MétaCan
Menu
Back to cohort
Record W2902939193 · doi:10.1097/sla.0000000000003125

The Construction of Surgical Trust

2018· article· en· W2902939193 on OpenAlexaff
Saad Y. Salim, Marjan Govaerts, Jonathan White

Bibliographic record

VenueAnnals of Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCompetence (human resources)MedicineLaparoscopic cholecystectomyTrustworthinessIntervention (counseling)Decision aidsNursingSocial psychologySurgeryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to explore how trust was constructed between surgeons and residents in the operating room. BACKGROUND: Entrustment is increasingly being used as a key element to assess trainees' competence in the clinical workplace. However, the cognitive process involved in the formulation of surgical trust remains poorly understood. METHODS: In semistructured interviews, 9 general surgeons discussed their experiences in making entrustment decisions during laparoscopic cholecystectomy. Template analysis methodology was employed to develop an explanatory model. RESULTS: Surgeons described the construction of trust as a stepwise process taking place before, during, and after the procedure. The main steps were as follows: (1) an initial propensity to trust based on the perceived risk of the case and trustworthiness of the resident; (2) a decision to initiate trust in the resident to begin the surgery; (3) close observation of preliminary steps; (4) an evolving decision based on whether the surgery is "on-track" or "off-track"; (5) intervention if the surgery was "off-track" (withdrawal of trust); (6) re-evaluation of trust for future cases. The main reasons described for withdrawing trust were: inability to follow instructions, failure to progress, and unsafe manoeuvres. CONCLUSIONS: This study showed that surgical trust is constructed through an iterative process involving gathering and valuing of information, decision-making, close observation, and supervisory intervention. There were strong underlying themes of control and responsibility, and trust was noted to increase over time and over repeated observations. The model presented here may be useful in improving judgements on competence in the surgical workplace.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.250
GPT teacher head0.387
Teacher spread0.137 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of SurgerySame topicSurgical Simulation and TrainingFrench-language works237,207