Exploring productivity outcomes from a brief intervention for at-risk drinking in an employee assistance program

Osilla, Karen Chan; Cruz, Erin Dela; Miles, Jeremy N. V.; Zellmer, Steven P.; Watkins, Katherine E.; Larimer, Mary E.; Marlatt, G. Alan

doi:10.1016/j.addbeh.2009.10.001

Cited by 37 publications

(38 citation statements)

References 44 publications

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“…If future studies confirm our preliminary findings, the implications are that occupations with a high degree of physical demand could be targets for employee-assistance programs focusing on primary and secondary prevention of alcohol misuse, particularly for male workers. Brief interventions for at-risk drinking in employee assistance programs have been shown to be effective in reducing drinking and increasing productivity (Osilla et al, 2008;Osilla et al, 2010). Programs such as these could be tailored for workers in physically demanding occupations to increase their likelihood of success.…”

Section: Discussionmentioning

confidence: 99%

Associations of occupational attributes and excessive drinking

Barnes

Zimmerman

2013

Social Science & Medicine

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Numerous work-related drinking mechanisms have been posited and, oftentimes, examined in isolation. We combined data from over 100 occupational attributes into several factors and tested the association of these factors with measures of alcohol use. We used the NLSY79 2006 wave, a U.S. representative sample of 6,426 workers ages 41 to 49 and the 2006 Occupational Information Network database (O*NET), a nationally representative sample of nearly 1,000 occupations. We conducted exploratory factor analysis on 119 occupational attributes and found three independent workplace characteristics -physical demands, job autonomy, and social engagement -explained the majority of the variation. We then tested the association of these composite attributes with three drinking measures, before and after adjusting for gender, race/ethnicity, and a measure of human capital using count data models. We then stratified by gender and repeated our analyses. Men working in occupations with a one standard deviation higher level of physical demand (e.g. construction) reported a higher number of heavy drinking occasions (+20%, p<0.05). Job autonomy was not significantly associated with measures of alcohol use and when the combined association of higher levels of physical demand and lower levels of job autonomy was examined, modest support for job strain as a mechanism for work-related alcohol consumption was found. In our pooled sample, working in occupations with one standard deviation higher levels of social engagement was associated with lower numbers of drinking days (−9%, p<0.05) after adjustment. Physical demand and social engagement were associated with alcohol consumption measures but these relationships varied by workers' gender. Future areas of research should include confirmatory analyses using other waves of O*Net data and replicating the current analysis in other samples of workers. If our results are validated, they suggest male workers in high physical demand occupations could be targets for intervention.

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Section: Discussionmentioning

confidence: 99%

Associations of occupational attributes and excessive drinking

Barnes

Zimmerman

2013

Social Science & Medicine

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“…The remaining 4 studies (4%) all used ad hoc approaches that (41, 45-48, 51, 56-58, 60, 62, 64, 66, 68, 70, 72-75, 79, 81, 83, 84, 87-90, 92, 93, 95, 97, 98, 100-102, 105, 107-110, 113, 117-125) North-America 34 (39, 40, 43, 44, 50, 52-55, 59, 61, 63, 65, 69, 71, 76, 80, 82, 85, 86, 91, 94, 96, 99, 103, 106, 111, 112, 114-116, 126- (39, 41, 42, 44, 45,49,50,(52)(53)(54)(55)59,60,67,68,70,71,76,77,82,87,95,115, 128) Inferred: 19 (40, 43, 46,57,61,63,65,80,86,91,92,94,96,103,111,116,(125)(126)(127)56,62,64,66,69,72,73,75,78,79,81,(83)(84)(85)…”

Section: Productivity Estimation Methodsmentioning

confidence: 99%

“…Measure for reduced productivity at work/ while working 31 (39, 41-44, 56, 60-65, 69, 70, 72, 77, 82, 87, 89, 94, 95, 98, 103, 104, 114, 115, 118, 119, 123, 124, 128) Source presenteeism Employee survey 18 (41, 44,56,62,64,69,72,82,87,89,94,95,98,104,115,118,119, 123) Simulated / assumptions 7 (39, 43, 44,103,114,124, 128) Previous studies 6 (42,60,61,63,65,70) Firm data 1 (115) Employer survey 1 (77) Survey/instrument presenteeism 56,62,69,82,94,95,118,119,123) Days (unspecified) 49 (39, 40, 42, 46,49,(51)(52)(53)(54)58,60,62,64,66,71,72,74,75,(77)(78)…”

Section: Presenteeismmentioning

confidence: 99%

“…One of these used the labor cost and individual operating income per employee (42) and another the replacement cost of a worker (115). Others adjusted wages only for taxes (90) or used a multiplier for non-wage benefits (94). Finally, 2 studies (52, 53) used disability benefits divided by wage, while Ektor-Anderson et al (58) used social security expenditures and Kärrholm and colleagues (75) applied income qualifying for sickness benefit, adjusted for payroll taxes.…”

Section: Valuing Time Lossmentioning

confidence: 99%

“…Steel et al 39-42, 45-49, 51-54, 56-58, 60-75, 77-91, 93-128) Source absenteeism Firm data 26 (45, 46, 54, 57, 67-69, 71, 85, 86, 88, 91, 95, 96, 100, 101, 105, 107, 110, 114-116, 119, 125-127 (39, 42,49,51,56,57,62,64,66,72,78,79,81,82,87,89,94,102,104,109,113,117,118,(121)(122)(123)) Previous studies 10 (52, 53, 60, 61, 63, 83, 84, 99, 111, 120) Insurance data 9 (47, 48, 58, 60, 74, 75, 80, 112, 124 39, 42,49,56,72,79,81,82,102,104,109,117 11 (41, 56, 62, 93, 100, 107, 118, 119, 121-123) Estimated by the author 1 (88) The Chartered Institute of Personnel and Development 1 (108)…”

mentioning

confidence: 99%

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Productivity estimation in economic evaluations of occupational health and safety interventions: a systematic review

Steel¹,

Godderis²,

Luyten³

2018

Scand J Work Environ Health

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Productivity estimation is a key factor in demonstrating the cost-effectiveness of occupational health and safety (OHS). However, the studies analysed in this systematic review lack standardization, exclude important factors, and the precision, validity and reliability of estimates widely differs. Researchers should be aware of how the method and precision of estimating productivity affects results, and, ultimately, the economic attractiveness of OHS. Key terms: absenteeism; cost-effectiveness; economic evaluation; friction cost; human capital; indirect cost; measurement; methodology; occupational health; occupational health and safety; presenteeism; productivity estimation; review; systematic review; valuation; work This article in PubMed: www.ncbi.nlm.nih.gov/pubmed/29405241 Additional materialPlease note that there is additional material available belonging to this article on the Scandinavian Journal of Work, Environment & Health -website. Scand J Work Environ Health -online first 1Review Productivity estimation in economic evaluations of occupational health and safety interventions: a systematic review by Jonas Steel, MSc, 1 Lode Godderis, MD,2,3 Jeroen Luyten, PhD 1,4 Steel J, Godderis L, Luyten J. Productivity estimation in economic evaluations of occupational health and safety interventions: a systematic review. Scand J Work Environ Health -online first. doi:10.5271/sjweh.3715Objectives Occupational health and safety (OHS) interventions' effect on worker productivity is an essential, but complex element of the value of these programs. The trustworthiness of economic evaluation studies, aiming to provide guidance to decision-makers in the field of OHS, depends at least partly on how accurately productivity changes are measured. We aim to review the methods used to estimate productivity changes in recently published economic evaluations of OHS interventions. MethodsWe performed systematic searches of economic evaluations of OHS programs published between 2007 and 2017 and reviewed these studies' methods to quantify the programs' impact on worker productivity ResultsOf the 90 identified studies, 44 used a human capital approach, 17 a friction cost approach, 13 stated productivity in natural units (eg, a cost-per-absence-day-avoided), 7 made use of compensation expenses, 4 used output-based methods, 4 an "ad hoc" approach, and 1 study did not state its method. Different approaches were combined in 19 studies. Within these methods, we observed a wide diversity in their precise implementation, especially regarding the measurement and valuation of absenteeism and presenteeism.Conclusions Productivity is a key element of the economic attractiveness of investing in OHS. Economic evaluation studies of OHS would benefit from more methodological standardization in their approach to quantifying productivity change. Future research should better account for the methodological uncertainty that occurs in estimating it in order to demonstrate the impact that particular choices and approaches to productivity estimation ca...

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Alcohol Misuse Interventions in the Workplace: A Systematic Review of Workplace and Sports Management Alcohol Interventions

Kolar

Treuer

2015

Int J Ment Health Addiction

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Exploring productivity outcomes from a brief intervention for at-risk drinking in an employee assistance program

Cited by 37 publications

References 44 publications

Associations of occupational attributes and excessive drinking

Associations of occupational attributes and excessive drinking

Productivity estimation in economic evaluations of occupational health and safety interventions: a systematic review

Alcohol Misuse Interventions in the Workplace: A Systematic Review of Workplace and Sports Management Alcohol Interventions

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