Top

Gepubliceerd in:

03-05-2018

The sensitivity of the MOS SF-12 and PROMIS® global summary scores to adverse health events in an older cohort

Auteurs: Joanne Allen, Fiona M. Alpass, Christine V. Stephens

Gepubliceerd in: Quality of Life Research | Uitgave 8/2018

Abstract

Purpose

To compare the predictive validity of two self-reported outcome measures, the Patient-Reported Outcome Measurement Information System (PROMIS) Global Health measure and the 12-item Health Survey (SF-12).

Methods

Data were obtained from 1286 persons (55% female) aged 61–77 responding to a longitudinal survey. Inter-correlations of the SF-12 and PROMIS physical and mental summary scores were examined. ROC and AUC analyses were conducted to compare mental health score sensitivity to high levels of depression symptoms. Multiple regression was used to assess physical health score sensitivity to adverse health events over 12-month follow-up.

Results

All scores displayed negatively skewed distributions. The respective SF-12 and PROMIS physical (r = .78) and mental (r = .62) health scores displayed strong associations. Mental health scores provided useful discrimination of persons reporting high depression symptoms (AUC_SF12 = 0.90; AUC_PROMIS = 0.84), although the SF-12 provided better case discrimination. Decreases in physical health over time were associated with recurrent falls (B_SF12 = − 1.62; B_PROMIS = − 1.14) and hospitalisations (B_SF12 = − 1.69; B_PROMIS = − 1.11).

Conclusions

The SF-12 and PROMIS brief measures of physical and mental health assess related but distinct health constructs. However, they display comparable sensitivity to adverse health outcomes. Results from studies utilising the SF-12 and PROMIS global health measures should be compared with sensitivity to differences in the content and scoring of these measures.

vorige artikel A new algorithm to build bridges between two patient-reported health outcome instruments: the MOS SF-36® and the VR-12 Health Survey

Alleen toegankelijk voor geautoriseerde gebruikers

Yu, D. S. F., Yan, E. C. W., & Chow, C. K. (2015). Interpreting SF-12 mental component score: An investigation of its convergent validity with CESD-10. Quality of Life Research, 24(9), 2209–2217. https://doi.org/10.1007/s11136-015-0959-x.CrossRefPubMed

Gill, S. C., Butterworth, P., Rodgers, B., & Mackinnon, A. (2007). Validity of the mental health component scale of the 12-item Short-Form Health Survey (MCS-12) as measure of common mental disorders in the general population. Psychiatry Research, 152(1), 63–71. https://doi.org/10.1016/j.psychres.2006.11.005.CrossRefPubMed

Bjorner, J. B., Fayers, P. M., & Idler, E. L. (2005). Self-rated health. In P. M. Fayers & R. D. Hays (Eds.), Assessing quality of life (pp. 309–323). Oxford: Oxford University Press.

Stewart, A. L., & Kamberg, C. (1992). Physical functioning. In A. L. Stewart & J. E. Ware (Eds.), Measuring functioning and well-being: The medical outcomes study approach (pp. 86–142). Durham, NC: Duke University Press.CrossRef

Stewart, A. L., Hays, R. D., & Ware, J. E. (1992). Health perceptions, energy/fatigue, and health distress measures. In A. L. Stewart & J. E. Ware (Eds.), Measuring functioning and well-being: The medical outcomes study approach (pp. 143–172). Durham, NC: Duke University Press.CrossRef

Dorr, D. A., Jones, S. S., Burns, L., Donnelly, S. M., Brunker, C. P., Wilcox, A., et al. (2006). Use of health-related, quality-of-life metrics to predict mortality and hospitalizations in community-dwelling seniors. Journal of the American Geriatrics Society, 54(4), 667–673. https://doi.org/10.1111/j.1532-5415.2006.00681.x.CrossRefPubMed

Sherbourne, C. D. (1992). Pain measures. In A. L. Stewart & J. E. Ware (Eds.), Measuring functional status and well-being: The medical outcomes study approach (pp. 230–234). Durham, NC: Duke University Press.

Hays, R. D., Bjorner, J. B., Revicki, D. A., Spritzer, K. L., & Cella, D. (2009). Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Quality of Life Research, 18(7), 873–880. https://doi.org/10.1007/s11136-009-9496-9.CrossRefPubMedPubMedCentral

Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194. https://doi.org/10.1016/j.jclinepi.2010.04.011.CrossRefPubMedPubMedCentral

10.

Fowles, J. B., Weiner, J. P., Knutson, D., Fowler, E., Tucker, A. M., & Ireland, M. (1996). Taking health status into account when setting capitation rates: A comparison of risk-adjustment methods. JAMA, 276(16), 1316–1321.CrossRefPubMed

11.

Hornbrook, M. C., & Goodman, M. J. (1995). Assessing relative health plan risk with the RAND-36 health survey. Inquiry, 32(1), 56–74.PubMed

12.

Hornbrook, M. C., & Goodman, M. J. (1996). Chronic disease, functional health status, and demographics: A multi-dimensional approach to risk adjustment. Health Services Research, 31(3), 283–307.PubMedPubMedCentral

13.

Ware, J., Kosinski, M., & Keller, S. (1996). A 12-item Short-Form Health Survey: Construction of scales and preliminary tests of reliability and validity. Medical Care, 34(3), 220–233.CrossRefPubMed

14.

Ware, J., Kosinski, M., Turner-Bowker, D., & Gandek, B. (2002). How to Score Version 2 of the SF-12® Health Survey (With a Supplement Documenting Version 1). Lincoln, RI: Quality Metric Incorporated.

15.

Selim, A. J., Rogers, W., Fleishman, J. A., Qian, S. X., Fincke, B. G., Rothendler, J. A., et al. (2009). Updated U.S. population standard for the Veterans RAND 12-item Health Survey (VR-12). Quality of Life Research, 18(1), 43–52. https://doi.org/10.1007/s11136-008-9418-2.CrossRefPubMed

16.

Fan, V. S., Au, D., Heagerty, P., Deyo, R. A., McDonell, M. B., & Fihn, S. D. (2002). Validation of case-mix measures derived from self-reports of diagnoses and health. Journal of Clinical Epidemiology, 55(4), 371–380. https://doi.org/10.1016/S0895-4356(01)00493-0.CrossRefPubMed

17.

Gandek, B., Ware, J. E., Aaronson, N. K., Apolone, G., Bjorner, J. B., Brazier, J. E., et al. (1998). Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: Results from the IQOLA Project. Journal of Clinical Epidemiology, 51(11), 1171–1178. https://doi.org/10.1016/S0895-4356(98)00109-7.CrossRefPubMed

18.

Cella, D., Yount, S., Rothrock, N., Gershon, R., Cook, K., Reeve, B., et al. (2007). The Patient-Reported Outcomes Measurement Information System (PROMIS): Progress of an NIH Roadmap Cooperative Group during its first two years. Medical Care, 45(5 Suppl 1), S3-S11. https://doi.org/10.1097/01.mlr.0000258615.42478.55.PubMedPubMedCentralCrossRef

19.

Schalet, B. D., Rothrock, N. E., Hays, R. D., Kazis, L. E., Cook, K. F., Rutsohn, J. P., et al. (2015). Linking Physical and Mental Health Summary Scores from the Veterans RAND 12-Item Health Survey (VR-12) to the PROMIS((R)) Global Health Scale. Journal of General Internal Medicine, 30(10), 1524–1530. https://doi.org/10.1007/s11606-015-3453-9.CrossRefPubMedPubMedCentral

20.

Revicki, D., Kawata, A., Harnam, N., Chen, W.-H., Hays, R., & Cella, D. (2009). Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Quality of Life Research, 18(6), 783–791. https://doi.org/10.1007/s11136-009-9489-8.CrossRefPubMedPubMedCentral

21.

Barile, J. P., Reeve, B. B., Smith, A. W., Zack, M. M., Mitchell, S. A., Kobau, R., et al. (2013). Monitoring population health for Healthy People 2020: Evaluation of the NIH PROMIS® Global Health, CDC Healthy Days, and satisfaction with life instruments. Quality of Life Research, 22(6), 1201–1211. https://doi.org/10.1007/s11136-012-0246-z.CrossRefPubMed

22.

Towers, A., Stevenson, B., Breheny, M., & Allen, J. (2015). Health, work, and retirement longitudinal study. In A. N. Pachana (Ed.), Encyclopedia of geropsychology (pp. 1–9). Singapore: Springer.

23.

Frieling, M. A., Davis, W. R., & Chiang, G. (2013). The SF-36v2 and SF-12v2 health surveys in New Zealand: Norms, scoring coefficients and cross-country comparisons. Australian and New Zealand Journal of Public Health, 37(1), 24–31. https://doi.org/10.1111/1753-6405.12006.CrossRefPubMed

24.

Radloff, L. S. (1977). The CES-D Scale: A Self-Report Depression Scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306.CrossRef

25.

Ensrud, K. E., Ewing, S. K., Taylor, B. C., Fink, H. A., Cawthon, P. M., Stone, K. L., et al. (2008). Comparison of 2 frailty indexes for prediction of falls, disability, fractures, and death in older women. Archives of Internal Medicine, 168(4), 382–389. https://doi.org/10.1001/archinternmed.2007.113.CrossRefPubMed

26.

Buchner, D. M., Rillamas-Sun, E., Di, C., LaMonte, M. J., Marshall, S. W., Hunt, J., et al. (2017). Accelerometer-measured moderate to vigorous physical activity and incidence rates of falls in older women. Journal of the American Geriatrics Society. https://doi.org/10.1111/jgs.14960.CrossRefPubMed

27.

Landis, J., & Koch, G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.CrossRefPubMed

28.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155.CrossRefPubMed

29.

Dorans, N. (2004). Equating, concordance, and expectation. Applied Psychological Measurement, 28, 227–246. https://doi.org/10.1177/0146621604265031.CrossRef

30.

Walters, S. J., Munro, J. F., & Brazier, J. E. (2001). Using the SF-36 with older adults: A cross-sectional community-based survey. Age and Ageing, 30(4), 337–343.CrossRefPubMed

31.

Kim, J., Chung, H., Askew, R. L., Park, R., Jones, S. M. W., Cook, K. F., et al. (2015). Translating CESD-20 and PHQ-9 Scores to PROMIS depression. Assessment, 24(3), 300–307. https://doi.org/10.1177/1073191115607042.CrossRef

32.

Choi, S. W., Schalet, B., Cook, K. F., & Cella, D. (2014). Establishing a common metric for depressive symptoms: Linking the BDI-II, CES-D, and PHQ-9 to PROMIS depression. Psychological Assessment, 26(2), 513–527. https://doi.org/10.1037/a0035768.CrossRefPubMedPubMedCentral

33.

Schalet, B. D., Revicki, D. A., Cook, K. F., Krishnan, E., Fries, J. F., & Cella, D. (2015). Establishing a common metric for physical function: Linking the HAQ-DI and SF-36 PF Subscale to PROMIS® physical function. Journal of General Internal Medicine, 30(10), 1517–1523. https://doi.org/10.1007/s11606-015-3360-0.CrossRefPubMedPubMedCentral

34.

Kolen, M. J., & Brennan, R. L. (2014). Test equating, scaling, and linking (2nd ed., statistics for social science and public policy) New York: Springer.

Titel: The sensitivity of the MOS SF-12 and PROMIS® global summary scores to adverse health events in an older cohort
Auteurs: Joanne Allen
Fiona M. Alpass
Christine V. Stephens
Publicatiedatum: 03-05-2018
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 8/2018
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-018-1871-y

Andere artikelen Uitgave 8/2018

Measurement properties of ThyPRO short-form (ThyPRO-39) for use in Chinese patients with benign thyroid diseases

Measuring health-related quality of life in patients with advanced cancer: a systematic review of self-administered measurement instruments

Open Access
Review

Influence of changes in the Spanish labor market during the economic crisis (2007–2011) on perceived health

Health-related quality of life of African-American female breast cancer survivors, survivors of other cancers, and those without cancer

Giving voice to the child perspective: psychometrics and relative precision findings for the Child Health Questionnaire self-report short form (CHQ-CF45)

Bohn Stafleu van Loghum

The sensitivity of the MOS SF-12 and PROMIS® global summary scores to adverse health events in an older cohort

Abstract

Purpose

Methods

Results

Conclusions

Andere artikelen Uitgave 8/2018

Measurement properties of ThyPRO short-form (ThyPRO-39) for use in Chinese patients with benign thyroid diseases

Measuring health-related quality of life in patients with advanced cancer: a systematic review of self-administered measurement instruments

Influence of changes in the Spanish labor market during the economic crisis (2007–2011) on perceived health

Health-related quality of life of African-American female breast cancer survivors, survivors of other cancers, and those without cancer

Giving voice to the child perspective: psychometrics and relative precision findings for the Child Health Questionnaire self-report short form (CHQ-CF45)

Deprivation is associated with worse physical and mental health beyond income poverty: a population-based household survey among Chinese adults

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Purpose

Methods

Results

Conclusions

Log in om toegang te krijgen

Measurement properties of ThyPRO short-form (ThyPRO-39) for use in Chinese patients with benign thyroid diseases

Measuring health-related quality of life in patients with advanced cancer: a systematic review of self-administered measurement instruments

Influence of changes in the Spanish labor market during the economic crisis (2007–2011) on perceived health

Health-related quality of life of African-American female breast cancer survivors, survivors of other cancers, and those without cancer

Giving voice to the child perspective: psychometrics and relative precision findings for the Child Health Questionnaire self-report short form (CHQ-CF45)

Deprivation is associated with worse physical and mental health beyond income poverty: a population-based household survey among Chinese adults