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Validity of Observational Job Analysis Methods Brian D. Lowe, Ph.D., CPE

Validity of Observational Job Analysis Methods Brian D. Lowe, Ph.D., CPE National Institute for Occupational Safety and Health Cincinnati, OH August 12, 2003. presentation outline. Physical risk factors for WMSDs and job analysis methods for their characterization

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Validity of Observational Job Analysis Methods Brian D. Lowe, Ph.D., CPE

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  1. Validity of Observational Job Analysis Methods Brian D. Lowe, Ph.D., CPE National Institute for Occupational Safety and Health Cincinnati, OH August 12, 2003

  2. presentation outline • Physical risk factors for WMSDs and job analysis methods for their characterization • NIOSH study of observational job analysis methods • Methods • Results • Conclusions • Validity considerations in job analysis

  3. methods for assessing WMSD risk factors increasing convenience Job Titles/SIC code Worker Self Report Systematic Observation Direct Measurement (Instrumentation) increasing reliability & precision

  4. External Validity - identify exposures associated with increased risk for WMSDs •  epidemiology • Internal Validity - exposure is classified accurately relative to a known standard • biomechanics Exposure Response goals for exposure characterization(Kilbom, 1994)

  5. Objective • Group methods of scaling risk factors used in observational-based job analyses • Compare observational estimates of risk factors with instrumentation-based measures • electrogoniometer – wrist/forearm posture/kinematics • optical motion capture – shoulder posture/kinematics • electromyography – force of exertion • explore the likelihood and nature of errors in exposure characterization

  6. jobs simulated in the laboratory Job B ~ 8 s Job A ~ 13 s Job C ~ 56 s Job D ~ 46 s

  7. α Job C - cycle 3 supination/pronation flexion/extension (α) angle (deg) electrogoniometer

  8. optical motion capture

  9.  - shoulder elevation - plane of shoulder elevation 0 motion capture – shoulder kinematics x – z’ – x” Euler angle sequence : Rotation about x : Rotation about z’ : Rotation about x”  = cos-1 (X · x)  = cos-1 [(Y · x)/sin()]  = cos-1 [ -(X · y)/sin()]

  10. video and instrumentation synchronization

  11. participants and procedure Participants • 28 professional ergonomists • 14 from academia,14 from industry/consulting • 12 - Ph.D./M.D., 13 - M.S., 3 - B.S. • Years experience in ergonomics (1 – 30 yrs.) Procedure • Assigned one method for posture analysis • Estimated posture from video recording of jobs • Analyses were unguided

  12. posture scalingmethod 1 – 3 categories

  13. posture scalingmethod 2 – 6 categories

  14. 0° 0° 0° 0° 0° 0° 0° wrist flexion wrist extension forearm supination forearm pronation elbow flexion shoulder elevation plane of shoulder elevation 95° 85° 145° 135° 150° 180° 150° posture scalingmethod 3 - visual analog scale (VAS)

  15. Resultswrist/forearm – 3 categories (method 1) error = estimated - measured

  16. elbow/shoulder – 3 categories (method 1)

  17. wrist/forearm – 6 categories (method 2)

  18. elbow/shoulder – 6 categories (method 2)

  19. VAS – flexion/extension (method 3) wrist flexion wrist extension r2 = 0.31* r2 = 0.28* r2 = 0.02 r2 = 0.00  peak  average

  20. VAS – supination/pronation (method 3) forearm supination forearm pronation r2 = 0.02 r2 = 0.03 r2 = 0.02 r2 = 0.09  peak  average

  21. VAS – shoulder and elbow (method 3) plane of shoulder elev + elbow flexion shoulder elevation r2 = 0.47* r2 = 0.49* r2 = 0.66* r2 = 0.46* r2 = 0.03 r2 = 0.18*  peak  average

  22. percent of work cycle N N temporal distribution of posture (wrist/forearm – 3 category) N = neutral posture

  23. percent of work cycle N N temporal distribution of posture(wrist/forearm – 6 category)

  24. percent of work cycle N N N temporal distribution of posture(elbow/shoulder – 3 category)

  25. percent of work cycle N N N temporal distribution of posture(elbow/shoulder – 6 category)

  26. Discussion • Performance does not necessarily reflect best case Limitations of the Study • Single video view • Simulated job tasks (laboratory study) • Analysts had no familiarity with jobs • Methods may not have been familiar to analysts • Little information regarding the strategy analysts used • Intended to reflect performance in the typical case

  27. summary of findings • Posture classification accuracy related to the size of the joint/limb segments (Genaidy et al, 1993; Baluyut et al, 1995) • Posture classification accuracy related to the number of scale categories • p(correct classification) = 73% for most frequent shoulder/elbow posture w/3 categories • p(correct classification) = 30% for most frequent wrist/forearm posture w/6 categories

  28. validity considerations in job analysis • Misclassification of working posture occurred in job analyses even when using a small number of posture categories • Posture misclassifications with higher precision scale were more frequent, but their effect is less • Duration severity of posture tended to be underestimated

  29. Acknowledgment The contributions of Dan Habes, NIOSH, Ed Krieg, NIOSH, and Ahmed Khalil, University of Cincinnati are greatly appreciated. Disclaimer Mention of any company name or product, or inclusion of any reference, does not constitute endorsement by the National Institute for Occupational Safety and Health.

  30. risk factors in physical work risk factors for work related musculoskeletal disorders (WMSDs) posture force repetition vibration

  31. lab simulation video recording presented to ergonomists observation Motion Analysis Goniometer magnitude scaling accuracy posture temporal scaling time Ergonomic Exposure Assessment – Observational Accuracy

  32. Temporal job analysis methods for the systematic observation of posture Spatial OCRA Armstrong et al (1982) RULA OWAS Keyserling (1986) STRAIN INDEX Drury (1987) increasing difficulty Latko (1997)

  33. shoulder elevation – Job C cycle 1 cycle 2 cycle 3 cycle 4 work cycle analysis

  34. electrogoniometer upper limb postures evaluated optical motion capture

  35. summary of other findings • Time to completion of the analysis was not related to the resulting accuracy • No relationship between years experience and accuracy of observational estimates • No relationship between work cycle variability and accuracy of observational estimates

  36. radial/ulnar deviation • Inter-rater agreement statistics • Intraclass correlation coefficient among raters (ergonomists) less than for flex/ext, sup/pro

  37. Juul-Kristensen et al. (1997)

  38. Electrogoniometer Calibration

  39. choice of ROM as VAS anchor 0° 100° 60% 0° 80° 75% true magnitude 60°

  40. Observation vs. Chance ergonomists’ observation chance

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