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Träfflista för sökning "WFRF:(Mathiassen Svend Erik) ;pers:(van der Beek Allard)"

Sökning: WFRF:(Mathiassen Svend Erik) > Van der Beek Allard

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1.
  • Coenen, Pieter, et al. (författare)
  • Calibration of self-reported physical behaviours among office workers: A compositional data analysis
  • 2019
  • Ingår i: ICAMPAM 2019. - Maastricht : ICAMPAM.
  • Konferensbidrag (refereegranskat)abstract
    • The aim of this study was to develop and evaluate calibration models to predict objectively measured time spent sitting, standing and walking during office work from self-reported time-use compositions using a compositional data analysis (CoDA) approach. Ninety-nine office workers (49 women) at the Swedish Transport Administration participated in an intervention study on relocation to activity-based offices. At baseline and at a 3-months follow-up, physical behaviours (sitting, standing and walking) at work were assessed for five days using a thigh-mounted accelerometer (Actigraph) and by self-report (IPAQ). The time-use composition of the three behaviours was expressed in terms of isometric log-ratios (ILR). Calibration models predicting accelerometry-based time-use from self-reported compositions were constructed using linear regression on baseline data, and then validated using follow-up data. The accelerometer data showed that, on average, workers spent 69.9% of their day sitting, 23.7% standing, and 6.4% walking. The corresponding percentages for self-reports were 71.7%, 21.6%, and 7.4%, respectively. Non-calibrated self-reports were biased: the RMS errors obtained from the ILRs expressing sitting, standing and walking were 0.73, 1.09 and 1.05, respectively. Calibration models reduced these errors by 45% (sitting), 56% (standing), and 76% (walking). Validation of the calibration models using follow-up data from the same workers showed calibration remained equally effective; RMS errors were reduced by 55% (sitting), 58% (standing), and 75% (walking). In conclusion, calibration models for compositional time-use data were effective in reducing bias in self-reported physical behaviours at work, and the models remained effective when used on new data from the same workers. Calibrated self-reports may represent a cost-effective method for obtaining physical behaviour data with a satisfying accuracy in large-scale cohort and intervention studies.
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2.
  • Coenen, Pieter, et al. (författare)
  • Correction of bias in self-reported sitting time among office workers – a study based on compositional data analysis
  • 2020
  • Ingår i: Scandinavian Journal of Work, Environment and Health. - : Scandinavian Journal of Work, Environment and Health. - 0355-3140 .- 1795-990X. ; 46:1, s. 32-42
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: Emerging evidence suggests that excessive sitting has negative health effects. However, this evidence largely relies on research using self-reported sitting time, which is known to be biased. To correct this bias, we aimed at developing a calibration model estimating "true" sitting from self-reported sitting.Methods: Occupational sitting time was estimated by self-reports (the International Physical Activity Questionnaire) and objective measurements (thigh-worn accelerometer) among 99 Swedish office workers at a governmental agency, at baseline and 3 and 12 months afterwards. Following compositional data analysis procedures, both sitting estimates were transformed into isometric log-ratios (ILR). This effectively addresses that times spent in various activities are inherently dependent and can be presented as values of only 0−100%. Linear regression was used to develop a simple calibration model estimating objectively measured "true" sitting ILR (dependent variable) from self-reported sitting ILR (independent variable). Additional self-reported variables were then added to construct a full calibration model. Performance of the models was assessed by root-mean-square (RMS) differences between estimated and objectively measured values. Models developed on baseline data were validated using the follow-up datasets.Results: Uncalibrated self-reported sitting ILR showed an RMS error of 0.767. Simple and full calibration models (incorporating body mass index, office type, and gender) reduced this error to 0.422 (55%) and 0.398 (52%), respectively. In the validations, model performance decreased to 57%/62% (simple models) and 57%/62% (full models) for the two follow-up data sets, respectively.Conclusions: Calibration adjusting for errors in self-reported sitting led to substantially more correct estimates of "true" sitting than uncalibrated self-reports. Validation indicated that model performance would change somewhat in new datasets and that full models perform no better than simple models, but calibration remained effective.
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3.
  • Gilson, Nicholas, et al. (författare)
  • Sedentary and physical activity behaviour in ‘blue-collar’ workers: A systematic review of accelerometer studies
  • 2019
  • Ingår i: Journal of Physical Activity and Health. - : ISPAH International Society for Physical Activity and Health. - 1543-3080 .- 1543-5474. ; 16:11, s. 1060-1069
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: This systematic review assessed evidence on the accelerometer-measured sedentary and physical activity (PA) behavior of nonoffice workers in “blue-collar” industries.Methods: The databases CINAHL, Embase, MEDLINE, PubMed, and Scopus were searched up to April 6, 2018. Eligibility criteria were accelerometer-measured sedentary, sitting, and/or PA behaviors in “blue-collar” workers (≥10 participants; agricultural, construction, cleaning, manufacturing, mining, postal, or transport industries). Data on participants’ characteristics, study protocols, and measured behaviors during work and/or nonwork time were extracted. Methodologic quality was assessed using a 12-item checklist.Results: Twenty studies (representing 11 data sets), all from developed world economies, met inclusion criteria. The mean quality score for selected studies was 9.5 (SD 0.8) out of a maximum of 12. Data were analyzed using a range of analytical techniques (eg, accelerometer counts or pattern recognition algorithms). “Blue-collar” workers were more sedentary and less active during nonwork compared with work time (eg, sitting 5.7 vs 3.2 h/d; moderate to vigorous PA 0.5 vs 0.7 h/d). Drivers were the most sedentary (work time 5.1 h/d; nonwork time 8.2 h/d).Conclusions: High levels of sedentary time and insufficient PA to offset risk are health issues for “blue-collar” workers. To better inform interventions, research groups need to adopt common measurement and reporting methodologies.
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5.
  • Hallman, David, 1979-, et al. (författare)
  • Calibration of self-reported time spent sitting, standing and walking among office workers: a compositional data analysis
  • 2019
  • Ingår i: International Journal of Environmental Research and Public Health. - : MDPI AG. - 1661-7827 .- 1660-4601. ; 16:17
  • Tidskriftsartikel (refereegranskat)abstract
    • We developed and evaluated calibration models predicting objectively measured sitting, standing and walking time from self-reported data using a compositional data analysis (CoDA) approach. A total of 98 office workers (48 women) at the Swedish Transport Administration participated. At baseline and three-months follow-up, time spent sitting, standing and walking at work was assessed for five working days using a thigh-worn accelerometer (Actigraph), as well as by self-report (IPAQ). Individual compositions of time spent in the three behaviors were expressed by isometric log-ratios (ILR). Calibration models predicting objectively measured ILRs from self-reported ILRs were constructed using baseline data, and then validated using follow-up data. Un-calibrated self-reports were inaccurate; root-mean-square (RMS) errors of ILRs for sitting, standing and walking were 1.21, 1.24 and 1.03, respectively. Calibration reduced these errors to 36% (sitting), 40% (standing), and 24% (walking) of those prior to calibration. Calibration models remained effective for follow-up data, reducing RMS errors to 33% (sitting), 51% (standing), and 31% (walking). Thus, compositional calibration models were effective in reducing errors in self-reported physical behaviors during office work. Calibration of self-reports may present a cost-e_ective method for obtaining physical behavior data with satisfying accuracy in large-scale cohort and intervention studies.
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7.
  • van der Beek, Allard, et al. (författare)
  • A research framework for the development and implementation of interventions preventing work-related musculoskeletal disorders
  • 2017
  • Ingår i: Scandinavian Journal of Work, Environment and Health. - : Scandinavian Journal of Work, Environment and Health. - 0355-3140 .- 1795-990X. ; 43:6, s. 526-539
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives: Work-related musculoskeletal disorders (MSD) are highly prevalent and put a large burden on the (working) society. Primary prevention of work-related MSD focuses often on physical risk factors (such as on manual lifting and awkward postures), but has not been too successful in reducing the MSD burden. This may partly be caused by insufficient knowledge of etiological mechanisms and/or a lack of adequately feasible interventions (theory failure and program failure, respectively), possibly due to limited integration of research disciplines. A research framework could link research disciplines thereby strengthening the development and implementation of preventive interventions. Our objective was to define and describe such a framework for multi-disciplinary research on work-related MSD prevention.Methods: We described a framework for MSD prevention research, partly based on frameworks from other research fields (i.e., sports injury prevention and public health).Results: The framework is composed of a repeated sequence of six steps comprising the assessment of 1) incidence and severity of MSD, 2) risk factors for MSD, and 3) underlying mechanisms; and the 4) development, 5) evaluation, and 6) implementation of preventive intervention(s).Conclusions: In the present framework for optimal work-related MSD prevention, research disciplines are linked. This framework can thereby help to improve theories and strengthen the development and implementation of prevention strategies for work-related MSD.
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8.
  • van der Beek, Allard, et al. (författare)
  • Efficient assessment of exposure to manual lifting using company data
  • 2013
  • Ingår i: Applied Ergonomics. - : Elsevier BV. - 0003-6870 .- 1872-9126. ; 44:3, s. 360-365
  • Tidskriftsartikel (refereegranskat)abstract
    • The objective of this study, based on an extensive dataset on manual materials handling during scaffolding, was to explore whether routinely collected company data can be used to estimate exposure to manual lifting.The number of manual lifts of scaffold parts while constructing/dismantling scaffolds was well predicted by the number of scaffolders in the team and the type of worksite, in combination with company data of either the number of scaffold parts or the scaffold volume. The proportion of explained variance in the number of lifts ranged from 77% to 92%, depending on the variables in the model. Data on scaffold parts and scaffold volume can easily be obtained from the company’s administration, since this is its usual paperwork supporting logistics and customer invoicing, respectively.We conclude that company data can be a promising source of information for ergonomic practitioners and researchers, to support assessment of manual lifting in scaffolding.
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9.
  • van der Beek, Allard J, et al. (författare)
  • An evaluation of methods assessing the physical demands of manual lifting in scaffolding.
  • 2005
  • Ingår i: Applied Ergonomics. - : Elsevier BV. - 0003-6870 .- 1872-9126. ; 36:2, s. 213-222
  • Tidskriftsartikel (refereegranskat)abstract
    • Four methods assessing the physical demands of manual lifting were compared. The scaffolding job was evaluated and three distinct scaffolding tasks were ranked using: (1) the revised NIOSH lifting equation (NIOSH method), (2) lifting guidelines for the Dutch construction industry (Arbouw method), (3) rapid appraisal of the NIOSH lifting equation (practitioners' method), and (4) systematic observations. For the three first-mentioned methods the same dataset was used; observation took place in a different setting in the same company. At job level, all methods indicated that ergonomic interventions are required to protect scaffolders from an increased risk for low back pain. The NIOSH, Arbouw and practitioners' method resulted in a similar ranking order of tasks (transport>construction>dismantlement). In contrast, the observational method gave transport the lowest ranking. The underlying cause was probably that the observational method is more sensitive to durations of tasks and lifting within tasks than the three other methods.
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