Evaluating the Factor Structure and Measurement Properties of Measurement Framework to Assess Social Exclusion Among Older Adults

BACKGROUND. Social exclusion is a dynamic process by which individual or populations are marginalized from opportunities and rights that affect advancement in society. Older adults more often experience the loss of income sources, and may have greater difficulties mobilizing for social activities or civic participations due to functional limitations. Because social exclusion is an abstract concept, it is important that measures of social exclusion are reliable, valid, and easily administered. Indeed, researchers have created several frameworks with which to measure social exclusion. Scutella and colleagues’ framework is promising measurement approach for social exclusion. However, to date, no studies have examined the factor structure of Scutella’s framework. It is critical to understand an instrument’s factor structure because assessing dimensionality is a key component of validity testing.

PURPOSE. To evaluate the measurement properties and factor structure of Scutella’s framework; and, in particular, to examine factors of social exclusion through an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

METHODS. Data were drawn from the 2014 Health and Retirement Study (HRS) core wave and its Psychosocial Supplement. The HRS is a nationally representative study of the health and economic status of older adults 50+ in the U.S. The HRS covered social exclusion indicators. The final analytic sample included 4,316 older adults. The sample was randomly split into two sub-samples before statistical analyses. Comparing these sub-samples, differences in demographic variables were examined. To examine measurement properties, internal consistency and construct validity (comparing with subjective social status and loneliness) were used. The EFA was conducted to identify the factor structure of the social exclusion framework using the first sub-sample. The CFA was conducted using the second sub-sample.

RESULTS. There are no differences between two sub-samples based on age, gender, race, and ethnicity (p>.05). Measurement properties were as follows: sub-sample 1 (a=.59), and sub-sample 2 (a=.59). In terms of construct validity, all indicators were statistically associated with subjective social status and loneliness with the exception of working for pay, and public and private service (p<.05). Results of the EFA identified an eight-factor model. Factor names are as follows: Material Resources, Social Support, Social Network, Health and Work, Education and Internet, Social Services, Social Participation, and Personal Safety. According to the EFA, the eight-factor model demonstrated the best fit to the data. The results of CFA showed that the eight-factor model was the most appropriate to describe the factor structure of the social exclusion measure. However, fit indices for CFA model were not satisfactory (χ²=3202.95, p<.001; RMSEA=.062; CFI=.774; and TLI=.737).

IMPLICATIONS. This study contributes to future research by examining the factor structure and instrument properties of the social exclusion measure using a large population-based dataset. Furthermore, results show that although eight factors contribute to older adults’ social exclusion, factor structure was not satisfactory. Thus, based on these results, further work is needed to develop a social exclusion measurement tool to measure social exclusion among older adults, better understand social exclusion factors, and reduce older adults’ social exclusion in social work practice.