Background: Valid, feasible measures of functional status are needed to evaluate the expanding nursing home population. This study attempts to increase relevance and reduce respondent burden of the Sickness Impact Profile (SIP) for nursing home residents while maintaining internal consistency and validity.

Methods: 231 residents from one academic and four community nursing homes, aged > or = 60 with a Mini-Mental State Exam score > or = 11, were study participants. Nominal group process was used to identify items and/or categories for removal. Candidate items were those that: represented restrictions of the nursing home environment, had weak item-total score correlations, and/or made minimal contribution to category internal consistency. Reduction was constrained by: minimum correlation of r = .90 between SIP and Sickness Impact Profile for Nursing Homes (SIP-NH) scores, coefficients alpha that fell within 95% confidence regions about predicted alpha. Convergent and discriminant validity were evaluated with the Katz Activities of Daily Living, Physical Disability Index, Geriatric Depression Scale, and Folstein Mini-Mental State Exam.

Results: The SIP-NH contains 66 items, a 51.5% reduction. Correlations between the SIP-NH and SIP were: total score r = .98, Physical dimension r = .97, and Psychosocial dimension r = .97. Alpha coefficients all fell within the 95% confidence regions. The SIP and the SIP-NH did not differ in correlations with validating instruments.

Conclusions: The SIP-NH reduces respondent burden and has acceptable internal consistency and external validity. Potentially useful for discriminatory and predictive purposes, responsiveness to change will require longitudinal evaluation.

Download full-text PDF

Source
http://dx.doi.org/10.1093/geronj/49.1.m2DOI Listing

Publication Analysis

Top Keywords

sickness impact
12
impact profile
12
nursing homes
12
internal consistency
12
profile nursing
8
homes sip-nh
8
respondent burden
8
mini-mental state
8
fell 95%
8
95% confidence
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!