{"title":"不同收入群体心理健康服务效率的稳健性检验","authors":"Gülnur İlgün","doi":"10.1002/mde.70043","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The aim of this study is to examine the efficiency of mental health services in different countries based on their economic levels (income groups) and to see how reliable the results are. It also aims to examine whether the efficiency scores of countries vary by region and income groups. Data from 75 countries were used in the analysis. Input factors were the number of mental hospitals, psychiatrists, psychologists, and nurses, while output variables included the prevalence of depression, anxiety, total years lived with disability (YLD) for depression, and YLD for anxiety. To ensure that the decision-making units in this study are homogeneous, countries were separated into three groups based on their income levels, and then the data envelopment analysis (DEA) (input-oriented VRS model) was performed individually for each income level. When comparing middle-income countries (MIC) to low-income countries (LIC) and high-income countries (HIC), I found that MIC has lower efficiency scores (0.48). In addition, I found that LIC (0.93) is more efficient than HIC (0.72). This analysis identifies countries' potential improvement gaps in improving the efficiency of mental health services. The findings of this study are intended to guide policymakers and decision-makers in the field of mental health treatment.</p>\n </div>","PeriodicalId":18186,"journal":{"name":"Managerial and Decision Economics","volume":"47 2","pages":"403-410"},"PeriodicalIF":2.7000,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficiency of Mental Health Services With Robustness Check of DEA Scores by Income Groups\",\"authors\":\"Gülnur İlgün\",\"doi\":\"10.1002/mde.70043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>The aim of this study is to examine the efficiency of mental health services in different countries based on their economic levels (income groups) and to see how reliable the results are. It also aims to examine whether the efficiency scores of countries vary by region and income groups. Data from 75 countries were used in the analysis. Input factors were the number of mental hospitals, psychiatrists, psychologists, and nurses, while output variables included the prevalence of depression, anxiety, total years lived with disability (YLD) for depression, and YLD for anxiety. To ensure that the decision-making units in this study are homogeneous, countries were separated into three groups based on their income levels, and then the data envelopment analysis (DEA) (input-oriented VRS model) was performed individually for each income level. When comparing middle-income countries (MIC) to low-income countries (LIC) and high-income countries (HIC), I found that MIC has lower efficiency scores (0.48). In addition, I found that LIC (0.93) is more efficient than HIC (0.72). This analysis identifies countries' potential improvement gaps in improving the efficiency of mental health services. The findings of this study are intended to guide policymakers and decision-makers in the field of mental health treatment.</p>\\n </div>\",\"PeriodicalId\":18186,\"journal\":{\"name\":\"Managerial and Decision Economics\",\"volume\":\"47 2\",\"pages\":\"403-410\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Managerial and Decision Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/mde.70043\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Managerial and Decision Economics","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mde.70043","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Efficiency of Mental Health Services With Robustness Check of DEA Scores by Income Groups
The aim of this study is to examine the efficiency of mental health services in different countries based on their economic levels (income groups) and to see how reliable the results are. It also aims to examine whether the efficiency scores of countries vary by region and income groups. Data from 75 countries were used in the analysis. Input factors were the number of mental hospitals, psychiatrists, psychologists, and nurses, while output variables included the prevalence of depression, anxiety, total years lived with disability (YLD) for depression, and YLD for anxiety. To ensure that the decision-making units in this study are homogeneous, countries were separated into three groups based on their income levels, and then the data envelopment analysis (DEA) (input-oriented VRS model) was performed individually for each income level. When comparing middle-income countries (MIC) to low-income countries (LIC) and high-income countries (HIC), I found that MIC has lower efficiency scores (0.48). In addition, I found that LIC (0.93) is more efficient than HIC (0.72). This analysis identifies countries' potential improvement gaps in improving the efficiency of mental health services. The findings of this study are intended to guide policymakers and decision-makers in the field of mental health treatment.
期刊介绍:
Managerial and Decision Economics will publish articles applying economic reasoning to managerial decision-making and management strategy.Management strategy concerns practical decisions that managers face about how to compete, how to succeed, and how to organize to achieve their goals. Economic thinking and analysis provides a critical foundation for strategic decision-making across a variety of dimensions. For example, economic insights may help in determining which activities to outsource and which to perfom internally. They can help unravel questions regarding what drives performance differences among firms and what allows these differences to persist. They can contribute to an appreciation of how industries, organizations, and capabilities evolve.