Associations between work factors and psychological distress in a convenience sample of commercial construction workers.
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2019/11/06
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By Dennerlein J
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Description:Problem. Mental health and well-being among construction workers is a significant public health burden in the United States. While there is little work examining the mental health of construction workers, our previous work indicates that mental distress (as measured by the Hopkins Symptom Checklist-251) is higher (16%) among commercial construction workers, than among the general male population. Construction workers have the second highest suicide rate compared to all occupational groups, second only to workers in the farming, fishing, and forestry industry. The rate in 2016 was 53.3 suicides per 100,000 persons, which is sizably higher than the fatal occupational injury rate of 10.1 fatalities per 100,000 full-time construction workers. With the construction industry employing on average 7.1 million workers, accounting for 5% of the working population, these high rates have a large impact on the U.S. general population. Based on this high prevalence in a given occupation, programs to improve construction worker mental health and well-being should probably target factors in the worksite environment within a Total Worker Health® Conceptual Framework. The construction industry has many different organizations that interact with the worker's safety, health, and well-being. More work is needed to understand the workplace factors that contribute to the higher prevalence mental health outcomes. This research is an important next step for identifying opportunities to best support construction workers mental health and well-being in the workplace. The goal of this abstract is to determine the associations of workplace factors and mental distressed in a convivence sample of commercial construction safety and health stakeholders as well as workers in the Boston metropolitan area through a sequential qualitative-quantitative mix-methods approach. Procedures. First, we conducted eight semi-structured interviews with key stakeholders and six focus groups of 4-12 construction workers. The interviews consisted of ten questions about their experiences with the mental health and well-being of construction workers and the role of workplace factors. The stakeholders included construction project managers and health and safety directors. Participants in the focus groups included foremen, journeymen, and apprentices. Participants in all but one of the focus groups were recruited via the sites' general contracting or subcontracting organizations. For one group, participants were recruited from a local union training facility. Second, we conducted a worker survey of 259 construction workers from five commercial construction sites in the Boston metropolitan. The primary outcome in the survey was the K6-psychological distress scale. Other factors in the survey included work-related factors identified in the interviews and the focus groups that participants considered important for mental health and well-being. The survey used validated scales to measure these factors. These factors included safety climate, job demands, decision latitude coworker and supervisor support, work to family conflict and job security. All scripts, surveys and procedures were approved by the Northeastern University Office for Human Subject Research Protection. Analyses. We used thematic analysis to explore the qualitative data collected from the key informant interviews and focus groups. To examine quantitative associations among workplace factors and mental health, crude and adjusted (age and position) rate ratios were estimated using negative-binomial regression models. Results. The qualitative analysis identified three types of work factors that were associated with mental health and well-being: 1) job structure including work place hazards, job demands including production pressures, and work-family conflict attributed to the working hours, 2) relational factors including relationships with foremen, supervisors, and coworkers as well as on the job harassment, and 3) job security. The quantitative analysis of the survey data identified associations between K6 psychological distress scale and many of the work factors. Better safety climate and greater supervisor support scales were associated with lower K6 scores. Greater perceptions of job demands, on the job harassment, and work to family conflict were associated with higher K6 scores. Those who reported they were likely to lose their job also reported higher K6 scores. These associations remained significant in the models adjusted for age and trade. Practical Implications and Conclusions. Approaches to improving mental health and well-being among commercial construction workers should consider the role of workplace factors. A novel outcome was the association with work to family conflict in a male population. Both the qualitative and quantitative data describe this association. Another factor was not knowing what the next commute would be like as well as nonflexible work hours typical of the industry making it difficult to participate in family tasks and activities. Relational factors play an important role, especially harassment. Production pressures were also discussed intensifying work and adding stress to work. These factors indicate many points of potential interventions; however, these interventions addressing these factors need to be examined to determine their feasibility and efficacy. [Description provided by NIOSH]
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Pages in Document:83-84
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NIOSHTIC Number:nn:20065674
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Citation:Work, Stress and Health 2019, November 6-9, 2019, Philadelphia, Pennsylvania. Washington, DC: American Psychological Association, 2019 Nov; :83-84
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Federal Fiscal Year:2020
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Performing Organization:Harvard University, Boston, Massachusetts
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Peer Reviewed:False
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Start Date:20070901
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Source Full Name:Work, Stress and Health 2019, November 6-9, 2019, Philadelphia, Pennsylvania
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End Date:20260831
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Main Document Checksum:urn:sha-512:8aca26616fa8a7921f23e23f1f14c4cec89ac1a662b79aed2ef68ba2c0c13129001d4c9e4769753d7fcc96f36be32f9aa55ba5c22851c47adfea99e2927bce55
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