Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees

被引:0
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作者
Nyberg, Solja T. [1 ,2 ]
Elovainio, Marko [3 ,4 ]
Pentti, Jaana [1 ,2 ,5 ,6 ,7 ]
Frank, Philipp [1 ,8 ]
Ervasti, Jenni [2 ]
Harma, Mikko [2 ]
Koskinen, Aki [2 ]
Peutere, Laura [2 ,9 ]
Ropponen, Annina [2 ,10 ]
Vahtera, Jussi
Virtanen, Marianna [9 ,10 ]
Airaksinen, Jaakko [2 ]
Batty, G. David [8 ]
Kivimaki, Mika [1 ,2 ,8 ]
机构
[1] Univ Helsinki, Fac Med, Clinicum, Tukholmankatu 8B, FI-00014 Helsinki, Finland
[2] Finnish Inst Occupat Hlth, Helsinki, Finland
[3] Univ Helsinki, Fac Med, Dept Psychol & Logoped, Helsinki, Finland
[4] Finnish Inst Hlth & Welf, Helsinki, Finland
[5] Univ Turku, Dept Publ Hlth, Turku, Finland
[6] Univ Turku, Populat Res Ctr, Turku, Finland
[7] Turku Univ Hosp, Turku, Finland
[8] UCL, UCL Brain Sci, London, England
[9] Univ Eastern Finland, Sch Educ Sci & Psychol, Kuopio, Finland
[10] Karolinska Inst, Div Insurance Med, Stockholm, Sweden
基金
芬兰科学院;
关键词
machine learning; risk prediction; survey data; RISK; HEALTH; WORK; NONRESPONSE; VALIDATION; DISABILITY; MORTALITY; DISEASE; MODELS;
D O I
10.5271/sjweh.4124
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Objective This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers.Methods This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting >= 90 days during a 4-year follow-up.Results The C-index of 0.73 [95% confidence interval (CI) 0.70-0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67-0.75) for an administrative records-only model, and 0.79 (95% CI 0.76-0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome.Conclusions The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.
引用
收藏
页码:610 / 620
页数:11
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