The construction industry has hit a plateau in terms of safety performance. Safety climate is regarded as a leading indicator of safety performance; however, relatively little safety climate research has been done in the Canadian construction industry. Safety climate may be geographically sensitive, thus it is necessary to examine how the construct of safety climate is defined and used to improve safety performance in different regions. On the other hand, more and more attention has been paid to job related stress in the construction industry. Previous research proposed that individual resilience may be associated with a better safety performance and may help employees manage stress. Unfortunately, few empirical research studies have examined this hypothesis. This paper aims to examine the role of safety climate and individual resilience in safety performance and job stress in the Canadian construction industry. The research was based on 837 surveys collected in Ontario between June 2015 and June 2016. Structural equation modeling (SEM) techniques were used to explore the impact of individual resilience and safety climate on physical safety outcomes and on psychological stress among construction workers. The results show that safety climate not only affected construction workers' safety performance but also indirectly affected their psychological stress. In addition, it was found that individual resilience had a direct negative impact on psychological stress but had no impact on physical safety outcomes. These findings highlight the roles of both organizational and individual factors in individual safety performance and in psychological well-being. Construction organizations need to not only monitor employees' safety performance, but also to assess their employees' psychological well-being. Promoting a positive safety climate together with developing training programs focusing on improving employees' psychological health - especially post-trauma psychological health - can improve the safety performance of an organization.

Interpersonal conflicts at work (ICW) have been widely regarded as a job stressor; however, it is rarely linked to physical safety outcomes. The ICW primarily has two forms on a construction site: conflicts with supervisors (${\mathrm{ICW}}_S$ ) and conflicts with coworkers (${\mathrm{ICW}}_C$ ). This study examined the occurrences of ${\mathrm{ICW}}_S$ and ${\mathrm{ICW}}_C$ on construction sites, and investigated the relationship among ${\mathrm{ICW}}_S$ , ${\mathrm{ICW}}_S$ , and physical safety outcomes together with job stress. In addition, possible antecedents of ${\mathrm{ICW}}_S$ and ${\mathrm{ICW}}_C$ including workhours, mobility, and individual resilience were also examined. The research was based on 837 surveys collected from more than 100 construction sites in Ontario, Canada between July 2015 and July 2016. Structural equation modeling (SEM) techniques were used to test the hypothesized relationships. This paper leads to the following conclusions. Although ICW was reported as quite often or very often by only 6.3% of respondents, it had a significant effect on both physical safety outcomes, including physical injuries and unsafe events, and job stress. Individual resilience (IR) had a significant negative correlation with both ${\mathrm{ICW}}_S$ and ${\mathrm{ICW}}_C$ , which in turn could decrease the frequency of physical safety outcomes and job stress. The contributions of this study are that safety professionals may consider adding coping skill training safety programs to improve the individual resilience of their workforce and reduce conflict-related safety outcomes.

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8–2323), posts (29–28,684), and Gini coefficients (0.15–0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527–0.835, p < .001), and Gini coefficients and number of posts (0.342–0.725, p < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p < .036). Linear regression models had positive but mixed R ² results (0.333–0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant (t = 3.346–7.381, p < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks (t = −4.305 and −5.934, p < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

A multidisciplinary journal on gaming and gamification for health education/promotion, teaching and social change.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet