How Is Clinical Reasoning Developed, Maintained, and Objectively Assessed? Views from Expert Internists and Internal Medicine Interns

Introduction. The clinical reasoning assessment tool (CRAT) is a patient-centered tool that was developed to assess students' progress in the development of clinical reasoning. The purpose of this qualitative study was to explore how academic and clinical faculty in a physical therapist curriculum use the CRAT to support the development and assessment of clinical reasoning in physical therapist student learners. Review of Literature. Clinical reasoning is a multifaceted process crucial to optimal patient care. The ability to teach, learn, and assess the development of clinical reasoning skills continues to be challenging due to the complexity of this necessary skill. Methods. A qualitative, thematic analysis approach was used to achieve the study objective. Qualitative data were collected from 3 focus group sessions, transcribed, and analyzed to identify, summarize, and interpret entry-level physical therapist educators' perceptions and experiences using the CRAT with physical therapist students. Results. Physical therapist educator participants (N = 13) reported using the CRAT as a guide for learning and assessment. Three qualitative themes were identified: 1) fostering understanding of clinical reasoning through organization and structure; 2) facilitating clinical reasoning through dialogue and self-reflection; and 3) assessment of clinical reasoning in the learner through benchmarking. Discussion and Conclusion. Study findings suggest that the structure and organization of the CRAT facilitated dialogue, student self-reflection, and assessment of clinical reasoning through benchmarking. The CRAT may support faculty in their work to further the learners' acquisition of clinical reasoning skills.

Clinical reasoning entails the application of knowledge and skills to collect and integrate information, typically with the goal of arriving at a diagnosis and management plan based on the patient’s unique circumstances and preferences. Evidence-informed, structured, and explicit teaching and assessment of clinical reasoning in educational programs of medical and other health professions remain unmet needs. We herein summarize recommendations for clinical reasoning learning objectives (LOs), as derived from a consensus approach among European and US researchers and health professions educators. A four-step consensus approach was followed: (1) identification of a convenience sample of the most relevant and applied national LO catalogues for health professions educational programs (N = 9) from European and US countries, (2) extraction of LOs related to clinical reasoning and translation into English, (3) mapping of LOs into predefined categories developed within the Erasmus+ Developing, implementing, and disseminating an adaptive clinical reasoning curriculum for healthcare students and educators (DID-ACT) consortium, and (4) synthesis of analysis findings into recommendations for how LOs related to clinical reasoning could be presented and incorporated in LO catalogues, upon consensus. Three distinct recommendations were formulated: (1) make clinical reasoning explicit, (2) emphasize interprofessional and collaboration aspects of clinical reasoning, and (3) include aspects of teaching and assessment of clinical reasoning. In addition, the consortium understood that implementation of bilingual catalogues with English as a common language might contribute to lower heterogeneity regarding amount, structure, and level of granularity of clinical reasoning LOs across countries. These recommendations will hopefully motivate and guide initiatives towards the implementation of LOs related to clinical reasoning in existing and future LO catalogues.

BackgroundClinical reasoning (CR) is a crucial ability that can prevent errors in patient care. Despite its important role, CR is often not taught explicitly and, even when it is taught, typically not all aspects of this ability are addressed in health professions education. Recent research has shown the need for explicit teaching of CR for both students and teachers. To further develop the teaching and learning of CR we need to improve the understanding of students' and teachers' needs regarding content as well as teaching and assessment methods for a student and trainer CR curriculum.MethodsParallel mixed-methods design that used web-surveys and semi-structured interviews to gather data from both students (nsurvey = 100; ninterviews = 13) and teachers (nsurvey = 112; ninterviews = 28). The interviews and surveys contained similar questions to allow for triangulation of the results. This study was conducted as part of the EU-funded project DID-ACT (https://did-act.eu).ResultsBoth the surveys and interview data emphasized the need for content in a clinical reasoning (CR) curriculum such as “gathering, interpreting and synthesizing patient information”, “generating differential diagnoses”, “developing a diagnostic and a treatment plan” and “collaborative and interprofessional aspects of CR”. There was high agreement that case-based learning and simulations are most useful for teaching CR. Clinical and oral examinations were favored for the assessment of CR. The preferred format for a train-the-trainer (TTT)-course was blended learning. There was also some agreement between the survey and interview participants regarding contents of a TTT-course (e.g. teaching and assessment methods for CR). The interviewees placed special importance on interprofessional aspects also for the TTT-course.ConclusionsWe found some consensus on needed content, teaching and assessment methods for a student and TTT-course in CR. Future research could investigate the effects of CR curricula on desired outcomes, such as patient care.

Traditional teaching and assessment of clinical reasoning has focused on the individual clinician because of the preeminence of the information processing (IP) theory perspective. The clinician's mind has been viewed as the main source of effective or ineffective reasoning, and other participants, the environment and their interactions have been largely ignored. A social cognitive theoretical lens could enhance our understanding of how reasoning and error and the environment are linked. Therefore, a new approach in which the clinical reasoning process is situated and examined within the context may be required. The theories of embodied cognition, ecological psychology, situated cognition (SitCog) and distributed cognition (DCog) offer new insights to help the teacher and assessor enhance the quality of clinical reasoning instruction and assessment. We describe the teaching and assessment implications of clinical reasoning and error through the lens of this family of theories. Direct observation in different contexts focused on individual and team performance, simulation (with or without enhancement of technology), stimulated recall, think-aloud, and modeling are examples of teaching and assessment strategies grounded in this family of social cognitive theories. Educators may consider the instructional design of learning environments and educational tools that promote a situated educational approach to the teaching and assessment of clinical reasoning.

The objective of this review was to examine the characteristics and processes of clinical reasoning used by registered nurses in clinical practice, and to identify factors reported to relate to the use of clinical reasoning by registered nurses in clinical practice. Significant variability in the clinical reasoning of graduate registered nurses has been identified in research, with underdeveloped and unsafe clinical reasoning being linked to failure-to-rescue and sentinel events in the clinical setting. The identification of characteristics and processes of clinical reasoning, and factors relating to registered nurses' clinical reasoning when engaged in clinical practice, will increase understanding of the clinical reasoning requirements for undergraduate registered nurses and of potential factors that may affect their clinical reasoning. Studies including registered nurses who met the criteria for registered nurse registration in Australia and who used clinical reasoning to engage with health care consumers in all practice environments were eligible for inclusion. Eight databases were searched, with articles identified through CINAHL, MedNar, PubMed, Science Direct, ERIC, PsycINFO, Scopus, and ProQuest Dissertations and Theses. Database searches were conducted on December 31, 2020, and updated August 20, 2021, with primary qualitative and quantitative research studies in English from 2000 onwards considered for inclusion. Opinion papers, text, and reports were not included. Data were extracted based on the draft charting tool from the scoping review protocol, with results presented in tabular format and in a narrative summary. The 29 qualitative and 5 quantitative research studies included in the scoping review utilized exploratory descriptive, descriptive rationalist, narrative, ethnography, correlational, observational, and grounded theory methodologies in their research designs. Observation, think-aloud sessions, questionnaires, surveys, interviews, and focus groups were used to collect data from the 1099 participants in 9 countries. Multiple concepts related to the characteristics (n=35) and processes (n=30) of clinical reasoning were detected in the research studies, with 5 categories identified: i) situation management, ii) data management, iii) interpreting, iv) implementing and evaluating, and v) professional practice, with an additional processes category identified (decision-making processes). The factors (n=26) reported to relate to clinical reasoning were categorized into environment of care, care requirements, professional practice, experience, knowledge, and decision-making processes. Connections between the various concepts were evident throughout the review. The scoping review identified characteristics and processes of clinical reasoning, as well as factors reported to relate to clinical reasoning in all studies. The concepts that comprise the clinical reasoning of registered nurses in clinical practice must be considered in undergraduate registered nurse education. Registered nurses must complete their baccalaureate program with well-developed clinical reasoning to ensure safe clinical practice. Understanding the characteristics and processes of registered nurses' clinical reasoning in clinical practice, and the factors reported to relate to clinical reasoning, supports the creation of targeted resources for development and assessment of clinical reasoning.

Background Clinical reasoning processes involve gathering and interpreting information, creating differential diagnoses and testing hypotheses to inform and guide patient management. Effective clinical reasoning is an essential graduate outcome for medical students to ensure safe and efficient care of patients. In the clinical setting, a large proportion of hospital-related adverse events are attributed to errors in cognitive processes rather than knowledge, including diagnostic reasoning and decision-making. Teaching clinical reasoning is challenging due to its implicit nature, typically relying on internal thinking processes, pattern recognition and the use of prior clinical experiences. Current conventional teaching relies on student-driven application of clinical reasoning during their rotations as part of a hidden curriculum, which can be highly variable, unstructured, non-standardised, with limited oversight from faculty and with few opportunities for feedback. Furthermore, current barriers exist, including difficulties in teaching and assessing clinical reasoning. Due to this, many educators and faculty agree upon the significance of embedding explicit teaching and assessment of clinical reasoning into the curriculum, however the best approach remains poorly characterised. Methods A narrative synthesis was undertaken from the current literature and the authors’ collective experience. The synthesis distils this information into ten practical tips to guide design, integration and innovation of clinical reasoning teaching in medical education. Results Ten tips were identified to support educators’ efforts in embedding clinical reasoning into curriculum design and teaching. Together, these ten tips promote explicit, reflective and contextual clinical reasoning learning within the contemporary medical curriculum. Conclusions Clinical reasoning requires deliberate, longitudinal and student-centred approaches that are integrated within authentic situated learning experiences. The ten tips provide avenues for more evidence-based adoption of effective learning environments that focus on clinical reasoning skills development.

Clinical reasoning processes involve gathering and interpreting information, creating differential diagnoses and testing hypotheses to inform and guide patient management. Effective clinical reasoning is an essential graduate outcome for medical students to ensure safe and efficient care of patients. In the clinical setting, a large proportion of hospital-related adverse events are attributed to errors in cognitive processes rather than knowledge, including diagnostic reasoning and decision-making. Teaching clinical reasoning is challenging due to its implicit nature, typically relying on internal thinking processes, pattern recognition and the use of prior clinical experiences. Current conventional teaching relies on student-driven application of clinical reasoning during their rotations as part of a hidden curriculum, which can be highly variable, unstructured, non-standardised, with limited oversight from faculty and with few opportunities for feedback. Furthermore, current barriers exist, including difficulties in teaching and assessing clinical reasoning. Due to this, many educators and faculty agree upon the significance of embedding explicit teaching and assessment of clinical reasoning into the curriculum, however the best approach remains poorly characterised. A narrative synthesis was undertaken from the current literature and the authors' collective experience. The synthesis distils this information into ten practical tips to guide design, integration and innovation of clinical reasoning teaching in medical education. Ten tips were identified to support educators' efforts in embedding clinical reasoning into curriculum design and teaching. Together, these ten tips promote explicit, reflective and contextual clinical reasoning learning within the contemporary medical curriculum. Clinical reasoning requires deliberate, longitudinal and student-centred approaches that are integrated within authentic situated learning experiences. The ten tips provide avenues for more evidence-based adoption of effective learning environments that focus on clinical reasoning skills development.

Background Clinical reasoning processes involve gathering and interpreting information, creating differential diagnoses and testing hypotheses to inform and guide patient management. Effective clinical reasoning is an essential graduate outcome for medical students to ensure safe and efficient care of patients. In the clinical setting, a large proportion of hospital-related adverse events are attributed to errors in cognitive processes rather than knowledge, including diagnostic reasoning and decision-making. Teaching clinical reasoning is challenging due to its implicit nature, typically relying on internal thinking processes, pattern recognition and the use of prior clinical experiences. Current conventional teaching relies on student-driven application of clinical reasoning during their rotations as part of a hidden curriculum, which can be highly variable, unstructured, non-standardised, with limited oversight from faculty and with few opportunities for feedback. Furthermore, current barriers exist, including difficulties in teaching and assessing clinical reasoning. Due to this, many educators and faculty agree upon the significance of embedding explicit teaching and assessment of clinical reasoning into the curriculum, however the best approach remains poorly characterised. Methods A narrative synthesis was undertaken from the current literature and the authors’ collective experience. The synthesis distils this information into ten practical tips to guide design, integration and innovation of clinical reasoning teaching in medical education. Results Ten tips were identified to support educators’ efforts in embedding clinical reasoning into curriculum design and teaching. Together, these ten tips promote explicit, reflective and contextual clinical reasoning learning within the contemporary medical curriculum. Conclusions Clinical reasoning requires deliberate, longitudinal and student-centred approaches that are integrated within authentic situated learning experiences. The ten tips provide avenues for more evidence-based adoption of effective learning environments that focus on clinical reasoning skills development.

Event Abstract Back to Event Qualitative and quantitative differences between social and non-social cognition. Dar Meshi1, 2*, Hauke R. Heekeren2, 3 and Guido Biele4 1 Humboldt Universität Berlin, Center for Integrative Life Sciences, Germany 2 Freie Universität Berlin, Department of Education and Psychology, Germany 3 Max Planck Institute, Max Planck Institute for Human Development, Germany 4 University of Oslo, Department of Psychology, Norway Background: Are there dedicated neural substrates for cognitive processes related to social interaction with other humans? To answer this question, researchers have employed functional magnetic resonance imaging (fMRI) to compare brain activity during social and non-social interaction (Adolphs, 2010). For example, interaction with humans can be contrasted with similar interaction with non-human machines like computers. This research has demonstrated differences in the blood-oxygen-level dependent (BOLD) signal between the two conditions. However, the categorical type of change seen in brain activity has not been clearly delineated in the literature. This is important, because qualitative BOLD differences provide the clearest evidence for dedicated neural substrates of social cognition. Thus, we set out to categorize the observed BOLD differences as either quantitative or qualitative. Method: We conducted an exhaustive pubmed search to find and then review fMRI papers that reported finding a difference in brain activation between interaction with humans and interaction with computers. Based on criteria proposed by Henson (2006) we classified results as showing no difference, a quantitative difference, or a qualitative difference between the two modes of interaction. The criteria for a quantitative difference consisted of a significant change in the BOLD signal in the same brain area between the human and non-human conditions. The criterion for a qualitative difference consisted of a significant interaction between experimental conditions and brain regions. Specifically, for two conditions (C1, C2) and two brain regions (R1, R2), three conditions needed to be met: (1) C1 and C2 must lead to significant activation both in R1 and R2. (2) C1 must lead to greater activation than C2 in R1. (3) C2 must lead to greater activation than C1 in R2. Result: This review found ample evidence for quantitative differences between the two modes; many papers reported significant differences in the same brain regions between the social and non-social conditions. However, we could not identify a single paper that demonstrated a qualitative difference in brain activation between social and non-social interaction. One caveat to our finding is that given the limited temporal and spatial resolution of fMRI, different neural substrates may actually appear as activation in the same region. Thus, a qualitative difference may appear as a quantitative one. Nevertheless, our analysis is valid given the current state of technology. We conclude our assessment by outlining an analysis strategy to identify qualitative differences between the neural substrates of interaction with humans and computers. References Adolphs, R. (2010) Conceptual challenges and directions for social neuroscience. Neuron. Mar 25;65(6):752-67. Henson, R. (2006) Forward inference using functional neuroimaging: dissociations versus associations. Trends Cogn Sci. Feb;10(2):64-9. Keywords: computer, fMRI analysis, social cognition Conference: Decision Neuroscience From Neurons to Societies, Berlin, Germany, 23 Sep - 25 Sep, 2010. Presentation Type: Poster Topic: Abstracts Citation: Meshi D, Heekeren HR and Biele G (2010). Qualitative and quantitative differences between social and non-social cognition.. Front. Neurosci. Conference Abstract: Decision Neuroscience From Neurons to Societies. doi: 10.3389/conf.fnins.2010.82.00036 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Aug 2010; Published Online: 07 Sep 2010. * Correspondence: Dr. Dar Meshi, Humboldt Universität Berlin, Center for Integrative Life Sciences, Berlin, Germany, darmeshi@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Dar Meshi Hauke R Heekeren Guido Biele Google Dar Meshi Hauke R Heekeren Guido Biele Google Scholar Dar Meshi Hauke R Heekeren Guido Biele PubMed Dar Meshi Hauke R Heekeren Guido Biele Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

BackgroundClinical reasoning processes involve gathering and interpreting information, creating differential diagnoses and testing hypotheses to inform and guide patient management. Effective clinical reasoning is an essential graduate outcome for medical students to ensure safe and efficient care of patients. In the clinical setting, a large proportion of hospital-related adverse events are attributed to errors in cognitive processes rather than knowledge, including diagnostic reasoning and decision-making. Teaching clinical reasoning is challenging due to its implicit nature, typically relying on internal thinking processes, pattern recognition and the use of prior clinical experiences. Current conventional teaching relies on student-driven application of clinical reasoning during their rotations as part of a hidden curriculum, which can be highly variable, unstructured, non-standardised, with limited oversight from faculty and with few opportunities for feedback. Furthermore, current barriers exist, including difficulties in teaching and assessing clinical reasoning. Due to this, many educators and faculty agree upon the significance of embedding explicit teaching and assessment of clinical reasoning into the curriculum, however the best approach remains poorly characterised.MethodsA narrative synthesis was undertaken from the current literature and the authors’ collective experience. The synthesis distils this information into ten practical tips to guide design, integration and innovation of clinical reasoning teaching in medical education.ResultsTen tips were identified to support educators’ efforts in embedding clinical reasoning into curriculum design and teaching. Together, these ten tips promote explicit, reflective and contextual clinical reasoning learning within the contemporary medical curriculum.ConclusionsClinical reasoning requires deliberate, longitudinal and student-centred approaches that are integrated within authentic situated learning experiences. The ten tips provide avenues for more evidence-based adoption of effective learning environments that focus on clinical reasoning skills development.

Background The cognitive pathways that lead to an accurate diagnosis and efficient management plan can touch on various clinical reasoning tasks (1). These tasks can be employed at any point during the clinical reasoning process and though the four distinct categories of framing, diagnosis, management, and reflection provide some insight into how these tasks map onto clinical reasoning, much is still unknown about the task-based clinical reasoning process. For example, when and how are these tasks typically used? And more importantly, do these clinical reasoning task processes evolve when patient encounters become complex and/or challenging (i.e. with contextual factors)? Methods We examine these questions through the lens of situated cognition, context specificity, and cognitive load theory. Sixty think-aloud transcripts from 30 physicians who participated in two separate cases - one with a contextual factor and one without - were coded for 26 clinical reasoning tasks (1). These tasks were organized temporally, i.e. when they emerged in their think-aloud process. Frequencies of each of the 26 tasks were aggregated, categorized, and visualized in order to analyze task category sequences. Results We found that (a) as expected, clinical tasks follow a general sequence, (b) contextual factors can distort this emerging sequence, and (c) the presence of contextual factors prompts more experienced physicians to clinically reason similar to that of less experienced physicians. Conclusions These findings add to the existing literature on context specificity in clinical reasoning and can be used to strengthen teaching and assessment of clinical reasoning.

Clinical reasoning processes are complex and interwoven with culture and context. While these relationships have been explored to understand the outcomes of clinical reasoning, there has been little exploration of how to integrate these relationships when teaching and learning clinical reasoning. Using semi-structured interviews, this research explored the role of context and culture in clinical reasoning medical education. Participants were clinical teachers recruited from across Northern Ontario. The data were analysed independently by two reviewers using both thematic analysis and critical discourse analysis, and peer reviewed by a third researcher. The role of context and culture is inherent to the personal, professional and pedagogical aspects of clinical reasoning, especially when teaching about the complexities of Northern Ontario. The major themes that came through were: 1) teaching and learning clinical reasoning needs reflexivity, 2) developing clinical reasoning skills needs time and 3) clinical reasoning pedagogy should acknowledge and encompass practice variation and patient diversity. Teaching clinical reasoning in Northern Ontario involves being aware of the complexities that are inherent in interacting with patients and communities. Through personal, professional and pedagogical models, the students and teachers can address the complexities of cultural and contextual clinical reasoning.

Numerous challenges exist in effectively bridging theory and practice in the teaching and assessment of clinical reasoning, despite an abundance of theoretical models. This study compares clinical reasoning practices and decisions between medical students and expert clinicians using a problem-solving framework from the learning sciences, which identifies clinical reasoning as distinct, observable actions in clinical case solving. We examined students at various training stages against expert clinicians to address the research question: How do expert clinicians and medical students differ in their practices and decisions during the diagnostic process?. We developed a questionnaire about a pediatric infectious disease case based on the problem-solving framework from the learning sciences to probe clinical reasoning decisions. The questionnaire had four sections: medical history, physical examination, medical tests, and working diagnosis. The questionnaire was administered at Stanford University between January 2019 and June 2023 to collect data from 10 experts and 74 medical students. We recruited participants through maximum variation sampling. We applied deductive content analysis to systematically code responses to identify patterns in the execution of the practices and decisions across the questionnaire. This research introduces a highly detailed, empirically developed framework that holds potential to bridge theory and practice, offering practical insights for medical instructors in teaching clinical reasoning to students across various stages of their training. This framework involves nine practices, with a total of twenty-nine decisions that need to be made when carrying out these practices. Differences between experts and students centered on ten decisions across the practices: Differential diagnosis formulation, Diagnostic plan and execution, Clinical data reassessment, and Clinical solution review. We were able to identify nuanced differences in clinical reasoning between students and expert physicians under one comprehensive problem-solving framework from the learning sciences. Identifying key clinical reasoning practices and decision differences could help develop targeted instructional materials and assessment tools, aiding instructors in fostering clinical reasoning in students.

The purpose of this study was to explore whether clinical reasoning of occupational therapists varied depending on their field of practice. The subjects were six occupational therapists working in rheumatology and six working in neurology who individually viewed a videofilm showing either a patient with rheumatoid arthritis or a hemiplegic patient in three different situations. While watching each situation, the participants were asked to ?think aloud? or ?reflect on action?. Comments were tape-recorded and transcribed. The analyses, using a phenomenographic approach, focused on how participants reason in order to make sense of the situation. Five qualitatively different groups of comments were identified: confident, tentative, understanding, generalized and teaching. The results showed both qualitative and quantitative differences between the two groups of therapists. In conclusion, differences in clinical reasoning may influence patient-occupational therapist interaction.

Diagnostic error is a challenging problem; addressing it effectively will require innovation across multiple domains of health care, including medical education. Diagnostic errors often relate to problems with clinical reasoning, which involves the cognitive and relational steps up to and including establishing a diagnostic and therapeutic plan with a patient. However, despite a call from the National Academies of Sciences for medical educators to improve the teaching and assessment of clinical reasoning, the creation of explicit, theory-informed clinical reasoning curricula, faculty development resources, and assessment tools has proceeded slowly in both undergraduate and graduate medical education. To accelerate the development of this critical element of health professions education and to promote needed research and innovation in clinical reasoning education, the Accreditation Council for Graduate Medical Education (ACGME) should revise its core competencies to include clinical reasoning. The core competencies have proven to be an effective means of expanding educational innovation across the United States and ensuring buy-in across a diverse array of institutions and disciplines. Reformulating the ACGME core competencies to include clinical reasoning would spark much-needed educational innovation and scholarship in graduate medical education, as well as collaboration across institutions in this vital aspect of physicianship, and ultimately, could contribute to a reduction of patient suffering by better preparing trainees to build individual, team-based, and system-based tools to monitor for and avoid diagnostic error.