Biomedical subjects

Nu V Vu

Publications and source records attributed to Nu V Vu.

8 recordsLinked to original sources

PubMed2006

Tutor training, evaluation criteria and teaching environment influence students' ratings of tutor feedback in problem-based learning.

AIM: In a problem-based learning (PBL) curriculum, tutor's feedback skills are important. However, evaluation studies often show that students rate many tutors as ineffective in providing feedback. We explored whether this is related: (a) to tutors' skills, and hence a teaching intervention might improve their performance; (b) to the formulation of the evaluation item, hence a more specific wording might help students better recognize a feedback when received; (c) to PBL teaching environment, and hence the tutors' teaching unit might influence students' ratings. METHODS: Students rated 126 tutors of 13 one-month teaching units over three consecutive years on their ability of providing feedback. We assessed how (a) a teaching intervention given between years 1 and 2, (b) a rewording of the evaluation item which took place in year 3, and (c) the tutors' teaching unit, influenced students' ratings. RESULTS: The ratings of tutors considered as effective by students at year 1 improved after the teaching intervention, while those of unsatisfactory tutors did not progress. However the ratings of the latter increased after reformulation of the evaluation item. This increase varied across teaching units. DISCUSSION: Students' ratings of tutors' ability to give feedback seem to vary in function of the tutors' training, of the formulation of the evaluation item, and of the tutors' teaching environment. These variables should be considered for setting up effective strategies in faculty development.

Analysis of Variance↗

PubMed2006

Effect of teaching context and tutor workshop on tutorial skills.

Effective faculty development workshops are essential to develop and sustain the quality of faculty's teaching. In an integrated problem-based curriculum, tutors expressed the needs to further develop their skills in facilitating students' content learning and small-group functioning. Based on the authors' prior observations that tutors' performance depends on their teaching context, a workshop was designed not only tailored to the tutors' needs but also organized within their respective teaching unit. The purposes of this study are (1) to evaluate whether this workshop is effective and improves tutors' teaching skills, and (2) to assess whether workshop effectiveness depends on tutors' performance before the workshop and on their teaching unit environment. Workshop effectiveness was assessed using (a) tutors' perception of workshop usefulness and of their improvement in tutorial skills, and (b) students' ratings of tutor performance before and after the workshop. In addition, an analysis of variance model was designed to analyse how tutors' performance before the workshop and their teaching unit influence workshop effectiveness. Tutors judged the workshop as helpful in providing them with new teaching strategies and reported having improved their tutorial skills. Workshop attendance enhanced students' ratings of tutors' knowledge of problem content and ability to guide their learning. This improvement was also long-lasting. The workshop effect on tutor performance was relative: it varied across teaching units and was higher for tutors with low scores before the workshop. A workshop tailored to tutors' needs and adapted to their teaching unit improves their tutorial skills. Its effectiveness is, however, influenced by tutors' level of performance before the workshop and by the environment of their teaching unit. Thus, to be efficient, the design of a workshop should consider not only individual tutors' needs, but also the background of their teaching units, with special attention to their internal organization and tutor group functioning.

Analysis of Variance↗

PubMed2006

Live or computerized simulation of clinical encounters: do clinicians work up patient cases differently?

Computer simulation of clinical encounters is increasingly used in clinical settings to train patient work-up. The aim of this prospective, controlled study was to compare the characteristics of data collection and diagnostic exploration of physicians working up cases with a standardized patient and in a computerized simulation. Six clinicians of different clinical experience in internal medicine worked up three cases with a standardized patient and through a computer simulation allowing free inquiry. After each encounter, we asked the subjects to justify the information collected and to comment on their working diagnoses. The characteristics of data collected and working diagnoses generated were assessed and compared, according to the simulation method used. In the computer simulation, physicians limited their data collection and focused earlier and more specifically on information and working diagnoses with high levels of relevance. They reached a similar diagnostic accuracy and made decisions of a similar relevance. Computer simulation with a free-inquiry approach reproduces the data collection and the diagnostic exploration observed in a standardized-patient simulation and promotes an early collection of relevant data. Its contribution to extend the competence of learners in clinical settings should be further evaluated.

Clinical Competence↗

PubMed2006

Brief report: beyond clinical experience: features of data collection and interpretation that contribute to diagnostic accuracy.

BACKGROUND: Clinical experience, features of data collection process, or both, affect diagnostic accuracy, but their respective role is unclear. OBJECTIVE, DESIGN: Prospective, observational study, to determine the respective contribution of clinical experience and data collection features to diagnostic accuracy. METHODS: Six Internists, 6 second year internal medicine residents, and 6 senior medical students worked up the same 7 cases with a standardized patient. Each encounter was audiotaped and immediately assessed by the subjects who indicated the reasons underlying their data collection. We analyzed the encounters according to diagnostic accuracy, information collected, organ systems explored, diagnoses evaluated, and final decisions made, and we determined predictors of diagnostic accuracy by logistic regression models. RESULTS: Several features significantly predicted diagnostic accuracy after correction for clinical experience: early exploration of correct diagnosis (odds ratio [OR] 24.35) or of relevant diagnostic hypotheses (OR 2.22) to frame clinical data collection, larger number of diagnostic hypotheses evaluated (OR 1.08), and collection of relevant clinical data (OR 1.19). CONCLUSION: Some features of data collection and interpretation are related to diagnostic accuracy beyond clinical experience and should be explicitly included in clinical training and modeled by clinical teachers. Thoroughness in data collection should not be considered a privileged way to diagnostic success.

Clinical Competence↗

PubMed2005

Common strategies in clinical data collection displayed by experienced clinician-teachers in internal medicine.

The role model displayed by clinician-teachers influences learning experiences but learners may face various reasoning styles. Our goal was to describe common strategies in clinical data collection displayed by experienced clinician-teachers in internal medicine. We studied six internists heavily involved in teaching while they were working up the same seven cases portrayed by a standardized patient. Each encounter was audio-recorded and replayed to allow the subjects commenting on the purpose and diagnostic hypotheses considered for each piece of information collected. Information and hypotheses elicited by all physicians were considered key items. Although the subjects reached the same final diagnoses, they differed on several characteristics of their data collection process. They also displayed common behaviours, such as: early acquisition of key data (half of them acquired within the first 19 questions asked) through clarification of the patients' complaints and focused data collection; early generation of the final diagnosis (within the first 10 questions asked) and use of diagnostic hypotheses to frame data collection; and summarization of the information at hand during the encounter (at least twice). Whether making teachers explicitly conscious about their own reasoning processes may help them better model and explain their diagnostic approach to specific cases should be assessed in follow-up studies.

Adolescent↗

PubMed2005

Effects of item and rater characteristics on checklist recording: what should we look for?

OBJECTIVE: Examinations based on using standardised patients (SPs) commonly use checklist recordings to evaluate students' clinical performance. This paper examines whether and to what extent item and rater characteristics affect the reliability of history checklist recording in an SP-based assessment. METHODS: Checklist items were reviewed for the presence or absence of 5 item characteristics and a 2-point versus 3-point scoring scale. Agreement between checklist recordings obtained from SPs and clinician-examiners (CEs) were compared by item characteristics, scoring scale and CEs' level of involvement in the assessment. RESULTS: Based on 3179 pairs of recordings, the overall percentage of agreement between SPs and CEs was 83% (kappa = 0.64). Agreement was significantly higher for items scored on a 2-point than on a 3-point scale, and when the CE was also the author and the trainer of the station. After controlling for other factors, item characteristics were only marginally associated with level of interrater agreement. CONCLUSIONS: This study suggests that attention should be paid to specific aspects of checklist development and checklist recording training when an SP or CE is used as recorder.

Clinical Competence↗

PubMed2004

Degree of concurrency among experts in data collection and diagnostic hypothesis generation during clinical encounters.

BACKGROUND: Given that there are variations in clinicians' reasoning, methods to elaborate scoring checklists for standardised patient-based assessment need to be valid. The use of data elicited by experts solving problems independently has been advocated as a method of setting performance standards. AIMS: To determine the degree of concurrence and common characteristics among items independently elicited by doctors during patient encounters and to assess the number of experts needed to derive reliable performance standards. METHODS: Six experienced internists worked-up the same 7 chief complaints with standardised patients (SPs). A stimulated recall of the recorded encounter was then performed. The degree of concurrence of the collected history and physical examination information and the generated diagnostic hypotheses was computed. Reliability was derived from generalisability analyses. RESULTS: By case, experts elicited a mean of 114 information items (SD = 15) and generated 30 diagnostic hypotheses (SD = 6). A high concurrence (80-100%) was observed for a mean of 22 information items (20%; SD = 6) and 7 diagnostic hypotheses (24%; SD = 2). More than a third of the 153 highly concurrent information items were clarification questions. At least 3 doctors were needed to obtain a reliability of 0.80 or higher when deriving the scoring checklists. CONCLUSION: The limited concurrency in data elicited by clinicians during a patient encounter supports the use of high-fidelity methods to develop performance checklists used in SP-based assessment. It also suggests that relying only on information collected to assess clinical competence may not be sufficient. Additional criteria, such as structure and style of work-up, should be further explored.

Clinical Competence↗

PubMed2003

Development of clinical reasoning from the basic sciences to the clerkships: a longitudinal assessment of medical students' needs and self-perception after a transitional learning unit.

BACKGROUND: To facilitate students' transition from basic, science-oriented, problem-based learning (PBL) to clinical reasoning-oriented PBL, the University of Geneva School of Medicine introduced a 12-week unit of Introduction to Clinical Reasoning (ICR) at the beginning of its fourth or clerkship year. PURPOSE: The aims of the present study were to determine, after 12 weeks in the ICR unit, to what extent students had: (1) identified the learning content set by the faculty while adapting to the hypothetico-deductive reasoning approach; (2) familiarised themselves with the clinical reasoning-oriented learning process, and (3) transferred and further developed this process during the clinical years. METHOD: Students' derived objectives from the problems were compared to the objectives preset by the faculty to determine acquisition of intended learning content. To assess their adaptation to the clinical reasoning-oriented PBL approach, students (n = 124) were asked to list and freely comment on aspects of the unit they felt most at ease with or had difficulty with, and to complete a questionnaire on the clinical reasoning process (CRP). The same questionnaire was administered 6 and 12 months later to assess the evolution of the students' self-perception during clerkships. RESULTS: On average, student objectives matched 62% of faculty objectives. Half of the missed (38%) objectives were in basic sciences. Students generated 16% additional objectives, also predominantly in the basic sciences category (41%). Free comments indicated that the difficulties perceived by students were very similar to those previously reported in studies on reasoning and errors, such as difficulty in gathering, interpreting and weighting relevant data, synthesising information, and organising it hierarchically. These results were confirmed with the CRP questionnaire administered at the end of the unit. For most of the competencies assessed on the CRP questionnaire, a gradual improvement was seen to have occurred by 6 and 12 months after the unit. CONCLUSIONS: To ease students' transition from the preclinical to clinical years, a learning unit should give them the opportunity to train their clinical reasoning processes on standardised and prototypical problems, before encountering real patients with more ill-structured problems during clerkships. Such a transitional structure should particularly emphasise a developed repertoire of problem representations, recognition of key findings and a hierarchical classification of working hypotheses. It should foster the creation of links between the acquired basic clinical knowledge and the diagnostic, management and therapy steps of problem solving.

Clinical Clerkship↗