Assessment of Working Conditions and Job Satisfaction of Neurology Specialists

Objective: This study aimed to examine the demographic characteristics and working conditions of neurology specialists working in Türkiye and to determine the factors that play a role in neurologists’ resignations.
Materials and Methods: This study was designed as a multiple-choice survey. The study included 472 neurology specialists who were actively practicing in clinics. The data collected through the questionnaire were analyzed.
Results: Most (78.2%) of neurologist work in public hospitals, while 15.7% work in private hospitals, 3.6% work in foundation hospitals, and 2.5% work in private practices. 70.1% of the participants examine 41 or more patients per day. 37.7% of neurologists take on-call duty for ten or more days per month. 93.8% think their payment is not at a deserved level. 70% of the participants (n = 328) reported experiencing verbal violence. The rate of those who reported being exposed to mobbing is 62.5% (n = 295). 56% of the participants (n = 264) frequently feel burned out or depressed. Only 10% of them are satisfied with their working conditions. We used Logistic regression analysis to investigate factors for resigning. Accordingly, exposure to verbal or physical violence (P = 0.033), working in a particular institution (P = 0.038), and the number of emergency shifts affect the likelihood of resignation (P = 0.046). The probability of resigning for lecturers is significantly lower (OR: 0.05). The likelihood of resigning for those who report earning less than what they deserve is about 16 times higher than those who feel they are adequately paid.
Conclusion: The workload of neurology specialists is high. Neurologists have a high rate of exposure to violence and low job satisfaction. The workload of physicians varies significantly across different units and regions and is unequally distributed. To increase job satisfaction among healthcare workers and prevent physician migration, there is a need to improve working conditions, distribute workload and resources more equally among units.