Measure-Description

The Fordyce’s Happiness Measure (FHM) was developed by Dr. Gregory N. Fordyce and is designed to assess an individual’s general sense of happiness and well-being. The scale typically includes questions related to daily satisfaction, sense of happiness, and personal well-being. It usually has two main sections:
Self-Reported Happiness: Participants are asked about their personal happiness in various aspects of their life, such as social life, work, and general satisfaction.
Emotional Well-Being: Focuses on evaluating positive and negative emotions experienced by the individual.
Responses are typically provided on Likert-type scales, which allow for quantitative assessment of different aspects of happiness.

Data Analysis and Use

The data collected from the FHM can be used to evaluate participants’ levels of happiness. Data analysis may include:
Descriptive Statistics: Extracting means, variances, and distributions for participants’ responses.
Comparative Analysis: Comparing happiness levels across different groups, such as gender, age, or socioeconomic status.
Correlation: Examining relationships between happiness and other variables, such as social support or stress levels.
Statistical analyses such as multiple regression, analysis of variance (ANOVA), and correlation analysis are used to process the data.

Purpose

The primary goal of the Fordyce’s Happiness Measure (FHM) is to determine the level of happiness and life satisfaction of an individual. This tool helps understand the factors influencing well-being and allows the assessment of overall happiness in various populations and under different conditions.
Additionally, FHM is used in studies that evaluate the effectiveness of mental health interventions and well-being programs, as well as in research examining the connection between happiness and other psychological or social factors.

Calibration

The calibration of the FHM involves the following steps:
Reliability Analysis: Calculating Cronbach’s alpha to assess the internal consistency of the scale. Typically, values above 0.7 are considered acceptable.
Validity: Checking the validity of the scale, i.e., how well it measures happiness and well-being as intended. This can be done using factor analysis.
Cross-Validation: Testing the scale in different populations to ensure that the results are generalizable to other groups.

Bibliography

Fordyce, M. W. (1988). A review of research on the happiness measures: A sixty-second index of happiness and mental health. Social Indicators Research, 20(1), 355-381.
Fordyce, M. W. (1985). The relationship of happiness and life satisfaction to health and longevity. Social Indicators Research, 17(1), 63-87.
Diener, E., & Seligman, M. E. P. (2004). Beyond money: Toward an economy of well-being. Psychological Science in the Public Interest, 5(1), 1-31.