The Geriatric Institutional Assessment Profile (GIAP) is a self-administered survey of hospital nurses designed to assess a hospital's readiness to implement geriatric programs. The GIAP measures nurses' knowledge and attitudes toward older adults as well as the organizational attributes that support or constrain geriatric best practices. Test—retest reliability estimates of the GIAP were conducted with a sample of 166 direct care nurses in three urban, university-affiliated hospitals over a 3-week time period. Intraclass correlation coefficients of GIAP scales and subscales ranged between .82 and .92, demonstrating good to very good reliability. The GIAP is a reliable measure of organizational attributes of the hospital relevant to geriatric care.
Abraham, I.L., Bottrell, M.M., Dash, K.R., Fulmer, T., Mezey, M., O'Donnell, L., et al. (1999). Profiling care and benchmarking best practice in care of hospitalized elderly: The Geriatric Institutional Assessment Profile . Nursing Clinics of North America, 34, 237-255.
2.
Boltz, M., Capezuti, E., Bower-Ferres, S., Norman, R., Secic, M., Kim, H., et al. (2008a). Hospital nurses' perceptions of the geriatric care environment. Journal of Nursing Scholarship, 40, 282-289.
3.
Boltz, M., Capezuti, E., Bower-Ferres, S., Norman, R., Secic, M., Kim, H., et al. (2008b). Changes in the geriatric care environment associated with NICHE (Nurses Improving Care to Healthsystem Elders). Geriatric Nursing, 29, 176-185.
4.
Chang, E., Chenoweth, L., & Hancock, K. (2003). Nursing needs of hospitalized older adults. Journal of Gerontological Nursing, 29, 32-41.
5.
DeFrances, C.J., Hall, M.J., & Podgornik, M.N. (2005). 2003 National Hospital Discharge Survey. Advance Data from Vital and Health Statistics , 359, 1-20.
6.
Fulmer, T., Mezey, M., Bottrell, M., Abraham, I., Sazant, J., Grossman, S., et al. (2002). Nurses Improving Care for Healthsystem Elders (NICHE): Nursing outcomes and bench-marks for evidence-based practice . Geriatric Nursing, 23, 121-127.
7.
Health Resources and Services Administration, U.S. Department of Health and Human Services. (2006). The registered nurse population: National Sample Survey of Registered Nurses 2004. Retrieved December 1, 2008, from http://bhpr.hrsa.gov/healthworkforce/rnsurvey04/2.htm
8.
Kim, H., Capezuti, E., Boltz, M., Fairchild, S., Fulmer, T., & Mezey, M. (2007). Factor structure of the Geriatric Care Environment Scale. Nursing Research, 56, 339-347.
9.
Kline, T.J.B. (2005). Psychological testing: A Practical approach to design and evaluation. Thousand Oaks, CA: Sage.
10.
Lee, V.K., & Fletcher, K.R. (2002). Sustaining the geriatric resource nurse model at the University of Virginia. Geriatric Nursing, 23, 128-132.
11.
Mezey, M., Kobayashi, M., Grossman, S., Firpo, A., Fulmer, T., & Mitty, E. (2004). Nurses Improving Care to Healthsystem Elders (NICHE): Implementation of best practice models. Journal of Nursing Administration, 34, 451-457.
12.
National Research Council Committee on Population, Committee on National Statistics. (2001). Preparing for an aging world: The case for cross-national research. Retrieved November 29, 2008, from http://www.nap.edu/catalog/10120.html
13.
Pfaff, J. (2002). The geriatric resource nurse model: A culture change. Geriatric Nursing, 23, 140.
14.
Russo, C.A., & Elixhauser, A. (2006). Hospitalization in the elderly population, 2003 (Statistical Brief No. 6) [Electronic Version]. Rockville, MD: Agency for Healthcare Research and Quality . Retrieved November 28, 2008, from http://www.hcup-us.ahrq.gov/reports/statbriefs/sb6.pdf
15.
SAS Institute. (2003). SAS (Version 9.1.3) [Computer software]. Cary, NC: Author.
16.
Shrout, P.E., & Fleiss, J.L. (1979). Intraclass correlations: Use in assessing rater reliability. Psychological Bulletin, 86, 420-428.
17.
Streiner, D.L., & Norman, G.R. (2003). Reliability, in health measurement scales. A practical guide to their development and use (3rd ed.). Oxford, UK: Oxford University Press .
18.
Swauger, K., & Tomlin, K. (2002). Best care for the elderly at Forsyth Medical Center . Geriatric Nursing, 23, 145-150.
19.
Yuan, Y.C. (2000). Multiple imputation for missing data: Concepts and new developments (Tech. Rep. No. 267-225). Cary, NC: SAS Institute.
