Development of a Model and Components of Happiness Needs among Older Adults: A Case Study in Lat Krabang District Bangkok

Abstract

The objectives of this research are: 1) to synthesize the happiness needs of the older adults in Lat Krabang District Bangkok, and 2) to analyze the components and model of happiness needs for the older adults in Lat Krabang District. The research method involved data collection through in-depth interviews with 6 experts, followed by content analysis. The population for this study consisted of elderly individuals in Lat Krabang District, with the sample group comprising 1) elderly individuals receiving a pension from government service and 2) older adults individuals not receiving a pension due to lack of government service, totaling 400 individuals. The research instrument used was a 5-point Likert scale questionnaire to survey the happiness needs of the older adults. Data were collected by distributing 400 questionnaires. The researcher applied purposive sampling to distribute the questionnaires to the sample group of older adults’ individuals. Data analysis was conducted by examining the frequency distribution and percentage of responses. Exploratory Factor Analysis (EFA) was used to analyze the data through statistical analysis software to explore and identify common components that explain the relationship between observed variables.

           The findings revealed that the model and components of happiness needs for the older adults were appropriate and could be analyzed through exploratory factor analysis. The statistical estimates showed that Chi-Square = 4357.453, and the significance value was .000, which is less than .05. This suggests that all 15 variables were interrelated and could be analyzed through exploratory factor analysis. The model and components of happiness needs for the older adults in Lat Krabang District were identified as four components: 1) Physical and Mental Health, 2) Financial Management, 3) Religious Beliefs and Practices, and 4) Social Network and Family. These four components explained the variance of the variables by 24.53%, 39.18%, 52.84%, and 65.66%, respectively.