Nicholas R Nicholson1, Richard Feinn2, E A Casey3, Jane Dixon4. 1. School of Nursing, Quinnipiac University, Hamden, Connecticut. 2. School of Medicine, Quinnipiac University, Hamden, Connecticut. 3. AARP, Washington, District of Columbia, New Haven, Connecticut. 4. School of Nursing, Yale University, New Haven, Connecticut.
Abstract
BACKGROUND AND OBJECTIVES: Social isolation is known to be detrimental to the health of older adults, yet there is no brief instrument to measure it. The objective was to describe the psychometric testing of a brief instrument constructed from theoretical underpinnings to measure social isolation in older adults. RESEARCH DESIGN AND METHODS: A sample of 9,245 participants, all aged 60 years and older, was obtained from 44 states in the United States. Summary descriptive statistics were calculated, followed by exploratory factor analysis using Geomin rotation and subsequently confirmatory factor analysis (CFA). After finding the best model, differential item functioning (DIF) was conducted using a multiple indicator multiple cause structural equation model to determine if item responses differed by gender or race after controlling for level of social isolation. Internal consistency was calculated and validity was assessed by correlating factor scores with 2 external measures. RESULTS: Exploratory factor analysis resulted in all items having statistically significant loadings. CFA showed the 2-factor model demonstrated excellent fit (CFI = 0.997, RMSEA = .038). The 2 factors were labeled connectedness and belongingness. After adjusting for demographic variables, no evidence suggested DIF. Internal consistency was good (alpha = .77) and the scale moderately correlated with the Social Network Index (r = .47). DISCUSSION AND IMPLICATIONS: The Social Isolation Scale has been shown to be an effective measure of social isolation in older adults. Using this concise instrument to quickly measure social isolation in a fast-paced health care environment would be beneficial to health care providers and patients.
BACKGROUND AND OBJECTIVES: Social isolation is known to be detrimental to the health of older adults, yet there is no brief instrument to measure it. The objective was to describe the psychometric testing of a brief instrument constructed from theoretical underpinnings to measure social isolation in older adults. RESEARCH DESIGN AND METHODS: A sample of 9,245 participants, all aged 60 years and older, was obtained from 44 states in the United States. Summary descriptive statistics were calculated, followed by exploratory factor analysis using Geomin rotation and subsequently confirmatory factor analysis (CFA). After finding the best model, differential item functioning (DIF) was conducted using a multiple indicator multiple cause structural equation model to determine if item responses differed by gender or race after controlling for level of social isolation. Internal consistency was calculated and validity was assessed by correlating factor scores with 2 external measures. RESULTS: Exploratory factor analysis resulted in all items having statistically significant loadings. CFA showed the 2-factor model demonstrated excellent fit (CFI = 0.997, RMSEA = .038). The 2 factors were labeled connectedness and belongingness. After adjusting for demographic variables, no evidence suggested DIF. Internal consistency was good (alpha = .77) and the scale moderately correlated with the Social Network Index (r = .47). DISCUSSION AND IMPLICATIONS: The Social Isolation Scale has been shown to be an effective measure of social isolation in older adults. Using this concise instrument to quickly measure social isolation in a fast-paced health care environment would be beneficial to health care providers and patients.
Authors: Christine Miaskowski; Steven M Paul; Karin Snowberg; Maura Abbott; Hala T Borno; Susan M Chang; Lee May Chen; Bevin Cohen; Bruce A Cooper; Marilyn J Hammer; Stacey A Kenfield; Kord M Kober; Angela Laffan; Jon D Levine; Rachel Pozzar; Kim Rhoads; Katy K Tsai; Erin L Van Blarigan; Katherine Van Loon Journal: Cancer Date: 2021-04-27 Impact factor: 6.921
Authors: Christine Miaskowski; Steven M Paul; Karin Snowberg; Maura Abbott; Hala Borno; Susan Chang; Lee M Chen; Bevin Cohen; Marilyn J Hammer; Stacey A Kenfield; Kord M Kober; Jon D Levine; Rachel Pozzar; Kim F Rhoads; Erin L Van Blarigan; Katherine Van Loon Journal: J Pain Symptom Manage Date: 2020-09-02 Impact factor: 3.612