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Record W3174976755 · doi:10.1192/bjo.2021.783

Interview skills – psychiatry reel to reality

2021· article· en· W3174976755 on OpenAlexaboutno aff
Mathuri Tharmapoopathy, Santosh Kumar, Abishan Thavarajah

Bibliographic record

VenueBJPsych Open · 2021
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyObjectivity (philosophy)make.believeInterviewIntrospectionEpistemologyCognitive psychologyPsychotherapistSociologyPhilosophy

Abstract

fetched live from OpenAlex

Aims This reel analysis identifies quotes and actions of fictional characters from TV shows, namely: Hercules Poirot, Sherlock Holmes and House who can demonstrate learning points for clinical students to use within real psychiatric practice, using scientific theories such as the Hypothetico-deductive model, Empirical falsification and Occam's razor. This analysis explores what an ideal psychiatric interview consists of and what can be learnt from these characters and implemented within medical education. Method Each show was watched by one researcher over the period of March to August 2020. The researcher noted insightful quotes which were relevant to one of the three philosophical theories. Quotes were included if they demonstrated deduction skills, revealed a character's ethos and supported the Calgary-Cambridge model of interviewing such as building rapport. 32 quotations were collected in total and narrowed to 6 quotations. These were then analysed, learning points were made and linked to the Calgary Cambridge model. Result Dr House demonstrates objectivity when taking a patient's history. He utilises empirical falsification when diagnosing to avoid missing a differential diagnosis. Detective Poirot displays how empathic listening allows disclosure of details in the history, which would have otherwise been omitted. Additionally, he illustrates the importance of collateral interviewing which allows one to identify misinterpretations and inconsistencies. Sherlock teaches us the importance of perception regarding mismatching information which can help to gather new facts. All three characters interview beginning with open questions to more closed questions, supplementing with deductive reasoning in order to solve cases. Objectivity, empirical falsification, empathetic listening and deductive reasoning are the key skills displayed by these characters, that medical students can most use in their own practices. Conclusion The perfect interview discovers new information through synchronised collaboration, whilst adhering to the Hypothetico-deductive model of thought. A combination of the Calgary-Cambridge model of interviewing and skillset of the TV characters should be considered for implementation in some aspects of psychiatric interviewing. Medical education can utilise these TV shows to teach students how to conduct history-taking.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.324
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.069
GPT teacher head0.433
Teacher spread0.364 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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