The importance of mental health variables for life expectancy by entropy weighting method: a case of OECD countries


JOURNAL OF PSYCHIATRIC NURSING, vol.14, no.1, pp.9-14, 2023 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 1
  • Publication Date: 2023
  • Doi Number: 10.14744/phd.2022.79836
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.9-14
  • Keywords: Entropy, healthcare resources, life expectancy, mental health, well-being, SATISFACTION, PERSONALITY, RESOURCES, MORTALITY, PEOPLE, CARE
  • Eskisehir Osmangazi University Affiliated: Yes


Objectives: This study aims to determine the weights (order of importance) of the mental health variables associated with life expectancy and rank them from the most important.Methods: This is a retrospective study involving member countries of the Organization for Economic Co-operation and Development (OECD). Mental health variables were divided into two groups: (i) healthcare resources (psychiatric beds in mental hospitals or general hospitals, psychiatrists, and nurses working in the mental health sector); (ii) subjective well-being measures (perceived health status, life satisfaction, and quality of support network). Accordingly, the secondary data for the variables of mental health-related healthcare resources used in this study covers the years 2013-2017, and the data of subjective well-being measures covers 2017. The order of importance (weights) of the study variables was determined using the "entropy weighting method," which is one of the criteria weighting methods employed in multi-criteria decision-making.Results: The most important variables associated with life expectancy were beds in mental hospitals and nurses working in the mental health sector. The quality of the support network was relatively less important.Conclusion: The results obtained point to the necessity of strengthening mental health resources in order to increase life expectancy. These results can guide health professionals about the priority interventions and policies that should be planned to increase life expectancy and the management of life expectancy-related variables.