Piloting an empirical approach to link the international classification of functioning, disability, and health to job demand classification

Chih Ying Li, Paul B. Arthur, Ickpyo Hong, Craig A. Velozo

Research output: Contribution to journalArticle

Abstract

BACKGROUND: The Social Security Administration has a thorough disability claims process, though one goal is to process claims more efficiently. This pilot described the creation and trial of a web-based tool to assist this process. OBJECTIVE: To empirically link the International Classification of Functioning, Disability and Health (ICF) model to the Occupational Information Network (O*NET) with a self-reported activity measure (physical domain). METHODS: ICF Activity domains and item difficulty calibrations were obtained from a self-reported ICF-Activity Measure. Three work/disability experts matched measurement constructs, job names, and item difficulties with job demands. Item difficulties were linked for 'Positioning and Transfer' with O*NET data values of 'Stamina'; 'Trunk Strength', and 'Walking and Moving' with O*NET data values of 'Stamina.' The system was then pilot tested with 14 adults with more than one activity challenges. RESULTS: An average total of 613 jobs were generated per participant and each job was categorized into one of 16 job clusters. Person ability measures and constructs were significant predictors for numbers of job (R2 = 0.92, p < 0.05). Participants demonstrated moderate satisfaction with program usability, and reported capability in performing jobs. CONCLUSIONS: The system provides a feasible means to assist disability examiners and claimants in identifying relevant job abilities and options.

Original languageEnglish (US)
Pages (from-to)721-729
Number of pages9
JournalWork
Volume64
Issue number4
DOIs
StatePublished - Jan 1 2019

Keywords

  • Social security
  • disability evaluation
  • employment assessment
  • outcome assessment (healthcare)
  • self-report

ASJC Scopus subject areas

  • Rehabilitation
  • Public Health, Environmental and Occupational Health

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