title: Evaluation of Automatically Assigned Job-Specific Interview Modules.
abstract: OBJECTIVE
  In community-based epidemiological studies, job- and industry-specific 'modules' are often used to systematically obtain details about the subject's work tasks. The module assignment is often made by the interviewer, who may have insufficient occupational hygiene knowledge to assign the correct module. We evaluated, in the context of a case-control study of lymphoid neoplasms in Asia ('AsiaLymph'), the performance of an algorithm that provided automatic, real-time module assignment during a computer-assisted personal interview.
  
  
  METHODS
  AsiaLymph's occupational component began with a lifetime occupational history questionnaire with free-text responses and three solvent exposure screening questions. To assign each job to one of 23 study-specific modules, an algorithm automatically searched the free-text responses to the questions 'job title' and 'product made or services provided by employer' using a list of module-specific keywords, comprising over 5800 keywords in English, Traditional and Simplified Chinese. Hierarchical decision rules were used when the keyword match triggered multiple modules. If no keyword match was identified, a generic solvent module was assigned if the subject responded 'yes' to any of the three solvent screening questions. If these question responses were all 'no', a work location module was assigned, which redirected the subject to the farming, teaching, health professional, solvent, or industry solvent modules or ended the questions for that job, depending on the location response. We conducted a reliability assessment that compared the algorithm-assigned modules to consensus module assignments made by two industrial hygienists for a subset of 1251 (of 11409) jobs selected using a stratified random selection procedure using module-specific strata. Discordant assignments between the algorithm and consensus assignments (483 jobs) were qualitatively reviewed by the hygienists to evaluate the potential information lost from missed questions with using the algorithm-assigned module (none, low, medium, high).
  
  
  RESULTS
  The most frequently assigned modules were the work location (33%), solvent (20%), farming and food industry (19%), and dry cleaning and textile industry (6.4%) modules. In the reliability subset, the algorithm assignment had an exact match to the expert consensus-assigned module for 722 (57.7%) of the 1251 jobs. Overall, adjusted for the proportion of jobs in each stratum, we estimated that 86% of the algorithm-assigned modules would result in no information loss, 2% would have low information loss, and 12% would have medium to high information loss. Medium to high information loss occurred for <10% of the jobs assigned the generic solvent module and for 21, 32, and 31% of the jobs assigned the work location module with location responses of 'someplace else', 'factory', and 'don't know', respectively. Other work location responses had ≤8% with medium to high information loss because of redirections to other modules. Medium to high information loss occurred more frequently when a job description matched with multiple keywords pointing to different modules (29-69%, depending on the triggered assignment rule).
  
  
  CONCLUSIONS
  These evaluations demonstrated that automatically assigned modules can reliably reproduce an expert's module assignment without the direct involvement of an industrial hygienist or interviewer. The feasibility of adapting this framework to other studies will be language- and exposure-specific.
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA; friesenmc@mail.nih.gov.
authors.forename: Melissa C
authors.initials: MC
authors.lastname: Friesen
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA;
authors.forename: Qing
authors.initials: Q
authors.lastname: Lan
authors.affiliation: 2.University of Utrecht, Utrecht, The Netherlands;
authors.forename: Calvin
authors.initials: C
authors.lastname: Ge
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA;
authors.forename: Sarah J
authors.initials: SJ
authors.lastname: Locke
authors.affiliation: 3.Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA;
authors.forename: Dean
authors.initials: D
authors.lastname: Hosgood
authors.affiliation: 4.School of Public Health, Curtin University, Perth, Australia;
authors.forename: Lin
authors.initials: L
authors.lastname: Fritschi
authors.affiliation: 5.Data Scientists Pty Ltd, Sunshine Coast, Queensland, Australia;
authors.forename: Troy
authors.initials: T
authors.lastname: Sadkowsky
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA; 6.Environmental Health Research Center, National Health Research Institutes, Zhunan, Taiwan;
authors.forename: Yu-Cheng
authors.initials: YC
authors.lastname: Chen
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA;
authors.forename: Hu
authors.initials: H
authors.lastname: Wei
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA; 7.Division of Community Medicine and Public Health Practice, School of Public Health, The University of Hong Kong, Hong Kong;
authors.forename: Jun
authors.initials: J
authors.lastname: Xu
authors.affiliation: 7.Division of Community Medicine and Public Health Practice, School of Public Health, The University of Hong Kong, Hong Kong;
authors.forename: Tai Hing
authors.initials: TH
authors.lastname: Lam
authors.affiliation: 8.Bone Marrow Transplant Unit, Queen Mary Hospital, Hong Kong; 9.Division of Haematology, Oncology and Bone Marrow Transplantation, Department of Medicine, The University of Hong Kong, Hong Kong;
authors.forename: Yok Lam
authors.initials: YL
authors.lastname: Kwong
authors.affiliation: 10.Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China;
authors.forename: Kexin
authors.initials: K
authors.lastname: Chen
authors.affiliation: 11.Department of Hematology, Hematology Research Laboratory and Pathology, West China Hospital of Sichuan University, Chengdu, Sichuan, China;
authors.forename: Caigang
authors.initials: C
authors.lastname: Xu
authors.affiliation: 12.Division of Hematology-Oncology, Department of Internal Medicine, Buddhist Dalin Tzu Chi General Hospital, Chiayi, Taiwan; 13.School of Medicine, Tzu Chi University, Hualian, Taiwan;
authors.forename: Yu-Chieh
authors.initials: YC
authors.lastname: Su
authors.affiliation: 14.Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
authors.forename: Brian C H
authors.initials: BC
authors.lastname: Chiu
authors.affiliation: 7.Division of Community Medicine and Public Health Practice, School of Public Health, The University of Hong Kong, Hong Kong;
authors.forename: Kai Ming Dennis
authors.initials: KM
authors.lastname: Ip
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA;
authors.forename: Mark P
authors.initials: MP
authors.lastname: Purdue
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA;
authors.forename: Bryan A
authors.initials: BA
authors.lastname: Bassig
authors.affiliation: 1.Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, North Bethesda, MD 20980, USA;
authors.forename: Nat
authors.initials: N
authors.lastname: Rothman
authors.affiliation: 2.University of Utrecht, Utrecht, The Netherlands;
authors.forename: Roel
authors.initials: R
authors.lastname: Vermeulen
mesh_terms: D000465:Algorithms; D001208:Asia; D016022:Case-Control Studies; D016021:Epidemiologic Studies; D006801:Humans; D007587:Job Description; D016273:Occupational Exposure / Q000032:analysis*; D009790:Occupations / Q000145:classification*; D015203:Reproducibility of Results; D012307:Risk Factors; D012984:Software; D012997:Solvents / Q000009:adverse effects; D011795:Surveys and Questionnaires
chemical_list: D012997:Solvents
keywords: case-control studies; epidemiologic studies; occupational exposure; solvents