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Record W3120511490 · doi:10.1186/s12909-020-02459-w

Understanding the clinical reasoning processes involved in the management of multimorbidity in an ambulatory setting: study protocol of a stimulated recall research

2021· article· en· W3120511490 on OpenAlexaff
Marie‐Claude Audétat, Sarah Cairo Notari, Julia Sader, Claire Ritz, Thomas Fassier, Johanna Sommer, Mathieu Nendaz, N. Caire-Fon

Bibliographic record

VenueBMC Medical Education · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsRecallQualitative researchMedicineProtocol (science)CognitionCognitive interviewAmbulatoryInterviewMedical educationPsychologyApplied psychologyAlternative medicinePsychiatryCognitive psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Primary care physicians are at the very heart of managing patients suffering from multimorbidity. However, several studies have highlighted that some physicians feel ill-equipped to manage these kinds of complex clinical situations. Few studies are available on the clinical reasoning processes at play during the long-term management and follow-up of patients suffering from multimorbidity. This study aims to contribute to a better understanding on how the clinical reasoning of primary care physicians is affected during follow-up consultations with these patients. METHODS: A qualitative research project based on semi-structured interviews with primary care physicians in an ambulatory setting will be carried out, using the video stimulated recall interview method. Participants will be filmed in their work environment during a standard consultation with a patient suffering from multimorbidity using a "button camera" (small camera) which will be pinned to their white coat. The recording will be used in a following semi-structured interview with physicians and the research team to instigate a stimulated recall. Stimulated recall is a research method that allows the investigation of cognitive processes by inviting participants to recall their concurrent thinking during an event when prompted by a video sequence recall. During this interview, participants will be prompted by different video sequence and asked to discuss them; the aim will be to encourage them to make their clinical reasoning processes explicit. Fifteen to twenty interviews are planned to reach data saturation. The interviews will be transcribed verbatim and data will be analysed according to a standard content analysis, using deductive and inductive approaches. CONCLUSION: Study results will contribute to the scientific community's overall understanding of clinical reasoning. This will subsequently allow future generation of primary care physicians to have access to more adequate trainings to manage patients suffering from multimorbidity in their practice. As a result, this will improve the quality of the patient's care and treatments.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.495
GPT teacher head0.569
Teacher spread0.074 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations7
Published2021
Admission routes1
Has abstractyes

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