130
Views
0
CrossRef citations to date
0
Altmetric
Original Research

Mapping the World Health Organization Disability Assessment Scale 2.0 to the EQ-5D-5L in patients with mental disorders

ORCID Icon, , , , , , & show all
Received 15 Apr 2024, Accepted 25 Jun 2024, Published online: 11 Jul 2024

References

  • Christensen MK, Lim CCW, Saha S, et al. The cost of mental disorders: a systematic review. Epidemiol Psychiatr Sci. 2020;29:e161. doi: 10.1017/S204579602000075X
  • Commission L. Report: mental illness will cost the world $16 trillion (USD) by 2030. Ment Health Wkly. 2018;28(39):1–8. doi: 10.1002/mhw.31630
  • Brazier J. Measuring and valuing mental health for use in economic evaluation. J Health Serv Res & Policy. 2008;13 Suppl 3(3_suppl):70–75. doi: 10.1258/jhsrp.2008.008015
  • Brazier J, Connell J, Papaioannou D, et al. A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures. Health Technol Assess. 2014;18(34):vii–viii, xiii–xxv, 1–188. doi: 10.3310/hta18340
  • Longworth L, Rowen D. Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value Health. 2013;16(1):202–210. doi: 10.1016/j.jval.2012.10.010
  • Dakin H. Review of studies mapping from quality of life or clinical measures to EQ‐5D: an online database. Health Qual Life Outcomes. 2013;11(1):151. doi: 10.1186/1477-7525-11-151
  • NICE. Guide to the methods of technology appraisal 2013. (UK): National Institute for Health and Care Excellence; 2013. Available from: https://www.nice.org.uk/process/pmg9/chapter/foreword
  • Longworth L, Yang Y, Young T, et al. Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: a systematic review, statistical modelling and survey. Health Technol Assess. 2014;18(9):1–224. doi: 10.3310/hta18090
  • Ustun TB, Chatterji S, Kostanjsek N, et al. Developing the world health organization disability assessment schedule 2.0. Bull World Health Organ. 2010;88(11):815–823. doi: 10.2471/BLT.09.067231
  • Federici S, Bracalenti M, Meloni F, et al. World health organization disability assessment schedule 2.0: an international systematic review. Disabil Rehabil. 2017;39(23):2347–2380. doi: 10.1080/09638288.2016.1223177
  • Sjonnesen K, Bulloch AG, Williams J, et al. Characterization of disability in Canadians with mental disorders using an abbreviated version of a DSM-5 emerging measure: the 12-Item WHO disability assessment schedule (WHODAS) 2.0. Can J Psychiatry. 2016;61(4):227–235. doi: 10.1177/0706743716632514
  • Selb M, Kohler F, Robinson Nicol MM, et al. ICD-11: a comprehensive picture of health, an update on the ICD–ICF joint use initiative. J Rehabil Med. 2015;47(1):2–8. doi: 10.2340/16501977-1928
  • Ma BH, Chen G, Badji S, et al. Mapping the 12‑item world health organization disability assessment schedule 2.0 (WHODAS 2.0) onto the assessment of quality of life (AQoL)‑4D utilities. Qual Life Res. 2023;33:411–422.
  • van Hout B, Janssen MF, Feng YS, et al. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Value Health. 2012;15(5):708–715. doi: 10.1016/j.jval.2012.02.008
  • Subramaniam M, Abdin E, Vaingankar JA, et al. Validation of the world health organization disability assessment schedule 2.0 among older adults in an Asian country. Singapore Med J. 2020;61(5):246–253. doi: 10.11622/smedj.2019049
  • Xie F, Pullenayegum EM, Li SC, et al. Use of a disease-specific instrument in economic evaluations: mapping WOMAC onto the EQ-5D utility index. Value Health. 2010;13(8):873–878. doi: 10.1111/j.1524-4733.2010.00770.x
  • Brazier JE, Yang Y, Tsuchiya A, et al. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ. 2010;11(2):215–225. doi: 10.1007/s10198-009-0168-z
  • Verardi V, Croux C. Robust regression in stata. Stata J. 2009;9(3):439–453. doi: 10.1177/1536867X0900900306
  • Wijeysundera HC, Tomlinson AJ, Norris CM, et al. Predicting EQ-5D utility scores from the Seattle Angina Questionnaire in coronary artery disease: a mapping algorithm using a bayesian framework. Med Decis Making. 2011;31(3):481. doi: 10.1177/0272989X10386800
  • Austin PC. A comparison of methods for analyzing health-related quality-of-life measures. Value Health. 2002;5(4):329–337. doi: 10.1046/j.1524-4733.2002.54128.x
  • Tobin J. Estimation of relationships for limited dependent variables. Econometrica. 1985;26(1):24–36. doi: 10.2307/1907382
  • Alava MH, Wailoo AJ. Fitting adjusted limited dependent variable mixture models to EQ-5D. Stata J. 2015;15(3):737–750. doi: 10.1177/1536867X1501500307
  • Steiner IM, Bokemeyer B, Stargardt T. Mapping from SIBDQ to EQ-5D-5L for patients with inflammatory bowel disease. Eur J Health Econ. 2023;25(3):539–548. doi: 10.1007/s10198-023-01603-9
  • Papaioannou D, Brazier J, Parry G. How valid and responsive are generic health status measures, such as EQ-5D and SF-36, in schizophrenia? A systematic review. Value Health. 2011;14(6):907–920. doi: 10.1016/j.jval.2011.04.006
  • Cheung YB, Luo N, Ng R, et al. Mapping the functional assessment of cancer therapy-breast (FACT-B) to the 5-level EuroQoL Group’s 5-dimension questionnaire (EQ-5D-5L) utility index in a multi-ethnic Asian population. Health Qual Life Outcomes. 2014;12(1):180. doi: 10.1186/s12955-014-0180-6