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Mathiassen SE, Waleh Åström A, Strömberg A, Heiden M. Cost and statistical efficiency of posture assessment by inclinometry and observation, exemplified by paper mill work. PLoS One 2023; 18:e0292261. [PMID: 37788296 PMCID: PMC10547196 DOI: 10.1371/journal.pone.0292261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 09/16/2023] [Indexed: 10/05/2023] Open
Abstract
Postures at work are paramount in ergonomics. They can be determined using observation and inclinometry in a variety of measurement scenarios that may differ both in costs associated with collecting and processing data, and in efficiency, i.e. the precision of the eventual outcome. The trade-off between cost and efficiency has rarely been addressed in research despite the obvious interest of obtaining precise data at low costs. Median trunk and upper arm inclination were determined for full shifts in 28 paper mill workers using both observation and inclinometry. Costs were estimated using comprehensive cost equations; and efficiency, i.e. the inverted standard deviation of the group mean, was assessed on basis of exposure variance components. Cost and efficiency were estimated in simulations of six sampling scenarios: two for inclinometry (sampling from one or three shifts) and four for observation (one or three observers rating one or three shifts). Each of the six scenarios was evaluated for 1 through 50 workers. Cost-efficiency relationships between the scenarios were intricate. As an example, inclinometry was always more cost-efficient than observation for trunk inclination, except for observation strategies involving only few workers; while for arm inclination, observation by three observers of one shift per worker outperformed inclinometry on three shifts up to a budget of €20000, after which inclinometry prevailed. At a budget of €10000, the best sampling scenario for arm inclination was 2.5 times more efficient than the worst. Arm inclination could be determined with better cost-efficiency than trunk inclination. Our study illustrates that the cost-efficiency of different posture measurement strategies can be assessed and compared using easily accessible diagrams. While the numeric examples in our study are specific to the investigated occupation, exposure variables, and sampling logistics, we believe that inclinometry will, in general, outperform observation. In any specific case, we recommend a thorough analysis, using the comparison procedure proposed in the present study, of feasible strategies for obtaining data, in order to arrive at an informed decision support.
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Affiliation(s)
- Svend Erik Mathiassen
- Centre for Musculoskeletal Research, Department of Occupational Health Science and Psychology, Faculty of Health and Occupational Studies, University of Gävle, Gävle, Sweden
| | - Amanda Waleh Åström
- Centre for Musculoskeletal Research, Department of Occupational Health Science and Psychology, Faculty of Health and Occupational Studies, University of Gävle, Gävle, Sweden
| | - Annika Strömberg
- Department of Business and Economic Studies, Faculty of Education and Business Studies, University of Gävle, Gävle, Sweden
| | - Marina Heiden
- Centre for Musculoskeletal Research, Department of Occupational Health Science and Psychology, Faculty of Health and Occupational Studies, University of Gävle, Gävle, Sweden
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Waleh Åström A, Heiden M, Mathiassen SE, Strömberg A. Uncertainty in monetary cost estimates for assessing working postures using inclinometry, observation or self-report. APPLIED ERGONOMICS 2018; 71:73-77. [PMID: 29764616 DOI: 10.1016/j.apergo.2018.04.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 03/15/2018] [Accepted: 04/17/2018] [Indexed: 06/08/2023]
Abstract
OBJECTIVE To assess uncertainty in cost estimates for collecting posture data by inclinometry, observations and self-report. METHOD In a study addressing physical workloads at a paper mill, costs were calculated for measuring postures of twenty-eight workers during three shifts. Uncertainty in costs was assessed for all three methods as the range between an assumed best case (lowest cost) and worst case (highest cost) using scenario analysis. RESULTS The cost for observation was larger, but also more uncertain (€16506 and €89552 in the best and worst case, respectively) than that of inclinometry (€7613 - €45896). Self-report costs were both lower and less uncertain (€3743 - €23368). CONCLUSIONS The extent of uncertainty in cost estimates implies that observation could be less expensive than inclinometry, e.g., in a scenario where experienced observers could use existing software, while inclinometers would have to be purchased. We propose adding uncertainty assessments to cost estimates when selecting a method for measuring working postures, and offer guidance in how to proceed in a specific setting.
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Affiliation(s)
- Amanda Waleh Åström
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, Faculty of Health and Occupational Studies, University of Gävle, SE-801 76, Gävle, Sweden.
| | - Marina Heiden
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, Faculty of Health and Occupational Studies, University of Gävle, SE-801 76, Gävle, Sweden.
| | - Svend Erik Mathiassen
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, Faculty of Health and Occupational Studies, University of Gävle, SE-801 76, Gävle, Sweden.
| | - Annika Strömberg
- Faculty of Health and Occupational Studies, University of Gävle, SE-801 76, Gävle, Sweden.
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Holtermann A, Schellewald V, Mathiassen SE, Gupta N, Pinder A, Punakallio A, Veiersted KB, Weber B, Takala EP, Draicchio F, Enquist H, Desbrosses K, García Sanz MP, Malińska M, Villar M, Wichtl M, Strebl M, Forsman M, Lusa S, Tokarski T, Hendriksen P, Ellegast R. A practical guidance for assessments of sedentary behavior at work: A PEROSH initiative. APPLIED ERGONOMICS 2017; 63:41-52. [PMID: 28502405 DOI: 10.1016/j.apergo.2017.03.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2016] [Revised: 03/23/2017] [Accepted: 03/24/2017] [Indexed: 06/07/2023]
Abstract
Sedentary behavior is defined as sitting or lying with low energy expenditure. Humans in industrialized societies spend an increasing amount of time in sedentary behaviors every day. This has been associated with detrimental health outcomes. Despite a growing interest in the health effects of sedentary behavior at work, associations remain unclear, plausibly due to poor and diverse methods for assessing sedentary behavior. Thus, good practice guidance for researchers and practitioners on how to assess occupational sedentary behavior are needed. The aim of this paper is to provide a practical guidance for practitioners and researchers on how to assess occupational sedentary behavior. Ambulatory systems for use in field applications (wearables) are a promising approach for sedentary behavior assessment. Many different small-size consumer wearables, with long battery life and high data storage capacity are commercially available today. However, no stand-alone commercial system is able to assess sedentary behavior in accordance with its definition. The present paper offers decision support for practitioners and researchers in selecting wearables and data collection strategies for their purpose of study on sedentary behavior. Valid and reliable assessment of occupational sedentary behavior is currently not easy. Several aspects need to be considered in the decision process on how to assess sedentary behavior. There is a need for development of a cheap and easily useable wearable for assessment of occupational sedentary behavior by researchers and practitioners.
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Affiliation(s)
- Andreas Holtermann
- National Research Centre for the Working Environment (NRCWE), Copenhagen, Denmark.
| | - Vera Schellewald
- German Sport University Cologne (DSHS), Köln, Germany; Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA), Sankt Augustin, Germany
| | | | - Nidhi Gupta
- National Research Centre for the Working Environment (NRCWE), Copenhagen, Denmark
| | - Andrew Pinder
- HSE's Health & Safety Laboratory (HSL), Buxton, Derbyshire, United Kingdom
| | - Anne Punakallio
- Finnish Institute of Occupational Health (FIOH), Helsinki, Finland
| | | | - Britta Weber
- Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA), Sankt Augustin, Germany
| | - Esa-Pekka Takala
- Finnish Institute of Occupational Health (FIOH), Helsinki, Finland
| | - Francesco Draicchio
- National Institute for Insurance Against Accidents at Work (INAIL), Rome, Italy
| | - Henrik Enquist
- Lund University, Skane Medical Services, Department of Laboratory Medicine, Occupational and Environmental Medicine, Lund, Sweden
| | - Kevin Desbrosses
- French National Research and Safety Institute for the Prevention of Occupational Accidents and Diseases (INRS), Vandoeuvre Les Nancy, France
| | | | - Marzena Malińska
- Central Institute for Labour Protection - National Research Institute (CIOP-PIB), Warszawa, Poland
| | - María Villar
- Spanish National Institute for Safety and Hygiene at Work (INSHT), Madrid, Spain
| | - Michael Wichtl
- Austrian Workers' Compensation Board (AUVA), Wien, Austria
| | | | | | - Sirpa Lusa
- Finnish Institute of Occupational Health (FIOH), Helsinki, Finland
| | - Tomasz Tokarski
- Central Institute for Labour Protection - National Research Institute (CIOP-PIB), Warszawa, Poland
| | - Peter Hendriksen
- National Research Centre for the Working Environment (NRCWE), Copenhagen, Denmark
| | - Rolf Ellegast
- Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA), Sankt Augustin, Germany
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Critical and Theoretical Perspective on Scapular Stabilization: What Does It Really Mean, and Are We on the Right Track? Phys Ther 2016; 96:1162-9. [PMID: 26847012 DOI: 10.2522/ptj.20140230] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2014] [Accepted: 01/24/2016] [Indexed: 11/17/2022]
Abstract
Stabilization exercises have been a focus and mainstay of many therapeutic and performance training programs in the past decade. Whether the focus is core stabilization for the spine or scapular stabilization, clinicians and trainers alike have endorsed these programs, largely on the basis of conceptual theory and anecdotal experience. The notion that an unstable scapula is related to shoulder dysfunction and pathology is well accepted, but is it accurate? The aim of this perspective article is to challenge the concept of scapular stabilization through the application of biomechanical and motor control constructs. The objectives are to critically examine current beliefs about scapular stabilization, to discuss definitions of stabilization and stability in the context of the scapulothoracic region, and to evaluate key evidence regarding scapular stabilization and scapular dyskinesia. Several new approaches that may affect the understanding of normal and atypical scapula motion are explored. Finally, a historical analogy is presented and future research and clinical directions are suggested. The aims are to lead readers to the essential concepts implied on scapular stabilization, to increase the critical thought process in rehabilitation practice, and to suggest some open topics to be explored in future research.
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Heiden M, Mathiassen SE, Garza J, Liv P, Wahlström J. A Comparison of Two Strategies for Building an Exposure Prediction Model. ANNALS OF OCCUPATIONAL HYGIENE 2015; 60:74-89. [PMID: 26424806 DOI: 10.1093/annhyg/mev072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2015] [Accepted: 08/09/2015] [Indexed: 12/30/2022]
Abstract
Cost-efficient assessments of job exposures in large populations may be obtained from models in which 'true' exposures assessed by expensive measurement methods are estimated from easily accessible and cheap predictors. Typically, the models are built on the basis of a validation study comprising 'true' exposure data as well as an extensive collection of candidate predictors from questionnaires or company data, which cannot all be included in the models due to restrictions in the degrees of freedom available for modeling. In these situations, predictors need to be selected using procedures that can identify the best possible subset of predictors among the candidates. The present study compares two strategies for selecting a set of predictor variables. One strategy relies on stepwise hypothesis testing of associations between predictors and exposure, while the other uses cluster analysis to reduce the number of predictors without relying on empirical information about the measured exposure. Both strategies were applied to the same dataset on biomechanical exposure and candidate predictors among computer users, and they were compared in terms of identified predictors of exposure as well as the resulting model fit using bootstrapped resamples of the original data. The identified predictors were, to a large part, different between the two strategies, and the initial model fit was better for the stepwise testing strategy than for the clustering approach. Internal validation of the models using bootstrap resampling with fixed predictors revealed an equally reduced model fit in resampled datasets for both strategies. However, when predictor selection was incorporated in the validation procedure for the stepwise testing strategy, the model fit was reduced to the extent that both strategies showed similar model fit. Thus, the two strategies would both be expected to perform poorly with respect to predicting biomechanical exposure in other samples of computer users.
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Affiliation(s)
- Marina Heiden
- 1.Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, 801 76 Gävle, Sweden;
| | - Svend Erik Mathiassen
- 1.Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, 801 76 Gävle, Sweden
| | - Jennifer Garza
- 1.Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, 801 76 Gävle, Sweden; 2.Division of Occupational and Environmental Medicine, UConn Health, Farmington, CT 06030, USA
| | - Per Liv
- 1.Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, 801 76 Gävle, Sweden; 3.Centre for Research and Development, Uppsala University/County Council of Gävleborg, 801 88 Gävle, Sweden
| | - Jens Wahlström
- 4.Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine, Umeå University, 901 87 Umeå, Sweden
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Mathiassen SE, Jackson JA, Punnett L. Statistical performance of observational work sampling for assessment of categorical exposure variables: a simulation approach illustrated using PATH data. ACTA ACUST UNITED AC 2013; 58:294-316. [PMID: 24353010 PMCID: PMC3954517 DOI: 10.1093/annhyg/met063] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Objectives: Observational work sampling is often used in occupational studies to assess categorical biomechanical exposures and occurrence of specific work tasks. The statistical performance of data obtained by work sampling is, however, not well understood, impeding informed measurement strategy design. The purpose of this study was to develop a procedure for assessing the statistical properties of work sampling strategies evaluating categorical exposure variables and to illustrate the usefulness of this procedure to examine bias and precision of exposure estimates from samples of different sizes. Methods: From a parent data set of observations on 10 construction workers performing a single operation, the probabilities were determined for each worker of performing four component tasks and working in four mutually exclusive trunk posture categories (neutral, mild flexion, severe flexion, twisted). Using these probabilities, 5000 simulated data sets were created via probability-based resampling for each of six sampling strategies, ranging from 300 to 4500 observations. For each strategy, mean exposure and exposure variability metrics were calculated at both the operation level and task level and for each metric, bias and precision were assessed across the 5000 simulations. Results: Estimates of exposure variability were substantially more uncertain at all sample sizes than estimates of mean exposures and task proportions. Estimates at small sample sizes were also biased. With only 600 samples, proportions of the different tasks and of working with a neutral trunk posture (the most common) were within 10% of the true target value in at least 80% of all the simulated data sets; rarer exposures required at least 1500 samples. For most task-level mean exposure variables and for all operation-level and task-level estimates of exposure variability, performance was low, even with 4500 samples. In general, the precision of mean exposure estimates did not depend on the exposure variability between workers. Conclusions: The suggested probability-based simulation approach proved to be versatile and generally suitable for assessing bias and precision of data collection strategies using work sampling to estimate categorical data. The approach can be used in both real and hypothetical scenarios, in ergonomics, as well as in other areas of occupational epidemiology and intervention research. The reported statistical properties associated with sample size are likely widely relevant to studies using work sampling to assess categorical variables.
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Affiliation(s)
- Svend Erik Mathiassen
- 1. Department of Occupational and Public Health Sciences, Centre for Musculoskeletal Research, University of Gävle, Kungsbäcksvägen, SE- 80176 Gävle, Sweden
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Trask C, Mathiassen SE, Jackson J, Wahlström J. Data processing costs for three posture assessment methods. BMC Med Res Methodol 2013; 13:124. [PMID: 24118872 PMCID: PMC4015999 DOI: 10.1186/1471-2288-13-124] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2013] [Accepted: 10/10/2013] [Indexed: 12/02/2022] Open
Abstract
Background Data processing contributes a non-trivial proportion to total research costs, but documentation of these costs is rare. This paper employed a priori cost tracking for three posture assessment methods (self-report, observation of video, and inclinometry), developed a model describing the fixed and variable cost components, and simulated additional study scenarios to demonstrate the utility of the model. Methods Trunk and shoulder postures of aircraft baggage handlers were assessed for 80 working days using all three methods. A model was developed to estimate data processing phase costs, including fixed and variable components related to study planning and administration, custom software development, training of analysts, and processing time. Results Observation of video was the most costly data processing method with total cost of € 30,630, and was 1.2-fold more costly than inclinometry (€ 26,255), and 2.5-fold more costly than self-reported data (€ 12,491). Simulated scenarios showed altering design strategy could substantially impact processing costs. This was shown for both fixed parameters, such as software development and training costs, and variable parameters, such as the number of work-shift files processed, as well as the sampling frequency for video observation. When data collection and data processing costs were combined, the cost difference between video and inclinometer methods was reduced to 7%; simulated data showed this difference could be diminished and, even, reversed at larger study sample sizes. Self-report remained substantially less costly under all design strategies, but produced alternate exposure metrics. Conclusions These findings build on the previously published data collection phase cost model by reporting costs for post-collection data processing of the same data set. Together, these models permit empirically based study planning and identification of cost-efficient study designs.
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Affiliation(s)
- Catherine Trask
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, SE - 801 76 Gävle, Sweden.
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Koehoorn M, Trask CM, Teschke K. Recruitment for Occupational Research: Using Injured Workers as the Point of Entry into Workplaces. PLoS One 2013; 8:e68354. [PMID: 23826387 PMCID: PMC3694907 DOI: 10.1371/journal.pone.0068354] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2012] [Accepted: 06/04/2013] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE To investigate the feasibility, costs and sample representativeness of a recruitment method that used workers with back injuries as the point of entry into diverse working environments. METHODS Workers' compensation claims were used to randomly sample workers from five heavy industries and to recruit their employers for ergonomic assessments of the injured worker and up to 2 co-workers. RESULTS The final study sample included 54 workers from the workers' compensation registry and 72 co-workers. This sample of 126 workers was based on an initial random sample of 822 workers with a compensation claim, or a ratio of 1 recruited worker to approximately 7 sampled workers. The average recruitment cost was CND$262/injured worker and CND$240/participating worksite including co-workers. The sample was representative of the heavy industry workforce, and was successful in recruiting the self-employed (8.2%), workers from small employers (<20 workers, 38.7%), and workers from diverse working environments (49 worksites, 29 worksite types, and 51 occupations). CONCLUSIONS The recruitment rate was low but the cost per participant reasonable and the sample representative of workers in small worksites. Small worksites represent a significant portion of the workforce but are typically underrepresented in occupational research despite having distinct working conditions, exposures and health risks worthy of investigation.
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Affiliation(s)
- Mieke Koehoorn
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
- * E-mail:
| | - Catherine M. Trask
- Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Kay Teschke
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
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Mathiassen SE, Liv P, Wahlström J. Cost-efficient measurement strategies for posture observations based on video recordings. APPLIED ERGONOMICS 2013; 44:609-617. [PMID: 23333111 DOI: 10.1016/j.apergo.2012.12.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2012] [Revised: 12/04/2012] [Accepted: 12/20/2012] [Indexed: 06/01/2023]
Abstract
Assessment of working postures by observation is a common practice in ergonomics. The present study investigated whether monetary resources invested in a video-based posture observation study should preferably be spent in collecting many video recordings of the work and have them observed once by one observer, or in having multiple observers rate postures repeatedly from fewer videos. The study addressed this question from a practitioner's perspective by focusing two plausible scenarios: documenting the mean exposure of one individual, and of a specific occupational group. Using a data set of observed working postures among hairdressers, empirical values of posture variability, observer variability, and costs for recording and observing one video were entered into equations expressing the total cost of data collection and the information (defined as 1/SD) provided by the resulting estimates of two variables: percentage time with the arm elevated <15° and >90°. Sixteen measurement strategies involving 1-4 observers repeating their posture ratings 1-4 times were examined for budgets up to €2000. For both posture variables and in both the individual and group scenario, the most cost-efficient strategy at any specific budget was to engage 3-4 observers and/or having observer(s) rate postures multiple times each. Between 17% and 34% less information was produced when using the commonly practiced approach of having one observer rate a number of video recordings one time each. We therefore recommend observational posture assessment to be based on video recordings of work, since this allows for multiple observations; and to allocate monetary resources to repeated observations rather than many video recordings.
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Affiliation(s)
- Svend Erik Mathiassen
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.
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Trask C, Mathiassen SE, Wahlström J, Heiden M, Rezagholi M. Data collection costs in industrial environments for three occupational posture exposure assessment methods. BMC Med Res Methodol 2012; 12:89. [PMID: 22738341 PMCID: PMC3439320 DOI: 10.1186/1471-2288-12-89] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2012] [Accepted: 06/27/2012] [Indexed: 11/10/2022] Open
Abstract
Background Documentation of posture measurement costs is rare and cost models that do exist are generally naïve. This paper provides a comprehensive cost model for biomechanical exposure assessment in occupational studies, documents the monetary costs of three exposure assessment methods for different stakeholders in data collection, and uses simulations to evaluate the relative importance of cost components. Methods Trunk and shoulder posture variables were assessed for 27 aircraft baggage handlers for 3 full shifts each using three methods typical to ergonomic studies: self-report via questionnaire, observation via video film, and full-shift inclinometer registration. The cost model accounted for expenses related to meetings to plan the study, administration, recruitment, equipment, training of data collectors, travel, and onsite data collection. Sensitivity analyses were conducted using simulated study parameters and cost components to investigate the impact on total study cost. Results Inclinometry was the most expensive method (with a total study cost of € 66,657), followed by observation (€ 55,369) and then self report (€ 36,865). The majority of costs (90%) were borne by researchers. Study design parameters such as sample size, measurement scheduling and spacing, concurrent measurements, location and travel, and equipment acquisition were shown to have wide-ranging impacts on costs. Conclusions This study provided a general cost modeling approach that can facilitate decision making and planning of data collection in future studies, as well as investigation into cost efficiency and cost efficient study design. Empirical cost data from a large field study demonstrated the usefulness of the proposed models.
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Affiliation(s)
- Catherine Trask
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, SE-80176 Gävle, Sweden.
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Liv P, Mathiassen SE, Svendsen SW. Accuracy and precision of variance components in occupational posture recordings: a simulation study of different data collection strategies. BMC Med Res Methodol 2012; 12:58. [PMID: 22533627 PMCID: PMC3377541 DOI: 10.1186/1471-2288-12-58] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2011] [Accepted: 04/25/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Information on exposure variability, expressed as exposure variance components, is of vital use in occupational epidemiology, including informed risk control and efficient study design. While accurate and precise estimates of the variance components are desirable in such cases, very little research has been devoted to understanding the performance of data sampling strategies designed specifically to determine the size and structure of exposure variability. The aim of this study was to investigate the accuracy and precision of estimators of between-subjects, between-days and within-day variance components obtained by sampling strategies differing with respect to number of subjects, total sampling time per subject, number of days per subject and the size of individual sampling periods. METHODS Minute-by-minute values of average elevation, percentage time above 90° and percentage time below 15° were calculated in a data set consisting of measurements of right upper arm elevation during four full shifts from each of 23 car mechanics. Based on this parent data, bootstrapping was used to simulate sampling with 80 different combinations of the number of subjects (10, 20), total sampling time per subject (60, 120, 240, 480 minutes), number of days per subject (2, 4), and size of sampling periods (blocks) within days (1, 15, 60, 240 minutes). Accuracy (absence of bias) and precision (prediction intervals) of the variance component estimators were assessed for each simulated sampling strategy. RESULTS Sampling in small blocks within days resulted in essentially unbiased variance components. For a specific total sampling time per subject, and in particular if this time was small, increasing the block size resulted in an increasing bias, primarily of the between-days and the within-days variance components. Prediction intervals were in general wide, and even more so at larger block sizes. Distributing sampling time across more days gave in general more precise variance component estimates, but also reduced accuracy in some cases. CONCLUSIONS Variance components estimated from small samples of exposure data within working days may be both inaccurate and imprecise, in particular if sampling is laid out in large consecutive time blocks. In order to estimate variance components with a satisfying accuracy and precision, for instance for arriving at trustworthy power calculations in a planned intervention study, larger samples of data will be required than for estimating an exposure mean value with a corresponding certainty.
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Affiliation(s)
- Per Liv
- Centre for Musculoskeletal Research, University of Gävle, Gävle, Sweden
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