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Students’ and tutors’ experiences of remote ‘student–patient’ consultations

2023· article· en· W6902186797 on OpenAlexaff

Bibliographic record

VenueFigshare · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsHealth Sciences North
Fundersnot available
KeywordsEXPOSETUTORAutonomyInclusion (mineral)TriageVariety (cybernetics)Clinical PracticeCommunication skills

Abstract

fetched live from OpenAlex

Remote consulting has become part of the medical student clinical experience in primary care, but little research exists regarding the impact on learning. To describe the experiences of General Practitioner (GP) educators and medical students in using student-led remote consultations as an educational tool. A qualitative, explorative study conducted at four UK medical schools. GP educators and medical students were purposively sampled and interviewed. Nine themes arose: practical application, autonomy, heuristics, safety, triage of undifferentiated patients, clinical reasoning, patient inclusion in student education, student–patient interaction, and student–doctor interaction. Remote consulting has become part of the clinical placement experience. This has been found to expose students to a wider variety of clinical presentations. Verbal communication, history-taking, triage, and clinical reasoning skills were practised through remote consulting, but examination skills development was lacking. Students found building rapport more challenging, although this was mitigated by having more time with patients. Greater clinical risk was perceived in remote consulting, which had potential to negatively impact students’ psychological safety. Frequent debriefs could ameliorate this risk and positively impact student–doctor relationships. Student autonomy and independence increased due to greater participation and responsibility. Pre-selection of patients could be helpful but had potential to expose students to lower complexity patients. Practice pointsRemote consulting confers unique educational benefits.Remote consulting can help develop history-taking and communication skills, as well as clinical reasoning skills.The psychological safety of the student and the supervisory risk of the tutor can be impacted by remote consulting, but frequent debriefs between the student and tutor can help mitigate this risk.Learning how to conduct remote, and face-to-face consultations is important in medical education. Practice points Remote consulting confers unique educational benefits. Remote consulting can help develop history-taking and communication skills, as well as clinical reasoning skills. The psychological safety of the student and the supervisory risk of the tutor can be impacted by remote consulting, but frequent debriefs between the student and tutor can help mitigate this risk. Learning how to conduct remote, and face-to-face consultations is important in medical education.

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)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0050.002
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.082
GPT teacher head0.418
Teacher spread0.337 · 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 designQualitative
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
Published2023
Admission routes1
Has abstractyes

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