Proposing a new score to measure personal happiness by identifying the contributing factors

Abstract

Different assessment tools and questionnaires have been developed to measure happiness. The Oxford Happiness Questionnaire (OHQ), that has 29 items, has been used widely to estimate personal happiness. The OHQ is used to quantify personal happiness based on an equal effectiveness assumption for all 29 items. Although the OHQ has been used by several studies, very few studies assess the contribution of the individual OHQ items in explaining personal happiness. The current study attempts to fill this gap by assessing the contribution of the individual OHQ items in explaining personal happiness as a latent variable. Structural Equation Modeling (SEM) is used to assess the relationship of the individual OHQ items in explaining personal happiness in Skudai, Johor, Malaysia. The significant OHQ items that are extracted from SEM results, are used to develop a new personal happiness measurement score. The SEM factor loading values are used to weight the extracted items. All usual clustering methods are used in this study and the most suitable one based on the higher silhouette value is chosen to cluster the proposed personal happiness index. Finally, the relationships between socio demographic factors and the proposed personal happiness index clusters are tested by Gamm and Pearson Chi-Square tests. The SEM results show that 16 out of the 29 OHQ items have poor associations with personal happiness and can be excluded from the model. Most of the non-significant items (items with low level of association) are negatively worded items and the majority of the significant items are related to personal attitudes. The proposed personal happiness index can help to save time and avoid confusion.