Assessment of Medical Students’ Shared Decision-Making in Standardized Patient Encounters

BackgroundShared decision-making, in which physicians and patients openly explore beliefs, exchange information, and reach explicit closure, may represent optimal physician-patient communication. There are currently no universally accepted methods to assess medical students' competence in shared decision-making.ObjectiveTo characterize medical students' shared decision-making with standardized patients (SPs) and determine if students' use of shared decision-making correlates with SP ratings of their communication.DesignRetrospective study of medical students' performance with four SPs.ParticipantsSixty fourth-year medical students.MeasurementsObjective blinded coding of shared decision-making quantified as decision moments (exploration/articulation of perspective, information sharing, explicit closure for a particular decision); SP scoring of communication skills using a validated checklist.ResultsOf 779 decision moments generated in 240 encounters, 312 (40%) met criteria for shared decision-making. All students engaged in shared decision-making in at least two of the four cases, although in two cases 5% and 12% of students engaged in no shared decision-making. The most commonly discussed decision moment topics were medications (n = 98, 31%), follow-up visits (71, 23%), and diagnostic testing (44, 14%). Correlations between the number of decision moments in a case and students' communication scores were low (rho = 0.07 to 0.37).ConclusionsAlthough all students engaged in some shared decision-making, particularly regarding medical interventions, there was no correlation between shared decision-making and overall communication competence rated by the SPs. These findings suggest that SP ratings of students' communication skill cannot be used to infer students' use of shared decision-making. Tools to determine students' skill in shared decision-making are needed

The Relative Contribution of High-Gamma Linguistic Processing Stages of Word Production, and Motor Imagery of Articulation in Class Separability of Covert Speech Tasks in EEG Data

Word production begins with high-Gamma automatic linguistic processing functions followed by speech motor planning and articulation. Phonetic properties are processed in both linguistic and motor stages of word production. Four phonetically dissimilar phonemic structures “BA”, “FO”, “LE”, and “RY” were chosen as covert speech tasks. Ten neurologically healthy volunteers with the age range of 21–33 participated in this experiment. Participants were asked to covertly speak a phonemic structure when they heard an auditory cue. EEG was recorded with 64 electrodes at 2048 samples/s. Initially, one-second trials were used, which contained linguistic and motor imagery activities. The four-class true positive rate was calculated. In the next stage, 312 ms trials were used to exclude covert articulation from analysis. By eliminating the covert articulation stage, the four-class grand average classification accuracy dropped from 96.4% to 94.5%. The most valuable features emerge after Auditory cue recognition (~100 ms post onset), and within the 70–128 Hz frequency range. The most significant identified brain regions were the Prefrontal Cortex (linked to stimulus driven executive control), Wernicke’s area (linked to Phonological code retrieval), the right IFG, and Broca’s area (linked to syllabification). Alpha and Beta band oscillations associated with motor imagery do not contain enough information to fully reflect the complexity of speech movements. Over 90% of the most class-dependent features were in the 30-128 Hz range, even during the covert articulation stage. As a result, compared to linguistic functions, the contribution of motor imagery of articulation in class separability of covert speech tasks from EEG data is negligible

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin

Advancing theories, models and measurement for an interprofessional approach to shared decision making in primary care: a study protocol.

Contains fulltext : 69578.pdf (publisher's version ) (Open Access)BACKGROUND: Shared decision-making (SDM) is defined as a process by which a healthcare choice is made by practitioners together with the patient. Although many diagnostic and therapeutic processes in primary care integrate more than one type of health professional, most SDM conceptual models and theories appear to be limited to the patient-physician dyad. The objectives of this study are to develop a conceptual model and propose a set of measurement tools for enhancing an interprofessional approach to SDM in primary healthcare. METHODS/DESIGN: An inventory of SDM conceptual models, theories and measurement tools will be created. Models will be critically assessed and compared according to their strengths, limitations, acknowledgement of interprofessional roles in the process of SDM and relevance to primary care. Based on the theory analysis, a conceptual model and a set of measurements tools that could be used to enhance an interprofessional approach to SDM in primary healthcare will be proposed and pilot-tested with key stakeholders and primary healthcare teams. DISCUSSION: This study protocol is informative for researchers and clinicians interested in designing and/or conducting future studies and educating health professionals to improve how primary healthcare teams foster active participation of patients in making health decisions using a more coordinated approach