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Does providing the correct diagnosis as feedback after self-explanation improve medical students diagnostic performance?

ABSTRACT:

Background

Self-explanation without feedback has been shown to improve medical students' diagnostic reasoning. While feedback is generally seen as beneficial for learning, available evidence of the value of its combination with self-explanation is conflicting. This study investigated the effect on medical students' diagnostic performance of adding immediate or delayed content-feedback to self-explanation while solving cases.

Methods

Ninety-four 3rd-year students from a Canadian medical school were randomly assigned to three experimental conditions (immediate-feedback, delayed-feedback, control). In the learning phase, all students solved four clinical cases by giving i) the most likely diagnosis, ii) two main arguments supporting this diagnosis, and iii) two plausible alternative diagnoses, while using self-explanation. The immediate-feedback group was given the correct diagnosis after each case; delayed-feedback group received the correct diagnoses only after the four cases; control group received no feedback. One week later, all students solved four near-transfer (i.e., same final diagnosis as the learning cases but different scenarios) and four far-transfer cases (i.e., different final diagnosis from the learning cases and different scenarios) by answering the same three questions. Students' diagnostic accuracy (score for the response to the first question only) and diagnostic performance (combined score of responses to the three questions) scores were assessed in each phase. Four one-way ANOVAs were performed on each of the two scores for near and far-transfer cases.

Results

There was a significant effect of experimental condition on diagnostic accuracy on near-transfer cases (p?ConclusionsProviding feedback to students in the form of the correct diagnosis after using self-explanation with clinical cases is potentially beneficial to improve their diagnostic accuracy but this effect is limited to similar cases. Further studies should explore how more elaborated feedback combined with self-explanation may impact students' diagnostic performance on different cases.

SUBMITTER: Chamberland M

PROVIDER: S-EPMC6558772 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Does providing the correct diagnosis as feedback after self-explanation improve medical students diagnostic performance?

Chamberland M M Setrakian J J St-Onge C C Bergeron L L Mamede S S Schmidt H G HG

BMC medical education 20190611 1

<h4>Background</h4>Self-explanation without feedback has been shown to improve medical students' diagnostic reasoning. While feedback is generally seen as beneficial for learning, available evidence of the value of its combination with self-explanation is conflicting. This study investigated the effect on medical students' diagnostic performance of adding immediate or delayed content-feedback to self-explanation while solving cases.<h4>Methods</h4>Ninety-four 3rd-year students from a Canadian me ...[more]

PMID: 31185971

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Project description:BackgroundThe use of feedback has been integral to medical student learning, but rigorous evidence to evaluate its education effect is limited, especially in the role of patient feedback in clinical teaching and practice improvement. The aim of the Patient Teaching Associate (PTA) Feedback Study was to evaluate whether additional written consumer feedback on patient satisfaction improved consultation skills among medical students and whether multisource feedback (MSF) improved student performance.MethodsIn this single site, double-blinded randomised controlled trial, 71 eligible medical students from two universities in their first clinical year were allocated to intervention or control and followed up for one semester. They participated in five simulated student-led consultations in a teaching clinic with patient volunteers living with chronic illness. Students in the intervention group received additional written feedback on patient satisfaction combined with guided self-reflection. The control group received usual immediate formative multisource feedback from tutors, patients and peers. Student characteristics, baseline patient-rated satisfaction scores and tutor-rated consultation skills were measured.ResultsFollow-up assessments were complete in 70 students attending the MSF program. At the final consultation episodes, both groups improved patient-rated rapport (P = 0.002), tutor-rated patient-centeredness and tutor-rated overall consultation skills (P = 0.01). The intervention group showed significantly better tutor-rated patient-centeredness (P = 0.003) comparing with the control group. Distress relief, communication comfort, rapport reported by patients and tutor-rated clinical skills did not differ significantly between the two groups.ConclusionsThe innovative multisource feedback program effectively improved consultation skills in medical students. Structured written consumer feedback combined with guided student reflection further improved patient-centred practice and effectively enhanced the benefit of an MSF model. This strategy might provide a valuable adjunct to communication skills education for medical students.Trial registrationAustralian New Zealand Clinical Trials Registry Number ACTRN12613001055796 .

Project description:During clinical reasoning case conferences, a learner-centered approach using teleconferencing can create a psychologically safe environment and help learners speak up. This study aims to measure the psychological safety of students who are supposed to self-explain their clinical reasoning to conference participants. This crossover study compared the effects of two clinical reasoning case conference methods on medical students' psychological safety. The study population comprised 4th-5th year medical students participating in a two-week general medicine clinical clerkship rotation, from September 2019 to February 2020. They participated in both a learner-centered approach teleconference and a traditional, live-style conference. Teleconferences were conducted in a separate room, with only a group of students and one facilitator. Participants in group 1 received a learner-centered teleconference in the first week and a traditional, live-style conference in the second week. Participants assigned to group 2 received a traditional, live-style conference in the first week and a learner-centered approach teleconference in the second week. After each conference, Edmondson's Psychological Safety Scale was used to assess the students' psychological safety. We also counted the number of students who self-explained their clinical reasoning processes during each conference. Of the 38 students, 34 completed the study. Six out of the seven psychological safety items were significantly higher in the learner-centered approach teleconferences (p<0.01). Twenty-nine (85.3%) students performed self-explanation in the teleconference compared to ten (29.4%) in the live conference (p<0.01). A learner-centered approach teleconference could improve psychological safety in novice learners and increase the frequency of their self-explanation, helping educators better assess their understanding. Based on these results, a learner-centered teleconference approach has the potential to be a method for teaching clinical reasoning to medical students.

Project description:BackgroundLearning from routine healthcare data is important for the improvement of the quality of care. Providing feedback on clinicians' performance in comparison to their peers has been shown to be more efficient for quality improvements. However, the current methods for providing feedback do not fully address the privacy concerns of stakeholders.MethodsThe paper proposes a distributed architecture for providing feedback to clinicians on their clinical performances while protecting their privacy. The indicators for the clinical performance of a clinician are computed within a healthcare institution based on pseudonymized data extracted from the electronic health record (EHR) system. Group-level indicators of clinicians across healthcare institutions are computed using privacy-preserving distributed data-mining techniques. A clinician receives feedback reports that compare his or her personal indicators with the aggregated indicators of the individual's peers. Indicators aggregated across different geographical levels are the basis for monitoring changes in the quality of care. The architecture feasibility was practically evaluated in three general practitioner (GP) offices in Norway that consist of about 20,245 patients. The architecture was applied for providing feedback reports to 21 GPs on their antibiotic prescriptions for selected respiratory tract infections (RTIs). Each GP received one feedback report that covered antibiotic prescriptions between 2015 and 2018, stratified yearly. We assessed the privacy protection and computation time of the architecture.ResultsOur evaluation indicates that the proposed architecture is feasible for practical use and protects the privacy of the patients, clinicians, and healthcare institutions. The architecture also maintains the physical access control of healthcare institutions over the patient data. We sent a single feedback report to each of the 21 GPs. A total of 14,396 cases were diagnosed with the selected RTIs during the study period across the institutions. Of these cases, 2924 (20.3%) were treated with antibiotics, where 40.8% (1194) of the antibiotic prescriptions were narrow-spectrum antibiotics.ConclusionsIt is feasible to provide feedback to clinicians on their clinical performance in comparison to peers across healthcare institutions while protecting privacy. The architecture also enables monitoring changes in the quality of care following interventions.

Dataset Information

Does providing the correct diagnosis as feedback after self-explanation improve medical students diagnostic performance?

Background

Methods

Results

Publications

Does providing the correct diagnosis as feedback after self-explanation improve medical students diagnostic performance?

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