Bringing explicit insight into cognitive psychology features during clinical reasoning seminars: a prospective, controlled study

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Bringing Explicit Insight into Cognitive Psychology Features during Clinical Reasoning Seminars: A Prospective, Controlled Study MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu University of Geneva, Faculty of Medicine, Geneva Published: April 2011 Nendaz MR, Gut AM, Louis-Simonet M, Perrier A, Vu NV Bringing Explicit Insight into Cognitive Psychology Features during Clinical Reasoning Seminars: A Prospective, Controlled Study Education for Health, Volume 24, Issue 1, 2011 Available from:


Context: Facets of reasoning competence influenced by an explicit insight into cognitive psychology features during clinical reasoning seminars have not been specifically explored. Objective: This prospective, controlled study, conducted at the University of Geneva Faculty of Medicine, Switzerland, assessed the impact on sixth-year medical students’ patient work-up of case-based reasoning seminars, bringing them explicit insight into cognitive aspects of their reasoning. Methods: Volunteer students registered for our three-month Internal Medicine elective were assigned to one of two training conditions: standard (control) or modified (intervention) case-based reasoning seminars. These seminars start with the patient’s presenting complaint and the students must ask the tutor for additional clinical information to progress through case resolution. For this intervention, the tutors made each step explicit to students and encouraged self-reflection on their reasoning processes. At the end of their elective, students’ performances were assessed through encounters with two standardized patients and chart write-ups. Findings: Twenty-nine students participated, providing a total of 58 encounters. The overall differences in accuracy of the final diagnosis given to the patient at the end of the encounter (control 63% vs intervention 74%, p=0.53) and of the final diagnosis mentioned in the patient chart (61% vs 70%, p=0.58) were not statistically significant. The students in the intervention group significantly more often listed the correct diagnosis among the differential diagnoses in their charts (75% vs 97%, p=0.02).

© MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu, 2011. A licence to publish this material has been given to Education for Health: 1

Conclusion: This case-based clinical reasoning seminar intervention, designed to bring students insight into cognitive features of their reasoning, improved aspects of diagnostic competence. Keywords: Bedside teaching, case-based learning, clinical reasoning, internal medicine, medical education, medical reasoning, precepting, problem-solving

Context During the past 25 years, several studies in cognitive psychology have brought a better understanding about the mechanisms involved in clinical reasoning1-3. In particular, they have demonstrated that clinicians’ diagnostic accuracy is associated with characteristic features of a medical encounter, such as detailed inquiry about the chief complaint and frequent summarization of the collected information4,5. The most important predictor of diagnostic accuracy, however, was the early generation and evaluation of relevant diagnostic hypotheses and their use to frame the collection of further relevant information from the patient6-10. Case-based seminars allowing for iterative hypothesis testing may be adapted as a teaching method to put into practice the understanding brought by studies in cognitive psychology11. This format not only trains students to evaluate different diagnostic hypotheses through an analytical approach but also allows them to take into account their initial, non-analytical, intuitive diagnostic impression, a condition reported to increase teaching efficacy12-14. However, further exploration is needed into which facets of clinical reasoning may be particularly influenced by the explicit use of these cognitive theories during teaching. The purpose of this prospective, controlled study was to assess the impact on senior medical students of case-based reasoning seminars designed explicitly to bring them insight into cognitive aspects of their reasoning.

Methods Setting and participants The last year of the six-year medical curriculum at the University of Geneva Faculty of Medicine, Switzerland, consists of a 10month clinical elective program. Each promotion encompasses about 100 students. Our internal medicine elective admits successive groups of students for a two- or three-month clerkship rotation. Students registered for three-month rotations were eligible for the study. From January 2005 to end of April 2006, 39 students registered for four successive three-month elective rotations and were asked at the beginning of their elective to volunteer for the study. The students who declined participation attended the regular teaching provided during the clerkship, either with control groups or with students who were not eligible for the study (e.g. those who registered for a 2-month elective rotation). At this point of their curriculum, all students were at the same stage of training and had attended the same mandatory clerkships. They were randomly distributed across the patient units of our in-patient department.

© MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu, 2011. A licence to publish this material has been given to Education for Health: 2

Intervention During their elective in the division of internal medicine, students attend regular, weekly case-based clinical reasoning seminars conducted by faculty members15,16. This learning method is derived from Kassirer’s case-based seminars allowing for iterative hypothesis testing11. The seminars started with the patient’s presenting complaint and the students were instructed to ask the tutor for additional information about the patient’s history and physical examination while justifying their requests and mentioning which diagnostic hypothesis would be tested. The tutor provided them with the requested information and the same process continued until a final working diagnostic hypothesis was reached. The case was frequently summarized between natural steps of the seminar, when the group moved from history to physical examination and from physical findings to ancillary tests. For this study, we developed two types of case-based clinical reasoning seminars and we trained the tutors accordingly. For the first type (control group), the tutors followed the usual steps described above. For the second type (intervention group), the tutors additionally made each step explicit to the students, encouraged them to self-reflect on their processes of reasoning, related each step to the cognitive concepts described in the cognitive psychology literature and trained students to use these features. The tutors actively and explicitly provided guided feedback during the case resolution by reinforcing the following processes: a) setting up a plan for the collection of the information once the presenting complaint is exposed; b) characterizing each complaint (e.g. duration, characteristics, etc.); c) regularly summarizing the information at hand to enhance problem representation; d) generating early diagnostic hypotheses to be evaluated through a directed enquiry and using these hypotheses to frame the collection of further information (Figures 1 and 2). There is little evidence that the acquisition of generic thinking processes without the necessary contextual knowledge can lead to a transfer of competence from problem to problem1,2. Hence, the case-related content knowledge was simultaneously addressed in all seminars. The tutors involved in this study were all experienced physicians in general internal medicine and members of a pool of faculty members who had already experienced case-based reasoning seminars for several years. Their yearly tutoring schedule had been established independently from the present study. The tutors actually scheduled to teach intervention groups received an additional training by one investigator (MN) about the cognitive features of clinical reasoning and the way to relate them to the reasoning process of the students (Figures 1 and 2). They also received a written summary describing each step of the tutorial with examples of questions to ask and had a debriefing session with one investigator after the first tutorial to discuss potential difficulties. Four of them taught the intervention groups and five taught the control groups. Each tutor provided a total of 10 to 12 seminars during each three-month elective rotation. The four successive three-month student rotations were assigned to the control or the intervention groups according to a predefined plan designed to balance students’ acquired clinical experiences during the elective year (control-intervention-intervention-control).

Data Collection and Analysis On the last week of their elective, students worked up two cases portrayed by standardized patients. At the end of each encounter, the students provided the patient with the final working diagnosis and proposed a management plan, wrote up a patient chart listing the differential diagnosis and patient management plan (triage, investigation and treatment), and completed a multiple-choice knowledge test about their respective encountered cases. Each encounter was videotaped and reviewed for a thinking-aloud stimulated recall during which the participants indicated the diagnostic hypotheses underlying their data collection. The stimulated recall sessions were audio-taped and transcribed verbatim for analysis. © MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu, 2011. A licence to publish this material has been given to Education for Health: 3

Figure 1: Characteristics of data collection and reasoning made explicit by the tutors to the students of the intervention group during the case-based clinical reasoning seminars

© MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu, 2011. A licence to publish this material has been given to Education for Health: 4

Tutor (T)

Student1 (S1) S2 T

S3 T

S2 T S4 T S4 T S5 T

S6 T

S5 T

S and T


S and T

Good morning. In today’s seminar, we will try to solve the case of Mrs H, a 73 year-old woman admitted in our department of internal medicine because of shortness of breath. She comes from the psychiatry unit where she had been admitted for bipolar disorder and benzodiazepine abuse. Before we go on with your requests for further information, has anyone already an idea about what could happen with this lady? I remember that during my psychiatry clerkship, one patient had psychogenic dyspnea due to conversion disorder. This reminds me a man who abused alcohol and had aspiration pneumonia OK. You see that, even with few clinical elements, you already may have some hypotheses. We are keeping your hypotheses in mind and check later whether they are supported by additional clinical findings. This reflects what has been shown in the literature about how physicians think. We may have the impression that spontaneous hypotheses should be ignored because they are not part of a systematic and rigorous thinking process. However, some studies have demonstrated that a process mixing the valorization of these first diagnostic impressions with a more analytical process may enhance diagnostic accuracy. Don’t discard your first diagnostic impressions! Now, before we enter the details of data collection, what would be your general approach to shortness of breath? See this first step as a road map for the upcoming encounter. We should first characterize the chief complaint, for example see whether the dyspnea is acute or chronic, what the circumstances of apparition were, what associated symptoms were present. Right. Very often, younger physicians tend to immediately test specific detailed diagnostic hypotheses while it has been demonstrated that a first step aimed at better defining what the problem to think about really looks like, enhances diagnostic ability. This is called problem representation. In the case of this patient, the dyspnea began quickly over 2 hours while she was sitting at a table. [… the tutor gives the characteristics of the complaint, following the students’ requests]. Now that we have some characteristics of the complaint, who would like to summarize the problem, so that we get a good representation about what is going on. [… a student summarizes the complaint characteristics] OK. What information would you like to get from the patient now? Is the patient complaining about lateral thoracic pain? Why do you ask this question? Because it could be a pleural tumor. OK, this is an option. Has anyone another alternative to propose, related to lateral thoracic pain? An inflammation of pleura, associated, for example, with a pneumonia OK. Between the two hypotheses mentioned so far, which one seems to you more typical of this pain? Why? I am asking this because, according to literature about knowledge organization, using first typical diagnoses related to a complaint helps learners organize their knowledge in memory and retrieve it later. Pneumonia seems more frequent and typical of this condition In the case of this patient, there was a left lateral chest pain [… the tutor gives the characteristics of the pain, according to the students’ requests] If you think about pneumonia, what additional information would you like? Has the patient cough, fever, or chills? Right. Let’s analyze what happened now regarding clinical reasoning. Every time any of you requested additional information, I asked “Why”, because it is very important to collect information from the patient in a non-mechanistic way, knowing what you are looking for. Cognitive literature has shown that using diagnostic hypotheses to frame data collection was related to better diagnostic success. Use your diagnostic hypotheses to collect relevant information from the patient. Begin by using more typical or frequent diagnoses, here for example pneumonia instead of pleural tumor. In this case, the patient had fever or cough but had a recent dry cough. How do we continue? [… the same process goes on, the students ask the preceptor for additional information of the history and then of the physical examination; the tutor provides the information only once the students have justified their requests. The following questions are typical of this step: What is the purpose of this question ? What is/are the diagnostic hypothesis(es) tested ? Is the complaint clarified enough ? Summarize, rephrase, and reformulate the information at hand to get a representation about what the problem now has become. The tutor also reinforces the cognitive aspects reinforced by this step: problem representation, early elaboration of diagnostic hypotheses, early collection of key information] Now that we have a choice of different diagnostic hypotheses and the related information, let’s try to order them. What are the most likely diagnoses in this case? Why? Which data support these hypotheses? What if the patient was a 32 year-old man? When you have several diagnostic hypotheses in mind, a useful step is to compare and contrast them by using the information at hand. If this information is transformed into more abstract terms (for example acute or chronic, pleuritic pain, old woman, in-patient…) used to compare and contrast diagnostic hypotheses, this seems to help the diagnostic accuracy, according to some studies. Now here, what is the most likely diagnosis? Why? What would be the next step to manage the patient? [… the same approach is used to discuss tests to order or treatment to prescribe, as well as patient triage, according to the objectives of the session]

Figure 2: Examples of verbatim interactions between tutor and students during a case-based reasoning seminar, making the process explicit to students and relating it to features of cognitive psychology. © MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu, 2011. A licence to publish this material has been given to Education for Health: 5

Two assessment cases out of a set of four cases were randomly selected for each rotation. The presenting situations were abdominal distension, weight loss, headache and chronic diarrhoea. These complaints might have been encountered during the clerkship on the wards but were not directly addressed during the case-based reasoning seminars. Primary outcomes consisted of the accuracy of the final diagnosis and of the differential diagnosis, respectively, during the encounter - as determined by the explanations to the patient and the stimulated recall - and in the patient chart. Secondary outcomes included the characteristics of the patient data collection that were observed on the videotapes or reported by the participant during the stimulated recall. These characteristics encompassed clarification of patient complaints, summarization of the information at hand, use of key diagnostic hypotheses to frame data collection and early testing of the final diagnosis. We assessed the relevance of the tested diagnostic hypotheses, the collected information and the management decisions, using as a gold standard their frequency of occurrence (0 to 1) in a group of expert physicians who previously worked up the same cases8,17. We used student’s t-tests with Bonferroni corrections as needed, to compare the continuous variables of the intervention and control groups and Chi-squared tests to assess categorical variables. Analyses of variance were conducted on the relevance scores of diagnoses and management decisions to take into account a potential effect of case difficulty (SPSS Inc, Chicago, version 14.0). We built models with relevance scores of diagnoses as dependent variable and case difficulty, training condition and their interaction as factors. We estimated that 14 students in each group allowed the detection of a difference in relevance scores of 8% (SD 0.08) with a power of .80 when using two-tailed t-tests with an alpha value of .05. A complete ethical review was not requested by our institution for this type of project and the study was approved by our Curriculum Committee and Internal Medicine Head.

Findings Thirty-nine students were eligible for the study: 29 participated, 14 in the control group and 15 in the intervention group, thus providing 28 and 30 encounters, respectively. The students who declined participation (N=10) at the time of recruitment reported anticipated time constraints on the assessment day. The value of kappa between two coders analyzing the characteristics of a random sample of 13 encounters was 0.90. Students’ backgrounds were similar in both groups, as well as their clinical knowledge related to the cases (Table 1). Table 2 summarizes the primary outcomes regarding students’ diagnostic performance. The difference in accuracy of the final diagnosis given to the patient (63% for the control group vs 74% for the intervention group, p=.53) or reported in the chart (61% for the control group vs 70% for the intervention group, p=.58) was not statistically significant between the groups. The students in the intervention group mentioned significantly more often the correct diagnosis among the differential diagnostic hypotheses listed in the patient charts (75% for the control group vs 97% for the intervention group, p=.02). As displayed in Table 3, the characteristics of the information items collected and of the diagnostic hypotheses evaluated during the encounters were similar in both groups, except that the control group more often summarized the available information during the encounters (2.68 vs 1.73, p=.03). The relevance of the management decisions (tests, triage and treatment) recorded in the students’ written charts was not statistically significant.

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Table 1: Participants’ characteristics

Males: Females, N Entire curriculum accomplished at our medical school, N of students Problem-based learning curriculum followed, N of years (SD) Internal medicine mark (1-6) at the end of the previous year, mean (SD) Previous elective clerkships accomplished, N of months, mean (SD) Assessment cases encountered, N encounters Abdominal distension Chronic diarrhoea Weight loss Headache Mean scores (SD) on case-related multiple- choice test

Control group N=14 7:7 12 3.7 (.7) 5.1 (1.2) 3.5 (.8)

Intervention group N=15 8:7 14 3.9 (.5) 5.4 (.7) 2.8 (3.0)

28 7 7 7 7 .56 (.21)

30 5 10 10 5 .58 (.18)

No comparison between both groups was statistically significant.

Table 2: Primary outcomes: Diagnostic performance according to the training received Control group N encounters % (95% CI) Encounters Correct diagnosis given to patient Correct diagnosis evaluated during the encounterc Charts Correct final diagnosis Correct diagnosis mentioned in the differential

15/24b 25/28

17/28 21/28

Intervention group N encounters % (95% CI)

63 (43-80) 89 (73-96)


61 (42-76) 75 (57-87)





74 (54-88) 90 (74-97)


70 (52-83) 97 (83-99)





Fisher’s exact test In some encounters, students did not mention any diagnosis to the patient, explaining the different denominators c Determined during a post-encounter stimulated recall b

Case difficulty, as defined by the correctness of the final diagnosis, varied among students: the easiest were abdominal distension (92% correctness) and chronic diarrhea (77%) cases while the most difficult situations were the headache (59%) and weight loss (33%) cases. We found the same pattern of difficulty among gold-standard experts. For the more difficult cases, univariate analyses of variance showed that students in the intervention group performed better than those in the control group on the following variables: earlier exploration of the correct diagnosis during the encounter (case headache: after 6 questions vs after 42 questions, p=0.05), use of a diagnostic hypothesis to frame information collection from the patient (case headache: for 68% of the questions vs for 50%, p=0.03), and the relevance of the differential diagnosis in the chart (case weight loss: relevance score 0.56 vs 0.83, p=0.04). Multivariate analyses of variance demonstrated that the relevance score of the differential diagnosis was significantly affected by case difficulty and training condition (Table 4). There was an interaction effect between case difficulty and training condition (intervention or control) for the early exploration of the correct diagnosis (p=.01) and for the relevance score of treatment decisions (p=.04).

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Table 3: Secondary outcomes: characteristics of information items collected and diagnostic hypotheses evaluated

Encounters Encounter duration (min) Information items collected, N Summary occurrences, N Relevance scoreb of information items collected Diagnostic hypotheses evaluatedc, N Relevance scoreb of diagnostic hypotheses evaluated Information items collected until correct diagnosis first generated, N Body systems explored, N Charts Diagnoses mentioned, N Relevance scoreb of the differential diagnosis Relevance scoreb of the tests ordered Relevance scoreb of triage decisions Relevance scoreb of treatment decisions

Control group N = 28 Mean SD

Intervention group N = 30 Mean SD


15.45 60.39 2.68 .46 14.18 .44

2.52 10.46 1.74 .05 4.36 .08

15.86 58.30 1.73 .45 15.47 .40

2.03 11.72 1.44 .06 4.34 .08

.50 .48 .03 .58 .27 .10











2.79 .65 .46 .50 .15

1.57 .27 .27 .51 .29

2.37 .76 .50 .63 .33

1.07 .22 .22 .49 .36

.24 .09 .50 .31 .16


Student’s t-tests. If Bonferroni correction for multiple comparisons is applied, the significance threshold becomes .004. Relevance scores (0 to 1) of information items collected, diagnostic hypotheses generated, and management decisions made are issued from their frequency of use by experts previously solving the same cases. c Determined during the post-encounter stimulated recall. b

Table 4: Relevance score (from 0 to 1) of the differential diagnosis in the chart according to training condition and cases Case

Abdominal distension Diarrhea Weight loss Headache All casesa

Control group N = 28 Mean SD .61 .23 .62 .30 .56 .32 .80 .17 .65 .27

Intervention group N = 30 Mean SD .52 .28 .74 .21 .83 .17 .90 .11 .76 .22


Model with relevance score of differential diagnosis as a dependent variable and case difficulty, training condition, and their interaction as factors (F=2.23, p=.047, R2=.24)

Discussion The essence of our intervention was to bring students an explicit insight into their ongoing processes of clinical reasoning during case-based seminars and to encourage reflection at each step of the teaching approach described in Figures 1 and 2. This did not significantly affect their global diagnostic or decisional competencies but helped them increase the relevance of their differential diagnosis written in the post-encounter charts. The analysis of the variables collected during the stimulated recall showed no differences between students at the time of the encounter. This reinforces the finding that this training did not improve the students’ abilities to test more relevant hypotheses

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during the encounter by collecting more relevant information. It did, however, help them select the most relevant ones after the encounter, at the time they integrated the information gathered during the SP encounter and wrote their differential diagnosis in the charts. Students did not necessarily select the correct hypothesis as their final diagnosis, which is not surprising at their stage of training and gives credence to existing assumptions that, while the selection of the relevant diagnoses is dependent on the reasoning process, diagnostic accuracy requires further clinical experience, exposure to clinical cases, as well as the integration of some elements of the clinical decision-making process1,18,19. The analyses by case showed that the students in the intervention group performed significantly better than the control group in the more difficult weight loss and headache cases. As the diagnoses related to these complaints (respectively hyperthyroidism and giant cell arteritis) are more often represented in an ambulatory setting and less frequently encountered during our clerkship on the wards than the other cases used for this study, our intervention may particularly prove useful with more difficult cases. There is a rational explanation to this observation. When students already have an experience with certain cases, a non-analytical, more intuitive approach may first take place2, thus making a teaching approach using analytical steps less likely to influence the outcomes. On the other hand, such an intervention turned out more influential with harder, ill-defined cases requiring a more elaborate analytical process. Explicit reflective learning and the metacognition of learning processes is a model issued from cognitive psychology that emerged in medical education during the 1980s. Lately, this notion has emerged as a potentially important tool for expertise acquisition20-22. Its application in clinical teaching aims mainly at making doctors more aware of their underlying reasoning processes, with the hope that this may minimize errors. In a recent study, Mamede23 showed that reflective practice had a positive effect on residents’ diagnosis of complex, unusual cases. This may also explain why our intervention seemed more efficacious with more difficult cases. However, methods to enhance reflective practice among medical students have still to be further explored and validated in medical education24. The introduction of problem-based learning25 has been a way to put this learning-oriented teaching model into practice at curricular or course levels. The use of portfolios is another attempt to enhance students’ self-reflection and is under current investigation for learning and assessment26,27. Reflective physical examination and reasoning represents a potential way of enhancing clinical competence28,29 but the real impact on learning outcomes is still open for further research. Contextual metacognition has been reported in a study in emergency medicine showing that experienced residents were sensitive to metacognitive approaches to understand errors30. In a study aiming at teaching communication and reasoning skills through an iterative reflective process, students performed better in integrating aspects of communication into their reasoning31. Our study adds an additional piece of evidence suggesting that the introduction of a contextual reflective approach leading to the metacognition of clinical reasoning processes related to specific problems may influence some aspects of clinical competence. Students in the control group summarized more often the available information during the encounters than the students in the intervention group. Summarizing the data collected from the patient is a frequent step of the regular case-based seminars. This occurs generally between natural steps of the seminar, when the group moves from history to physical examination and from physical findings to ancillary tests. There is also a frequent final summary at the end of the session. Each seminar provides thus two to three natural summary opportunities, which corresponds to the mean number of occurrences found in this study for the control group (2.68). The instructions given to the tutors of the intervention group included 'summarizing' as an explicit way to

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increase problem representation but was not directly related to a specific step of the seminar. The observed difference in the number of summarization occurrences in each group might, therefore, not convey exactly the same meaning. Summarizing was probably the reflection of the natural steps in the regular seminar (2-3 natural steps), while it represented a way to apply cognitive principles in the intervention group. Additionally, as the tutor had many tasks to manage at the same time, he might have focused on other aspects than systematically summarizing information at each step of the seminar.

Limitations This study presents some limitations that may have hampered the impact of the intervention. First, the usual baseline performance of our students at the end-of-clerkship Objective Structured Clinical Exams (OSCEs) turns out relatively high (mean class scores ranging from 79 to 80% from 2005 to 2007). This suggests that the baseline training program already confers a certain degree of clinical proficiency, which potentially let little room for a dramatic change resulting from our intervention. Second, our students are issued from a problem-based learning (PBL) system involving the clinical years, which may already nurture their ability to analyze content and process in group sessions. An earlier intervention during the curriculum would perhaps have brought greater effect sizes, at the time of transition from the preclinical to the clinical years. Third, as recently suggested by Mamede23, reflective practice may take its full effect only with more difficult clinical scenarios. Some of our cases were potentially not difficult enough, limiting the effect of our intervention, which is supported by our analysis showing a more important effect of our intervention on more difficult cases. This finding may also be explained by the fact that a non-analytical, more intuitive approach could take place with easier cases, thus preventing an analytical teaching approach to show a major effect on the outcomes. As we have not looked for data on students who declined participation to the study, one cannot exclude a possible volunteer bias. However, if this bias would possibly have affected the type of students included in the study, it is unlikely that it could influence the differences observed between control and intervention groups. Given the limited size of the student sample in this study, one cannot exclude a lack of power to detect other significant effects of the training. In addition, at the time of this study we had no available data on tutor effectiveness, thus raising the possibility that the difference in student outcomes were due to more effective teachers in the intervention groups. However, as the tutors involved in this study were part of a pool of faculty members who had already experienced case-based reasoning seminars for several years and as their yearly tutoring schedule had been established independently from the present study, there is a limited likelihood that tutor effectiveness alone could explain our results. Moreover, the tutors specifically trained for the intervention group may nevertheless have applied the teaching recommendations with variable intensity, which could have lessened the impact of this approach. This limitation, however, gives even more credence to the effect found in this study.

Conclusion In this study, increasing students’ insight into the cognitive aspects of their reasoning processes and characteristics seems to improve the relevance of the working diagnostic hypotheses selected after the encounter at the time of case synthesis in the chart. To our knowledge, few studies, if any, have been able to capture the impact of an intervention grounded in cognitive psychology © MR Nendaz, AM Gut, M Louis-Simonet, A Perrier, NV Vu, 2011. A licence to publish this material has been given to Education for Health: 10

and applied in a real setting on specific components of clinical reasoning. Further research should try to better understand the reasoning process taking place at the time of patient chart writing. Moreover, our results may have important clinical implication, since the quality of the differential diagnosis may influence the subsequent diagnostic work-up of the patient and the tests chosen to confirm or disprove the diagnostic hypotheses. Whether this ability would impact the diagnostic work-up of the patients, and bring better diagnostic accuracy and better management decisions with more complex cases, is open to further research.

Acknowledgements The authors acknowledge the participation of students and tutors in this study. The study was funded by the Swiss National Science Foundation (3200B0-102265), the Elie Safra foundation, Geneva University, the Department of Internal Medicine, University Hospitals, Geneva and the Gabriella Giorgi-Cavaglieri foundation, Geneva, Switzerland.

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