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<h1>Publikation Lieb</h1>
<p>Int. J. Environ. Res. Public Health2021, 18, 9171 11of 15 The literature pool of 262 publications, compiled for the primary publication, was scanned for indications that any multiple regression methods were used for predictor analyses. Only 32 articles (12%) could be identified, indicating that the usage of multivariate analyses is still not common in this type of study. The very lowp-values for effects in the analysis of grip strength and range of motion (see Table 6) probably resulted from the increase in power due to the higher number of individual measurements (2 ×3 measurements per subject, i.e., total n= 420 in 70 subjects). However, the variance analysis employed in regression models with other simply measured values lacks such an amount of information regarding the variance of the measurements. The additional information gave the analysis of variance more statistical power, i.e., more sensitivity for effects detection. We intentionally tried to avoid the term “significant” in regard to this analysis, in order not to refer our reportedp-values to the conventional 5.0% significance level, which may be prone to misinterpretation [58,73]. Using the concept of hypothesis testing in the scientifically accurate way, setting a significance level would require a multiplicity correction for a number of pre-defined tests. Such explicit correction would, on the other hand, take away our flexibility to follow the effects and relations in our data, which contains a complex network of endpoints and their predictors. For this reason, this secondary analysis was clearly explorative. This means that the p-values shown in the tables are not referred to any significance level. They rather provide continuous information of how effects are related or ranked according to their strengths. In this respect, Table 3 in the results section has to be considered as identification of two potential candidates for appropriate surrogate measures for WMSDs prevalence. However, real evidence for the adequacy of any of these candidates for WMSDs detection in clinical use has to be generated by a dedicated study. The DASH score was considered to be the surrogate endpoint of choice for our primary analysis of WMSDs prevalence among medical device manufacturing employees. The current analyses confirm that DASH still has to remain as the closer choice when assessing the WMSDs status of a population. Regarding the limitations of our study, it should be noted that cross-sectional studies always represent a snapshot, and no statement can be made about the duration of an existing WMSDs. In particular, it is not possible to clearly distinguish between chronic, recurrent, or acute diseases. As in other studies, we also focused on a manageable number of potential risk factors, because an increasing number of predictors increases the probability of false positive effects, especially in smaller samples. This makes it difficult to assess these effects as a whole. Due to the single investigator approach, there is a risk of systematic error for over-sensitive detection of WMSDs, which is indicated by the higher number of diagnoses compared to symptoms in our study. On the other hand, the examination was performed by the same hand surgeon, which may have led to the diagnosis at an earlier stage than in a clinical setting. However, reducing the systematic error by a multiple investigator approach would have brought an inter-observer error into play, arising as a result of different teaching backgrounds and subjective assessments. Repeating the physical examination tests by having two investigators examine the same person was not an option for the authors. A major reason for this is that most test results depend on the announcement of symptoms (pain, numbness, etc.), and participants learn during follow-up examinations, which limits the objectivity of such study designs [57]. The small study sample of 70 individuals might not provide power to detect small effects, so it may be considered another limitation. Even though the cross-sectional design of our study does not permit causal inference, the observed relations provide valuable evidence for further research and policy making. For further limitations with regard to the three occupational activities, we would like to refer to our previous publication [17].</p>
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