Abstract
Purpose
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.
Methods
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 %).
Results
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.
Conclusion
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.
Similar content being viewed by others
References
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.
Bodenheimer, T., Lorig, K., Holman, H., & Grumbach, K. (2002). Patient self-management of chronic disease in primary care. Journal of the American Medical Association, 288(19), 2469–2475.
Leventhal, H., Weinman, J., Leventhal, E. A., & Phillips, L. A. (2008). Health psychology: The search for pathways between behavior and health. Annual Review of Psychology, 59, 477–505. doi:10.1146/annurev.psych.59.103006.093643.
Jones, F., Partridge, C., & Reid, F. (2008). The Stroke Self-Efficacy Questionnaire: Measuring individual confidence in functional performance after stroke. Journal of Clinical Nursing, 17(7b), 244–252. doi:10.1111/j.1365-2702.2008.02333.x.
Gramstad, A., Iversen, E., & Engelsen, B. A. (2001). The impact of affectivity dispositions, self-efficacy and locus of control on psychosocial adjustment in patients with epilepsy. Epilepsy Research, 46(1), 53–61.
Schwartz, C. E., Coulthard-Morris, L., Zeng, Q., & Retzlaff, P. (1996). Measuring self-efficacy in people with multiple sclerosis: A validation study. Archives of Physical Medicine and Rehabilitation, 77(4), 394–398.
Beckham, J. C., Burker, E. J., Lytle, B. L., Feldman, M. E., & Costakis, M. J. (1997). Self-efficacy and adjustment in cancer patients: A preliminary report. Behavioral Medicine, 23(3), 138–142. doi:10.1080/08964289709596370.
Wilcox, S., Schoffman, D. E., Dowda, M., & Sharpe, P. A. (2014). Psychometric properties of the 8-item english arthritis self-efficacy scale in a diverse sample. Arthritis, 2014, 385256. doi:10.1155/2014/385256.
Edwards, R., Telfair, J., Cecil, H., & Lenoci, J. (2001). Self-efficacy as a predictor of adult adjustment to sickle cell disease: One-year outcomes. Psychosomatic Medicine, 63(5), 850–858.
Lorig, K., Chastain, R. L., Ung, E., Shoor, S., & Holman, H. R. (1989). Development and evaluation of a scale to measure perceived self-efficacy in people with arthritis. Arthritis and Rheumatism, 32(1), 37–44.
Lorig, K. R., Sobel, D. S., Ritter, P. L., Laurent, D., & Hobbs, M. (2001). Effect of a self-management program on patients with chronic disease. Effective Clinical Practice, 4(6), 256–262.
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.
van der Linden, W. J., & Hambleton, R. K. (1997). Handbook of modern item response theory. New York: Springer.
DeWalt, D. A., Rothrock, N., Yount, S., & Stone, A. A. (2007). Evaluation of item candidates: The PROMIS qualitative item review. Medical Care, 45(5 Suppl 1), S12–S21. doi:10.1097/01.mlr.0000254567.79743.e2.
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.
Revicki, D. A., Chen, W. H., Harnam, N., Cook, K. F., Amtmann, D., Callahan, L. F., et al. (2009). Development and psychometric analysis of the PROMIS pain behavior item bank. Pain, 146(1–2), 158–169. doi:10.1016/j.pain.2009.07.029.
IBM SPSS Statistics for Windows. (2013). (22.0 ed.). Armonk, NY: IBM Corp.
Hair, J. F., Anderson, R. E., Tatham, R. I., & Black, W. C. (1998). Multivariate data analysis with readings. Prentice Hall: NY.
Cronbach, L. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. doi:10.1007/BF02310555.
McHorney, C. A., & Tarlov, A. R. (1995). Individual-patient monitoring in clinical practice: Are available health status surveys adequate? Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 4(4), 293–307.
Muthén, L. K., & Muthén, B. O. (2012). Mplus (7.11th ed.). CA: Los Angeles.
Revicki, D. A., Cook, K. F., Amtmann, D., Harnam, N., Chen, W. H., & Keefe, F. J. (2014). Exploratory and confirmatory factor analysis of the PROMIS pain quality item bank. Quality of Life Research, 23(1), 245–255. doi:10.1007/s11136-013-0467-9.
Cai, L., Thissen, D., & du Toit, S. H. C. (2011). IRTPRO for Windows (2.1st ed.). Lincolnwood, IL: Scientific Software International.
Orlando, M., & Thissen, D. (2000). Likelihood-based item-fit indices for dichotomous item response theory models. Applied Psychological Measurement, 24(1), 50–64.
Orlando, M., & Thissen, D. (2003). Further investigation of the performance of S − χ2: An item fit index for use with dichotomous item response theory models. Applied Psychological Measurement, 27(4), 289–298. doi:10.1177/0146621603027004004.
Dodd, B., Koch, W., & De Ayala, R. (1989). Operational characteristics of adaptive testing procedures using the graded response model. Applied Psychological Measurement, 13(2), 129–143.
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.
Crane, P. K., van Belle, G., & Larson, E. B. (2004). Test bias in a cognitive test: Differential item functioning in the CASI. Statistics in Medicine, 23(2), 241–256. doi:10.1002/sim.1713.
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.
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.
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.
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.
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.
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.
Acknowledgments
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.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
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.
Ethical approval
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
Informed consent was obtained from all individual participants included in the study.
Appendix
Appendix
Raw scores were converted into a T score metric
Raw score | T score | SE | Raw score | T score | SE | Raw score | T score | SE |
---|---|---|---|---|---|---|---|---|
35 | 16.31 | 3.73 | 82 | 35.05 | 0.87 | 129 | 42.63 | 0.87 |
36 | 18.98 | 2.91 | 83 | 35.17 | 0.91 | 130 | 42.75 | 0.93 |
37 | 20.28 | 2.70 | 84 | 35.30 | 0.97 | 131 | 42.89 | 1.01 |
38 | 21.32 | 2.52 | 85 | 35.45 | 1.06 | 132 | 43.06 | 1.10 |
39 | 22.18 | 2.37 | 86 | 35.63 | 1.14 | 133 | 43.25 | 1.19 |
40 | 22.97 | 2.21 | 87 | 35.84 | 1.22 | 134 | 43.48 | 1.25 |
41 | 23.65 | 2.08 | 88 | 36.07 | 1.26 | 135 | 43.72 | 1.28 |
42 | 24.26 | 1.99 | 89 | 36.31 | 1.27 | 136 | 43.97 | 1.28 |
43 | 24.82 | 1.90 | 90 | 36.55 | 1.24 | 137 | 44.21 | 1.23 |
44 | 25.33 | 1.84 | 91 | 36.76 | 1.17 | 138 | 44.43 | 1.17 |
45 | 25.81 | 1.77 | 92 | 36.95 | 1.08 | 139 | 44.63 | 1.09 |
46 | 26.26 | 1.71 | 93 | 37.11 | 0.98 | 140 | 44.80 | 1.03 |
47 | 26.67 | 1.65 | 94 | 37.24 | 0.89 | 141 | 44.95 | 0.99 |
48 | 27.05 | 1.60 | 95 | 37.35 | 0.82 | 142 | 45.10 | 0.99 |
49 | 27.42 | 1.57 | 96 | 37.44 | 0.78 | 143 | 45.25 | 1.03 |
50 | 27.77 | 1.55 | 97 | 37.53 | 0.78 | 144 | 45.42 | 1.10 |
51 | 28.12 | 1.53 | 98 | 37.62 | 0.81 | 145 | 45.62 | 1.18 |
52 | 28.46 | 1.51 | 99 | 37.72 | 0.87 | 146 | 45.84 | 1.26 |
53 | 28.78 | 1.48 | 100 | 37.85 | 0.95 | 147 | 46.09 | 1.31 |
54 | 29.09 | 1.43 | 101 | 38.00 | 1.05 | 148 | 46.36 | 1.34 |
55 | 29.37 | 1.37 | 102 | 38.17 | 1.14 | 149 | 46.64 | 1.33 |
56 | 29.64 | 1.32 | 103 | 38.38 | 1.22 | 150 | 46.90 | 1.29 |
57 | 29.88 | 1.30 | 104 | 38.61 | 1.26 | 151 | 47.16 | 1.25 |
58 | 30.13 | 1.30 | 105 | 38.85 | 1.26 | 152 | 47.39 | 1.22 |
59 | 30.38 | 1.32 | 106 | 39.08 | 1.23 | 153 | 47.62 | 1.22 |
60 | 30.64 | 1.34 | 107 | 39.29 | 1.16 | 154 | 47.85 | 1.25 |
61 | 30.91 | 1.36 | 108 | 39.47 | 1.07 | 155 | 48.10 | 1.31 |
62 | 31.18 | 1.36 | 109 | 39.63 | 0.97 | 156 | 48.37 | 1.38 |
63 | 31.45 | 1.33 | 110 | 39.76 | 0.89 | 157 | 48.68 | 1.44 |
64 | 31.70 | 1.27 | 111 | 39.86 | 0.82 | 158 | 49.01 | 1.49 |
65 | 31.92 | 1.20 | 112 | 39.96 | 0.78 | 159 | 49.36 | 1.52 |
66 | 32.11 | 1.13 | 113 | 40.04 | 0.78 | 160 | 49.72 | 1.53 |
67 | 32.29 | 1.07 | 114 | 40.14 | 0.81 | 161 | 50.08 | 1.55 |
68 | 32.45 | 1.05 | 115 | 40.24 | 0.88 | 162 | 50.46 | 1.60 |
69 | 32.62 | 1.06 | 116 | 40.37 | 0.97 | 163 | 50.85 | 1.67 |
70 | 32.79 | 1.10 | 117 | 40.52 | 1.06 | 164 | 51.29 | 1.76 |
71 | 32.98 | 1.17 | 118 | 40.70 | 1.15 | 165 | 51.77 | 1.87 |
72 | 33.20 | 1.23 | 119 | 40.91 | 1.22 | 166 | 52.31 | 1.98 |
73 | 33.43 | 1.28 | 120 | 41.14 | 1.26 | 167 | 52.91 | 2.11 |
74 | 33.68 | 1.29 | 121 | 41.38 | 1.27 | 168 | 53.56 | 2.25 |
75 | 33.92 | 1.28 | 122 | 41.61 | 1.23 | 169 | 54.31 | 2.44 |
76 | 34.16 | 1.22 | 123 | 41.83 | 1.16 | 170 | 55.19 | 2.67 |
77 | 34.37 | 1.15 | 124 | 42.01 | 1.07 | 171 | 56.38 | 3.21 |
78 | 34.54 | 1.06 | 125 | 42.17 | 0.98 | 172 | 57.28 | 3.26 |
79 | 34.70 | 0.97 | 126 | 42.30 | 0.91 | 173 | 58.68 | 3.56 |
80 | 34.82 | 0.90 | 127 | 42.42 | 0.86 | 174 | 60.39 | 3.82 |
81 | 34.94 | 0.87 | 128 | 42.53 | 0.85 | 175 | 65.11 | 5.41 |
Rights and permissions
About this article
Cite this article
Hong, I., Velozo, C.A., Li, CY. et al. Assessment of the psychometrics of a PROMIS item bank: self-efficacy for managing daily activities. Qual Life Res 25, 2221–2232 (2016). https://doi.org/10.1007/s11136-016-1270-1
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-016-1270-1