Translation of mechanical exposure in the workplace into common metrics for meta-analysis: a reliability and validity study

Publication type
Journal article
Authors
Griffith LE, Wells R, Shannon HS, Walter SD, Cole DC, Cote P, Frank JW, Hogg-Johnson S, Langlois LE
Date published
2011 Jan 25
Journal
Occupational and Environmental Medicine
Volume
68
Issue
8
Pages
605-610
PMID
21075768
Open Access?
No
Abstract

Objectives We previously assessed inter-rater reliability of expert raters using six scales to estimate the intensity of literature-based mechanical exposures. The objectives of this study were to estimate the impact on the inter-rater reliability of using non-expert (NE) raters and to assess the validity of our scales. Methods We used 7-point scales to represent three dimensions of mechanical exposures at work: 1) trunk posture, 2) weight lifted or force exerted and 3) spinal loading. We estimated both peak and cumulative loads and called this an 'interpretive translation' of exposure. A second method, 'algorithmic translation', used the original units in which the exposure data was collected. These data were used to assess the inter-rater reliability and validity of the NE interpretive translation of exposure. Results The NE inter-rater reliability for the scales ranged from 0.24 to 0.46. The correlation between the means of the NE and expert ratings were >0.7. Although there was a strong relationship between the NE interpretive and the algorithmic translation, there was some evidence that the interpretive translation plateaus at higher level of exposure. Conclusions This study supports using NE raters to estimate the intensity of literature-based mechanical exposure metrics using a common set of scales which can be applied across epidemiologic studies. We would need to average the ratings of at least five NE raters to have an acceptable level of reliability (>0.7). These metrics may be useful to quantify the relationship between workplace mechanical exposure and low back pain in a systematic review and meta-analysis