Doctor of Philosophy (PhD)



Document Type



Identifying risk factors and those at risk for falls is necessary. The first purpose of the dissertation was to validate the Comprehensive Falls Risk Screening Instrument (CFRSI) that weights falls risk factors and includes the subscale scores of history, physical, vision, medication, and environment, and a total falls risk score. The CFRSI total falls risk score was compared to subscale scores, physical activity, physical function, health-related quality of life (HRQL), and history of falls (Study 1). The second purpose of the dissertation was to determine associations between the CFRSI total falls risk score, race, education, and income (Study 2). Data were collected at falls risk screenings conducted at 10 community organizations with 286 older adults (M age=74.2 years, SD=10.0, 75.9% female, 52.9% White/Caucasian, 52.4% low-income status, and 43.1% low educational level). The total falls risk score was associated with all risk subscale scores (r=.25, p<.01 to r=.69, p<.01), total physical activity score (r=-.30, p<.01), total physical function score (r=.30, p<.01), and total HRQL scores (r=-.44, p<.01 to r=-.24, p=.03). Fallers (n=90) had higher total falls risk scores (M=41.03, SD=9.38) than non-fallers (n=188; M=34.06, SD=10.05), t(276)=5.53, p<.001). Discriminant function analysis indicated the most important predictor of falling status (i.e., fallers and non-fallers) was the history risk score (r=.96). A 2x2x2 factorial ANOVA only revealed a significant main effect for education (F[1,205]=10.19, p=.002), indicating that the total falls risk score was greater for participants with a lower educational level (M=41.1) than for those with a higher educational level (M=34.5). ANCOVA revealed that individuals with low-income reported higher falls risk scores (M=39.2) than individuals with high-income (M=34.5) when controlling for race (F[1,204]=10.4, p=.001,ç2=.05). There were no significant differences between fallers and non-fallers by education (÷2[1,N=262]=.03, p=.86) or income (÷2[1,N=212]=.38, p=.54), but there were differences by race (÷2[1,N=267]=6.44, p=.0). White/Caucasians (63.2%) were more likely to fall than African American/Black/Others (36.8%). Results provide evidence of the construct validity of the CFRSI and that sociodemographic factors such as education, income, and race are important when identifying older adults at risk for falls, determining applicability of falls risk screening instruments, and implementing falls reduction programs.



Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Ellis, Rebecca

Included in

Kinesiology Commons