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{ "item_title" : "Assessing the Association between Pre-Employment Drug Screening and a Reduction in Workplace Accidents and Injuries", "item_author" : [" Jon Myron Fox "], "item_description" : "The purpose of this quasi-experimental quantitative study was to expand on previous scholarly work, demonstrating enhanced workplace health and safety through a reduction of workplace accidents and injuries. The association between pre-screening employees for drug use, and accident and/or injury rates was assessed. Using two subsets of archival records, it was investigated whether or not lower workplace accident/injury rates were associated with records representing employees pre-screened for drug use, compared with records representing employees who were not pre-screened. Archive data records were randomly sampled, creating a group of 300 records representing employees pre-screened for drug use before hire, testing negative, and a comparison group of 300 records representing employees not undergoing any drug screening. Average annual accident rate for the pre-screened employees' subset (2.16%) was less than one-half the rate for the non-screened employees' subset (4.50%). A Mann-Whitney U test showed pre-screened employee accident/injury rate {Mdn = 2) differed from non-screened employees {Mdn - 2, U= 40950.0 , p 0.0013, r = .13). A Kruskal-Wallis test indicated significant effect of gender (H(2) = 7.2924, p .0001), and industry sector (H(2) = 12.1231 , p - .0172) on the non-screened employee subset. A Mann-Whitney U test showed positive post-accident rates of pre-screened employees {Mdn = 99) differed from non-screened employees {Mdn = 99, U - 40864.0, p r = .13). A Kruskal- Wallis test indicated significant effect of gender (H(2) = 7.6620, p .0001), and industry sector (H(2) = 12.7233, /? = .0119) on the non-screened subset. A Pearson's Chi-Square Test for Independence revealed industry classification assignment as not independent, X,2(12, N = 600) = 109.26, p", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/834/965/9798349659836_b.jpg", "price_data" : { "retail_price" : "59.95", "online_price" : "59.95", "our_price" : "59.95", "club_price" : "59.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Assessing the Association between Pre-Employment Drug Screening and a Reduction in Workplace Accidents and Injuries|Jon Myron Fox

Assessing the Association between Pre-Employment Drug Screening and a Reduction in Workplace Accidents and Injuries

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Overview

The purpose of this quasi-experimental quantitative study was to expand on previous scholarly work, demonstrating enhanced workplace health and safety through a reduction of workplace accidents and injuries. The association between pre-screening employees for drug use, and accident and/or injury rates was assessed. Using two subsets of archival records, it was investigated whether or not lower workplace accident/injury rates were associated with records representing employees pre-screened for drug use, compared with records representing employees who were not pre-screened. Archive data records were randomly sampled, creating a group of 300 records representing employees pre-screened for drug use before hire, testing negative, and a comparison group of 300 records representing employees not undergoing any drug screening. Average annual accident rate for the pre-screened employees' subset (2.16%) was less than one-half the rate for the non-screened employees' subset (4.50%). A Mann-Whitney U test showed pre-screened employee accident/injury rate {Mdn = 2) differed from non-screened employees {Mdn - 2, U= 40950.0 , p 0.0013, r = .13). A Kruskal-Wallis test indicated significant effect of gender (H(2) = 7.2924, p .0001), and industry sector (H(2) = 12.1231 , p - .0172) on the non-screened employee subset. A Mann-Whitney U test showed positive post-accident rates of pre-screened employees {Mdn = 99) differed from non-screened employees {Mdn = 99, U - 40864.0, p r = .13). A Kruskal- Wallis test indicated significant effect of gender (H(2) = 7.6620, p .0001), and industry sector (H(2) = 12.7233, /? = .0119) on the non-screened subset. A Pearson's Chi-Square Test for Independence revealed industry classification assignment as not independent, X,2(12, N = 600) = 109.26, p

Details

  • ISBN-13: 9798349659836
  • ISBN-10: 9798349659836
  • Publisher: 7000 Islands Publishing
  • Publish Date: November 2025
  • Dimensions: 11 x 8.5 x 0.88 inches
  • Shipping Weight: 2.65 pounds
  • Page Count: 398

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