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Record W4379881878 · doi:10.2196/46809

Toward Shared Decision-Making in Degenerative Cervical Myelopathy: Protocol for a Mixed Methods Study

2023· article· en· W4379881878 on OpenAlexaffvenue
Irina Sangeorzan, Grazia Antonacci, Anne Martin, Ben Grodzinski, Carl Moritz Zipser, Rory K. J. Murphy, Panoraia Andriopoulou, Chad Cook, David Anderson, James D. Guest, Julio C. Furlan, Mark Kotter, Timothy F. Boerger, Iwan Sadler, Elizabeth A. Roberts, Helen Wood, Christine Fraser, Michael G. Fehlings, Vishal Kumar, Josephine Jung, James Milligan, Aria Nouri, Allan R. Martin, Tammy Blizzard, Luiz Roberto Vialle, Lindsay Tetreault, Sukhvinder Kalsi‐Ryan, Anna MacDowall, Esther Martin‐Moore, Martin Burwood, Lianne Wood, Abdul Ghaaliq Lalkhen, Manabu Ito, Nicky Wilson, Caroline Treanor, Sheila A. Dugan, Benjamin M. Davies

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsToronto Western HospitalMcMaster UniversityToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersEvelyn TrustDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsMedicineProtocol (science)Decision aidsHealth careMyelopathyWorkflowNursingKnowledge managementComputer scienceAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Health care decisions are a critical determinant in the evolution of chronic illness. In shared decision-making (SDM), patients and clinicians work collaboratively to reach evidence-based health decisions that align with individual circumstances, values, and preferences. This personalized approach to clinical care likely has substantial benefits in the oversight of degenerative cervical myelopathy (DCM), a type of nontraumatic spinal cord injury. Its chronicity, heterogeneous clinical presentation, complex management, and variable disease course engenders an imperative for a patient-centric approach that accounts for each patient's unique needs and priorities. Inadequate patient knowledge about the condition and an incomplete understanding of the critical decision points that arise during the course of care currently hinder the fruitful participation of health care providers and patients in SDM. This study protocol presents the rationale for deploying SDM for DCM and delineates the groundwork required to achieve this. OBJECTIVE: The study's primary outcome is the development of a comprehensive checklist to be implemented upon diagnosis that provides patients with essential information necessary to support their informed decision-making. This is known as a core information set (CIS). The secondary outcome is the creation of a detailed process map that provides a diagrammatic representation of the global care workflows and cognitive processes involved in DCM care. Characterizing the critical decision points along a patient's journey will allow for an effective exploration of SDM tools for routine clinical practice to enhance patient-centered care and improve clinical outcomes. METHODS: Both CISs and process maps are coproduced iteratively through a collaborative process involving the input and consensus of key stakeholders. This will be facilitated by Myelopathy.org, a global DCM charity, through its Research Objectives and Common Data Elements for Degenerative Cervical Myelopathy community. To develop the CIS, a 3-round, web-based Delphi process will be used, starting with a baseline list of information items derived from a recent scoping review of educational materials in DCM, patient interviews, and a qualitative survey of professionals. A priori criteria for achieving consensus are specified. The process map will be developed iteratively using semistructured interviews with patients and professionals and validated by key stakeholders. RESULTS: Recruitment for the Delphi consensus study began in April 2023. The pilot-testing of process map interview participants started simultaneously, with the formulation of an initial baseline map underway. CONCLUSIONS: This protocol marks the first attempt to provide a starting point for investigating SDM in DCM. The primary work centers on developing an educational tool for use in diagnosis to enable enhanced onward decision-making. The wider objective is to aid stakeholders in developing SDM tools by identifying critical decision junctures in DCM care. Through these approaches, we aim to provide an exhaustive launchpad for formulating SDM tools in the wider DCM community. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46809.

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)0.047
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.688
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0470.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.689
GPT teacher head0.738
Teacher spread0.048 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations3
Published2023
Admission routes2
Has abstractyes

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