Underlying construct of empathy, optimism, and burnout in medical students.

OBJECTIVE: This study was designed to explore the underlying construct of measures of empathy, optimism, and burnout in medical students. METHODS: Three instruments for measuring empathy (Jefferson Scale of Empathy, JSE); Optimism (the Life Orientation Test-Revised, LOT-R); and burnout (the Maslach Burnout Inventory, MBI, which includes three scales of Emotional Exhaustion, Depersonalization, and Personal Accomplishment) were administered to 265 third-year students at Sidney Kimmel (formerly Jefferson) Medical College at Thomas Jefferson University. Data were subjected to factor analysis to examine relationships among measures of empathy, optimism, and burnout in a multivariate statistical model. RESULTS: Factor analysis (principal component with oblique rotation) resulted in two underlying constructs, each with an eigenvalue greater than one. The first factor involved positive personality attributes (factor coefficients greater than .58 for measures of empathy, optimism, and personal accomplishment). The second factor involved negative personality attributes (factor coefficients greater than .78 for measures of emotional exhaustion, and depersonalization). CONCLUSIONS: Results confirmed that an association exists between empathy in the context of patient care and personality characteristics that are conducive to relationship building, and considered to be positive personality attributes, as opposed to personality characteristics that are considered as negative personality attributes that are detrimental to interpersonal relationships. Implications for the professional development of physicians-in-training and in-practice are discussed

Trauma Early Mortality Prediction Tool (TEMPT) for assessing 28-day mortality.

Background:Prior mortality prediction models have incorporated severity of anatomic injury quantified by Abbreviated Injury Severity Score (AIS). Using a prospective cohort, a new score independent of AIS was developed using clinical and laboratory markers present on emergency department presentation to predict 28-day mortality. Methods:All patients (n=1427) enrolled in an ongoing prospective cohort study were included. Demographic, laboratory, and clinical data were recorded on admission. True random number generator technique divided the cohort into derivation (n=707) and validation groups (n=720). Using Youden indices, threshold values were selected for each potential predictor in the derivation cohort. Logistic regression was used to identify independent predictors. Significant variables were equally weighted to create a new mortality prediction score, the Trauma Early Mortality Prediction Tool (TEMPT) score. Area under the curve (AUC) was tested in the validation group. Pairwise comparison of Trauma Injury Severity Score (TRISS), Revised Trauma Score, Glasgow Coma Scale, and Injury Severity Score were tested against the TEMPT score. Results:There was no difference between baseline characteristics between derivation and validation groups. In multiple logistic regression, a model with presence of traumatic brain injury, increased age, elevated systolic blood pressure, decreased base excess, prolonged partial thromboplastin time, increased international normalized ratio (INR), and decreased temperature accurately predicted mortality at 28 days (AUC 0.93, 95% CI 0.90 to 0.96, P<0.001). In the validation cohort, this score, termed TEMPT, predicted 28-day mortality with an AUC 0.94 (95% CI 0.92 to 0.97). The TEMPT score preformed similarly to the revised TRISS score for severely injured patients and was highly predictive in those having mild to moderate injury. Discussion:TEMPT is a simple AIS-independent mortality prediction tool applicable very early following injury. TEMPT provides an AIS-independent score that could be used for early identification of those at risk of doing poorly following even minor injury. Level of evidence:Level II

Finding the signal in the noise: Could social media be utilized for early hospital notification of multiple casualty events?

IntroductionDelayed notification and lack of early information hinder timely hospital based activations in large scale multiple casualty events. We hypothesized that Twitter real-time data would produce a unique and reproducible signal within minutes of multiple casualty events and we investigated the timing of the signal compared with other hospital disaster notification mechanisms.MethodsUsing disaster specific search terms, all relevant tweets from the event to 7 days post-event were analyzed for 5 recent US based multiple casualty events (Boston Bombing [BB], SF Plane Crash [SF], Napa Earthquake [NE], Sandy Hook [SH], and Marysville Shooting [MV]). Quantitative and qualitative analysis of tweet utilization were compared across events.ResultsOver 3.8 million tweets were analyzed (SH 1.8 m, BB 1.1m, SF 430k, MV 250k, NE 205k). Peak tweets per min ranged from 209-3326. The mean followers per tweeter ranged from 3382-9992 across events. Retweets were tweeted a mean of 82-564 times per event. Tweets occurred very rapidly for all events (<2 mins) and represented 1% of the total event specific tweets in a median of 13 minutes of the first 911 calls. A 200 tweets/min threshold was reached fastest with NE (2 min), BB (7 min), and SF (18 mins). If this threshold was utilized as a signaling mechanism to place local hospitals on standby for possible large scale events, in all case studies, this signal would have preceded patient arrival. Importantly, this threshold for signaling would also have preceded traditional disaster notification mechanisms in SF, NE, and simultaneous with BB and MV.ConclusionsSocial media data has demonstrated that this mechanism is a powerful, predictable, and potentially important resource for optimizing disaster response. Further investigated is warranted to assess the utility of prospective signally thresholds for hospital based activation

Local Currencies in Community Development or Too Much Mngwotngwotiki Is Bad For You

This useful resource guide for trainers and community activists discusses alternative currencies as part of creating alternative economic systems at the local level. The guide includes a case study of HOURS in Ithaca, New York and a discussion of the scripts and LETS alternative currency systems and their usefulness to community-development. The Tangu people of New Guinea have a word for what occurs between people when they temporarily suspend their sense of obligation to one another. It is mngwotngwotiki (pronounced nig-what-gwoh-teekee). This study of local currency systems counters too much mngwotngwotiki by offering a concrete way to develop a sense of care and mutual obligation that forms the cornerstone of healthy communities. In Local Currencies in Community Development, Savdie and Cohen-Mitchell have made an important contribution to the literature on local currency systems by clearly situating their study within the context of community development. An overview and history of alternative currency systems by clearly situating their study within the context of community development. An overview and history of alternative currency systems, along with an engaging case study of HOURS in Ithaca, New York and a look at related critical issues such as gender, poverty and ideological diversity make this book a valuable resource for practitioners and educators committed to community development from the ground up

Know What You Don't Know: Consistency in Sliding Window Filtering with Unobservable States Applied to Visual-Inertial SLAM (Extended Version)

Estimation algorithms, such as the sliding window filter, produce an estimate and uncertainty of desired states. This task becomes challenging when the problem involves unobservable states. In these situations, it is critical for the algorithm to ``know what it doesn't know'', meaning that it must maintain the unobservable states as unobservable during algorithm deployment. This letter presents general requirements for maintaining consistency in sliding window filters involving unobservable states. The value of these requirements when designing a navigation solution is experimentally shown within the context of visual-inertial SLAM making use of IMU preintegration.Comment: Main paper submitted to RAL. Main paper has 8 pages, 4 figures. Supplemental materials are 6 pages, 0 figures after the main pape