Swipe om te navigeren naar een ander artikel
To evaluate the degree to which applying alternative stopping rules would reduce response burden while maintaining score precision in the context of computer adaptive testing (CAT).
Analyses were conducted on secondary data comprised of CATs administered in a clinical setting at multiple time points (baseline and up to two follow ups) to 417 study participants who had back pain (51.3%) and/or depression (47.0%). Participant mean age was 51.3 years (SD = 17.2) and ranged from 18 to 86. Participants tended to be white (84.7%), relatively well educated (77% with at least some college), female (63.9%), and married or living in a committed relationship (57.4%). The unit of analysis was individual assessment histories (i.e., CAT item response histories) from the parent study. Data were first aggregated across all individuals, domains, and time points in an omnibus dataset of assessment histories and then were disaggregated by measure for domain-specific analyses. Finally, assessment histories within a “clinically relevant range” (score ≥ 1 SD from the mean in direction of poorer health) were analyzed separately to explore score level-specific findings.
Two different sets of CAT administration rules were compared. The original CAT (CATORIG) rules required at least four and no more than 12 items be administered. If the score standard error (SE) reached a value < 3 points (T score metric) before 12 items were administered, the CAT was stopped. We simulated applying alternative stopping rules (CATALT), removing the requirement that a minimum four items be administered, and stopped a CAT if responses to the first two items were both associated with best health, if the SE was < 3, if SE change < 0.1 (T score metric), or if 12 items were administered. We then compared score fidelity and response burden, defined as number of items administered, between CATORIG and CATALT.
CATORIG and CATALT scores varied little, especially within the clinically relevant range, and response burden was substantially lower under CATALT (e.g., 41.2% savings in omnibus dataset).
Alternate stopping rules result in substantial reductions in response burden with minimal sacrifice in score precision.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
Ahmed, S., Ware, P., Gardner, W., Witter, J., Bingham, C. O. 3rd, Kairy, D., et al. (2017) Montreal Accord on patient-reported outcomes use series-paper 8: Patient-reported outcomes in electronic health records can inform clinical and policy decisions. Journal of Clinical Epidemiology, 89, 160–167. CrossRefPubMed
Broderick, J. E., DeWitt, E. M., Rothrock, N., Crane, P. K., & Forrest, C. B. (2013) Advances in patient-reported outcomes: The NIH PROMIS((R)) measures. EGEMS (Wash DC), 1, 1015.
Health USDo, Human Services FDACfDE, Research, Health USDo, Human Services FDACfBE, Research, et al. (2006). Guidance for industry: Patient-reported outcome measures: Use in medical product development to support labeling claims: Draft guidance. Health and Quality of Life Outcomes, 4, 79. CrossRef
Noonan, V. K., Lyddiatt, A., Ware, P., Jaglal, S. B., Riopelle, R. J., & Bingham, C. O. 3rd, et al. (2017) Montreal Accord on patient-reported outcomes use series-paper 3: Patient-reported outcomes can facilitate shared decision-making and guide self-management. Journal of Clinical Epidemiology, 89, 125–135 CrossRefPubMed
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, 1179–1194. CrossRefPubMedPubMedCentral
Pilkonis, P. A., Choi, S. W., Reise, S. P., Stover, A. M., Riley, W. T., Cella, D., et al. (2011). Item banks for measuring emotional distress from the patient-reported outcomes measurement information system (PROMIS(R)): Depression, anxiety, and anger. Assessment, 18, 263–283. CrossRefPubMedPubMedCentral
Christodoulou, C., Junghaenel, D. U., DeWalt, D. A., Rothrock, N., & Stone, A. A. (2008). Cognitive interviewing in the evaluation of fatigue items: Results from the patient-reported outcomes measurement information system (PROMIS). Quality of life research: An international journal of quality of life aspects of treatment. Care and Rehabilitation, 17, 1239–1246.
Noonan, V. K., Cook, K. F., Bamer, A. M., Choi, S. W., Kim, J., & Amtmann, D. (2012). Measuring fatigue in persons with multiple sclerosis: Creating a crosswalk between the Modified Fatigue Impact Scale and the PROMIS fatigue short form. Quality of life research: An international journal of quality of life aspects of treatment. Care and Rehabilitation, 21, 1123–1133.
Flynn, K. E., Shelby, R. A., Mitchell, S. A., Fawzy, M. R., Hardy, N. C., Husain, A. M., et al. (2010). Sleep-wake functioning along the cancer continuum: Focus group results from the patient-reported outcomes measurement information system (PROMIS((R))). Psychooncology, 19, 1086–1093. CrossRefPubMedPubMedCentral
Hahn, E. A., Devellis, R. F., Bode, R. K., Garcia, S. F., Castel, L. D., Eisen, S. V., et al. (2010). Measuring social health in the patient-reported outcomes measurement information system (PROMIS): Item bank development and testing. Quality of life research: An international journal of quality of life aspects of treatment. Care and Rehabilitation, 19, 1035–1044.
Pilkonis, P. A., Yu, L., Dodds, N. E., Johnston, K. L., Maihoefer, C. C., & Lawrence, S. M. (2014). Validation of the depression item bank from the patient-reported outcomes measurement information system (PROMIS) in a three-month observational study. Journal of Psychiatric Research, 56, 112–119. CrossRefPubMedPubMedCentral
Ware, J. E. Jr., Kosinski, M., Bjorner, J. B., Bayliss, M. S., Batenhorst, A., Dahlof, C. G., et al. (2003) Applications of computerized adaptive testing (CAT) to the assessment of headache impact. Quality of life research: An international journal of quality of life aspects of treatment. Care and Rehabilitation, 12, 935–952.
- Grooming a CAT: customizing CAT administration rules to increase response efficiency in specific research and clinical settings
Michael A. Kallen
Karon F. Cook
Richard C. Gershon
- Springer International Publishing