Anna S Geraedts1, Marjolein Fokkema, Annet M Kleiboer, Filip Smit, Noortje W Wiezer, Maria Cristina Majo, Willem van Mechelen, Pim Cuijpers, Brenda W J H Penninx. 1. From the Department of Clinical Psychology (Ms Geraedts, Ms Fokkema, and Drs Kleiboer, Smit, and Cuijpers), VU University; EMGO Institute for Health and Care Research (Ms Geraedts and Drs Kleiboer, Smit, van Mechelen, Cuijpers, and Penninx), VU University Amsterdam and VU University Medical Center Amsterdam; Body@Work (Ms Geraedts and Drs Kleiboer, Wiezer, van Mechelen, and Cuijpers), Research Center Physical Activity, Work and Health, TNO-VU-VUmc, Amsterdam; Trimbos Institute (Netherlands Institute of Mental Health and Addiction) (Dr Smit), Utrecht; TNO (Dr Wiezer), Hoofddorp; Departments of Public and Occupational Health (Dr van Mechelen) and Psychiatry (Dr Penninx), VU University Medical Center, Amsterdam; Department of Psychiatry (Dr Penninx), Leiden University Medical Centre; and Department of Psychiatry (Dr Penninx), University Medical Centre Groningen, University of Groningen, the Netherlands.
Abstract
OBJECTIVE: To examine how various predictors and subgroups of respondents contribute to the prediction of health care and productivity costs in a cohort of employees. METHODS: We selected 1548 employed people from a cohort study with and without depressive and anxiety symptoms or disorders. Prediction rules, using the RuleFit program, were applied to identify predictors and subgroups of respondents, and to predict estimations of subsequent 1-year health care and productivity costs. RESULTS: Symptom severity and diagnosis of depression and anxiety were the most important predictors of health care costs. Depressive symptom severity was the most important predictor for productivity costs. Several demographic, social, and work predictors did not predict economic costs. CONCLUSIONS: Our data suggest that from a business perspective it can be beneficial to offer interventions aimed at prevention of depression and anxiety.
OBJECTIVE: To examine how various predictors and subgroups of respondents contribute to the prediction of health care and productivity costs in a cohort of employees. METHODS: We selected 1548 employed people from a cohort study with and without depressive and anxiety symptoms or disorders. Prediction rules, using the RuleFit program, were applied to identify predictors and subgroups of respondents, and to predict estimations of subsequent 1-year health care and productivity costs. RESULTS: Symptom severity and diagnosis of depression and anxiety were the most important predictors of health care costs. Depressive symptom severity was the most important predictor for productivity costs. Several demographic, social, and work predictors did not predict economic costs. CONCLUSIONS: Our data suggest that from a business perspective it can be beneficial to offer interventions aimed at prevention of depression and anxiety.
Authors: Manish K Jha; Abu Minhajuddin; Tracy L Greer; Thomas Carmody; A John Rush; Madhukar H Trivedi Journal: Am J Psychiatry Date: 2016-08-13 Impact factor: 18.112
Authors: Eva Szigethy; Francis Solano; Meredith Wallace; Dina L Perry; Lauren Morrell; Kathryn Scott; Megan Jones Bell; Megan Oser Journal: BMJ Open Date: 2018-01-13 Impact factor: 2.692