Motivation in health institutions and examination of thesis made in this field with content analysis
2022
0 views
0 downloads
Advisor: Prof. Dr. Aslı Beyhan Acar
Abstract (EN)
Motivation is early on obvious factors that make people live effectively. The importance of the motivation factor in health institutions is more noticeable. After the literature screening in this study, the definition of motivation was informed about motivational theories and factors that affect motivation, and emphasized the importance of motivation in the health sector. The research consists of 112 Master's, Ph.D. and Medical Specialty theses written in 2010-2020 on motivation. In detail, the number of examples, the scales they use, the expressions used instead of motivation, the variables examined with motivation, the objectives and results of the study were reviewed. The impact of motivation factors on employees was analyzed in the conclusion of the thesis. The meaning of the hypothesis studies, the meaning of relations between the measured variables, has been researched and shared in the result section. In short, the most important motivational factors have been identified as fees, working conditions, recognition, respect, participation in decisions.
Author
Dr. Shaig Naghızade
Institution
İstanbul University
Hastane ve Sağlık Kur. Yön. Bilim Dalı
How to Cite
Shaig Naghızade (Master Thesis). Motivation in health institutions and examination of thesis made in this field with content analysis, 2022, İstanbul University.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from İstanbul University
- In the covid 19 pandemic of female employees at a university hospital attitudes and affecting factors in nutrition of 9 months-6 years old children(2022)
- The perception of the right-wing movements in Turkey as to the 27 May Coup: 1960-1980(2020)
- Economic and social life in the Ottoman Empire according to the 1890 year's news of La Turquie Newspaper(2022)
- Land regime in the Umayyads period(2022)
- Merkel hücreli karsinomda tanısal ve prognostik belirteçler(2022)
- Use of machine learning methods in classification of respiratory system diseases(2021)