OBJECTIVE: Among people with arthritis, the need for work transitions may signal a risk for more adverse work outcomes in the future, such as permanent work loss. Our aim was to evaluate the ability of the Work Instability Scale for Rheumatoid Arthritis (RA-WIS) to predict arthritis-related work transitions within a 12-month period. METHODS: Workers with osteoarthritis or rheumatoid arthritis (n = 250) from 3 clinical sites participated in self-administered surveys that assessed the impact of health on employment at multiple time points over 12 months. Multivariable logistic regressions were conducted to assess the ability of the RA-WIS (range 0-23, where 23 = highest work instability) to predict 4 types of work transition: reductions in work hours, disability leaves of absence, changes in job/occupation, or temporary unemployment, assembled as a composite outcome. Covariates assessed include age, sex, education, marital status, income, pain intensity, disease duration, and the Health Assessment Questionnaire. Areas under the receiver operating characteristic curves (AUROCCs) were also assessed to further examine the predictive ability of the RA-WIS and to determine optimal cut points for predicting specific work transitions. RESULTS: After 12 months, 21.7% (n = 50 of 230) of the participants had indicated at least one arthritis-related work transition. Higher baseline RA-WIS was predictive of such an outcome (relative risk [RR] 1.05 [95% confidence interval (95% CI) 1.00-1.11]), particularly at >17 (RR 2.30 [95% CI 1.11-4.77]). The RA-WIS cut point of >13 was found to be most accurate for prediction (AUROCC 0.68 [95% CI 0.58-0.78]). CONCLUSION: The RA-WIS demonstrated the ability to predict arthritis-related work transitions within a short timeframe, and could be a promising measurement candidate for risk prognostication where work disability outcomes are of concern.
OBJECTIVE: Among people with arthritis, the need for work transitions may signal a risk for more adverse work outcomes in the future, such as permanent work loss. Our aim was to evaluate the ability of the Work Instability Scale for Rheumatoid Arthritis (RA-WIS) to predict arthritis-related work transitions within a 12-month period. METHODS: Workers with osteoarthritis or rheumatoid arthritis (n = 250) from 3 clinical sites participated in self-administered surveys that assessed the impact of health on employment at multiple time points over 12 months. Multivariable logistic regressions were conducted to assess the ability of the RA-WIS (range 0-23, where 23 = highest work instability) to predict 4 types of work transition: reductions in work hours, disability leaves of absence, changes in job/occupation, or temporary unemployment, assembled as a composite outcome. Covariates assessed include age, sex, education, marital status, income, pain intensity, disease duration, and the Health Assessment Questionnaire. Areas under the receiver operating characteristic curves (AUROCCs) were also assessed to further examine the predictive ability of the RA-WIS and to determine optimal cut points for predicting specific work transitions. RESULTS: After 12 months, 21.7% (n = 50 of 230) of the participants had indicated at least one arthritis-related work transition. Higher baseline RA-WIS was predictive of such an outcome (relative risk [RR] 1.05 [95% confidence interval (95% CI) 1.00-1.11]), particularly at >17 (RR 2.30 [95% CI 1.11-4.77]). The RA-WIS cut point of >13 was found to be most accurate for prediction (AUROCC 0.68 [95% CI 0.58-0.78]). CONCLUSION: The RA-WIS demonstrated the ability to predict arthritis-related work transitions within a short timeframe, and could be a promising measurement candidate for risk prognostication where work disability outcomes are of concern.
Authors: Maria N Tamborenea; Cecilia Pisoni; Sergio Toloza; Eduardo Mysler; Guillermo Tate; Dora Pereira; M García Carrasco; J Quintero; A Cappuccio; A Granel; M Lazaro; Pablo Arturi; Gustavo Citera; J Velazco Zamora; Veronica Saurit; A Alvarellos; S B Pons Estel; C Danielsen; C Graf; Sergio Paira; F Ceccatto; Javier Cavallasca; E Civit; J Moreno; A Estevez; M Diaz; Marcela Verando; Antonio Catalan Pellet; G Gomez; Pablo Maid; Ana Beron; Gabriela Salvatierra; Marcos Mendez; A Cusa; Oscar Rillo; M Paez; M Larraude; D Sohn; M Gallo; A Conforti; Veronica Malah; Patricio Tate; A Baños Journal: Rheumatol Int Date: 2014-06-20 Impact factor: 2.631
Authors: Myrthe van Vilsteren; Cecile R L Boot; Dirk L Knol; Dirkjan van Schaardenburg; Alexandre E Voskuyl; Romy Steenbeek; Johannes R Anema Journal: BMC Musculoskelet Disord Date: 2015-05-06 Impact factor: 2.362
Authors: Erin C Carruthers; Pamela Rogers; Catherine L Backman; Charles H Goldsmith; Monique A Gignac; Carlo Marra; Judy Village; Linda C Li; John M Esdaile; Diane Lacaille Journal: BMC Med Inform Decis Mak Date: 2014-07-21 Impact factor: 2.796