2014
DOI: 10.5271/sjweh.3416
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Cost-efficient assessment of biomechanical exposure in occupational groups, exemplified by posture observation and inclinometry

Abstract: This study is the first to carry out comprehensive cost-efficiency comparisons of ergonomic exposure assessment, providing quantitative rationale for the development of a hierarchy of exposure assessment methods. Combined with the accompanying model for assessing cost-efficiency, the empirical data provides a basis for planning posture assessment and allows for informed use of limited resources when designing ergonomic studies.

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Cited by 45 publications
(43 citation statements)
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References 53 publications
(70 reference statements)
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“…by occupational physicians. However, observations may be as resource demanding as measurements, and may introduce bias [53]. The choice of thresholds may be based on hypotheses on pathogenesis [27] and safe lower levels of exposure.…”
Section: Discussionmentioning
confidence: 99%
“…by occupational physicians. However, observations may be as resource demanding as measurements, and may introduce bias [53]. The choice of thresholds may be based on hypotheses on pathogenesis [27] and safe lower levels of exposure.…”
Section: Discussionmentioning
confidence: 99%
“…Thus, it is difficult to obtain an accurate estimate of the physical load during working situations using only observations (Eliasson et al 2017;Takala et al 2010). Moreover, a study by Trask and co-workers showed that in most situations assessment of trunk and upper arm inclination was more cost-effective using inclinometers than using visual posture observations (Trask et al 2014).…”
Section: Kinematicsmentioning
confidence: 99%
“…In this line of development, we encourage paying consideration to the trade-off between resources required to collect predictors and the eventual performance of the model. We did not in the present study compare costs associated with collecting exposure data directly by objective measurements versus costs of developing prediction models using questionnaire data, but we emphasize that a major rationale for modeling exposures in future studies would be that they deliver more exposure data at a lower cost than objective measurements, and thus represent a favorable trade-off between cost and performance (57,58). We also emphasize the need for validating the performance of any future model in new datasets, either using a genuinely new sample or by internal bootstrap validation techniques; this has very rarely been attempted in previous modelling studies (41).…”
Section: Gupta Et Almentioning
confidence: 99%