OverviewPsychosocial occupational epidemiology has mainly focused on the demand-control and, to a much lesser extent, the effort-reward-imbalance (ERI) models. These models and the strong focus on them raise some conceptual and methodological issues we will address in the following letter.The conceptual issues include the empirical confirmation of the assumptions of these models, the extent to which the focus on the demand-control and ERI models is warranted, and whether the sub-dimensions of the scales in these models have common health effects. We argue that there is a lack of empirical approval of (i) the assumptions behind both models and (ii) the focus on these models.The methodological issues include how exposure to job strain is categorized, how ERI previously has been measured, and the validity of self-reports of job strain. We argue that (i) a population independent definition of job strain is lacking, (ii) the older measurements of ERI mix exposure and effect, and (iii) we know little regarding the validity of the measurement of the psychosocial working environment.Finally, we suggest that analyses of monitoring data with a broader focus on the psychosocial working environment can be used to shed light to some of the issues raised above.
Purpose The Work Ability Index (WAI) is a routinely applied instrument for the assessment of work ability. It is a single score index, based on the implicit assumption of a single factor underlying the construct of work ability. The few studies with a focus on the WAI's factor structure are mainly based on non-representative samples. The objective of this study was to examine the factor structure of the WAI within a representative sample of employees working in Germany, applying analysis procedures that consider the metric of the variables. Methods Analyses are based on a nationwide representative sample of employees aged 31-60 years from the "Study on Mental Health at Work" (German: S-MGA). Responses from n = 3968 participants were used in confirmatory factor analyses comparing competing models of the structure underlying the WAI. Results The results of the analyses suggest that the intercorrelations between the indicators of the WAI are explained better by a model with two correlated factors than by a simple one-factor structure. A model solely allowing a single loading for each indicator fits the data well and allows for an easy interpretation of the two underlying factors. Conclusions There are two correlated factors underlying the WAI: one refers to "subjective work ability and resources", the other one can be considered a "health related factor".
This study provides first evidence for occupational differences in the risk of SARS-CoV-2 infection for Germany during the beginning of the pandemic. Findings confirm previous studies from Norway and the UK, reporting high infection rates in essential occupations and in personal services. In addition, we also test for vertical differences and find that infections were more common in higher occupational status positions.
BackgroundThe prevalence of workers with demanding physical working conditions in the European work force remains high, and occupational physical exposures are considered important risk factors for musculoskeletal disorders (MSD), a major burden for both workers and society. Exposures to physical workloads are therefore part of the European nationwide surveys to monitor working conditions and health. An interesting question is to what extent the same domains, dimensions and items referring to the physical workloads are covered in the surveys. The purpose of this paper is to determine 1) which domains and dimensions of the physical workloads are monitored in surveys at the national level and the EU level and 2) the degree of European consensus among these surveys regarding coverage of individual domains and dimensions.MethodItems on physical workloads used in one European wide/Spanish and five other European nationwide work environment surveys were classified into the domains and dimensions they cover, using a taxonomy agreed upon among all participating partners.ResultsThe taxonomy reveals that there is a modest overlap between the domains covered in the surveys, but when considering dimensions, the results indicate a lower agreement. The phrasing of items and answering categories differs between the surveys. Among the domains, the three domains covered by all surveys are “lifting, holding & carrying of loads/pushing & pulling of loads”, “awkward body postures” and “vibrations”. The three domains covered less well, that is only by three surveys or less, are “physical work effort”, “working sitting”, and “mixed exposure”.ConclusionsThis is the fırst thorough overview to evaluate the coverage of domains and dimensions of self-reported physical workloads in a selection of European nationwide surveys. We hope the overview will provide input to the revisions and updates of the individual countries’ surveys in order to enhance coverage of relevant domains and dimensions in all surveys and to increase the informational value of the surveys.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-017-4465-7) contains supplementary material, which is available to authorized users.
Zusammenfassung. Die internationale Forschung im Bereich der Hochschulzulassung zeigt eindrücklich, dass Leistungstests gute Prädiktoren der späteren Studienleistung sind und inkrementelle Validität über Schulnoten hinaus aufweisen. An deutschen Hochschulen ist der Einsatz standardisierter Leistungstests jedoch nach wie vor die Ausnahme. In der vorliegenden Arbeit schildern wir die Entwicklung und Validierung einer Testbatterie für die Zulassung von Psychologiestudierenden an deutschen Hochschulen. Im Rahmen der Testung von 1187 Bewerberinnen und Bewerbern für die Vergabe von 60 Studienplätzen prüfen wir mit Strukturgleichungsmodellen und Regressionsanalysen die prädiktive und inkrementelle Validität der neuen Testbatterie. Neben einem allgemeinen Faktor für das schlussfolgernde Denken kann auf der Prädiktorseite ein zweiter, geschachtelter Faktor für relevantes Vorwissen etabliert werden. Beide latenten Faktoren tragen nennenswert zur Vorhersage der Studienleistungen bei. Die Ergebnisse unterstützen nachdrücklich die Forderung, bei der Zulassung zu Studiengängen mit hohem Bewerberandrang Leistungstests einzusetzen. Neben schlussfolgerndem Denken verdient das relevante Vorwissen besondere Beachtung.
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