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Models for diagnostic reasoning in radiology have been based on the observed behaviors of experienced radiologists but have not directly focused on the thought processes of novices as they improve their accuracy of image interpretation. By collecting think-aloud verbal reports, the current study was designed to investigate differences in specific thought processes between medical students (novices) as they learn and radiologists (experts), so that we can better design future instructional environments. Seven medical students and four physicians with radiology training were asked to interpret and diagnose pediatric elbow radiographs where fracture is suspected. After reporting their diagnosis of a case, they were given immediate feedback. Participants were asked to verbalize their thoughts while completing the diagnosis and while they reflected on the provided feedback. The protocol analysis of their verbalizations showed that participants used some combination of four processes to interpret the case: "gestalt interpretation," "purposeful search," "rule application," and "reasoning from a prior case." All types of processes except reasoning from a prior case were applied significantly more frequently by experts. Further, gestalt interpretation was used with higher frequency in abnormal cases while purposeful search was used more often for normal cases. Our assessment of processes could help guide the design of instructional environments with well-curated image banks and analytics to facilitate the novice's journey to expertise in image interpretation.

Introduction: Given the potential malignancy risks associated with computed tomography (CT), some physicians are increasingly advocating for risk disclosure to patients/families.Objective: Our goal was to evaluate the practices and attitudes of pediatric emergency medicine (PEM) fellowship program leaders’ regarding CT radiation-risk disclosure.Methods: We conducted a cross-sectional survey study of U.S. and Canadian PEM fellowship directors and associate/assistant directors. We developed a web-based survey using a modified Dillman technique. Primary outcome was the proportion who “almost always” or “most of the time” discussed potential malignancy risks from CT prior to ordering this test.Results: Of 128 physicians who received the survey, 108 (86%) responded. Of those respondents, 73%, 95% confidence interval (CI) [64-81] reported “almost always” or “most of the time” discussing potential malignancy risks when ordering a CT for infants; proportions for toddlers, school-age children, and teenagers were 72% (95% CI [63-80]), 66% (95% CI [56-75]), and 58% (95% CI [48-67]), respectively (test for trend, p=0.008). Eighty percent reported being “extremely” or “very” comfortable discussing radiation risks. Factors of “high” or “very high” importance in disclosing risks included parent request for a CT not deemed clinically indicated for 94% of respondents, and parent-initiated queries about radiation risks for 79%. If risk disclosure became mandatory, 82% favored verbal discussion over written informed consent.Conclusion: PEM fellowship program leaders report frequently disclosing potential malignancy risks from CT, with the frequency varying inversely with patient age. Motivating factors for discussions included parental request for a CT deemed clinically unnecessary and parental inquiry about risks.

Learning curves are a useful way of representing the rate of learning over time. Features include an index of baseline performance (y-intercept), the efficiency of learning over time (slope parameter) and the maximal theoretical performance achievable (upper asymptote). Each of these parameters can be statistically modelled on an individual and group basis with the resulting estimates being useful to both learners and educators for feedback and educational quality improvement. In this primer, we review various descriptive and modelling techniques appropriate to learning curves including smoothing, regression modelling and application of the Thurstone model. Using an example dataset we demonstrate each technique as it specifically applies to learning curves and point out limitations.

Sequential context effects, the psychological interactions occurring between the events of successive trials when a sequence of similar stimuli are judged, have interested psychologists for decades. It has been well established that individuals exhibit sequential context effects in psychophysical experiments involving unidimensional stimuli. Recent evidence shows that these effects generalize to quantitative judgments of more complex multidimensional stimuli such as images of faces, chairs, and shoes. In this article, we test for the presence of sequential context effects by re-examining previously published data on categorical judgments of 234 complex radiographic images made by 20 experienced physicians and 20 medical students engaged in an online training task. We found that medical students, but not experienced physicians, displayed evidence of sequential context effects. We also found evidence suggesting that as the students learned over blocks of trials, they tended to shift from relative comparisons between consecutive images toward more independent comparisons of each image against (strengthening) internalized standards.

Introduction: There is limited knowledge on pediatric chest radiograph (pCXR) interpretation skill among practicing physicians. We systematically determined baseline interpretation skill, the number of pCXR cases physicians required complete to achieve a performance benchmark, and which diagnoses posed the greatest diagnostic challenge. Methods: Physicians interpreted 434 pCXR cases via a web-based platform until they achieved a performance benchmark of 85% accuracy, sensitivity, and specificity. Interpretation difficulty scores for each case were derived by applying one-parameter item response theory to participant data. We compared interpretation difficulty scores across diagnostic categories and described the diagnoses of the 30% most difficult-to-interpret cases. Results: 240 physicians who practice in one of three geographic areas interpreted cases, yielding 56,833 pCXR case interpretations. The initial diagnostic performance (first 50 cases) of our participants demonstrated an accuracy of 68.9%, sensitivity of 69.4%, and a specificity of 68.4%. The median number of cases completed to achieve the performance benchmark was 102 (interquartile range 69, 176; min, max, 54, 431). Among the 30% most difficult-to-interpret cases, 39.2% were normal pCXR and 32.3% were cases of lobar pneumonia. Cases with a single trauma-related imaging finding, cardiac, hilar, and diaphragmatic pathologies were also among the most challenging. Discussion: At baseline, practicing physicians misdiagnosed about one-third of pCXR and there was up to an eight-fold difference between participants in number of cases completed to achieve the standardized performance benchmark. We also identified the diagnoses with the greatest potential for educational intervention. [ABSTRACT FROM AUTHOR]

Signal detection theory (SDT) parameters can describe a learner's ability to discriminate (d[prime symbol]) normal from abnormal and the learner's criterion ([lambda]) to under or overcall abnormalities. To examine the serial changes in SDT parameters with serial exposure to radiological cases. 46 participants were recruited for this study: 20 medical students (MED), 6 residents (RES), 12 fellows (FEL), 5 staff pediatric emergency physicians (PEM), and 3 staff radiologists (RAD). Each participant was presented with 234 randomly assigned ankle radiographs using a web-based application. Participants were given a clinical scenario and considered 3 views of the ankle. They classified each case as normal or abnormal. For abnormal cases, they specified the location of the abnormality. Immediate feedback included highlighting on the images and the official radiologist's report. The low experience group (MED, RES, FEL) showed steady improvement in discrimination ability with each case, while the high experience group (PEM, RAD) had higher and stable discrimination ability throughout the exercise. There was also a difference in the way the high and low experience groups balanced sensitivity and specificity ([lambda]) with the low experience group tending to make more errors calling positive radiographs negative. This tendency was progressively less evident with each increase in expertise level. SDT metrics provide valuable insight on changes associated with learning radiograph interpretation, and may be used to design more effective instructional strategies for a given learner group. (Contains 2 tables and 6 figures.)

Objective: To assess the co-occurrence and clustering of post-concussive symptoms in children, and to identify distinct patient phenotypes based on symptom type and severity.Methods: We performed a secondary analysis of the prospective, multicentre Predicting and Preventing Post-concussive Problems in Pediatrics (5P) cohort study, evaluating children 5-17 years of age presenting within 48 hours of an acute concussion. Our primary outcome was the simultaneous occurrence of two or more persistent post-concussive symptoms on the Post-Concussion Symptom Inventory at 28 days post-injury. Analyses of symptom and patient clusters were performed using hierarchical cluster analyses of symptom severity ratings.Results: 3063 patients from the parent 5P study were included. Median age was 12.1 years (IQR: 9.2-14.6 years), and 1857 (60.6%) were male. Fatigue was the most common persistent symptom (21.7%), with headache the most commonly reported co-occurring symptom among patients with fatigue (55%; 363/662). Headache was common in children reporting any of the 12 other symptoms (range: 54%-72%). Physical symptoms occurred in two distinct clusters: vestibular-ocular and headache. Emotional and cognitive symptoms occurred together more frequently and with higher severity than physical symptoms. Fatigue was more strongly associated with cognitive and emotional symptoms than physical symptoms. We identified five patient groups (resolved/minimal, mild, moderate, severe and profound) based on symptom type and severity.Conclusion: Post-concussive symptoms in children occur in distinct clusters, facilitating the identification of distinct patient phenotypes based on symptom type and severity. Care of children post-concussion must be comprehensive, with systems designed to identify and treat distinct post-concussion phenotypes. [ABSTRACT FROM AUTHOR]

For assessing the skill of visual diagnosis such as radiograph interpretation, competency standards are often developed in an ad hoc method, with a poorly delineated connection to the target clinical population. Commonly used methods to assess for competency in radiograph interpretation are subjective and potentially biased due to a small sample size of cases, subjective evaluations, or include an expert-generated case-mix versus a representative sample from the clinical field. Further, while digital platforms are available to assess radiograph interpretation skill against an objective standard, they have not adopted a data-driven competency standard which informs educators and the public that a physician has achieved adequate mastery to enter practice where they will be making high-stakes clinical decisions. Operating on a purposeful sample of radiographs drawn from the clinical domain, we adapted the Ebel Method, an established standard setting method, to ascertain a defensible, clinically relevant mastery learning competency standard for the skill of radiograph interpretation as a model for deriving competency thresholds in visual diagnosis. Using a previously established digital platform, emergency physicians interpreted pediatric musculoskeletal extremity radiographs. Using one-parameter item response theory, these data were used to categorize radiographs by interpretation difficulty terciles (i.e. easy, intermediate, hard). A panel of emergency physicians, orthopedic surgeons, and plastic surgeons rated each radiograph with respect to clinical significance (low, medium, high). These data were then used to create a three-by-three matrix where radiographic diagnoses were categorized by interpretation difficulty and significance. Subsequently, a multidisciplinary panel that included medical and parent stakeholders determined acceptable accuracy for each of the nine cells. An overall competency standard was derived from the weighted sum. Finally, to examine consequences of implementing this standard, we reported on the types of diagnostic errors that may occur by adhering to the derived competency standard. To determine radiograph interpretation difficulty scores, 244 emergency physicians interpreted 1,835 pediatric musculoskeletal extremity radiographs. Analyses of these data demonstrated that the median interpretation difficulty rating of the radiographs was −1.8 logits (IQR −4.1, 3.2), with a significant difference of difficulty across body regions (p < 0.0001). Physician review classified the radiographs as 1,055 (57.8%) as low, 424 (23.1%) medium or 356 (19.1%) high clinical significance. The multidisciplinary panel suggested a range of acceptable scores between cells in the three-by-three table of 76% to 95% and the sum of equal-weighted scores resulted in an overall performance-based competency score of 85.5% accuracy. Of the 14.5% diagnostic interpretation errors that may occur at the bedside if this competency standard were implemented, 9.8% would be in radiographs of low-clinical significance, while 2.5% and 2.3% would be in radiographs of medium or high clinical significance, respectively. This study's novel integration of radiograph selection and a standard setting method could be used to empirically drive evidence-based competency standard for radiograph interpretation and can serve as a model for deriving competency thresholds for clinical tasks emphasizing visual diagnosis. [ABSTRACT FROM AUTHOR]