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The Study on Mental Health at Work: Design and sampling

Aims: The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a...

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Autores principales: Rose, Uwe, Schiel, Stefan, Schröder, Helmut, Kleudgen, Martin, Tophoven, Silke, Rauch, Angela, Freude, Gabriele, Müller, Grit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5598876/
https://www.ncbi.nlm.nih.gov/pubmed/28673202
http://dx.doi.org/10.1177/1403494817707123
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author Rose, Uwe
Schiel, Stefan
Schröder, Helmut
Kleudgen, Martin
Tophoven, Silke
Rauch, Angela
Freude, Gabriele
Müller, Grit
author_facet Rose, Uwe
Schiel, Stefan
Schröder, Helmut
Kleudgen, Martin
Tophoven, Silke
Rauch, Angela
Freude, Gabriele
Müller, Grit
author_sort Rose, Uwe
collection PubMed
description Aims: The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. Methods: S-MGA is a representative study of German employees aged 31–60 years subject to social security contributions. The sample was drawn from the employment register based on a two-stage cluster sampling procedure. Firstly, 206 municipalities were randomly selected from a pool of 12,227 municipalities in Germany. Secondly, 13,590 addresses were drawn from the selected municipalities for the purpose of conducting 4500 face-to-face interviews. The questionnaire covers psychosocial working and employment conditions, measures of mental health, work ability and functioning. Data from personal interviews were combined with employment histories from register data. Descriptive statistics of socio-demographic characteristics and logistic regressions analyses were used for comparing population, gross sample and respondents. Results: In total, 4511 face-to-face interviews were conducted. A test for sampling bias revealed that individuals in older cohorts participated more often, while individuals with an unknown educational level, residing in major cities or with a non-German ethnic background were slightly underrepresented. Conclusions: There is no indication of major deviations in characteristics between the basic population and the sample of respondents. Hence, S-MGA provides representative data for research on work and health, designed as a cohort study with plans to rerun the survey 5 years after the first assessment.
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spelling pubmed-55988762017-09-20 The Study on Mental Health at Work: Design and sampling Rose, Uwe Schiel, Stefan Schröder, Helmut Kleudgen, Martin Tophoven, Silke Rauch, Angela Freude, Gabriele Müller, Grit Scand J Public Health Study Design, validation of variables and instruments Aims: The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. Methods: S-MGA is a representative study of German employees aged 31–60 years subject to social security contributions. The sample was drawn from the employment register based on a two-stage cluster sampling procedure. Firstly, 206 municipalities were randomly selected from a pool of 12,227 municipalities in Germany. Secondly, 13,590 addresses were drawn from the selected municipalities for the purpose of conducting 4500 face-to-face interviews. The questionnaire covers psychosocial working and employment conditions, measures of mental health, work ability and functioning. Data from personal interviews were combined with employment histories from register data. Descriptive statistics of socio-demographic characteristics and logistic regressions analyses were used for comparing population, gross sample and respondents. Results: In total, 4511 face-to-face interviews were conducted. A test for sampling bias revealed that individuals in older cohorts participated more often, while individuals with an unknown educational level, residing in major cities or with a non-German ethnic background were slightly underrepresented. Conclusions: There is no indication of major deviations in characteristics between the basic population and the sample of respondents. Hence, S-MGA provides representative data for research on work and health, designed as a cohort study with plans to rerun the survey 5 years after the first assessment. SAGE Publications 2017-07-04 2017-08 /pmc/articles/PMC5598876/ /pubmed/28673202 http://dx.doi.org/10.1177/1403494817707123 Text en © Author(s) 2017 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Study Design, validation of variables and instruments
Rose, Uwe
Schiel, Stefan
Schröder, Helmut
Kleudgen, Martin
Tophoven, Silke
Rauch, Angela
Freude, Gabriele
Müller, Grit
The Study on Mental Health at Work: Design and sampling
title The Study on Mental Health at Work: Design and sampling
title_full The Study on Mental Health at Work: Design and sampling
title_fullStr The Study on Mental Health at Work: Design and sampling
title_full_unstemmed The Study on Mental Health at Work: Design and sampling
title_short The Study on Mental Health at Work: Design and sampling
title_sort study on mental health at work: design and sampling
topic Study Design, validation of variables and instruments
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5598876/
https://www.ncbi.nlm.nih.gov/pubmed/28673202
http://dx.doi.org/10.1177/1403494817707123
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