Literature DB >> 29390128

The Effect of Workforce Mobility on Intervention Effectiveness Estimates.

Justin Manjourides1, Emily H Sparer2,3, Cassandra A Okechukwu2, Jack T Dennerlein3,4.   

Abstract

Background: Little is known about how mobile populations of workers may influence the ability to implement, measure, and evaluate health and safety interventions delivered at worksites.
Methods: A simulation study is used to objectively measure both precision and relative bias of six different analytic methods as a function of the amount of mobility observed in the workforce. Those six methods are then used to reanalyze a previously conducted cluster-randomized control trial involving a highly mobile workforce in the construction industry.
Results: As workforce mobility increases, relative bias in treatment effects derived from standard models to analyze cluster-randomized trials also increases. Controlling for amount of time exposed to the intervention can greatly reduce this bias. Analyzing only subsets of workers who exhibit the least amount of mobility can result in decreased precision of treatment effect estimates. We demonstrate a 59% increase in the treatment effect size from the reanalysis of the previously conducted trial. Conclusions: When evaluating organizational interventions implemented at specific worksites by measuring perceptions and outcomes of workers present at those sites, researchers should consider the effects that the mobility of the workforce may have on the estimated treatment effects. The choice of analytic method can greatly affect both precision and accuracy of estimates.

Mesh:

Year:  2018        PMID: 29390128      PMCID: PMC5873524          DOI: 10.1093/annweh/wxx112

Source DB:  PubMed          Journal:  Ann Work Expo Health        ISSN: 2398-7308            Impact factor:   2.179


  16 in total

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Journal:  Tuberculosis (Edinb)       Date:  2012-03-06       Impact factor: 3.131

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Authors:  Elizabeth M Barbeau; Gregory Delaurier; Graham Kelder; Deborah McLellan; Glorian Sorensen; Edith D Balbach; Charles Levenstein
Journal:  J Public Health Policy       Date:  2007       Impact factor: 2.222

6.  Missing data and the trouble with LOCF.

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7.  Does analysis using "last observation carried forward" introduce bias in dementia research?

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8.  Improving the power of chronic disease surveillance by incorporating residential history.

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9.  Length of time spent working on a commercial construction site and the associations with worker characteristics.

Authors:  Emily H Sparer; Cassandra A Okechukwu; Justin Manjourides; Robert F Herrick; Jeffrey N Katz; Jack T Dennerlein
Journal:  Am J Ind Med       Date:  2015-06-29       Impact factor: 2.214

Review 10.  Systematic review of the role of occupational health and safety interventions in the prevention of upper extremity musculoskeletal symptoms, signs, disorders, injuries, claims and lost time.

Authors:  Carol A Kennedy; Benjamin C Amick; Jack T Dennerlein; Shelley Brewer; Starly Catli; Renee Williams; Consol Serra; Fred Gerr; Emma Irvin; Quenby Mahood; Al Franzblau; Dwayne Van Eerd; Bradley Evanoff; David Rempel
Journal:  J Occup Rehabil       Date:  2010-06
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  1 in total

1.  A Cluster Randomized Controlled Trial of a Total Worker Health® Intervention on Commercial Construction Sites.

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Journal:  Int J Environ Res Public Health       Date:  2018-10-25       Impact factor: 3.390

  1 in total

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