Elsevier

Applied Ergonomics

Volume 41, Issue 2, March 2010, Pages 295-304
Applied Ergonomics

The ability of limited exposure sampling to detect effects of interventions that reduce the occurrence of pronounced trunk inclination

https://doi.org/10.1016/j.apergo.2009.08.006Get rights and content

Abstract

Ergonomics interventions often focus on reducing exposure in those parts of the job having the highest exposure levels, while leaving other parts unattended. A successful intervention will thus change the form of the job exposure distribution. This disqualifies standard methods for assessing the ability of various exposure measurement strategies to correctly detect an intervention's effect on the overall job exposure of an individual worker, in particular for the safety or ergonomics practitioner who with limited resources can only collect a few measurements. This study used a non-parametric simulation procedure to evaluate the relationship between the number of measurements collected during a self-paced manufacturing job undergoing ergonomics interventions of varying effectiveness, and the probability of correctly determining whether and to which extent the interventions reduced the overall occurrence of pronounced trunk inclination, defined as an inclination of at least 20°. Sixteen video-recordings taken at random times on multiple days for each of three workers were used to estimate the time distribution of each worker's exposure to pronounced trunk inclination. Nine hypothetical ergonomics intervention scenarios were simulated, in which the occurrence of pronounced trunk inclination in the upper 1/8, 1/4, and 1/2 of the job exposure distribution was reduced by 10%, 30% and 50%. Ten exposure measurement strategies were explored, collecting from one to ten pre- and post-intervention exposure samples from an individual worker. For each worker, intervention scenario and sampling strategy, data were bootstrapped from the measured (pre-intervention) and simulated (post-intervention) exposure distributions to generate empirical distributions of the estimated intervention effect. Results showed that for the one to three intervention scenarios that had the greatest effect on the overall occurrence of trunk inclination in the job, one to four pre- and post-intervention measurements, depending on worker, were sufficient to reach an 80% probability of detecting that the intervention did, indeed, have an effect. However, even for the intervention scenario that had the greatest effect on job exposure, seven or more samples were needed for two of the three workers to obtain a probability larger than 50% of estimating the magnitude of the intervention effect to within ±50% of its true size. For almost all interventions affecting 1/8 or 1/4 of the job, limited exposure sampling led to low probabilities of detecting any intervention effect, let alone its correct size.

Introduction

Extensive research has been performed to evaluate workplace interventions designed to reduce employee risks of contracting work-related musculoskeletal disorders (WMSD). This research includes numerous field and laboratory studies that have evaluated the effects of changes in tools, work methods, work environment or work organization. A number of recent reviews discuss different aspects of this large body of literature (e.g. Westgaard and Winkel, 1997, Silverstein and Clark, 2004, van der Molen et al., 2005, Brewer et al., 2006, Boocock et al., 2007, Denis et al., 2008). While the ultimate goal of the intervention is to reduce the risk of contracting or maintaining WMSD, changes in biomechanical exposure accompanying the intervention are often used as a proxy for its eventual effect on health (Westgaard and Winkel, 1997, Lötters and Burdorf, 2002, Cole et al., 2003). Due to constraints on time and resources, safety and ergonomics practitioners are particularly compelled to judging intervention effects by how they affect exposure.

There are significant challenges to quantifying the exposure effects of ergonomics interventions (Burdorf and van Riel, 1996, Burdorf and van Tongeren, 2003, Dempsey, 2007). One important issue appears from the growing literature demonstrating that biomechanical exposures often vary considerably across people within the same job or task, and over time for the same individual. Thus, postures and muscle activity of the back or upper extremities have been shown to vary between and within individuals in several settings, including dairy factory work, cyclic assembly work, cleaning and construction (Burdorf, 1993, Burdorf et al., 1994, van der Beek et al., 1995, Burdorf and van Riel, 1996, Paquet et al., 1999, van der Beek et al., 1999, Hoozemans et al., 2001, Mathiassen et al., 2002, van Dieën et al., 2002, Mathiassen et al., 2003a, Mathiassen et al., 2003b, Möller et al., 2004, Nordander et al., 2004, Paquet et al., 2005, Hansson et al., 2006, Jackson et al., 2009). This inherent exposure variability leads to uncertainties when limited samples of subjects and/or exposure data within a subject are collected and compared as a means of deciding whether an intervention is effective or not. With an insufficient sample size, the investigation will have a low ability to detect a true intervention effect; i.e. it lacks statistical power. The issue of determining a suitable measurement strategy is a challenge, both to researchers operating at the level of groups of workers with the aim of generalizing their results to other workers or other similar work situations, and to practitioners, who are often more interested in knowing whether or not specific individuals benefit from, for instance, modifications of their work station or a course in work technique.

Analytical methods are available by which the ability of an exposure assessment strategy to detect changes in the exposure mean can be estimated on the basis of data on exposure variability and allocated resources (Mathiassen et al., 2002, Mathiassen et al., 2003b). These methods are generally applicable for situations in which the compared pre- and post-intervention exposure distributions are both normal. Normality is a reasonable assumption if the compared mean exposures are both based on a large number of samples, since the distribution of a large-sample mean will approach normal, irrespective of the underlying distribution of the individual samples (Cochran, 1977). However, both in research (Mathiassen et al., 2002) and, in particular, in ergonomics practice (Paquet et al., 2006), exposure samples are often both few and short. While rarely addressed in intervention studies, pre- and post-intervention mean values cannot in this case be expected to be normally distributed without further study.

In ergonomics practice, improvements aimed at reducing the overall mean exposure are often focused on those parts of the job that are considered the worst or those that can be most easily improved upon, while the rest of the job is left unattended. A successful intervention will then change only parts of the overall exposure distribution. For an example, an intervention that reduces the upper 1/4 of a worker's exposures by 50% will, indeed, change the overall mean exposure, but it will also have a pronounced effect on the shape of the exposure distribution (Fig. 1). Thus, with interventions focusing only on the “worst” exposures, pre- and post-intervention exposures are unlikely both to be normally distributed. For instance, the occurrence of trunk flexion of at least 20° illustrated in Fig. 1 is normally distributed across the job before the “intervention”, while afterwards it is not. Examples of intervention concepts with a scope of reducing large exposures while leaving lower ones unattended are courses in lifting technique intended to reduce biomechanical peak loads on the back (Martimo et al., 2008), and biofeedback devices returning an auditory or visual signal when a certain exposure level is exceeded (Madeleine et al., 2006; the Virtual Corset™ (www.microstrain.com/virtual-corset.aspx)).

In this practitioner's case of a successful intervention changing only a part of the exposure distribution, and the intervention effect being assessed on the basis of few pre- and post-intervention exposure samples from one or a few workers, standard analytical procedures cannot be used to evaluate the performance of exposure assessment strategies. Non-parametric approaches then offer a viable alternative. Statistical re-sampling techniques that do not rely on assumptions about the shape of the exposure distribution have been used previously to empirically test the performance of different measurement strategies for quantitative assessment of biomechanical exposures in the field (e.g., Burdorf and van Riel, 1996, Hoozemans et al., 2001, Mathiassen et al., 2002, Mathiassen et al., 2005, Paquet et al., 2005, Fethke et al., 2007), but these methods have not previously been used to investigate ergonomics intervention assessment practices.

The objective of this empirical simulation study was to evaluate the relationship between the number of measurements collected before and after ergonomics interventions of varying effectiveness in a self-paced manufacturing job, and the probability of correctly determining whether and to which extent the interventions reduced the overall occurrence of pronounced trunk inclination, defined as inclination of at least 20°. Taking a practitioner's rather than researcher's perspective, the study was designed to evaluate this relationship for interventions carried out on individual workers, and assessed by few measurements.

Section snippets

Exposure data

Three workers performing the same physically demanding job were randomly selected from a convenience sample of nine workers at a manufacturing plant to provide realistic biomechanical exposure distributions at an individual level. The job was a self-paced automotive upsetting manufacturing job that required the following tasks: lift a steel rod weighing between 45 and 70 N from a pallet (depending on the batch), place rod in an electrical heater, place the rod into a die casting machine, operate

Detecting a reduction in the overall job exposure

As expected, the ability of a sampling strategy to correctly detect that the intervention reduced the overall occurrence of pronounced trunk inclination generally increased with an increasing number of pre- and post-intervention measurements (Fig. 6). For all three workers, this ability was acceptable (p > 0.8) for sampling strategies with three or more pre- and post-intervention measurements when the most extreme half of the exposure distribution was reduced by 50%. The probability of detecting

Job exposure assessment for interventions

While ergonomics interventions are usually aimed to reduce the risk of MSD, intervention effects on biomechanical exposure are often used as proxies of health effects, assuming that exposure is predictive of risk (Westgaard and Winkel, 1997, Lötters and Burdorf, 2002, Cole et al., 2003). One major reason is that the exposure effects of an intervention have a much shorter latency (if any) than health outcomes, making them more readily accessible, in particular to practitioners. Thus, a large

Conclusions

For interventions in self-paced manufacturing that lead to substantial reductions of trunk inclination in those parts of the job where it occurs the most, as few as three pre- and post-intervention exposure samples of ten work cycles each can be sufficient to reach a fair probability of detecting that the intervention has an effect at all on the overall occurrence of pronounced trunk inclination in the job for an individual worker. Larger samples are needed to reasonably estimate the magnitude

Acknowledgements

This work was supported by the Swedish Council for Working Life and Social Research, (grant #2004-0600) and the National Institute for Occupational Safety and Health (grant #R03 OH04105-02).

References (89)

  • G.-Å. Hansson et al.

    Precision of measurements of physical workload during standardised manual handling. Part II: inclinometry of head, upper back, neck and upper arms

    J Electromyogr Kinesiol

    (2006)
  • M. Häkkänen et al.

    Effects of changes in work methods on musculoskeletal load. An intervention study in the trailer assembly

    Appl Ergon

    (1997)
  • J.A. Jackson et al.

    Methodological variance associated with normalization of occupational upper trapezius EMG using submaximal reference contractions

    J Electromyogr Kinesiol

    (2009)
  • B. Juul-Kristensen et al.

    Criteria for classification of posture in repetitive work by observation methods

    Int J Ind Ergon

    (1997)
  • B. Juul-Kristensen et al.

    Assessment of work postures and movements using a video-based observation method and direct technical measurements

    Appl Ergon

    (2001)
  • O. Karhu et al.

    Correcting working postures in industry: a practical method for analysis

    Appl Ergon

    (1977)
  • K. Kazmierczak et al.

    Observer reliability of industrial activity analysis based on video recordings

    Int J Ind Ergon

    (2006)
  • L. McAtamney et al.

    RULA: a survey method for the investigation of work-related upper limb disorders

    Appl Ergon

    (1993)
  • G. Mirka et al.

    Ergonomics interventions for the reduction of low back stress in framing carpenters in the home building industry

    Int J Ind Ergon

    (2003)
  • C. Nordander et al.

    Precision of measurements of physical workload during standardised manual handling. Part I: surface electromyography of m. trapezius, m. infraspinatus and the forearm extensors

    J Electromyogr Kinesiol

    (2004)
  • R. Norman et al.

    A comparison of peak vs cumulative physical work exposure risk factors for the reporting of low back pain in the automotive industry

    Clin Biomech

    (1998)
  • V. Paquet et al.

    An evaluation of manual materials handling in highway construction work

    Int J Ind Ergon

    (1999)
  • J. Paskiewicz et al.

    Effectiveness of manual furniture handling device in reducing low back disorder risk factors

    Int J Ind Ergon

    (2007)
  • S.M. Rappaport et al.

    An exposure-assessment strategy accounting for within- and between-worker sources of variability

    Ann Occup Hyg

    (1995)
  • B. Silverstein et al.

    Interventions to reduce work-related musculoskeletal disorders

    J Electromyogr Kinesiol

    (2004)
  • L. Straker et al.

    An evaluation of visual display unit placement by electromyography, posture, discomfort and preference

    Int J Ind Ergon

    (2000)
  • E. Tielemans et al.

    Individual-based and group-based occupational exposure assessment: some equations to evaluate different strategies

    Ann Occup Hyg

    (1998)
  • A.J. van der Beek et al.

    Assessment of exposure to pushing and pulling in epidemiological field studies: an overview of methods, exposure measures, and measurement strategies

    Int J Ind Ergon

    (1999)
  • A.J. van der Beek et al.

    An evaluation of methods assessing the physical demands of manual lifting in scaffolding

    Appl Ergon

    (2005)
  • J.H. van Dieën et al.

    Precision of estimates of mean and peak spinal loads in lifting

    J Biomech

    (2002)
  • O. Vasseljen et al.

    Arm and trunk posture during work in relation to shoulder and neck pain and trapezius activity

    Clin Biomech

    (1997)
  • R.H. Westgaard et al.

    Ergonomic intervention research for improved musculoskeletal health: a critical review

    Int J Ind Ergon

    (1997)
  • J. Alders et al.

    Biomechanical assessment of three rebar tying techniques

    Int J Occup Saf Ergon

    (2007)
  • W.G. Allread et al.

    Measuring trunk motions in industry: variability due to task factors, individual differences, and the amount of data collected

    Ergonomics

    (2000)
  • B. Bernard

    Musculoskeletal Disorders and Workplace Factors

    (1997)
  • M.G. Boocock et al.

    Interventions for the prevention and management of neck/upper extremity musculoskeletal conditions: a systematic review

    Occup Environ Med

    (2007)
  • S. Brewer et al.

    Workplace interventions to prevent musculoskeletal and visual symptoms and disorders among computer users: a systematic review

    J Occup Rehabil

    (2006)
  • A. Burdorf

    Sources of variance in exposure to postural load on the back in occupational groups

    Scand J Work Environ Health

    (1992)
  • A. Burdorf

    Bias in risk estimates from variability of exposure to postural load on the back in occupational groups

    Scand J Work Environ Health

    (1993)
  • A. Burdorf et al.

    Time-dependent variation in back load of workers in a dairy factory

    Occup Hyg

    (1994)
  • A. Burdorf et al.

    Positive and negative evidence of risk factors for back disorders

    Scand J Work Environ Health

    (1997)
  • A. Burdorf et al.

    Physical load as risk factor for musculoskeletal complaints among tank terminal workers

    Am Ind Hyg Assoc J

    (1997)
  • A. Burdorf et al.

    Exposure assessment strategies for work-related risk factors for musculoskeletal disorders

    Scand J Work Environ Health

    (1999)
  • A. Burdorf et al.

    Variability in workplace exposures and the design of efficient measurement and control strategies

    Ann Occup Hyg

    (2003)
  • Cited by (0)

    View full text