Failure to demonstrate effects of interruptions on diagnostic reasoning: three experiments.

BACKGROUND: Diagnostic error is a major source of patient suffering. Researchshows that physicians experience frequent interruptions while being engaged with patients and indicate that diagnostic accuracy may be impaired as a result. Since most studies in the field are observational, there is as yet no evidence suggesting a direct causal link between being interrupted and diagnostic error. Theexperiments reported in this article were intended to assess this hypothesis. METHODS: Three experiments were conducted to test the hypothesis that interruptions hurt diagnostic reasoning and increase time on task. In the first experiment (N = 42), internal medicine residents, while diagnosing vignettes of actual clinical cases were interrupted halfway with a task unrelated to medicine, solving word-spotting puzzles and anagrams. In the second experiment (N = 78), the interruptions were medically relevant ones. In the third experiment (N = 30), we put additional time pressure on the participants. In all these experiments, a control group diagnosed the cases without interruption. Dependent variables were diagnostic accuracy and amount of time spent on the vignettes. RESULTS: In none of the experiments interruptions were demonstrated to influence diagnostic accuracy. In Experiment 1: Mean of interrupted group was 0.88 (SD = 0.37) versus non- interrupted group 0.91 (SD = 0.32). In Experiment 2: Mean of interrupted group was 0.95 (SD = 0.32) versus non-interrupted group 0.94 (SD = 0.38). In Experiment 3: Mean of interrupted group was 0.42 (SD = 0.12) versus non-interrupted group 0.37 (SD = 0.08). Although interrupted residents in all experiments needed more time to complete the diagnostic task, only in Experiment 2, this effect was statistically significant. CONCLUSIONS: These three experiments, taken together, failed to demonstrate negative effects of interruptions on diagnostic reasoning. Perhaps physicians who are interrupted may still have sufficient cognitive resources available to recover from it most of the time.

Effective Learning in Virtual Conferences: The Application of Five Principles of Learning.

In this article, we examine the adaptation of learning among scientists and healthcare professionals in conferences and symposia from face-to-face to fully virtual meetings accelerated in the last years. Advantages and limitations for both settings have been described in different research studies but the effectiveness of learning can be reflected similarly by applying five fundamental principles of learning, which are based on empirical research in cognitive psychology. From a practical context, we compared the individual learning outcomes from two satellite symposia conducted face-to-face in 2019 and virtually in 2021 at the European Congress of Urology, EAU. Although both conference formats were almost identical, the five principles of learning were applied in both symposia. There were also some differences due to adaptation to online conferences, and our findings suggest that the virtual conference was perceived as significantly more effective than the face-to-face conference on all five criteria, and digital learning is a valid alternative to face-to-face conferences. What still needs to be better understood and analysed is the informal learning that is taking place during conferences, but suggesting an active design of any digital event by combining "technical literacy· with "learning literacy" will enable us to better analyse and study the impact of learning using the five learning principles in the design of other events in the future.

Learning to diagnose X-rays: a neuroscientific study of practice-related activation changes in the prefrontal cortex.

OBJECTIVES: Medical expertise manifests itself by the ability of a physician to rapidly diagnose patients. How this expertise develops from a neural-activation perspective is not well understood. The objective of the present study was to investigate practice-related activation changes in the prefrontal cortex (PFC) as medical students learn to diagnose chest X-rays. METHODS: The experimental paradigm consisted of a learning and a test phase. During the learning phase, 26 medical students were trained to diagnose four out of eight chest X-rays. These four cases were presented repeatedly and corrective feedback was provided. During the test phase, all eight cases were presented together with near- and far-transfer cases to examine whether participants' diagnostic learning went beyond simple rote recognition of the trained X-rays. During both phases, participants' PFC was scanned using functional near-infrared spectroscopy. Response time and diagnostic accuracy were recorded as behavioural indicators. One-way repeated measures ANOVA were conducted to analyse the data. RESULTS: Results revealed that participants' diagnostic accuracy significantly increased during the learning phase (F=6.72, p<0.01), whereas their response time significantly decreased (F=16.69, p<0.001). Learning to diagnose chest X-rays was associated with a significant decrease in PFC activity (F=33.21, p<0.001) in the left dorsolateral prefrontal cortex, the orbitofrontal area, the frontopolar area and the frontal eye field. Further, the results of the test phase indicated that participants' diagnostic accuracy was significantly higher for the four trained cases, second highest for the near-transfer, third highest for the far-transfer cases and lowest for the untrained cases (F=167.20, p<0.001) and response time was lowest for the trained cases, second lowest for the near-transfer, third lowest for the far-transfer cases and highest for the untrained cases (F=9.72, p<0.001). In addition, PFC activity was lowest for the trained and near-transfer cases, followed by the far-transfer cases and highest for the untrained cases (F=282.38, p<0.001). CONCLUSIONS: The results suggest that learning to diagnose X-rays is associated with a significant decrease in PFC activity. In terms of dual-process theory, these findings support the notion that students initially rely more on slow analytical system-2 reasoning. As expertise develops, system-2 reasoning transitions into faster and automatic system-1 reasoning.

Virtual Clinical Encounter Examination (VICEE): A novel approach for assessing medical students' non-psychomotor clinical competency.

INTRODUCTION: The Corona Virus Disease-19 (COVID-19) pandemic disrupted medical education across the world. Online teaching has grown rapidly under lockdown. Yet the online approach for assessment presents a number of challenges, particularly when evaluating clinical competencies. The aim of this study was to investigate the feasibility, acceptability, reliability and validity of an online Virtual Clinical Encounter Examination (VICEE) to assess non-psychomotor competencies (non-procedure or manual skills) of medical students. METHOD: Sixty-one final year medical students took the VICEE as part of the final summative examination. A panel of faculty experts developed the exam cases and competencies. They administered the test online via real-time interaction with artificial intelligence (AI) based virtual patients, along with faculty and IT support. RESULTS: Student and faculty surveys demonstrated satisfaction with the experience. Confirmatory factor analysis supported convergent validity of VICEE with Direct Observation Clinical Encounter Examination (DOCEE), a previously validated clinical examination. The observed sensitivity was 81.8%, specificity 64.1% and likelihood ratio 12.6, supporting the ability of VICEE to diagnose 'clinical incompetence' among students. CONCLUSION: Our results suggest that online AI-based virtual patient high fidelity simulation may be used as an alternative tool to assess some aspects of non-psychometric competencies.

Dyadic explanations during preparatory self-study enhance learning: A randomised controlled study.

OBJECTIVES: The objective of the present study was to investigate to which extent preparatory self-study can be improved by encouraging students to engage in individual self-explanations or dyadic explanations (ie in pairs). Individual self-explanations refer to an act of metacognition in which students, after having processed a certain amount of information, attempt to explain their understanding to themselves of what was just learned. Dyadic explanations refer to the same process, but instead of explaining to oneself, the student explains his/her understanding to another student. METHOD: An experiment was conducted in which 120 medical students studied a video-recorded lecture on the role of protein synthesis inhibition on memory reconsolidation. Participants were randomly allocated to one of four conditions: (1) a control condition in which they listened to the lecture once; (2) a control condition in which they listened to the lecture twice; (3) an experimental condition in which they had to listen to the lecture and provide self-explanations individually; and (4) an experimental condition in which they had to listen to the lecture and provide dyadic explanations. Participants' knowledge regarding the topic was measured three times: at the start and end of the experiment, and one week after the experiment to determine knowledge retention. Data were analysed by means of a 2 × 2 and 4 × 3 repeated-measures ANOVA. RESULTS: The results suggest that participants who engaged in individual self- or dyadic explanations significantly outperformed participants in the two control conditions in terms of learning and retention (F = 5.67, Wilks Λ = 0.94, P = .019, η2  = 0.05). Moreover, the results suggest that dyadic explanations were more effective than individual self-explanations (F = 3.70, Wilks Λ = 0.83, P = .002, η2  = 0.09). CONCLUSIONS: These outcomes suggest that encouraging students to work in pairs or in small teams to prepare for a learning event results in superior preparation and learning.

Promotion of knowledge transfer and retention in year 2 medical students using an online training exercise.

It was recently shown that novice medical students could be trained to demonstrate the speed-to-diagnosis and diagnostic accuracy typical of System-1-type reasoning. However, the effectiveness of this training can only be fully evaluated when considering the extent to which knowledge transfer and long-term retention occur as a result, the former of which is known to be notoriously difficult to achieve. This study aimed to investigate whether knowledge learned during an online training exercise for chest X-ray diagnosis promoted either knowledge transfer or retention, or both. Second year medical students were presented with, and trained to recognise the features of four chest X-ray conditions. Subsequently, they were shown the four trained-for cases again as well as different representations of the same conditions varying in the number of common elements and asked to provide a diagnosis, to test for near-transfer (four cases) and far-transfer (four cases) of knowledge. They were also shown four completely new conditions to diagnose. Two weeks later they were asked to diagnose the 16 aforementioned cases again to assess for knowledge retention. Dependent variables were diagnostic accuracy and time-to-diagnosis. Thirty-six students volunteered. Trained-for cases were diagnosed most accurately and with most speed (mean score = 3.75/4, mean time = 4.95 s). When assessing knowledge transfer, participants were able to diagnose near-transfer cases more accurately (mean score = 2.08/4, mean time = 15.77 s) than far-transfer cases (mean score = 1.31/4, mean time = 18.80 s), which showed similar results to those conditions previously unseen (mean score = 0.72/4, mean time = 19.46 s). Retention tests showed a similar pattern but accuracy scores were lower overall. This study demonstrates that it is possible to successfully promote knowledge transfer and retention in Year 2 medical students, using an online training exercise involving diagnosis of chest X-rays, and is one of the few studies to provide evidence of actual knowledge transfer.

Team-Based Learning Analytics: An Empirical Case Study.

Many medical schools that have implemented team-based learning (TBL) have also incorporated an electronic learning architecture, commonly referred to as a learning management system (LMS), to support the instructional process. However, one LMS feature that is often overlooked is the LMS's ability to record data that can be used for further analysis. In this article, the authors present a case study illustrating how one medical school used data that are routinely collected via the school's LMS to make informed decisions. The case study started with one instructor's observation that some teams in one of the undergraduate medical education learning modules appeared to be struggling during one of the team activities; that is, some teams seemed unable to explain or justify their responses to items on the team readiness assurance test (tRAT). Following this observation, the authors conducted 4 analyses. Their analyses demonstrate how LMS-generated and recorded data can be used in a systematic manner to investigate issues in the real educational environment. The first analysis identified a team that performed significantly poorer on the tRAT. A subsequent analysis investigated whether the weaker team's poorer performance was consistent over a whole module. Findings revealed that the weaker team performed poorer on the majority of the TBL sessions. Further investigation using LMS data showed that the weaker performance was due to the lack of preparation of one individual team member (rather than a collective poor tRAT performance). Using the findings obtained from this case study, the authors hope to convey how LMS data are powerful and may form the basis of evidence-based educational decision making.

Summative and Formative Style Anatomy Practical Examinations: Do They Have Impact on Students' Performance and Drive for Learning?

Anatomical knowledge is commonly assessed by practical examinations that are often administered in summative format. The format of anatomy practical examination was changed at the Lee Kong Chian School of Medicine in Singapore from summative (graded; must pass) to formative (ungraded; no pass/fail) in academic year (AY) 2017-2018. Both assessment formats were undertaken online, but the formative mode used a team-based learning activity comprising individual and team assessments. This gave an unique opportunity to investigate: (1) the impact of two different online assessment formats on student performance in practical examination; (2) the impact of new formative practical examination on students' performance in summative examinations; and (3) students' opinions of these two practical examination formats. The class of 2021 perceptions was obtained as they experienced both formats. A retrospective cohort study was also conducted to analyze the Year 2 students' performance in anatomy practical and year-end summative examinations of cohorts AY 2015-2016, AY 2016-2017 (summative format), and AY 2017-2018 (formative format). There were no significant differences in students' performance between two practical examination formats. The cohort who experienced the formative format, performed significantly better in summative examinations (mean ± SD: 82.32 ± 10.22%) compared with the cohort who experienced the summative format (73.77 ± 11.09%) (P < 0.001). Students highlighted positive features of the formative practical examination, including team reinforcement of learning, instant feedback, and enhanced learning. These findings indicate that students continue to study for anatomy practical examination without the need for external drivers. The team-based learning style practical examination enhances students' performance in summative examinations.

A Psychological Foundation for Team-Based Learning: Knowledge Reconsolidation.

Although team-based learning is a popular instructional approach, little is known about its psychological foundation. In this Perspective, the authors propose a theoretical account of the psychological mechanisms through which team-based learning works. They suggest a knowledge reconsolidation hypothesis to explain how the distinct phases of team-based learning enable students to learn. Knowledge reconsolidation is the process whereby previously consolidated knowledge is retrieved from memory with the purpose of actively consolidating it again. Reconsolidation aims to preserve, strengthen, and adjust knowledge that is already stored in long-term memory. This process is generally considered an important reason why people who reactivate what they have previously learned many times develop knowledge structures that are extremely stable and easily retrieved.The authors propose that 4 psychological mechanisms enable knowledge reconsolidation, each of which is tied to a distinct phase of team-based learning: retrieval practice, peer elaboration, feedback, and transfer of learning. Before a team-based learning session, students engage in independent, self-directed learning that is often followed by at least one night of sleep. The latter is known to facilitate synaptic consolidation in the brain. During the actual team-based learning session, students are first tested individually on what they learned, then they discuss the answers to the test with a small group of peers, ask remaining "burning questions" to the teacher, and finally engage in a number of application exercises.This knowledge reconsolidation hypothesis may be considered a framework to guide future research into how team-based learning works and its outcomes.

Digital Problem-Based Learning in Health Professions: Systematic Review and Meta-Analysis by the Digital Health Education Collaboration.

BACKGROUND: The use of digital education in problem-based learning, or digital problem-based learning (DPBL), is increasingly employed in health professions education. DPBL includes purely digitally delivered as well as blended problem-based learning, wherein digital and face-to-face learning are combined. OBJECTIVE: The aim of this review is to evaluate the effectiveness of DPBL in improving health professionals' knowledge, skills, attitudes, and satisfaction. METHODS: We used the gold-standard Cochrane methods to conduct a systematic review of randomized controlled trials (RCTs). We included studies that compared the effectiveness of DPBL with traditional learning methods or other forms of digital education in improving health professionals' knowledge, skills, attitudes, and satisfaction. Two authors independently screened studies, extracted data, and assessed the risk of bias. We contacted study authors for additional information, if necessary. We used the random-effects model in the meta-analyses. RESULTS: Nine RCTs involving 890 preregistration health professionals were included. Digital technology was mostly employed for presentation of problems. In three studies, PBL was delivered fully online. Digital technology modalities spanned online learning, offline learning, virtual reality, and virtual patients. The control groups consisted of traditional PBL and traditional learning. The pooled analysis of seven studies comparing the effect of DPBL and traditional PBL reported little or no difference in postintervention knowledge outcomes (standardized mean difference [SMD] 0.19, 95% CI 0.00-0.38). The pooled analysis of three studies comparing the effect of DPBL to traditional learning on postintervention knowledge outcomes favored DPBL (SMD 0.67, 95% CI 0.14-1.19). For skill development, the pooled analysis of two studies comparing DPBL to traditional PBL favored DPBL (SMD 0.30, 95% CI 0.07-0.54). Findings on attitudes and satisfaction outcomes were mixed. The included studies mostly had an unclear risk of bias. CONCLUSIONS: Our findings suggest that DPBL is as effective as traditional PBL and more effective than traditional learning in improving knowledge. DPBL may be more effective than traditional learning or traditional PBL in improving skills. Further studies should evaluate the use of digital technology for the delivery of other PBL components as well as PBL overall.

Effects of graded versus ungraded individual readiness assurance scores in team-based learning: a quasi-experimental study.

Pre-class preparation is a crucial component of team-based learning (TBL). Lack of preparation hinders both individual learning and team performance during TBL. The purpose of the present study was to explore how the grading of the individual readiness assurance test (iRAT) can affect pre-class preparation, iRAT performance and performance in the end-of-year examination. Using a quasi-experimental design, Year 1 and 2 students' download frequency for their pre-class materials, performance on iRAT and examination were examined under two conditions; (1) under which the iRAT was graded and (2) under which the iRAT was ungraded. Medical students (N = 220) from three cohorts were included in the study. Differences between both conditions were tested by means of six separate ANCOVAs, using medical school entry test scores as the covariate to account for potential cohort effects. Results revealed that students were downloading more pre-class materials prior to their TBL sessions, and were performed significantly better on iRAT when their performance was graded, even after controlling for cohort effects. Analysis of covariance demonstrated that performance on iRAT also appeared to affect performance on their examination scores. The results of the study suggest that grading has a positive effect on students' iRAT scores. Implications for TBL are discussed.

Evidence supporting dual-process theory of medical diagnosis: a functional near-infrared spectroscopy study.

PURPOSE: The objective of this study was to determine the extent to which the dual-process theory of medical diagnosis enjoys neuroscientific support. To that end, the study explored whether neurological correlates of system-2 thinking could be located in the brain. It was hypothesised that system-2 thinking could be observed as the activation of the prefrontal cortex. METHOD: An experimental paradigm was applied that consisted of a learning and a test phase. During the learning phase, 22 medical students were trained in diagnosing chest X-rays. Four of these eight cases were presented repeatedly, to develop a high level of expertise for these cases. During the test phase, all eight cases were presented and the participants' prefrontal cortex was scanned using functional near-infrared spectroscopy. Response time and diagnostic accuracy were recorded as behavioural indicators. RESULTS: The results revealed that participants' diagnostic accuracy in the test phase was significantly higher for the trained cases as compared with the untrained cases (F[1, 21] = 138.80, p < 0.001, η2  = 0.87). Also, their response time was significantly shorter for these cases (F[1, 21] = 18.12, p < 0.001, η2  = 0.46). Finally, the results revealed that only for the untrained cases, could a significant activation of the anterolateral prefrontal cortex be observed (F[1, 21] = 21.00, p < 0.01, η2  = 0.34). CONCLUSION: The fact that only untrained cases triggered higher levels of blood oxygenation in the prefrontal cortex is an indication that system-2 thinking is a cognitive process distinct from system 1. Implications of these findings for the validity of the dual-process theory are discussed.

Factors underlying suboptimal diagnostic performance in physicians under time pressure.

CONTEXT: Time pressure has been implicated in the suboptimal diagnostic performance of doctors and in increases in diagnostic errors. However, the reasons underlying these effects are not clear. The aim of this study was to investigate the influence of time pressure on physicians' diagnostic accuracy and to explore the mediating effects of perceived stress (emotional pathway) and number of plausible diagnostic hypotheses (cognitive pathway) on the proposed relationship. METHODS: We conducted a randomised controlled experiment. A total of 75 senior internal medicine residents completed eight written clinical cases under conditions with (n = 40) or without (n = 35) time pressure. They were then asked to: (i) rate the overall stress experienced, and (ii) write down any alternative hypotheses they had thought of when diagnosing the cases. In a post hoc analysis, a mediation path analysis was performed to test the causal relationships between time pressure, perceived stress and number of alternative diagnoses. RESULTS: Participants who were under time pressure spent less time diagnosing the cases (85.54 seconds versus 181.81 seconds; p< 0.001) and had a lower mean diagnostic accuracy score (0.44 versus 0.53; p = 0.01). In addition, they reported more stress (5.80 versus 4.69; p = 0.01) and generated fewer plausible tentative hypotheses (0.37 versus 0.51; p = 0.01). Two path coefficients were found to be statistically significant; the first path coefficient referred to the relationship between time pressure and perceived stress (standardised ß = 0.25, p = 0.029), and the second negative path coefficient referred to the relationship between time pressure and number of plausible alternative hypotheses (standardised ß = -0.32, p< 0.01). CONCLUSIONS: Time pressure adversely influences physicians' diagnostic accuracy by increasing their stress response and reducing the number of plausible hypotheses as mediators.

Implementation of team-based learning on a large scale: Three factors to keep in mind.

Team-based learning (TBL) is a structured form of small group learning that can be scaled up for delivery in large classes. The principles of successful TBL implementation are well established. TBL has become widely practiced in medical schools, but its use is typically limited to certain courses or parts of courses. Implementing TBL on a large scale, across different courses and disciplines, is the next logical step. The Lee Kong Chian School of Medicine (LKCMedicine), a partnership between Nanyang Technological University, Singapore and Imperial College London, admitted its first students in 2013. This new undergraduate medical program, developed collaboratively by faculty at both institutions, uses TBL as its main learning and teaching strategy, replacing all face-to-face lectures. TBL accounts for over 60% of the curriculum in the first two years, and there is continued learning through TBL during campus teaching in the remaining years. This paper describes our experience of rolling out TBL across all years of the medical curriculum, focusing on three success factors: (1) "team-centric" learning spaces, to foster active, collaborative learning; (2) an e-learning ecosystem, seamlessly integrated to support all phases of the TBL process and (3) teaching teams in which experts in pedagogical process (TBL Facilitators) co-teach with experts in subject matter (Content Experts).

Teaching clinical reasoning through hypothetico-deduction is (slightly) better than self-explanation in tutorial groups: An experimental study.

BACKGROUND: Self-explanation while individually diagnosing clinical cases has proved to be an effective instructional approach for teaching clinical reasoning. The present study compared the effects on diagnostic performance of self-explanation in small groups with the more commonly used hypothetico-deductive approach. METHODS: Second-year students from a six-year medical school in Saudi Arabia (39 males; 49 females) worked in small groups on seven clinical vignettes (four criterion cases representing cardiovascular diseases and three 'fillers', i.e. cases of other unrelated diagnoses). The students followed different approaches to work on each case depending on the experimental condition to which they had been randomly assigned. Under the self-explanation condition, students provided a diagnosis and a suitable pathophysiological explanation for the clinical findings whereas in the hypothetico-deduction condition students hypothesized about plausible diagnoses for signs and symptoms that were presented sequentially. One week later, all students diagnosed eight vignettes, four of which represented cardiovascular diseases. A mean diagnostic accuracy score (range: 0-1) was computed for the criterion cases. One-way ANOVA with experimental condition as between-subjects factor was performed on the mean diagnostic accuracy scores. RESULTS: Students in the hypothetico-deduction condition outperformed those in the self-explanation condition (mean = 0.22, standard deviation = 0.14, mean = 0.17; standard deviation = 0.12; F(1, 88) = 4.90, p = 0.03, partial η2 = 0.06, respectively). CONCLUSIONS: Students in the hypothetico-deduction condition performed slightly better on a follow-up test involving similar cases, possibly because they were allowed to formulate more than one hypothesis per case during the learning phase.

Inducing System-1-type diagnostic reasoning in second-year medical students within 15 minutes.

Purpose: Diagnostic reasoning literature debates the significance of "dual-process theory" and the importance of its constituent types of thinking: System-1and System-2. This experimental study aimed to determine whether novice medical students could be trained to utilize System-1 thinking when making diagnoses based on chest X-rays. Method: Second-year medical students were recruited and presented with a series of eight online chest X-rays cases. Participants were shown half of the cases repeatedly during a training phase and the other half only twice. During the final test phase, they were shown all eight cases, providing a diagnosis as a free text answer. Dependent variables were diagnostic accuracy and response time. Results: Thirty-two students participated. During the test phase, students responses were significantly more accurate and faster for cases which had been seen repeatedly during the training phase (mean score = 3.56/4, mean time = 2.34 s) compared with cases which had been seen only twice (mean score = 1.59/4, mean time = 7.50 s). Conclusion: This study demonstrates that it is possible to induce in novice students the speed-to-diagnosis and diagnostic accuracy typical of System-1-type reasoning. The full experimental design and the chest X-rays used may provide new opportunities to explore some of the issues surrounding dual-process theory.

How cognitive engagement fluctuates during a team-based learning session and how it predicts academic achievement.

The objective of the paper is to report findings of two studies that attempted to find answers to the following questions: (1) What are the levels of cognitive engagement in TBL? (2) Are there differences between students who were more exposed to TBL than students who were less exposed to TBL? (3) To which extent does cognitive engagement fluctuate as a function of the different activities involved in TBL? And (4) How do cognitive engagement scores collected over time correlate with each other and with academic achievement? The studies were conducted with Year-1 and -2 medical students enrolled in a TBL curriculum (N = 175, 62 female). In both studies, six measurements of cognitive engagement were taken during the distinct TBL activities (preparation phase, individual/team readiness assurance test, burning questions, and application exercises). Data were analysed by means of one-way repeated-measures ANOVAs and path modelling. The results of the repeated-measures ANOVA revealed that cognitive engagement systematically fluctuated as a function of the distinct TBL activities. In addition, Year-1 students reported significantly higher levels of cognitive engagement compared to Year-2 students. Finally, cognitive engagement was a significant predictor of performance (ß = .35). The studies presented in this paper are a first attempt to relate the different activities undertaken in TBL with the extent to which they arouse cognitive engagement with the task at hand. Implications of these findings for TBL are discussed.

Does Time Pressure Have a Negative Effect on Diagnostic Accuracy?

PURPOSE: Studies suggest time pressure has negative effects on physicians' working conditions and may lead to suboptimal patient care and medical errors. Experimental evidence supporting this is lacking, however. This study investigated the effect of time pressure on diagnostic accuracy. METHOD: In 2013, senior internal medicine residents at three hospitals in Saudi Arabia were divided randomly into two groups: a time-pressure condition and a control condition without time pressure. Both groups diagnosed eight written clinical cases presented on computers. In the time-pressure condition, after completing each case, participants received information that they were behind schedule. Response time was recorded, and diagnostic accuracy was scored. RESULTS: The 23 participants in the time-pressure condition spent significantly less time diagnosing the cases (mean = 96.00 seconds) than the 19 control participants (mean = 151.97 seconds) (P < .001). Participants under time pressure had a significantly lower diagnostic accuracy score (mean = 0.33; 95% CI, 0.23-0.43) than participants without time pressure (mean = 0.51; 95% CI, 0.42-0.60) (F[1, 41] = 6.90, P = .012, η = 0.15). This suggests participants in the time-pressure condition made on average 37% more errors than control participants. CONCLUSIONS: Time pressure has a negative impact on diagnostic performance. The authors propose that the effect of time pressure on diagnostic accuracy is moderated by both the case difficulty level and the physician's level of experience. Post hoc analyses demonstrated that time pressure affects diagnostic accuracy only if cases are not too difficult and physicians' expertise level is intermediate.