incorporated the program director, program coordinator, and residents into each roadshow experience.We began by using geographic filters to focus on applicants with ties to our 3-state region for the roadshow. After review of application credentials, we selected an average of 90 candidates for interviews. We then identified 4 regional cities that are home to academic medical centers (Augusta, Greenville/Spartanburg, Chapel Hill, and Charleston). Candidates were selected for individual days based on geographic proximity (FIGURE). Recruitment Roadshow days were divided into morning and afternoon sessions to minimize candidate time away from campus. All informational material, including information on current residents, program policies, local attractions, and contact information, were given to candidates in electronic format on a customized USB flash drive.The program director, program coordinator, and at least one resident representative with prior educational connections to the city-specific academic medical center traveled to each roadshow location. Information sessions and interviews were held at hotels in close proximity to each academic medical center. Two additional on-campus interview days with associated ''open houses'' at our institution were offered for applicants who were unable to attend the regional interviews, or for those regional participants who wanted to visit our institution in person. Outcomes to DateIn the 3 years since the Residency Recruitment Roadshow inception, 157 candidates have been interviewed through this program. An additional 94 applicants were scheduled for interviews on open house days at our institution. A total of 210 of 252 candidates (92%) attended medical school in either Georgia, South Carolina, or North Carolina. Nearly 85% of candidates (132 of 157) traveled less than 30 minutes to attend the interview. Feedback from applicants was universally positive regarding this regional interview concept.We present the Residency Recruitment Roadshow as a potential strategy for other residency programs to emulate for successful regionally targeted, candidatecentered recruitment. Our approach reduces time and financial burdens on applicants while still providing in-person interactions with key program leadership and current residents as they embark on their graduate medical education journey.Substance misuse is not consistently addressed within the scope of routine medical practice. More than 90% of primary care physicians fail to diagnose substance misuse when presented with early symptoms of alcohol or drug misuse in an adult patient. Screening, Brief Intervention, and Referral to Treatment (SBIRT) is an integrated, evidence-based approach aimed at delivering early intervention in medical settings for drug and alcohol misuse. An integral component of SBIRT is motivational interviewing (MI), a brief, evidence-based, interventional practice that has been demonstrated to be highly effective in triggering change in high-risk lifestyle behaviors. MI is a patient-focused conversation betwe...
Background Motivational interviewing (MI) is an evidence-based, brief interventional approach that has been demonstrated to be highly effective in triggering change in high-risk lifestyle behaviors. MI tends to be underutilized in clinical settings, in part because of limited and ineffective training. To implement MI more widely, there is a critical need to improve the MI training process in a manner that can provide prompt and efficient feedback. Our team has developed and tested a training tool, Real-time Assessment of Dialogue in Motivational Interviewing (ReadMI), that uses natural language processing (NLP) to provide immediate MI metrics and thereby address the need for more effective MI training. Methods Metrics produced by the ReadMI tool from transcripts of 48 interviews conducted by medical residents with a simulated patient were examined to identify relationships between physician-speaking time and other MI metrics, including the number of open- and closed-ended questions. In addition, interrater reliability statistics were conducted to determine the accuracy of the ReadMI’s analysis of physician responses. Results The more time the physician spent talking, the less likely the physician was engaging in MI-consistent interview behaviors ( r = −0.403, p = 0.007), including open-ended questions, reflective statements, or use of a change ruler. Conclusion ReadMI produces specific metrics that a trainer can share with a student, resident, or clinician for immediate feedback. Given the time constraints on targeted skill development in health professions training, ReadMI decreases the need to rely on subjective feedback and/or more time-consuming video review to illustrate important teaching points.
Interruption dissemination in proactive systems remains a challenge for efficient human-machine collaboration, especially in real-time distributed collaborative environments. In this paper a real-time interruption management system (IMS) is proposed that leverages speech information, the most commonly used and available means of communication within collaborative distributed environments. The key aspect of this paper includes a proposed real-time IMS system that leverages lexical affirmation cues to infer the end of a task or task boundary as a candidate interruption time. The performance results show the proposed real-time lexical Affirmation Cues based Interruption Management System (ACE-IMS) outperforms the current baseline real-time IMS system within the existing literature. ACE-IMS has the potential of reducing disruptive interruptions without incurring excessive missed opportunities to disseminate interruptions by utilizing only the most frequently used mode of human communication: voice. Thereby, providing a promising new baseline to further the system development of real-time interruption management systems within the ever-growing distributed collaborative domain.
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