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Record W4221028146 · doi:10.5498/wjp.v12.i2.323

Importance of communication in medical practice and medical education: An emphasis on empathy and attitudes and their possible influences

2022· article· en· W4221028146 on OpenAlexaff
Dagmar Steinmair, Katharina Zervos, Guoruey Wong, Henriette Löffler‐Stastka

Bibliographic record

VenueWorld Journal of Psychiatry · 2022
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCurriculumMedical educationEmpathyAnamnesisQualitative researchInclusion (mineral)Medical historyMedicinePsychologyHealth carePedagogySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Healthcare professionals need to be prepared to promote healthy lifestyles and care for patients. By focusing on what students should be able to perform one day as clinicians, we can bridge the gap between mere theoretical knowledge and its practical application. Gender aspects in clinical medicine also have to be considered when speaking of personalized medicine and learning curricula. AIM: To determine sets of intellectual, personal, social, and emotional abilities that comprise core qualifications in medicine for performing well in anamnesis-taking, in order to identify training needs. METHODS: An analysis of training clinicians' conceptions with respect to optimal medical history taking was performed. The chosen study design also aimed to assess gender effects. Structured interviews with supervising clinicians were carried out in a descriptive study at the Medical University of Vienna. Results were analyzed by conducting a qualitative computer-assisted content analysis of the interviews. Inductive category formation was applied. The main questions posed to the supervisors dealt with (1) Observed competencies of students in medical history taking; and (2) The supervisor's own conceptions of "ideal medical history taking". RESULTS: = 33), engaged in supervising medical students according to the MedUni Vienna's curriculum standards, agreed to be enrolled in the study and met inclusion criteria. The qualitative content analysis revealed the following themes relevant to taking an anamnesis: (1) Knowledge; (2) Soft skills (relationship-building abilities, trust, and attitude); (3) Methodical skills (structuring, precision, and completeness of information gathering); and (4) Environmental/contextual factors (language barrier, time pressure, interruptions). Overall, health care professionals consider empathy and attitude as critical features concerning the quality of medical history taking. When looking at physicians' theoretical conceptions, more general practitioners and psychiatrists mentioned attitude and empathy in the context of "ideal medical history taking", with a higher percentage of females. With respect to observations of students' history taking, a positive impact from attitude and empathy was mainly described by male health care professionals, whereas no predominance of specialty was found. Representatives of general medicine and internal medicine, when observing medical students, more often emphasized a negative impact on history taking when students lacked attitude or showed non-empathetic behavior; no gender-specific difference was detected for this finding. CONCLUSION: The analysis reveals that for clinicians engaged in medical student education, only a combination of skills, including adequate knowledge and methodical implementations, is supposed to guarantee acceptable performance. This study's findings support the importance of concepts like relationship building, attitude, and empathy. However, there may be contextual factors in play as well, and transference of theoretical concepts into the clinical setting might prove challenging.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.087
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.014
GPT teacher head0.359
Teacher spread0.345 · 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

Citations19
Published2022
Admission routes1
Has abstractyes

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