head0.585
GPT teacher head0.554
Teacher spread0.031 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations219
Published2015
Admission routes2
Has abstractyes

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