Investigation of divergent thinking among surgeons and surgeon trainees in Canada (IDEAS): a mixed-methods study.

OBJECTIVE: To assess the creative potential of surgeons and surgeon trainees, as measured by divergent thinking. The secondary objectives were to identify factors associated with divergent thinking, assess confidence in creative problem-solving and the perceived effect of surgical training on creative potential, and explore the value of creativity in surgery. DESIGN: We used a mixed-methods design, conducting a survey of divergent thinking ability using a validated questionnaire followed by two semi-structured interviews with top-scoring participants. PARTICIPANTS & SETTING: Surgeons and surgeon trainees in the Department of Surgery at McMaster University. OUTCOMES: The primary outcome was divergent thinking, assessed with the Abbreviated Torrance Test for Adults. Participants also self-assessed their confidence in creative problem-solving and the effect of surgical training on their creative potential. We performed descriptive analyses and multivariable linear regression to identify factors associated with divergent thinking. We conducted a thematic analysis of the interview responses. RESULTS: 82 surgeons and surgeon trainees were surveyed; 43 were junior trainees and 28 were senior trainees. General surgery, orthopaedic surgery and plastic surgery represented 71.9% of the participants. The median participant age was 28 years (range 24-73), 51.2% of whom were female. Participants demonstrated levels of divergent thinking that were higher but not meaningfully different from the adult norm (62.39 (95% CI 61.25, 63.53), p<0.001). While participants scored significantly higher than the average adult on fluency (the ability to produce quantities of ideas) and flexibility (the ability to process information in different ways) (p<0.001 for both), they scored below average on originality (the ability to produce uncommon, new or unique ideas) (p<0.001). Regression analysis identified higher divergent thinking scores among females (estimated ß=-3.58 (95% CI -6.25 to -0.90), p=0.010). CONCLUSIONS: The divergent thinking ability among surgeons and surgeon trainees was not meaningfully different from the adult normative score; however, their ability to generate original ideas was below average.

The McMaster Narrative Comment Rating Tool: Development and Initial Validity Evidence.

CONSTRUCT: The McMaster Narrative Comment Rating Tool aims to capture critical features reflecting the quality of written narrative comments provided in the medical education context: valence/tone of language, degree of correction versus reinforcement, specificity, actionability, and overall usefulness. BACKGROUND: Despite their role in competency-based medical education, not all narrative comments contribute meaningfully to the development of learners' competence. To develop solutions to mitigate this problem, robust measures of narrative comment quality are needed. While some tools exist, most were created in specialty-specific contexts, have focused on one or two features of feedback, or have focused on faculty perceptions of feedback, excluding learners from the validation process. In this study, we aimed to develop a detailed, broadly applicable narrative comment quality assessment tool that drew upon features of high-quality assessment and feedback and could be used by a variety of raters to inform future research, including applications related to automated analysis of narrative comment quality. APPROACH: In Phase 1, we used the literature to identify five critical features of feedback. We then developed rating scales for each of the features, and collected 670 competency-based assessments completed by first-year surgical residents in the first six-weeks of training. Residents were from nine different programs at a Canadian institution. In Phase 2, we randomly selected 50 assessments with written feedback from the dataset. Two education researchers used the scale to independently score the written comments and refine the rating tool. In Phase 3, 10 raters, including two medical education researchers, two medical students, two residents, two clinical faculty members, and two laypersons from the community, used the tool to independently and blindly rate written comments from another 50 randomly selected assessments from the dataset. We compared scores between and across rater pairs to assess reliability. FINDINGS: Single and average measures intraclass correlation (ICC) scores ranged from moderate to excellent (ICCs = .51-.83 and .91-.98) across all categories and rater pairs. All tool domains were significantly correlated (p's <.05), apart from valence, which was only significantly correlated with degree of correction versus reinforcement. CONCLUSION: Our findings suggest that the McMaster Narrative Comment Rating Tool can reliably be used by multiple raters, across a variety of rater types, and in different surgical contexts. As such, it has the potential to support faculty development initiatives on assessment and feedback, and may be used as a tool to conduct research on different assessment strategies, including automated analysis of narrative comments.

A History of Musculoskeletal Medicine and Its Place and Progress in Undergraduate Medical Education.

Musculoskeletal diseases are responsible for some of the most prevalent conditions affecting population health in the world. Despite the prevalence of these conditions, musculoskeletal medicine has a fraught history within the world of undergraduate medical education. We review the origins of musculoskeletal medicine, its evolution in undergraduate medical education, and progress that has been made over the last decade as a result of global initiatives such as the Bone and Joint Decade. Understanding the history of musculoskeletal medicine is essential to contextualizing the problems that exist today and creating comprehensive solutions to fill the gaps that persist in musculoskeletal curricula.

Automated grading of anatomical objective structured practical examinations using decision trees: An artificial intelligence approach.

An Objective Structured Practical Examination (OSPE) is an effective and robust, but resource-intensive, means of evaluating anatomical knowledge. Since most OSPEs employ short answer or fill-in-the-blank style questions, the format requires many people familiar with the content to mark the examinations. However, the increasing prevalence of online delivery for anatomy and physiology courses could result in students losing the OSPE practice that they would receive in face-to-face learning sessions. The purpose of this study was to test the accuracy of Decision Trees (DTs) in marking OSPE questions as a first step to creating an intelligent, online OSPE tutoring system. The study used the results of the winter 2020 semester final OSPE from McMaster University's anatomy and physiology course in the Faculty of Health Sciences (HTHSCI 2FF3/2LL3/1D06) as the data set. Ninety percent of the data set was used in a 10-fold validation algorithm to train a DT for each of the 54 questions. Each DT was comprised of unique words that appeared in correct, student-written answers. The remaining 10% of the data set was marked by the generated DTs. When the answers marked by the DT were compared to the answers marked by staff and faculty, the DT achieved an average accuracy of 94.49% across all 54 questions. This suggests that machine learning algorithms such as DTs are a highly effective option for OSPE grading and are suitable for the development of an intelligent, online OSPE tutoring system.

Investigating divergent thinking and creative ability in surgeons (IDEAS): a survey protocol.

INTRODUCTION: A strong pipeline of creative ideas and individuals is critical if we are to tackle the complex healthcare challenges we will face in the 21st century. The field of creativity is severely underinvestigated in the context of surgery, and it is of interest to explore the level and nature of creativity in surgeons, across various specialties and backgrounds. Identifying the areas of surgery with strong and weak levels of creativity, as well as the predictors of high creativity among surgeons, may aid in the selection and training of future surgeons. METHODS AND ANALYSIS: A convenience sample of surgeons from the Department of Surgery and McMaster University will be used for the recruitment of participants. The Abbreviated Torrance Test for Adults, a three-part test of divergent thinking ability, will be administered to measure the level and nature of creativity among surgeons. Descriptive analyses and multiple linear regression models are planned to synthesise the results of the survey and identify predictors of divergent thinking ability among surgeons. ETHICS AND DISSEMINATION: Ethics approval from the Hamilton Integrated Research Ethics Board was obtained. No harm is expected due to participation in this study. The results of this survey will be published in a peer-reviewed journal and disseminated through conferences and presentations at the regional, national and international levels.

Cognitive and social well-being in older adulthood: The CoSoWELL corpus of written life stories.

This paper presents the Cognitive and Social WELL-being (CoSoWELL) project that consists of two components. One is a large corpus of narratives written by over 1000 North American older adults (55+ years old) in five test sessions before and during the first year of the COVID-19 pandemic. The other component is a rich collection of socio-demographic data collected through a survey from the same participants. This paper introduces the first release of the corpus consisting of 1.3 million tokens and the survey data (CoSoWELL version 1.0). It also presents a series of analyses validating design decisions for creating the corpus of narratives written about personal life events that took place in the distant past, recent past (yesterday) and future, along with control narratives. We report results of computational topic modeling and linguistic analyses of the narratives in the corpus, which track the time-locked impact of the COVID-19 pandemic on the content of autobiographical memories before and during the COVID-19 pandemic. The main findings demonstrate a high validity of our analytical approach to unique narrative data and point to both the locus of topical shifts (narratives about recent past and future) and their detailed timeline. We make the CoSoWELL corpus and survey data available to researchers and discuss implications of our findings in the framework of research on aging and autobiographical memories under stress.

Personhood and aging: Exploring the written narratives of older adults as articulations of personhood in later life.

Personhood is a complex concept in gerontological research. It is often used to explore the maintenance or reconstruction of self-identity. Narrative analysis has commonly explored how the stories that older individuals living with cognitive impairment(s) produce preserve the personhood that is perceived to be threatened by cognitive decline. This article moves beyond this exploration by focusing on the experiences of aging more generally to better understand how non-cognitively impaired older adults construct personhood through narrative writing. This article uses thematic narrative analysis and argues that older adults articulate personhood through written narratives by creating coherent constructions of self. Importantly, it demonstrates that older adults are concerned with maintaining a sense of self rather than embracing changed aspects of identity in accordance with popularized conceptualizations of personhood as well as ideals of coherence and consistency promoted in successful and active aging discourses.

Comparing the Quality of Narrative Comments by Rotation Setting.

OBJECTIVE: To investigate the effect of rotation setting on trainee-directed narrative comments within a Canadian General Surgery Residency Program. The primary outcome was to use the McMaster Narrative Comment Rating Scale (MNCRS) to evaluate the quality of narrative comments across five domains: valence of language, degree of correction versus reinforcement, specificity, actionability and overall usefulness. As distributed medical education in the postgraduate training context becomes more prevalent, delineating differences in feedback between various sites will be imperative, as it may affect how narrative comments are interpreted by clinical competency committee (CCC) members. DESIGN, SETTING, AND PARTICIPANTS: A retrospective analysis of 2,469 assessments obtained between July 1, 2014 and May 5, 2019 from the General Surgery Residency Program at the University of British Columbia (UBC) was conducted. Narrative comments were rated using the McMaster Narrative Comment Rating Scale (MNCRS), a validated instrument for evaluating the quality of narrative comments. A repeated measures Analysis of Variance (ANOVA) was conducted to explore the impact of rotation setting, academic, urban tertiary, distributed urban, and distributed rural on the quality of narrative feedback. RESULTS: Overall, the quality of the narrative comments varied substantially between and within rotation settings. Academic sites tended to provide more actionable comments (p = 0.01) and more corrective versus reinforcing comments, compared with other sites (p's < 0.01). Comments produced by the urban tertiary rotation setting were consistently lower in quality across all scale categories compared with other settings (p's < 0.01). CONCLUSION: The type of rotation setting has a significant effect on the quality of faculty feedback for trainees. Faculty development on the provision of feedback is necessary, regardless of rotation setting, and should appropriately combine rotation-specific needs and overarching program goals to ensure trainees and clinical competence committees receive high quality narrative.

Competence committees: The steep climb from concept to implementation.

INTRODUCTION: Competence committees (CCs) are groups of educators tasked with reviewing resident progress throughout their training, making decisions regarding the achievement of Entrustable Professional Activities and recommendations regarding promotion and remediation. CCs have been mandated as part of competency-based medical education programmes worldwide; however, there has yet to be a thorough examination of the implementation challenges they face and how this impacts their functioning and decision-making processes. This study examined CC implementation at a Canadian institution, documenting the shared and unique challenges that CCs faced and overcame over a 3-year period. METHODS: This study consisted of three phases, which were conceptually and analytically linked using Moran-Ellis and colleagues' notion of 'following a thread.' Phase 1 examined the early perceptions and experiences of 30 key informants using a survey and semi-structured interviews. Phase 2 provided insight into CCs' operations through a survey sent to 35 CC chairs 1-year post-implementation. Phase 3 invited 20 CC members to participate in semi-structured interviews to follow up on initial themes 2 years post-implementation. Detailed observation notes from 16 CC meetings across nine disciplines were used to corroborate the findings from each phase. RESULTS: Response rates in each phase were 83% (n = 25), 43% (n = 15) and 60% (n = 12), respectively. Despite the high degree of support for CCs among faculty and resident members, several ongoing challenges were highlighted: adapting to programme size, optimising membership, engaging residents, maintaining capacity among members, sharing and aggregating data and developing a clear mandate. DISCUSSION: Findings of this study reinforce the importance of resident engagement and information sharing between disciplines. Challenges faced by CCs are discussed in relation to the existing literature to inform a better understanding of group decision-making processes in medical education. Future research could compare implementation practices across sites and explore which adaptations lead to better or worse decision-making outcomes.

Recent evidence on visual-spatial ability in surgical education: A scoping review.

BACKGROUND: Understanding the relationships between structures is critical for surgical trainees. However, the heterogeneity of the literature on visual-spatial ability (VSA) in surgery makes it challenging for educators to make informed decisions on incorporating VSA into their programs. We conducted a scoping review of the literature on VSA in surgery to provide a map of the literature and identify where gaps still exist for future research. METHODS: We searched databases until December 2019 using keywords related to VSA and surgery. The resulting articles were independently screened by two researchers for inclusion in our review. RESULTS: We included 117 articles in the final review. Fifty-nine articles reported significant correlations between VSA tests and surgical performance, and this association is supported by neuroimaging studies. However, it remains unclear whether VSA should be incorporated into trainee selection and whether there is a benefit of three-dimensional (3D) over two-dimensional (2D) training. CONCLUSIONS: It appears that VSA correlates with surgical performance in the simulated environment, particularly for novice learners. Based on our findings, we make suggestions for how surgical educators may use VSA to support novice learners. Further research should determine whether VSA remains correlated to surgical performance when trainees move into the operative environment.

CONTEXTE: Il est fondamental pour les chirurgiens en formation de comprendre les liens qui unissent les diverses structures corporelles. Étant donné l'hétérogénéité de la littérature portant sur les habiletés visuo-spatiales (HVS) nécessaires en chirurgie, les éducateurs ont de la difficulté à prendre des décisions éclairées quant à l'enseignement des HVS dans leurs programmes. On a effectué une étude exploratoire de la littérature sur les HVS en chirurgie afin de répertorier la littérature et de cerner des lacunes pouvant faire l'objet de recherches ultérieures. MÉTHODOLOGIE: On a interrogé des bases de données jusqu'à décembre 2019 à l'aide de mots-clés reliés aux HVS et à la chirurgie. Les articles trouvés ont été évalués de façon indépendante par deux chercheurs pour déterminer leur inclusion à la revue. RÉSULTATS: Au total, 117 articles ont été inclus dans la revue finale. Cinquante-neuf faisaient état d'importantes corrélations entre les tests d'évaluation des HVS et la performance chirurgicale. Cette association est étayée par les résultats d'études en neuro-imagerie. Il n'est pas clair cependant si les HVS devraient faire partie des critères de sélection des résidents et si une formation sur les techniques de visualisation en trois dimensions (3D) est préférable à une formation sur les techniques de visualisation en deux dimensions (2D). CONCLUSIONS: Il semble exister un lien entre les HVS et la performance chirurgicale en contexte de simulation, particulièrement chez les apprenants novices. À la lumière de nos résultats, nous présentons des recommandations sur la façon dont les formateurs en chirurgie pourraient se servir des HVS pour aider les apprenants novices. D'autres travaux de recherche devraient permettre de savoir si les HVS restent reliés à la performance chirurgicale lorsque les stagiaires passent à un environnement opératoire réel.

On the time-course of functional connectivity: theory of a dynamic progression of concussion effects.

The current literature presents a discordant view of mild traumatic brain injury and its effects on the human brain. This dissonance has often been attributed to heterogeneities in study populations, aetiology, acuteness, experimental paradigms and/or testing modalities. To investigate the progression of mild traumatic brain injury in the human brain, the present study employed data from 93 subjects (48 healthy controls) representing both acute and chronic stages of mild traumatic brain injury. The effects of concussion across different stages of injury were measured using two metrics of functional connectivity in segments of electroencephalography time-locked to an active oddball task. Coherence and weighted phase-lag index were calculated separately for individual frequency bands (delta, theta, alpha and beta) to measure the functional connectivity between six electrode clusters distributed from frontal to parietal regions across both hemispheres. Results show an increase in functional connectivity in the acute stage after mild traumatic brain injury, contrasted with significantly reduced functional connectivity in chronic stages of injury. This finding indicates a non-linear time-dependent effect of injury. To understand this pattern of changing functional connectivity in relation to prior evidence, we propose a new model of the time-course of the effects of mild traumatic brain injury on the brain that brings together research from multiple neuroimaging modalities and unifies the various lines of evidence that at first appear to be in conflict.

The role of gender in the decision to pursue a surgical career: A qualitative, interview-based study.

BACKGROUND: Previous literature has explored the underrepresentation of women in surgery. However, this research has often been quantitative or limited by considering only the perspectives and experiences of women at more advanced career stages. Here, we use a qualitative methodology and a sample of women and men across the career continuum to identify the role that gender plays in the decision to pursue a surgical career. METHODS: We audio-recorded and transcribed semi-structured interviews conducted with 12 women and 12 men ranging in their level of medical training from medical students to residents to staff surgeons. We used Braun and Clarke's six-step approach to thematic analysis to analyze the data, maintaining trustworthiness and credibility by employing strategies including reflexivity and participant input. RESULTS: Our findings suggested that the characteristics of surgery and early exposure to the profession served as important factors in participants' decisions to pursue a surgical career. Although not explicitly mentioned by participants, each of these areas may implicitly be gendered. Gender-based factors explicitly mentioned by participants included the surgical lifestyle and experiences with gender discrimination, including sexual harassment. These factors were perceived as challenges that disproportionately affected women and needed to be overcome when pursuing a surgical career. CONCLUSIONS: Our findings suggest that gender is more likely to act as a barrier to a career in surgery than as a motivator, especially among women. This suggests a need for early experiences in the operating room and mentorship. Policy change promoting work-life integration and education to target gender discrimination is also recommended.

CONTEXTE: Des publications antérieures ont exploré la sous-représentation des femmes en chirurgie. Toutefois, cette recherche a souvent été quantitative ou limitée en considérant uniquement les perspectives et expériences de femmes à des stades plus avancés de leur carrière. Ici, nous utilisons une méthodologie qualitative et un échantillon de femmes et d'hommes a des stades différents de leur carrière pour établir le rôle que le genre joue dans la décision de poursuivre une carrière en chirurgie. MÉTHODES: Nous avons enregistré et transcrit des entrevues semi-structurées menées avec douze femmes et douze hommes, dont la formation médicale variait d'étudiants en médecine à résidents et à chirurgiens membres du personnel hospitalier. Nous avons utilisé l'analyse thématique en six étapes de Braun et Clarke pour analyser les données, conservant la fiabilité et la crédibilité en utilisant des stratégies qui comprenaient la réflexivité et les commentaires des participants. RÉSULTATS: Nos résultats suggèrent que les caractéristiques de la chirurgie et d'une exposition précoce à la profession constituaient des facteurs importants dans la décision des participants de poursuivre une carrière en chirurgie. Bien que ce n'était pas explicitement mentionné par les participants, chacun de ces domaines peut être implicitement sexospécifique. Les facteurs fondés sur le genre mentionnés explicitement par les participants comprenaient le mode de vie chirurgical et les expériences avec la discrimination fondée sur le sexe, y compris le harcèlement sexuel. Ces facteurs étaient perçus comme des obstacles qui touchaient de manière disproportionnée les femmes et qui devaient être surmontés dans la poursuite d'une carrière en chirurgie. CONCLUSIONS: Nos résultats suggèrent que le genre est plus susceptible d'agir comme un obstacle à une carrière en chirurgie que comme facteur de motivation, plus particulièrement chez les femmes. Cela suggère un besoin pour des expériences précoces dans la salle d'opération et le mentorat. Un changement dans la politique favorisant l'intégration travail-vie et une éducation pour cibler la discrimination fondée sur le genre est également recommandé.

Use of the KT-MCC strategy to improve the quality of decision making for multidisciplinary cancer conferences: a pilot study.

BACKGROUND: Multidisciplinary Cancer Conferences (MCCs) are increasingly used to guide treatment decisions for patients with cancer, though numerous barriers to optimal MCC decision-making quality have been identified. We aimed to improve the quality of MCC decision making through the use of an implementation bundle titled the KT-MCC Strategy. The Strategy included use of discussion tools (standard case intake tool and a synoptic discussion tool), workshops, MCC team and chair training, and audit and feedback. Implementation strategies were selected using a theoretically-rooted and integrated KT approach, meaning members of the target population (MCC participants) assisted with the design and implementation of the intervention and strategies. We evaluated implementation quality of the KT-MCC Strategy and initial signals of impact on decision making quality. METHODS: This was a before-and-after study design among 4 MCC teams. Baseline data (before-phase) were collected for a period of 2 months to assess the quality of MCC decision making. Study teams selected the intervention strategies they wished to engage with. Post-intervention data (after-phase) were collected for 4 months. Implementation quality outcomes included reach, adherence/fidelity and adaptation. We also evaluated feasibility of data management. Decision making quality was evaluated on a per-case and per-round level using the MTB-MODe and MDT-OARS tools, respectively. RESULTS: There were a total of 149 cases and 23 MCCs observed in the before phase and 260 cases and 35 MCCs observed in the after phase. Teams implemented 3/5 strategies; adherence to selected strategies varied by MCC team. The per-round quality of MCCs improved by 11% (41.0 to 47.3, p = < 0.0001). The quality of per-case decision-making did not improve significantly (32.3 to 32.6, p = 0.781). CONCLUSION: While per round MCC decision making quality improved significantly, per-case decision-making quality did not. We posit that the limited improvements on decision making quality may be attributed to implementation quality gaps, including a lack of uptake of and adherence to theoretically-identified implementation strategies. Our findings highlight the importance of evaluating implementation quality and processes, iterative testing, and engagement of key gatekeepers in the implementation process.

Use of the theoretical domains framework and behaviour change wheel to develop a novel intervention to improve the quality of multidisciplinary cancer conference decision-making.

BACKGROUND: Multidisciplinary Cancer Conferences (MCCs) are prospective meetings involving cancer specialists to discuss treatment plans for patients with cancer. Despite reported gaps in MCC quality, there have been few efforts to improve its functioning. The purpose of this study was to use theoretically-rooted knowledge translation (KT) theories and frameworks to inform the development of a strategy to improve MCC decision-making quality. METHODS: A multi-phased approach was used to design an intervention titled the KT-MCC Strategy. First, key informant interviews framed using the Theoretical Domains Framework (TDF) were conducted with MCC participants to identify barriers and facilitators to optimal MCC decision-making. Second, identified TDF domains were mapped to corresponding strategies using the COM-B Behavior Change Wheel to develop the KT-MCC Strategy. Finally, focus groups with MCC participants were held to confirm acceptability of the proposed KT-MCC Strategy. RESULTS: Data saturation was reached at n = 21 interviews. Twenty-seven barrier themes and 13 facilitator themes were ascribed to 11 and 10 TDF domains, respectively. Differences in reported barriers by physician specialty were observed. The resulting KT-MCC Strategy included workshops, chair training, team training, standardized intake forms and a synoptic discussion checklist, and, audit and feedback. Focus groups (n = 3, participants 18) confirmed the acceptability of the identified interventions. CONCLUSION: Myriad factors were found to influence MCC decision making. We present a novel application of the TDF and COM-B to the context of MCCs. We comprehensively describe the barriers and facilitators that impact MCC decision making and propose strategies that may positively impact the quality of MCC decision making.

Using Deep Learning Algorithms to Grade Hydronephrosis Severity: Toward a Clinical Adjunct.

Grading hydronephrosis severity relies on subjective interpretation of renal ultrasound images. Deep learning is a data-driven algorithmic approach to classifying data, including images, presenting a promising option for grading hydronephrosis. The current study explored the potential of deep convolutional neural networks (CNN), a type of deep learning algorithm, to grade hydronephrosis ultrasound images according to the 5-point Society for Fetal Urology (SFU) classification system, and discusses its potential applications in developing decision and teaching aids for clinical practice. We developed a five-layer CNN to grade 2,420 sagittal hydronephrosis ultrasound images [191 SFU 0 (8%), 407 SFU I (17%), 666 SFU II (28%), 833 SFU III (34%), and 323 SFU IV (13%)], from 673 patients ranging from 0 to 116.29 months old (M age = 16.53, SD = 17.80). Five-way (all grades) and two-way classification problems [i.e., II vs. III, and low (0-II) vs. high (III-IV)] were explored. The CNN classified 94% (95% CI, 93-95%) of the images correctly or within one grade of the provided label in the five-way classification problem. Fifty-one percent of these images (95% CI, 49-53%) were correctly predicted, with an average weighted F1 score of 0.49 (95% CI, 0.47-0.51). The CNN achieved an average accuracy of 78% (95% CI, 75-82%) with an average weighted F1 of 0.78 (95% CI, 0.74-0.82) when classifying low vs. high grades, and an average accuracy of 71% (95% CI, 68-74%) with an average weighted F1 score of 0.71 (95% CI, 0.68-0.75) when discriminating between grades II vs. III. Our model performs well above chance level, and classifies almost all images either correctly or within one grade of the provided label. We have demonstrated the applicability of a CNN approach to hydronephrosis ultrasound image classification. Further investigation into a deep learning-based clinical adjunct for hydronephrosis is warranted.

A multiple-trainee, multiple-level, multiple-competency (multi-TLC) simulation-based approach to training obstetrical emergencies.

Competency-based education requires that programs increase the breadth of direct observation and assessment to improve resident training. To achieve these goals, the authors developed and executed a multiple-trainee, multiple-level, multiple-competency (Multi-TLC) obstetrical emergencies simulation curriculum. Depending upon their training level (PGY1-PGY5), obstetrics and gynaecology residents participated in various roles (i.e., first responder, second responder, confederates, and evaluators) within four simulation scenarios designed to provide opportunities for education, direct observation, and assessment across a number of competencies (i.e., medical expert, communicator, collaborator, leader, advocate, and scholar). The curriculum was carried out over 8 h spread evenly across 2 days (i.e., 4 h/day) and involved periods of pre-briefing, live simulation, and debriefing. An evaluation of the Multi-TLC was operationalised via a context-input-process-product model. This report presents the outcomes of that evaluation derived from quasi-experimental comparisons of the new and previous curricula across four priorities for simulation-based education identified by the Department of Obstetrics and Gynecology at McMaster University (Hamilton, ON, Canada): increasing learning opportunities, maintaining or improving resident learning, maintaining or reducing program costs, and improving resident satisfaction. The evaluation revealed that the Multi-TLC curriculum permitted a greater breadth of direct observation and assessment across competencies, maintained the previous learning objectives while also addressing additional ones, and was done so in a way that reduced the overall financial and human resource costs associated with the department's obstetrical emergency simulation curriculum. A Multi-TLC organisation of simulation curricula can facilitate efficient application of competency-based education principles.

Individualized pattern recognition for detecting mind wandering from EEG during live lectures.

NEURAL CORRELATES OF MIND WANDERING: The ability to detect mind wandering as it occurs is an important step towards improving our understanding of this phenomenon and studying its effects on learning and performance. Current detection methods typically rely on observable behaviour in laboratory settings, which do not capture the underlying neural processes and may not translate well into real-world settings. We address both of these issues by recording electroencephalography (EEG) simultaneously from 15 participants during live lectures on research in orthopedic surgery. We performed traditional group-level analysis and found neural correlates of mind wandering during live lectures that are similar to those found in some laboratory studies, including a decrease in occipitoparietal alpha power and frontal, temporal, and occipital beta power. However, individual-level analysis of these same data revealed that patterns of brain activity associated with mind wandering were more broadly distributed and highly individualized than revealed in the group-level analysis. MIND WANDERING DETECTION: To apply these findings to mind wandering detection, we used a data-driven method known as common spatial patterns to discover scalp topologies for each individual that reflects their differences in brain activity when mind wandering versus attending to lectures. This approach avoids reliance on known neural correlates primarily established through group-level statistics. Using this method for individual-level machine learning of mind wandering from EEG, we were able to achieve an average detection accuracy of 80-83%. CONCLUSIONS: Modelling mind wandering at the individual level may reveal important details about its neural correlates that are not reflected when using traditional observational and statistical methods. Using machine learning techniques for this purpose can provide new insight into the varieties of neural activity involved in mind wandering, while also enabling real-time detection of mind wandering in naturalistic settings.

Development of a point of care system for automated coma prognosis: a prospective cohort study protocol.

INTRODUCTION: Coma is a deep state of unconsciousness that can be caused by a variety of clinical conditions. Traditional tests for coma outcome prediction are based mainly on a set of clinical observations. Recently, certain event-related potentials (ERPs), which are transient electroencephalogram (EEG) responses to auditory, visual or tactile stimuli, have been introduced as useful predictors of a positive coma outcome (ie, emergence). However, such tests require the skills of clinical neurophysiologists, who are not commonly available in many clinical settings. Additionally, none of the current standard clinical approaches have sufficient predictive accuracies to provide definitive prognoses. OBJECTIVE: The objective of this study is to develop improved machine learning procedures based on EEG/ERP for determining emergence from coma. METHODS AND ANALYSIS: Data will be collected from 50 participants in coma. EEG/ERP data will be recorded for 24 consecutive hours at a maximum of five time points spanning 30 days from the date of recruitment to track participants' progression. The study employs paradigms designed to elicit brainstem potentials, middle-latency responses, N100, mismatch negativity, P300 and N400. In the case of patient emergence, data are recorded on that occasion to form an additional basis for comparison. A relevant data set will be developed from the testing of 20 healthy controls, each spanning a 15-hour recording period in order to formulate a baseline. Collected data will be used to develop an automated procedure for analysis and detection of various ERP components that are salient to prognosis. Salient features extracted from the ERP and resting-state EEG will be identified and combined to give an accurate indicator of prognosis. ETHICS AND DISSEMINATION: This study is approved by the Hamilton Integrated Research Ethics Board (project number 4840). Results will be disseminated through peer-reviewed journal articles and presentations at scientific conferences. TRIAL REGISTRATION NUMBER: NCT03826407.

Video-Based Assessment in Surgical Education: A Scoping Review.

BACKGROUND AND OBJECTIVE: Video-based assessment of residents' surgical skills may offer several advantages over direct observations of clinical performance in terms of objectivity, time-efficiency, and feasibility. Although video-based assessment is becoming more common in surgical training, a broad understanding of its utility is lacking. This scoping review explores video-based assessment in surgical training and presents the evidence supporting its use. DESIGN: A literature search was conducted using the Web of Science database with key words related to video-based assessment and surgical training. Exclusion criteria included articles not published in English and articles on undergraduate medical education, continuing professional development, or non-surgical disciplines. Initially, 702 articles were identified; after title, abstract, and full-text screening by two independent reviewers (SM and VM), 199 articles remained. RESULTS: We present the benefits of video-based assessment, including the ability to capture clinical ability in the operating room without decreasing intraoperative efficiency, as well as the potential to improve formative assessment and feedback practices. We describe the validity, reliability, and challenges of video-based assessment, as well as the use of video-based methods in clinical and simulated settings. We conclude by discussing questions that remain to be addressed. CONCLUSIONS: Although further research and cost-benefit analyses are required, greater adoption of video-based assessment into surgical training may help meet increased assessment demands in an era of competency-based medical education.

From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes.

There has been increased effort to understand the neurophysiological effects of concussion aimed to move diagnosis and identification beyond current subjective behavioral assessments that suffer from poor sensitivity. Recent evidence suggests that event-related potentials (ERPs) measured with electroencephalography (EEG) are persistent neurophysiological markers of past concussions. However, as such evidence is limited to group-level analyzes, the extent to which they enable concussion detection at the individual-level is unclear. One promising avenue of research is the use of machine learning to create quantitative predictive models that can detect prior concussions in individuals. In this paper, we translate the recent group-level findings from ERP studies of concussed individuals into a machine learning framework for performing single-subject prediction of past concussion. We found that a combination of statistics of single-subject ERPs and wavelet features yielded a classification accuracy of 81% with a sensitivity of 82% and a specificity of 80%, improving on current practice. Notably, the model was able to detect concussion effects in individuals who sustained their last injury as much as 30 years earlier. However, failure to detect past concussions in a subset of individuals suggests that the clear effects found in group-level analyses may not provide us with a full picture of the neurophysiological effects of concussion.