Factor Analysis of Health Biases: a Behavioral Economics Approach

Document Type : Research Paper


1 Associate Professor of Economics, Department of Economics, Faculty of Literature and Humanities, Ilam University

2 Master of Economics, Department of Economics, Faculty of Literature and Humanities, Ilam University


One of the barriers to people's health is following past behaviors and not changing habits based on past and current preferences and ignoring the future. Therefore, the main purpose of the present study is to investigate factor analysis of health biases related to people using behavioral economics approach. For this purpose, the data of the present study was collected through a questionnaire developed by the researcher and convenience sampling from faculty members and staff of Ilam University. The initial reliability of the questions related to health biases was measured based on the Cronbach's alpha criterion, and the result was 0.77. The results of exploratory and confirmatory factor analysis showed that eight dimensions of health biases are important reflections of people's biased beliefs during daily decisions regarding nutrition, physical activity, treatment, treatment cost and treatment period. Exploratory factor analysis showed that 8 factors explain about 72.55% of the changes in health biases. Also, the examination of the fit indices of the confirmatory factor analysis model showed that the eight-factor model has a good fit with the data. . People's health biases in the form of 8 main dimensions were named as follows:  impatience in nutrition, oversimplification in nutrition, presentism in physical activity, ignoring the cost of staying healthy, willingness to pay for immediate treatment, procrastination in emotional treatment, naivety about the treatment period and indiscretion in treatment. The results of the present study can help health activists (researchers, decision-makers, planners, etc.) to explain the biases of behavioral economics to informing new concepts of health


Main Subjects

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