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Alabama Road Bid Bundling Authority
(2019-10) Fisher, Justin
Evaluation of the Psychometric Properties of the Oldenburg Burnout Inventory among Bangladeshi Medical Doctors
(2020) Mousum, Sabrina
Background: Burnout, a psychosocial problem with professionals working with people, is characterized by mental exhaustion, depersonalization, and a sense of decreased performance in everyday activities. Owing to its negative effect on patient care and higher medical expenses, burnout in physicians has received substantial interest. Bangladesh, which is already suffering from a lack of human resources for health (HRH), has entered the COVID-19 pandemic with a critically low number of health staff. As a result, the workload of doctors working at the local scale is huge, leading to burnout. A proactive action should be taken to avoid the overwhelming result of burnout from affecting our health care infrastructure. Before assessing burnout, we need a reliable instrument to calculate burnout correctly. In order to maintain the legitimacy of any documented research findings, it is necessary to ensure the accuracy of the instruments used.
Aim: The present study was aimed to develop a culturally adapted and validated Bengali version of the Oldenburg Burnout Inventory (OLBI) for use in evaluating the burnout of medical doctors in Bangladesh.
Methodology: This cross-sectional study was conducted in six tertiary level hospitals in Dhaka city from January 2020 to December 2020 for one year. A total of 313 medical doctors serving in six tertiary-level hospitals in Dhaka City were taken as samples. For the data collection, a purposive sampling procedure was applied. The method of translation went through a structured forward-and back-translation method. Prior to the study, the research protocol was approved by the Institutional Review Board of BSMMU, Dhaka.
Results: Among 313 respondents 56.2% were male and 43.8% were female where 52.1% were from 31-40 years of age group. More than half of the respondents (51.8%) worked in the COVID-19 ward. About 61% of respondents did not have any significant comorbidities and 77% were not infected by COVID-19 at the time of this study. Internal consistency measured by Cronbach’s alpha (0.82) was acceptable. Exploratory factor analysis (EFI) and confirmatory factor analysis (CFI) supported a two-factor model (Exhaustion and Disengagement), which were correlated. The Bengali version of the OLBI showed an underlying two-factor structure where Goodness of Fit Indices was X2 – statistic/(df)= 1.942, p-value= <0.001, Tucker-Lewis Index (TLI)=0.919, Adjusted goodness of fit index (AGFI)= 0.915, Standardized Root Mean Square Residual (SRMR)=0.067. The mean scores of Exhaustion and Disengagement between fair to excellent sleep quality and terrible to poor sleep quality were 27.30 and 29.08 (p=0.022) and 14.23 and 16.66 (p=<0.001), respectively. This confirms, the excellent known group validity of the questionnaire.
Conclusions: The translation of OLBI revealed that it was not purely unidimensional. A bi-dimensional fit with two associated factors reflecting physical and psychological aspects of burnout was found to be supported. We discovered that the Questionnaire could detect significant differences between known classes, such as sleep quality. The translated OLBI was interpreted as a reliable instrument having strong validity evidence for measuring burnout in Bangladeshi medical doctors.
Gas Tax Alternatives: Mileage-Based User Fees
(2019-10) Bredikhina, Olga A.; Fisher, Justin W.; Mozayen, Bouran S.; Wheeler, L. Melissa
Transportation Cybersecurity Incidents
(2019-10) Callahan, John
Incorporating systems thinking approach in a multilevel framework for human-centered crash analysis
(Elsevier, 2019) Adanu, Emmanuel Kofi; Penmetsa, Praveena; Wood, Dustin; Jones, Steven L.
Variations that exist in the frequency and severities of crashes across regions may be due to differences in road user
behaviors or indirectly due to differences in regional characteristics. Regional strategies towards “vision zero” road fatalities, consisting of appropriate safety policies and laws, supported with public education and backed by appropriate
sanctions, have the ability to shape road user behaviors in the long term. In this paper, certain human-centered crash
factors are viewed as the outcome of a hierarchical system made up of road users nested in regions, in a way that regional characteristics like policies and punitive measures influence road user behaviors. Hence, we propose a multilevel framework that captures driver characteristics and regional attributes that directly and indirectly affect crash
outcomes. The concept was applied to crash data analysis for the state of Alabama, where it was found that the probability of a fatal crash involving a typical driver is 0.115. About 6.19% of the variability in the fatal crash rate involving
drivers from the state is accounted for by the city and 3.84% is accounted for by the county of residence of the causal
driver, leaving 89.97% of the variability to be accounted for by driver attributes or other crash contributing factors.
Fatal crash rates varied significantly across the state and some crash factors were more pronounced among drivers
from particular cities and counties. In view of these findings, specific countermeasures and structural adjustments
may be targeted in locations with the highest proportions of risky driver behaviors.