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Record W2929122648 · doi:10.2196/12039

Testing a Communication Assessment Tool for Ethically Sensitive Scenarios: Protocol of a Validation Study

2019· article· en· W2929122648 on OpenAlexaffvenue
Thierry Daboval, Natalie Ward, Jordan Richard Schoenherr, Gregory P. Moore, Caitlin Carew, Alicia Lambrinakos-Raymond, Emanuela Ferretti

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsCarleton UniversityGenome CanadaChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsProtocol (science)Computer scienceMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although well-designed instruments to assess communication during medical interviews and complex encounters exist, assessment tools that differentiate between communication, empathy, decision-making, and moral judgment are needed to assess different aspects of communication during situations defined by ethical conflict. To address this need, we developed an assessment tool that differentiates competencies associated with practice in ethically challenging situations. The competencies are grouped into three distinct categories: communication skills, civility and respectful behavior, clinical and ethical judgment and decision-making. OBJECTIVE: The overall objective of this project is to develop an assessment tool for ethically sensitive scenarios that measures the degree of respect for the attitudes and beliefs of patients and family members, the demands of clinical decision-making, and the success in dealing with ethical conflicts in the clinical context. In this article, we describe the research method we will use during the pilot-test study using the neonatal context to provide validity evidence to support the features of the Assessment Communication Tool for Ethics (ACT4Ethics) instrument. METHODS: This study is part of a multiphase project designed according to modern validity principles including content, response process, internal structure, relation to other variables, and social consequences. The design considers threats to validity such as construct underrepresentation and factors exerting nonrandom influence on scores. This study consists of two primary steps: (1) train the raters in the use of the new tool and (2) pilot-test a simulation using an Objective Structured Clinical Examination. We aim to obtain a total of 90 independent assessments based on the performance of 30 trainees rated by 15 trained raters for analysis. A comparison of raters' responses will allow us to compute a measure of interrater reliability. We will additionally compare the results of ACT4Ethics with another existing instrument. RESULTS: This study will take approximately 18 months to complete and the results should be available by September 2019. CONCLUSIONS: ACT4Ethics should allow clinician-teachers to assess and monitor the development of competency of trainees' judgments and communication skills when facing ethically sensitive clinical situations. The instrument will also guide the provision of meaningful feedback to ensure that trainees develop specific communication, empathy, decision-making, and ethical competencies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/12039.

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)0.117
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.117
Threshold uncertainty score0.621

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1170.108
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.003
Science and technology studies0.0030.004
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0270.009

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 head0.701
GPT teacher head0.689
Teacher spread0.012 · 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 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

Citations6
Published2019
Admission routes2
Has abstractyes

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