Validation of a Modified Jefferson Scale of Empathy for Observers to Assess Trainees

Objective“Demonstrate insight and understanding into emotion” is a competency amenable to simulation-based assessment. The Jefferson Scale of Patient Perceptions of Physician Empathy (JSPPPE) has validity evidence for patients to assess provider empathy. A version adapted for a third-party observers does not exist. Our aim was to modify the JSPPPE and use recorded standardized encounters to obtain validity evidence.MethodsThis cross-sectional study used video and data collected from 2 pediatric residencies. In 2018, 4 raters reviewed 24 videos of 12 interns communicating with standardized patients (SP) in 2 encounters and completed a modified JSPPE for observers (JSEO). Reliability between raters was established using Intraclass Correlations (ICC). JSEO mean scores were correlated to Essential Elements of Communication (EEC), JSPPPE, and faculty composite interpersonal communication (IC) scores using Spearman Rank.ResultsThe mean ICC for all 4 raters was 0.573 (0.376–0.755). When ICC was calculated for pairs of raters, Rater 1 was an outlier. ICCs for mean scores for pairs among the 3 remaining raters was 0.81 to 0.84. Mean JSEO scores from the four raters correlated with the JSPPPE (rho = 0.45, P = .03) and IC (rho = 0.68, P < .001), but not the EEC (rho = 0.345, P = .1).ConclusionsWe found validity evidence for the use of a modified JSPPPE for an observer to assess empathy in a recorded encounter with a SP. This may be useful as medical educators shift toward competency-based tracking. The brevity of this tool and potential assessment using video are also appealing.     

The effect of caffeine abstinence on sleep among habitual caffeine users with poor sleep

Caffeine is the most widely used psychoactive substance in the world and is known to disrupt healthy sleep. However, very few studies have directly tested the effect of caffeine abstinence on sleep, and these have yielded inconsistent findings. The purpose of the present study was to examine changes in sleep following caffeine abstinence and examine the extent to which characteristics of habitual caffeine use moderated this change. Participants included 66 healthy, young adults with habitual caffeine use and poor sleep. During the 2‐week baseline, sleep was assessed using wrist actigraphy and daily caffeine use was assessed with bedtime diaries. Eligible participants then completed 1 week of caffeine abstinence, during which sleep was measured with wrist actigraphy. Multilevel models found no significant differences between either mean levels or growth trajectories of total sleep time or sleep efficiency between baseline and caffeine abstinence. Mean levels of sleep onset latency also did not differ between baseline and caffeine abstinence. A small but significant quadratic effect was observed, such that sleep onset latency decreased during the first few days of caffeine abstinence, then increased to levels above baseline. Characteristics of caffeine use did not moderate changes in sleep between baseline and caffeine abstinence. These data suggest that abstaining from caffeine may not result in long‐term sleep improvement for habitual caffeine users, which contradicts the common sleep health recommendation. The present findings encourage more rigorous investigation of the effectiveness of caffeine restriction on sleep.     

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

PurposeAuto-contouring may reduce workload, interobserver variation, and time associated with manual contouring of organs at risk. Manual contouring remains the standard due in part to uncertainty around the time and workload savings after accounting for the review and editing of auto-contours. This preliminary study compares a standard manual contouring workflow with 2 auto-contouring workflows (atlas and deep learning) for contouring the bladder and rectum in patients with prostate cancer.Methods and MaterialsThree contouring workflows were defined based on the initial contour-generation method including manual (MAN), atlas-based auto-contour (ATLAS), and deep-learning auto-contour (DEEP). For each workflow, initial contour generation was retrospectively performed on 15 patients with prostate cancer. Then, radiation oncologists (ROs) edited each contour while blinded to the manner in which the initial contour was generated. Workflows were compared by time (both in initial contour generation and in RO editing), contour similarity, and dosimetric evaluation.ResultsMean durations for initial contour generation were 10.9 min, 1.4 min, and 1.2 min for MAN, DEEP, and ATLAS, respectively. Initial DEEP contours were more geometrically similar to initial MAN contours. Mean durations of the RO editing steps for MAN, DEEP, and ATLAS contours were 4.1 min, 4.7 min, and 10.2 min, respectively. The geometric extent of RO edits was consistently larger for ATLAS contours compared with MAN and DEEP. No differences in clinically relevant dose-volume metrics were observed between workflows.ConclusionAuto-contouring software affords time savings for initial contour generation; however, it is important to also quantify workload changes at the RO editing step. Using deep-learning auto-contouring for bladder and rectum contour generation reduced contouring time without negatively affecting RO editing times, contour geometry, or clinically relevant dose–volume metrics. This work contributes to growing evidence that deep-learning methods are a clinically viable solution for organ-at-risk contouring in radiation therapy.     

Therapeutics and delivery vehicles for local treatment of osteomyelitis

Osteomyelitis, or the infection of the bone, presents a major complication in orthopedics and may lead to prolonged hospital visits, implant failure, and in more extreme cases, amputation of affected limbs. Typical treatment for this disease involves surgical debridement followed by long-term, systemic antibiotic administration, which contributes to the development of antibiotic-resistant bacteria and has limited ability to eradicate challenging biofilm-forming pathogens including Staphylococcus aureus—the most common cause of osteomyelitis. Local delivery of high doses of antibiotics via traditional bone cement can reduce systemic side effects of an antibiotic. Nonetheless, growing concerns over burst release (then subtherapeutic dose) of antibiotics, along with microbial colonization of the nondegradable cement biomaterial, further exacerbate antibiotic resistance and highlight the need to engineer alternative antimicrobial therapeutics and local delivery vehicles with increased efficacy against, in particular, biofilm-forming, antibiotic-resistant bacteria. Furthermore, limited guidance exists regarding both standardized formulation protocols and validated assays to predict efficacy of a therapeutic against multiple strains of bacteria. Ideally, antimicrobial strategies would be highly specific while exhibiting a broad spectrum of bactericidal activity. With a focus on S. aureus infection, this review addresses the efficacy of novel therapeutics and local delivery vehicles, as alternatives to the traditional antibiotic regimens. The aim of this review is to discuss these components with regards to long bone osteomyelitis and to encourage positive directions for future research efforts.