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Classifying change with the Sickness Impact Profile for Nursing Homes (SIP-NH)

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Abstract

The aim of this cohort study was to evaluate the concordance of the Sickness Impact Profile for Nursing Homes (SIP- NH) and Sickness Impact Profile (SIP) in classifying change. Subjects consisted of 194 consecutive long- stay nursing home residents at one academic department of the V.A. and in 8 community proprietary nursing homes in San Antonio, Texas. They were to have more than 3 months residency; to be ⩾61 years; and to be dependent in at least 2 ADLs with an MMSE score of ⩾15. Subjects were administered a 128- item SIP and a reduced 66- item SIP- NH at baseline and 4, 8, and 12- month follow- up. At each follow- up, subjects were classified into 3 mutually exclusive change categories using a change score of ⩾5 points. Concordance of the classification of subjects by the SIP- NH and SIP was evaluated. The misclassification rate as well as its direction was also assessed. Both instruments classified a little over one- quarter of the subjects as better, over a third as being unchanged, and another third as being worse at the four- month follow- up. More subjects were classified as worse by both instruments at 8 and 12 months. All kappas ranged from 0.52 to 0.78, indicating good to excellent agreement. Overall, the SIP- NH characterized persons as changed more often than the SIP with no systematic directional bias. In conclusion, the SIP- NH was concordant with the SIP in classifying change in subjects. However, we cannot say which of the two is better for detecting change. Future research must focus on defining a change score which has clinical meaning, and evaluate responsiveness to change. (Aging Clin. Exp. Res. 7: 228–233, 1995)

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References

  1. Bergner M., Bobbitt R.A., Pollard W.E., Martin DP., Gilson B.S.: The Sickness Impact Profile: Validation of a health status measure. Med. Care 14: 57–67, 1976.

    Article  PubMed  CAS  Google Scholar 

  2. Rothman M.L., Hedrick S., Inui T.: The Sickness Impact Profile as a measure of the health status of non-cognitively impaired nursing home residents. Med. Care 27: S157–S167, 1989.

    Article  PubMed  CAS  Google Scholar 

  3. Granger C.V., Cotter A.C., Hamilton B.B., Fiedler R.C.: Functional assessment scales: a study of persons after stroke. Arch. Phys. Med. Rehabil. 74: 133–138, 1993.

    PubMed  CAS  Google Scholar 

  4. Laupacis A., Bourne R., Rorabeck C., Feeny D., Wong C., Tugwell P., Leslie K., Bullas R.: The effect of elective total hip replacement on health-related quality of life. J. Bone Joint Surg. Am. 75: 1619–1626, 1993.

    PubMed  CAS  Google Scholar 

  5. Chapko M., Rothman M.L., Eherth J., Hedrick S.C., Sullivan J., Erdly W., Cooper S.: Data collection in Adult day health study. Med. Care 31: SS3–SS14, 1993.

    PubMed  Google Scholar 

  6. Mackenzie R.C., Charlson M.E., DiGioia D., Kelley K.: A patient-specific measure of change in maximal function. Arch. Intern. Med. 146: 1325–1329, 1986.

    Article  PubMed  CAS  Google Scholar 

  7. Mackenzie R.C., Charlson M.E., DiGioia D., Kelley K.: Can the Sickness Impact Profile measure change? An example of scale assessment. J. Chronic Dis. 39: 429–438, 1986.

    Article  PubMed  CAS  Google Scholar 

  8. Gerety M.B., Cornell J.E., Mulrow C.D., Tuley M., Hazuda H.P., Lichtenstein M., Kanten D.N., Aguilar C., Kadri A.A., Rosenberg J.: The Sickness Impact Profile for nursing homes (SIP-NH). J. Gerontol. 49: M2–M8, 1994.

    Article  PubMed  CAS  Google Scholar 

  9. Mulrow C.D., Gerety M.B., Kanten D.N., DeNino L.A., Cornell J.E.: Effects of physical therapy on functional status of nursing home residents. J. Am. Geriatr. Soc. 41: 326–328, 1993.

    PubMed  CAS  Google Scholar 

  10. Mulrow C.D., Gerety M.B., Kanten D.N., Cornell J.E., De Nino L.A., Chiodo L., Aguilar C., O’Neil M.B., Rosenberg J., Solis R.M.: A randomized trial of physical rehabilitation for very frail nursing home residents. JAMA 271: 519–524, 1994.

    Article  PubMed  CAS  Google Scholar 

  11. Katz S., Ford A.B., Moskowitz R.W., Jackson B.A., Jaffee M.W.: Studies of illness in the aged: The index of ADL — a standardized measure of biological and psychosocial function. JAMA 185: 914–919, 1963.

    Article  PubMed  CAS  Google Scholar 

  12. Folstein M.F., Folstein S.E., McHugh P.R.: “Mini-Mental State”: A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 12: 189–198, 1975.

    Article  PubMed  CAS  Google Scholar 

  13. Cohen J.: A coefficient of agreement for nominal scale. Educ. Psychol. Meas. 20: 37–46, 1960.

    Article  Google Scholar 

  14. Landis J.R., Koch G.G.: The measurement of observer agreement for categorical data. Biometrics 33: 671–679, 1977.

    Article  Google Scholar 

  15. Lewis M.A., Kane R.L., Cretin S., Clark V.: The immediate and subsequent outcomes of nursing home care. Am. J. Public Health 75: 758–762, 1985.

    Article  PubMed  CAS  Google Scholar 

  16. Roher J.E., Yasalis C., Laughlin P.R., Wiley R.: Patterns of change in functional status in long-term care. Health Serv. Res. 23: 495–509, 1988.

    Google Scholar 

  17. Deyo R.A.: Measuring functional outcomes in therapeutic trials for chronic disease. Control Clin. Trials 5: 223–240, 1984.

    Article  PubMed  CAS  Google Scholar 

  18. Fiatarone M.A., O’Neill E.F., Tyan N.D., Clements K.M., Solares G.R., Nelson M.E., Roberts S.B., Kehayias J.J., Lipsitz L.A., Evans W.J.: Exercise training and nutritional supplementation for physical frailty in very elderly people. N. Engt. J. Med. 330: 1769–1775, 1994.

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Division of General Medicine, University of Texas Health Science Center, USA

    Rahul Dhanda Ph.D., C. D. Mulrow & M. B. Gerety

  2. Division of Geriatrics and Gerontology, University of Texas Health Science Center, USA

    C. D. Mulrow, M. B. Gerety & J. E. Cornell

  3. Geriatric Research, Education and Clinical Center, Audie L. Murphy Memorial Veterans Hospital, San Antonio, Texas

    C. D. Mulrow, M. B. Gerety & J. E. Cornell

  4. The Aging Research and Education Center, University of Texas Health Science Center, San Antonio, Texas, USA

    Rahul Dhanda Ph.D. & S. Lee

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  1. Rahul Dhanda Ph.D.
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  2. C. D. Mulrow
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  3. M. B. Gerety
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  4. S. Lee
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  5. J. E. Cornell
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Dhanda, R., Mulrow, C.D., Gerety, M.B. et al. Classifying change with the Sickness Impact Profile for Nursing Homes (SIP-NH). Aging Clin Exp Res 7, 228–233 (1995). https://doi.org/10.1007/BF03324340

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  • DOI: https://doi.org/10.1007/BF03324340

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