Visith Uy1, Ron D Hays2,3,4, Jay J Xu5, Peter M Fayers6,7, Andrew D Auerbach8, Jeanne T Black9, Lorraine S Evangelista10, Theodore G Ganiats11, Patrick S Romano12,13, Michael K Ong1,14,15. 1. Division of General Internal Medicine & Health Services Research, UCLA Department of Medicine, 1100 Glendon Avenue, Suite 850, Los Angeles, CA, 90024, USA. 2. Division of General Internal Medicine & Health Services Research, UCLA Department of Medicine, 1100 Glendon Avenue, Suite 850, Los Angeles, CA, 90024, USA. drhays@ucla.edu. 3. Department of Health Policy & Management, University of California, Los Angeles, Los Angeles, CA, USA. drhays@ucla.edu. 4. RAND Health, RAND Corporation, Santa Monica, CA, USA. drhays@ucla.edu. 5. UCLA Department of Biostatistics, 650 Charles E. Young Drive South, 51-254 CHS, Los Angeles, CA, 90024, USA. 6. Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. 7. Emeritus Professor, Institute of Applied Health Sciences, King's College, University of Aberdeen, Aberdeen, AB24 3FX, UK. 8. Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, 533 Parnassus Avenue, Room 131, San Francisco, CA, 94117, USA. 9. Department of Orthopaedics, Cedars-Sinai Medical Center, Los Angeles, 116 N. Robertson Blvd., Suite 800, Los Angeles, CA, 90048, USA. 10. Sue & Bill Gross School of Nursing, University of California, Irvine, 284 Berk Hall, Irvine, CA, 92697, USA. 11. Department of Family Medicine and Public Health, University of California, San Diego, 9500 Gilman Drive #0725, La Jolla, CA, 92093, USA. 12. Department of Internal Medicine, University of California, Davis, 4860 Y Street, Suites 0101 & 0400, Sacramento, CA, 95817, USA. 13. Department of Pediatrics, University of California, Davis, Sacramento, CA, USA. 14. Department of Health Policy & Management, University of California, Los Angeles, Los Angeles, CA, USA. 15. Department of Medicine, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Abstract
PURPOSE: Half of the 21-item Minnesota Living with Heart Failure Questionnaire (MLHFQ) response categories are labeled (0 = No, 1 = Very little, 5 = Very much) and half are not (2, 3, and 4). We hypothesized that the unlabeled response options would not be more likely to be chosen at some place along the scale continuum than other response options and, therefore, not satisfy the monotonicity assumption of simple-summated scoring. METHODS: We performed exploratory and confirmatory factor analyses of the MLHFQ items in a sample of 1437 adults in the Better Effectiveness After Transition-Heart Failure study. We evaluated the unlabeled response options using item characteristic curves from item response theory-graded response models for MLHFQ physical and emotional health scales. Then, we examined the impact of collapsing response options on correlations of scale scores with other variables. RESULTS:The sample was 46% female; 71% aged 65 or older; 11% Hispanic, 22% Black, 54% White, and 12% other. The unlabeled response options were rarely chosen. The standard approach to scoring and scores obtained by collapsing adjacent response categories yielded similar associations with other variables, indicating that the existing response options are problematic. CONCLUSIONS: The unlabeled MLHFQ response options do not meet the assumptions of simple-summated scoring. Further assessment of the performance of the unlabeled response options and evaluation of alternative scoring approaches is recommended. Adding labels for response options in future administrations of the MLHFQ should be considered.
RCT Entities:
PURPOSE: Half of the 21-item Minnesota Living with Heart Failure Questionnaire (MLHFQ) response categories are labeled (0 = No, 1 = Very little, 5 = Very much) and half are not (2, 3, and 4). We hypothesized that the unlabeled response options would not be more likely to be chosen at some place along the scale continuum than other response options and, therefore, not satisfy the monotonicity assumption of simple-summated scoring. METHODS: We performed exploratory and confirmatory factor analyses of the MLHFQ items in a sample of 1437 adults in the Better Effectiveness After Transition-Heart Failure study. We evaluated the unlabeled response options using item characteristic curves from item response theory-graded response models for MLHFQ physical and emotional health scales. Then, we examined the impact of collapsing response options on correlations of scale scores with other variables. RESULTS: The sample was 46% female; 71% aged 65 or older; 11% Hispanic, 22% Black, 54% White, and 12% other. The unlabeled response options were rarely chosen. The standard approach to scoring and scores obtained by collapsing adjacent response categories yielded similar associations with other variables, indicating that the existing response options are problematic. CONCLUSIONS: The unlabeled MLHFQ response options do not meet the assumptions of simple-summated scoring. Further assessment of the performance of the unlabeled response options and evaluation of alternative scoring approaches is recommended. Adding labels for response options in future administrations of the MLHFQ should be considered.
Entities:
Keywords:
Health-related quality of life; Heart failure; Item characteristic curves; Minnesota Living with Heart Failure Questionnaire; Survey response options
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