Assessment of the psychometrics of a PROMIS item bank: self-efficacy for managing daily activities
- 491 Downloads
The aim of this study is to investigate the psychometrics of the Patient-Reported Outcomes Measurement Information System self-efficacy for managing daily activities item bank.
The item pool was field tested on a sample of 1087 participants via internet (n = 250) and in-clinic (n = 837) surveys. All participants reported having at least one chronic health condition. The 35 item pool was investigated for dimensionality (confirmatory factor analyses, CFA and exploratory factor analysis, EFA), item-total correlations, local independence, precision, and differential item functioning (DIF) across gender, race, ethnicity, age groups, data collection modes, and neurological chronic conditions (McFadden Pseudo R 2 less than 10 %).
The item pool met two of the four CFA fit criteria (CFI = 0.952 and SRMR = 0.07). EFA analysis found a dominant first factor (eigenvalue = 24.34) and the ratio of first to second eigenvalue was 12.4. The item pool demonstrated good item-total correlations (0.59–0.85) and acceptable internal consistency (Cronbach’s alpha = 0.97). The item pool maintained its precision (reliability over 0.90) across a wide range of theta (3.70), and there was no significant DIF.
The findings indicated the item pool has sound psychometric properties and the test items are eligible for development of computerized adaptive testing and short forms.
KeywordsPatient-reported outcome measure Self-efficacy Daily activities Item response theory
The study was funded by the National Institutes of Health, Grant 1U01AR057967-01, “Development and Validation of a Self–Efficacy Item Bank,” Lisa Shulman (Principal Investigator) and Craig Velozo, Ann Gruber-Baldini and Sergio Romero (Co-Investigators). The results and conclusions presented in this paper are those of the authors and are independent from the funding source.
Compliance with ethical standards
Conflict of interest
Ickpyo Hong declares that he has no conflict of interest. Craig A. Velozo declares that he has no conflict of interest. Chih-Ying Li declares that she has no conflict of interest. Sergio Romero declares that he has no conflict of interest. Ann L. Gruber-Baldini declares that she has no conflict of interest. Lisa M. Shulman declares that she has no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study was approved by the Institutional review boards (IRB) of the Medical University of South Carolina (#Pro00033397), the University of Maryland (#HP-000432550), and the University of Florida (#261-2010).
Informed consent was obtained from all individual participants included in the study.
- 1.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. doi: 10.1097/01.mlr.0000258615.42478.55.CrossRefPubMedPubMedCentralGoogle Scholar
- 12.Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45(5 Suppl 1), S22–S31. doi: 10.1097/01.mlr.0000250483.85507.04.CrossRefPubMedGoogle Scholar
- 15.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. doi: 10.1016/j.jclinepi.2010.04.011.CrossRefPubMedPubMedCentralGoogle Scholar
- 17.IBM SPSS Statistics for Windows. (2013). (22.0 ed.). Armonk, NY: IBM Corp.Google Scholar
- 18.Hair, J. F., Anderson, R. E., Tatham, R. I., & Black, W. C. (1998). Multivariate data analysis with readings. Prentice Hall: NY.Google Scholar
- 21.Muthén, L. K., & Muthén, B. O. (2012). Mplus (7.11th ed.). CA: Los Angeles.Google Scholar
- 23.Cai, L., Thissen, D., & du Toit, S. H. C. (2011). IRTPRO for Windows (2.1st ed.). Lincolnwood, IL: Scientific Software International.Google Scholar
- 27.Choi, S. W., Gibbons, L. E., & Crane, P. K. (2011). Lordif: An R Package for detecting differential item functioning using iterative hybrid ordinal logistic regression/item response theory and Monte Carlo simulations. Journal of Statistical Software, 39(8), 1–30.CrossRefPubMedPubMedCentralGoogle Scholar
- 29.Irwin, D. E., Stucky, B., Langer, M. M., Thissen, D., DeWitt, E. M., Lai, J.-S., et al. (2010). An item response analysis of the pediatric PROMIS anxiety and depressive symptoms scales. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 19(4), 595–607. doi: 10.1007/s11136-010-9619-3.CrossRefGoogle Scholar
- 30.Lai, J.-S., Cella, D., Choi, S., Junghaenel, D. U., Christodoulou, C., Gershon, R., et al. (2011). How item banks and their application can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Archives of Physical Medicine and Rehabilitation, 92(10), S20–S27.CrossRefPubMedPubMedCentralGoogle Scholar
- 31.Pilkonis, P. A., Choi, S. W., Reise, S. P., Stover, A. M., Riley, W. T., & Cella, D. (2011). Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): Depression, anxiety, and anger. Assessment, 18(3), 263–283. doi: 10.1177/1073191111411667.CrossRefPubMedPubMedCentralGoogle Scholar
- 32.Hays, R. D., Morales, L. S., & Reise, S. P. (2000). Item response theory and health outcomes measurement in the 21st century. Medical Care, 38(9 Suppl), 28–42.Google Scholar
- 33.Rose, M., Bjorner, J. B., Becker, J., Fries, J. F., & Ware, J. E. (2008). Evaluation of a preliminary physical function item bank supported the expected advantages of the Patient-Reported Outcomes Measurement Information System (PROMIS). Journal of Clinical Epidemiology, 61(1), 17–33. doi: 10.1016/j.jclinepi.2006.06.025.CrossRefPubMedGoogle Scholar
- 34.Scott, N. W., Fayers, P. M., Aaronson, N. K., Bottomley, A., de Graeff, A., Groenvold, M., et al. (2009). A simulation study provided sample size guidance for differential item functioning (DIF) studies using short scales. Journal of Clinical Epidemiology, 62(3), 288–295. doi: 10.1016/j.jclinepi.2008.06.003.CrossRefPubMedGoogle Scholar