| 1. |
- Heiden, Marina, et al.
(författare)
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A comparison of two strategies for building an exposure prediction model
- 2016
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Ingår i: Annals of Occupational Hygiene. - : Oxford University Press (OUP). - 0003-4878 .- 1475-3162. ; 60:1, s. 74-89
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Tidskriftsartikel (refereegranskat)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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| 2. |
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| 3. |
- Jackson, Jennie A., et al.
(författare)
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Is what you see what you get? : Standard inclinometry of set upper arm elevation angles
- 2015
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Ingår i: Applied Ergonomics. - : Elsevier BV. - 0003-6870 .- 1872-9126. ; 47, s. 242-252
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Tidskriftsartikel (refereegranskat)abstract
- Previous research suggests inclinometers (INC) underestimate upper arm elevation. This study was designed to quantify possible bias in occupationally relevant postures, and test whether INC performance could be improved using calibration. Participants were meticulously positioned in set arm flexion and abduction angles between 0 degrees and 150 degrees. Different subject-specific and group-level regression models comprising linear and quadratic components describing the relationship between set and INC-registered elevation were developed using subsets of data, and validated using additional data. INC measured arm elevation showed a downward bias, particularly above 600. INC data adjusted using the regression models were superior to unadjusted data; a subject-specific, two-point calibration based on measurements at 0 and 900 gave results closest to the 'true' set angles. Thus, inclinometer measured arm elevation data required calibration to arrive at 'true' elevation angles. Calibration to a common measurement scale should be considered when comparing arm elevation data collected using different methods.
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| 4. |
- Jackson, Jennie A., et al.
(författare)
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Observer performance in estimating upper arm elevation angles under ideal viewing conditions when assisted by posture matching software
- 2016
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Ingår i: Applied Ergonomics. - : Elsevier BV. - 0003-6870 .- 1872-9126. ; 55, s. 208-215
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Tidskriftsartikel (refereegranskat)abstract
- Selecting a suitable body posture measurement method requires performance indices of candidate tools. Such data are lacking for observational assessments made at a high degree of resolution. The aim of this study was to determine the performance (bias and between- and within-observer variance) of novice observers estimating upper arm elevation postures assisted by posture matching software to the nearest degree from still images taken under ideal conditions. Estimates were minimally biased from true angles: the mean error across observers was less than 2. Variance between observers was minimal. Considerable variance within observers, however, underlined the risk of relying on single observations. Observers were more proficient at estimating 0 and 90 postures, and less proficient at 60. Thus, under ideal visual conditions observers, on average, proved proficient at high resolution posture estimates; further investigation is required to determine how non-optimal image conditions, as would be expected from occupational data, impact proficiency.
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| 5. |
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| 6. |
- Liv, Per, et al.
(författare)
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Accuracy and precision of variance components in occupational posture recordings : a simulation study of different data collection strategies
- 2012
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 12:1, s. 58-58
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Tidskriftsartikel (refereegranskat)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 betweensubjects, 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 90degrees and percentage time below 15degrees 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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| 7. |
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| 8. |
- Liv, Per, 1979-
(författare)
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Efficient strategies for collecting posture data using observation and direct measurement
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Relationships between occupational physical exposures and risks of contracting musculoskeletal disorders are still not well understood; exposure-response relationships are scarce in the musculoskeletal epidemiology literature, and many epidemiological studies, including intervention studies, fail to reach conclusive results. Insufficient exposure assessment has been pointed out as a possible explanation for this deficiency. One important aspect of assessing exposure is the selected measurement strategy; this includes issues related to the necessary number of data required to give sufficient information, and to allocation of measurement efforts, both over time and between subjects in order to achieve precise and accurate exposure estimates. These issues have been discussed mainly in the occupational hygiene literature considering chemical exposures, while the corresponding literature on biomechanical exposure is sparse. The overall aim of the present thesis was to increase knowledge on the relationship between data collection design and the resulting precision and accuracy of biomechanical exposure assessments, represented in this thesis by upper arm postures during work, data which have been shown to be relevant to disorder risk.Four papers are included in the thesis. In papers I and II, non-parametric bootstrapping was used to investigate the statistical efficiency of different strategies for distributing upper arm elevation measurements between and within working days into different numbers of measurement periods of differing durations. Paper I compared the different measurement strategies with respect to the eventual precision of estimated mean exposure level. The results showed that it was more efficient to use a higher number of shorter measurement periods spread across a working day than to use a smaller number for longer uninterrupted measurement periods, in particular if the total sample covered only a small part of the working day. Paper II evaluated sampling strategies for the purpose of determining posture variance components with respect to the accuracy and precision of the eventual variance component estimators. The paper showed that variance component estimators may be both biased and imprecise when based on sampling from small parts of working days, and that errors were larger with continuous sampling periods. The results suggest that larger posture samples than are conventionally used in ergonomics research and practice may be needed to achieve trustworthy estimates of variance components.Papers III and IV focused on method development. Paper III examined procedures for estimating statistical power when testing for a group difference in postures assessed by observation. Power determination was based either on a traditional analytical power analysis or on parametric bootstrapping, both of which accounted for methodological variance introduced by the observers to the exposure data. The study showed that repeated observations of the same video recordings may be an efficient way of increasing the power in an observation-based study, and that observations can be distributed between several observers without loss in power, provided that all observers contribute data to both of the compared groups, and that the statistical analysis model acknowledges observer variability. Paper IV discussed calibration of an inferior exposure assessment method against a superior “golden standard” method, with a particular emphasis on calibration of observed posture data against postures determined by inclinometry. The paper developed equations for bias correction of results obtained using the inferior instrument through calibration, as well as for determining the additional uncertainty of the eventual exposure value introduced through calibration.In conclusion, the results of the present thesis emphasize the importance of carefully selecting a measurement strategy on the basis of statistically well informed decisions. It is common in the literature that postural exposure is assessed from one continuous measurement collected over only a small part of a working day. In paper I, this was shown to be highly inefficient compared to spreading out the corresponding sample time across the entire working day, and the inefficiency was also obvious when assessing variance components, as shown in paper II. The thesis also shows how a well thought-out strategy for observation-based exposure assessment can reduce the effects of measurement error, both for random methodological variance (paper III) and systematic observation errors (bias) (paper IV).
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| 9. |
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| 10. |
- Liv, Per, 1979-, et al.
(författare)
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Statistical power and measurement requirements in studies comparing observed postures between groups
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Ergonomics studies comparing working postures and movements between independent groups are often based on observations. The present paper derives and exemplifies procedures for estimating the statistical power of such studies, addressing the effect of different strategies for allocating observations within and between observers. In the simple case of one observer rating the postures of all subjects in the study one or multiple times, a simple t-test is appropriate for testing the group difference, while statistical models acknowledging rating differences between observers are needed when multiple observers are involved. In the one-observer case, analytical power calculations are feasible, while a parametric bootstrapping approach is suggested and practiced in the paper for the multiple-observers case. Using empirical data from a previous study of postures among hairdressers observed from video recordings (percentages of time with the right upper arm elevated less than 15° and more than 90°), the study demonstrates that a considerable gain in power can be obtained by having one observer doing multiple repeated observations as compared to rating postures only once. Distributing a certain number of video recordings between multiple observers resulted in a loss of power when a simple t-test was used to test the group difference, but the comparison could be accomplished without loss of power if all observers were involved in rating both of the compared groups and the statistical model used to analyze data acknowledged variability in rating between observers. When different observers assessed the two compared groups, power decreased considerably. Thus, the study gives guidance for efficient design of posture observation studies comparing groups, as well as for appropriate statistical procedures for analyzing the data.
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