Diagnostic Problem Solving Research Articles

Exploring medical students’ metacognitive and regulatory dimensions of diagnostic problem solving

ABSTRACT Solving clinical problems requires an individual to apply not only domain-specific medical knowledge and cognitive skills for reasoning, but also to be consciously aware of, monitor, and evaluate their thinking processes (i.e., metacognition). The purpose of this study was to map critical metacognitive dimensions of clinical problem solving and to explore the structural relationships among them, which may help frame a conceptual framework and better pedagogy for effective intervention. A context-specific inventory was adapted and modified from a domain-general instrument to capture essential metacognitive skills for learning and solving clinical problems. This inventory was administered to 72 undergraduate medical students to survey their capabilities in five dimensions: knowledge of cognition, objectives, problem representation, monitoring, and evaluation. The interplay among these dimensions was further examined using partial least squares structural equation modeling. Our findings revealed that the medical students fell short of some expert-like, metacognitive, and regulatory competence, even after receiving years of medical education and on-site training. In particular, they did not know when a holistic understanding of a problem had been reached. Many of them often do not have a set of clear diagnostic procedures in mind, nor do they concurrently monitor their thinking during diagnostic reasoning. Moreover, their lack of self-improving approaches seemed to worsen their learning. Finally, the structural equation model indicated that knowledge of cognition and objectives significantly predicted problem representation, suggesting that medical learners’ knowledge of and goals for learning are influential in framing the clinical problems at hand. A significant linear prediction path was observed from problem representation, monitoring, to evaluation, signifying a possible sequenced process of clinical problem solving. Metacognitive-based instruction can help improve clinical problem-solving skills and awareness of potential biases or errors.

PET/CT and PET/MR Imaging of the Post-treatment Head and Neck: Traps and Tips.

PET/computed tomography and PET/MR imaging are used to evaluate the post-treatment neck. Although 18F-FDG is helpful in the staging and treatment response assessment of head and neck cancer, recently developed PET radiotracers targeting specific surface markers are promising for applications of diagnostic problem solving and improved extent delineation. Diffusion-weighted MR imaging is helpful in the differential diagnosis of head and neck neoplasms, and improves the sensitivity and specificity for the detection of certain pathologies. Following standardized imaging parameters for PET/computed tomography and diffusion-weighted imaging in PET/MR imaging improves diagnostic accuracy and allows for future research data mining.

Promoting car mechatronics apprentices' diagnostic strategy with modeling examples: Development and evaluation of a simulation-based learning environment

Crucial for training automotive mechatronics technicians (AMTs) is enabling them to diagnose car malfunctions. AMTs are particularly successful when they base their diagnostic process on a mental model of the affected automotive system. Still, only few AMT apprentices master such diagnoses after their apprenticeship. Therefore, we created a simulation-based learning environment with modeling examples to teach AMT apprentices a diagnostic strategy that builds on mental models. Following design-based research guidelines, we formatively evaluated our learning and testing materials by expert judgments and a small study during the development of the learning environment. Finally, an evaluation study showed that the learning environment promoted apprentices' knowledge about the diagnostic strategy. However, they could not transfer their knowledge to diagnostic problem-solving. Overall, the apprentices evaluated the learning environment positively, except it was considered too long and repetitive. Reasons for the outcomes as well as possible further developments of the learning environment are discussed.

Statistical reasoning in diagnostic problem-solving—The case of flow-rate measurements

There are various methods for measuring flow rates in rivers, but all of them have practical issues and challenges. A period of exceptionally high water levels revealed substantial discrepancies between two measurement setups in the same waterway. Finding a causal explanation of the discrepancies was important, as the problem might have ramifications for other flow-rate measurement setups as well. Finding the causes of problems is called diagnostic problem-solving. We applied a branch-and-prune strategy, in which we worked with a hierarchy of hypotheses, and used statistical analysis as well as domain knowledge to rule out options. We were able to narrow down the potential explanations to one main suspect and an alternative explanation. Based on the analysis, we discuss the role of statistical techniques in diagnostic problem-solving and reasoning patterns that make the application of statistics powerful. The contribution to theory in statistics is not in the individual techniques but in their application and integration in a coherent sequence of studies – a reasoning strategy.

Pearls and Pitfalls of Contrast-Enhanced Mammography.

Contrast-enhanced mammography (CEM) is a promising new imaging modality that uses a dual-energy acquisition to provide both morphologic and vascular assessment of breast lesions. Although no official BI-RADS lexicon exists, interpretation entails using the mammographic BI-RADS lexicon in combination with that for breast MRI. CEM has comparable performance to breast MRI, with sensitivity of 93-100% and specificity of 80-94%. Currently FDA approved for diagnostic imaging, this technology can be helpful in determining disease extent in patients with newly diagnosed breast malignancy, monitoring response to neoadjuvant therapy, identifying mammographically occult malignancies, and diagnostic problem-solving. Studies are ongoing about its role in screening, especially in women with dense breasts or at elevated risk. There are some challenges to successful implementation into practice, but overall, patients tolerate the study well, and exam times are less than the full breast MRI protocol.

ПЕДАГОГИЧЕСКИЕ УСЛОВИЯ РЕАЛИЗАЦИИ КОМПЛЕКСА МОДЕЛЕЙ ФОРМИРОВАНИЯ ГОТОВНОСТИ КУРСАНТОВ К РЕШЕНИЮ КОМПЕТЕНТНОСТНО-ОРИЕНТИРОВАННЫХ ПРОФЕССИОНАЛЬНЫХ ЗАДАЧ

Competence-oriented professional tasks reflect the substantive and procedural aspect of future officers training to fulfill official duties. We identified and justified the necessary and sufficient pedagogical conditions that in complex can increase the effectiveness of introducing into the educational process of military educational institutions a set of models to form students' readiness to solve competence-oriented professional tasks. The application of the following research methods contributed to the solution of the task: studying, analyzing and summarizing the experience of organizing and improving the educational process of military educational organizations, as well as training of the future military aviation specialist (military navigator and combat control officer). The complex of pedagogical conditions embodies: 1) the formation of the subjective cognitive experience of students using diagnostic problem solving; 2) the use of graphical methods of compression and presentation of educational information to form and develop a system of operational information on the cycles of disciplines; 3) the motivation growth of students through the use of checklists for the implementation of the reflection process of solving problems. The novelty of the results is determined by the combination and essence of the pedagogical conditions identified taking into account the methodological basis of the designed complex of models, features and patterns of both the educational process of military educational institutions of higher education of the RF Ministry of Defense, and the process of solving competenceoriented tasks by cadets along with their individual characteristics. The significance of the results obtained is that the introduction of the identified set of pedagogical conditions can increase the effectiveness of introducing a set of models of cadets’ readiness formation to solve competence- oriented professional tasks.

Fundamentals of Diagnostic Error in Imaging.

Imaging plays a pivotal role in the diagnostic process for many patients. With estimates of average diagnostic error rates ranging from 3% to 5%, there are approximately 40 million diagnostic errors involving imaging annually worldwide. The potential to improve diagnostic performance and reduce patient harm by identifying and learning from these errors is substantial. Yet these relatively high diagnostic error rates have persisted in our field despite decades of research and interventions. It may often seem as if diagnostic errors in radiology occur in a haphazard fashion. However, diagnostic problem solving in radiology is not a mysterious black box, and diagnostic errors are not random occurrences. Rather, diagnostic errors are predictable events with readily identifiable contributing factors, many of which are driven by how we think or related to the external environment. These contributing factors lead to both perceptual and interpretive errors. Identifying contributing factors is one of the keys to developing interventions that reduce or mitigate diagnostic errors. Developing a comprehensive process to identify diagnostic errors, analyze them to discover contributing factors and biases, and develop interventions based on the contributing factors is fundamental to learning from diagnostic error. Coupled with effective peer learning practices, supportive leadership, and a culture of quality, this process can unquestionably result in fewer diagnostic errors, improved patient outcomes, and increased satisfaction for all stakeholders. This article provides the foundational elements for implementing this type of process at a radiology practice, with examples to help radiologists and practice leaders achieve meaningful practice improvement. ©RSNA, 2018.

Case-Based and Multimodal Reasoning: the contribution of Piero Torasso

The paper reports the contribution of Piero Torasso to the field of Case-Based Reasoning (CBR), with particular attention to the role of CBR in multi-modal diagnostic problem solving. Starting from the idea that CBR could be adopted to focus model-based reasoning during diagnostic problem solving, Piero’s work concentrated on all the different steps of the CBR cycle, namely case retrieval, solution adaptation and case base maintenance. This resulted in the construction of a multi-modal system called ADAPtER that was used during all the phases of his research activity, both as a basis for the theoretical work and for the necessary experimental analysis.

Diagnostic Problem-Solving Process in Professional Contexts: Theory and Empirical Investigation in the Context of Car Mechatronics Using Computer-Generated Log-Files

This article deals with a theory-based investigation of the diagnostic problem-solving process in professional contexts. To begin with, a theory of the diagnostic problem-solving process was developed drawing on findings from different professional contexts. The theory distinguishes between four sub-processes of the diagnostic problem-solving process and includes several hypotheses. According to the theory, the quality of the sub-processes “representing information” and “testing hypotheses” causally influences the diagnostic problem-solving success. Additionally, the theory suggests that the influence of “testing hypotheses” on the problem-solving success is higher than the influence of “representing information”. Moreover, the theory assumes that the influence of the quality of “representing information” on the success is mediated by the quality of “testing hypotheses”. These hypotheses were examined in the context of car mechatronics using diagnostic problems of the car sector, a computer-based assessment and a sample of car mechatronic apprentices (N = 339). To operationalize the sub-processes’ quality, observable critical behavior was theoretically identified and extracted from computer-generated log-files. The empirical results were largely in line with the hypotheses and indicated a (very) first corroboration of the theory in the context of car mechatronics. The theory could be helpful to investigate and teach diagnostic problem solving in different professional contexts. Further studies, however, should scrutinize whether the theory applies to other studies and professional contexts.

Комплексная модульная система предупреждения профессиональных деструкций следователей в ходе их профессионального становления

The article substantiates the need to improve the readiness of the future legal psychologists to effective coping behavior in the light output at the present time in Russia professional standards governing the activities of professionals providing psychological assistance to minors, including those who are in legally relevant situations. The aim of the presented research - the identification of typical coping strategies for students of legal psychology in the educational practice and the analysis of the relationship of coping strategies with successful performance practices. Second-year students were diagnostic practice in various educational institutions, including schools and special schools for students with deviant behavior. Probationers acted as a psychologist, a holistic diagnostic problem solving - from the receipt of the request to make recommendations on the results of the survey. The method of content analysis was processed 41 report on the practice. Fixed mention of problematic situations that have caused negative emotions in the trainees, and mention of coping behavior. Revealed the typical difficulties of students and coping strategies when performing queries on psycho-diagnostics of children with behavioral problems. We found a significant positive correlation between the success of the implementation of practice tasks students with a variety mentioned in the report difficulties with the frequency of their appearance, as well as with a variety of coping strategies. The study offers methodological tools for the preparation of the future legal psychologists in diagnostic practice.

Проблема формирования готовности будущих юридических психологов к эффективному совладающему поведению

The article substantiates the need to improve the readiness of the future legal psychologists to effective coping behavior in the light output at the present time in Russia professional standards governing the activities of professionals providing psychological assistance to minors, including those who are in legally relevant situations. The aim of the presented research - the identification of typical coping strategies for students of legal psychology in the educational practice and the analysis of the relationship of coping strategies with successful performance practices. Second-year students were diagnostic practice in various educational institutions, including schools and special schools for students with deviant behavior. Probationers acted as a psychologist, a holistic diagnostic problem solving - from the receipt of the request to make recommendations on the results of the survey. The method of content analysis was processed 41 report on the practice. Fixed mention of problematic situations that have caused negative emotions in the trainees, and mention of coping behavior. Revealed the typical difficulties of students and coping strategies when performing queries on psycho-diagnostics of children with behavioral problems. We found a significant positive correlation between the success of the implementation of practice tasks students with a variety mentioned in the report difficulties with the frequency of their appearance, as well as with a variety of coping strategies. The study offers methodological tools for the preparation of the future legal psychologists in diagnostic practice.

Diagnostic problem solving in male collegiate athletic trainers.

Knowledge and experience may be important factors for understanding expertise based upon a clinician's ability to select and execute an appropriate response as a clinician during injury evaluation. To describe how collegiate male certified athletic trainers represent injury-evaluation domain knowledge during a situational interview using a think-aloud protocol. Qualitative. National Collegiate Athletic Association Division I and II colleges in National Athletic Trainers' Association District 3. A total of 20 male certified athletic trainers (n = 10 with less than 2 years of experience in the college setting and n = 10 with at least 10 years of experience in the college setting) participated in the study. We collected data using a situational interview and questionnaire. Data were transcribed, reduced to meaningful units, and analyzed using verbal analysis procedures. Member checks, triangulation of data, field journaling, and peer-debriefing techniques were used to ensure trustworthiness of the data. Knowledge concepts were enumerated to describe differences between experts and novices. Compared with novices, experts had more knowledge concepts of patient history and predictions and fewer concepts of situation appraisal. Expertise in athletic training shares traits with other areas in health care. Athletic training education and professional development may benefit from our understanding which cognitive processes differentiate expert practice. Future investigators should attempt to describe other settings and study diagnostic problem solving in a natural environment.

Computing Contingent Plans via Fully Observable Non-Deterministic Planning

Planning with sensing actions under partial observability is a computationally challenging problem that is fundamental to the realization of AI tasks in areas as diverse as robotics, game playing, and diagnostic problem solving. Recent work on generating plans for partially observable domains has advocated for online planning, claiming that offline plans are often too large to generate. Here we push the envelope on this challenging problem, proposing a technique for generating conditional (aka contingent) plans offline. The key to our planner's success is the reliance on state-of-the-art techniques for fully observable non-deterministic (FOND) planning. In particular, we use an existing compilation for converting a planning problem under partial observability and sensing to a FOND planning problem. With a modified FOND planner in hand, we are able to scale beyond previous techniques for generating conditional plans with solutions that are orders of magnitude smaller than previously possible in some domains.

Computer aided diagnostic problem solving: Identification of peripheral nerve disorders

AimThe aim was to design and develop a decision support system with a graphical user interface for the prediction of the case of peripheral nerve disorder and to build a classifier using artificial neural networks that can distinguish between carpal tunnel syndrome, neuropathy and normal peripheral nerve conduction. Materials and methodsThe data used were the Nerve Conduction Study data obtained from Kannur Medical College, India. A recurrent neural network and a two-layer feed forward network trained with scaled conjugate gradient back-propagation algorithm were implemented and results were compared. ResultsBoth the networks provided fast convergence and good performance, accuracy being 98.6% and 97.4% for the recurrent neural network and the feed forward networks respectively, the confusion matrix in each case indicated only a few misclassifications. The developed decision support system also gave accurate results in agreement with the specialist's diagnosis and was also useful in storing and viewing the results. DiscussionsIn the field of medicine, programs are being developed that aids in diagnostic decision making by emulating human intelligence such as logical thinking, decision making, learning, etc. The system developed proves useful in combination with other systems in providing diagnostic and predictive medical opinions. It was not meant to replace the specialist, yet it can be used to assist a general practitioner or specialist in diagnosing and predicting patient's condition. ConclusionsThe study proves that artificial neural networks are indeed of value in combination with other systems in providing diagnostic and predictive medical opinions. But the major drawback of these studies, which makes use of the nerve conduction study data are the inherent shortcomings of the interpretation of the results, which include lack of standardization and absence of population-based reference intervals.

Diagnostic Quality Problem Solving: A Conceptual Framework and Six Strategies

Diagnostic problem solving, which is the task of discovering causal explanations for unwanted effects, is an important element of problem solving. This paper contributes a conceptual framework for the generic process of diagnosis in quality problem solving by identifying its activities and how they are related. It then presents six strategies that structure the diagnostic process by suggesting a certain sequence of actions and techniques. The paper analyzes when each of these strategies is likely to be effective and how it may help in making the diagnostic process more efficient. Finally, the paper proposes and motivates a generic sequence of stages in diagnosing quality problems.The framework offers a scientific basis for studying and evaluating problem-solving methodologies such as Six Sigma's DMAIC model, Kepner and Tregoe's problem analysis method, and Shainin's system. For the practitioner, the framework clarifies the rationale for many problem-solving techniques offered in courses and textbooks. The paper also offers indications and contra-indications when techniques are promising, and demonstrates how they fit together in a coherent strategy.

An analysis of the Six Sigma DMAIC method from the perspective of problem solving

The DMAIC (Define-Measure-Analyze-Improve-Control) method in Six Sigma is often described as an approach for problem solving. This paper compares critically the DMAIC method with insights from scientific theories in the field of problem solving. As a single authoritative account of the DMAIC method does not exist, the study uses a large number of sources, consisting of prescriptive accounts of the method in the practitioner literature. Five themes are selected from the problem solving literature for the analysis of DMAIC—generality versus domain specificity of methods; problem structure; generic problem solving tasks; diagnostic problem solving; and remedial problem solving. The study provides a characterization of the types of problems for which DMAIC is a suitable method, but also identifies problems for which it may be ineffective. An important limitation of the method is its generality, which limits the methodological support it provides, and which fails to exploit task-domain specific knowledge. Domain-specific adaptations of the method partly overcome these weaknesses. Among the method's strengths are the powerful statistical techniques for fact finding and empirical verification of ideas, and the DMAIC stage model, which acts as a problem structuring device. The most prominent limitation identified in this study is Six Sigma's inferior methodology for efficient problem diagnosis. Methodological support for the identification of potential problem causes is offered as an incoherent and poorly structured collection of techniques, without strategic guidance to ensure efficiency of the diagnostic search. Adopters of the method should be aware of its potential limitations.

The tactical use of constraints and structure in diagnostic problem solving

This paper presents a prescriptive account of diagnostic problem solving, or diagnosis, in quality and process control. This paper identifies a general strategy, named branch-and-prune, whose manifestations can be found in disciplines such as medical diagnosis, troubleshooting of devices, and model-based diagnosis in artificial intelligence. The work aims to offer a clear conceptualization of this strategy, based on the notions of structures for the search space, and constraints to the cause's nature. The idea is to treat the search space of candidate explanations as a tree structure, in which general and high-level causal directions are branched into more specific and detailed explanations. Constraints eliminate all but a few branches (pruning), which are explored in more detail. We enumerate eight generic structures as a basis for branching the search tree. We demonstrate that our conceptualization in terms of structures and constraints gives a rationale for generally known methods and heuristics in quality engineering and operations management. The paper contributes a unifying conceptual understanding of a class of diagnostic techniques, and it improves the strategy's operationality by offering generic structures, and a simpler and more flexible account of its working. A description of a real-life quality problem solving effort forms a tangible basis for the discussion.

Non-analytical models of clinical reasoning: the role of experience

This paper aims to summarise the evidence supporting the role of experience-based, non-analytic reasoning (NAR) or pattern recognition as a central feature of expert medical diagnosis. The authors examine a series of studies, primarily from their own research programme at McMaster University, that demonstrate that expert and novice diagnostic problem solving is based, to some degree, on similarity to a prior specific exemplar in the memory. The studies reviewed have shown NAR to be a component of diagnostic reasoning at all levels from novice to subspecialist, and in dermatology, electrocardiography and psychiatry. The retrieval process is rapid and is not available to retrospect. It may be based on visual similarity, but can also be present in verbal descriptions. Some evidence exists that the process is unlikely to be available to introspection. Further, early hypotheses based on NAR can result in the re-interpretation of critical clinical findings. Non-analytic reasoning is a central component of diagnostic expertise at all levels. Clinical teaching should recognise the centrality of this process, and aim to both enhance the process through the learning of multiple examples and to supplement the process with analytical de-biasing strategies.

Integrated Case-Based Applied Pathology (ICAP): A Diagnostic-Approach Model for the Learning and Teaching of Veterinary Pathology

Integrative Case-Based Applied Pathology (ICAP) cases form one component of learning and understanding the role of pathology in the veterinary diagnostic process at the Faculty of Veterinary Science, University of Sydney. It is a strategy that focuses on student-centered learning in a problem-solving context in the year 3 curriculum. Learning exercises use real case material and are primarily delivered online, providing flexibility for students with differing learning needs, who are supported by online, peer, and tutor support. The strategy relies heavily on the integration of pre-clinical and para-clinical information with the introduction of clinical material for the purposes of a logical three-level, problem-oriented approach to the diagnosis of disease. The focus is on logical diagnostic problem solving, primarily using gross pathology and histopathological material, with the inclusion of microbiological, parasitological, and clinical pathological data. The ICAP approach is linked to and congruent with the problem-oriented approach adopted in veterinary medicine and the case-based format used by one of the authors (PJC) for the teaching and learning of veterinary clinical pathology in year 4. Additionally, final-year students have the opportunity, during a diagnostic pathology rotation, to assist in the development and refinement of further ICAPs, which reinforces the importance of pathology in the veterinary diagnostic process. Evidence of the impact of the ICAP approach, based primarily on student surveys and staff peer feedback collected over five years, shows that discipline-specific learning, vertical and horizontal integration, alignment of learning outcomes and assessment, and both veterinary and generic graduate attributes were enhanced. Areas for improvement were identified in the approach, most specifically related to assistance in the development of generic teamwork skills.

CONFIDENCE, ERROR AND INGENUITY IN DIAGNOSTIC PROBLEM SOLVING: CLARIFYING THE ROLE OF EXPLORATION AND EXPLOITATION.

Building on in-depth studies of diagnostic problem solving in a time-pressured acute care setting, we develop a formal mathematical model of the dynamic structures that underlie four diagnostic arc...