Abstract
BACKGROUND: In Iran, the issue of the nursing shortage and unequal distribution exist simultaneously. The shortage of healthcare workers is one of the most important concerns of the health systems. In addition, the disparity in the distribution of healthcare workers between large metropolises and remote or non-capital areas has become a serious concern and a top priority to address. We conducted this study to identify and create a sufficient understanding of the different financial and non-financial preferences of nurses for working in deprived areas. METHODS: This research was carried out in June and April 2022. It was carried out in three major phases. The factors influencing the nurses' job preferences were first discovered using qualitative methods. The second phase was conducting a pilot study and determining the best design for discrete choice experiment scenarios. The last phase involved publishing the questionnaire to gather information. Data were analyzed (discrete choice analysis) using JMP Pro 16 software. RESULTS: A desirable job for the participants (nurses) in this study would have a higher salary, work in a city, the Rasmi employment contract, a low workload, adequate workplace facilities, an appropriate work schedule, and 1 to 3 years spent on the assigned job to promote to a higher position. Willingness to pay (WTP) and the probability of selecting different attribute levels were also calculated and reported. For example, the highest amount of money that a nurse expected to be paid was for changing the geographical location of the workplace from a city to a deprived area. In this case, a nurse tends to receive 91.87 million IRR more to move from a city to a deprived area to work. This amount of money was by far the most among other WTPs. CONCLUSION: The results of this study indicated that nurses are willing to forego net income in exchange for other favorable characteristics of their working environment and conditions. This shows that a variety of actions are accessible to policymakers that can greatly enhance the working conditions for nurses. The WTP and the probability of selecting various attributes may help policymakers plan more effectively.