METHODS: Initially, to develop constructs related to social media activities, web-based structured interviews were conducted with five office employees working in the oil and gas industry for the last 5 years. Then, using an online questionnaire survey, data was collected from 424 office employees working in the oil and gas industry in Malaysia. Using statistical software for social science (SPSS) and Smart PLS, exploratory factor analysis and confirmatory factor analysis were conducted to identify reliability and validity (discriminant validity, convergent validity and composite validity) of the constructs. Following this, path analysis was conducted and the moderating effects were identified.
RESULTS: Social media activities related to work-life decrease health and wellbeing by 11% and weaken the negative effect of effort-reward-imbalance on health and wellbeing by 17.6% at a 1% level of significance. The results of social media activities related to personal and social life strengthen the negative effect of effort-reward imbalance on health and wellbeing by 12% and negatively affects health and wellbeing and job rewards by 13, 55%, respectively. The direct effect of effort-reward imbalance and job efforts is significantly negative on health and wellbeing by 59 and 10%, respectively.
CONCLUSION: It is concluded that social media activities of the office employees significantly moderate the effect of effort-reward imbalance on health and wellbeing and intervene in job rewards in the organizations. Hence, the effect of social media activities reduces the health and wellbeing of office employees.
METHODS: Thus, in this study, we used the Psychomotor Vigilance Test (PVT-192) and a short survey to address driving fatigue behavior and identify the influences of driving fatigue on driving performance in real life (on the road) with actual oil and gas tanker drivers. The total participants in the experimental study were 58 drivers.
RESULTS: For the analysis, a Wilcoxon Signed Ranks Test, Z value and Spearman's rho were used to measure the significant difference between the pre and post-tests of PVT and the correlation between the fatigue variables and driving performance.
DISCUSSION: During the experiment's first and second days, this study's results indicated that driving fatigue gradually escalated. Likewise, there was a negative correlation based on the test of the relationship between the PVT data and the driving performance survey data. Additionally, the drivers suffer from accumulative fatigue, which requires more effort from the transportation company management to promote the drivers awareness of fatigue consequences.
MATERIALS AND METHODS: A self-administered questionnaire was used for data collection from 373 post-graduate Ph.D. students registered in various universities throughout Malaysia with a non-probabilistic sampling technique. Research respondents belonged to management, humanities, engineering, computer science, and health sciences domains, and they responded through a questionnaire copy. Statistically, structural equation modeling (SEM) was applied to evaluate confirmatory factor analysis (CFA), reliability analysis, validity analysis, measurement model, structural model, and path analysis. Furthermore, the (5000) bootstrapping approach was utilized to test the final model.
RESULTS: For the hypothesized model, our results confirmed that positive emotions had a positive and significant effect on students' psychological capita as well as on their academic engagement behavior. Further, PsyCap also had a positive and significant effect on academic engagement behavior. Our results also reported that stress as a moderating variable has a negative and deteriorating effect on the relationship between PsyCap and the academic engagement of students.
CONCLUSION: The study's findings support the theoretical assumption that positive emotions help individuals generate cognitive resources, which in turn help them manage their engagement behavioral requirements. However, the stress caused by their study needs may deplete their psychological resources, consequently influencing their academic engagement behavior. Interventions like personal coaching/counseling, appropriate follow-up, and flexible goal settings with other measures may help post-graduate students in achieving their daunting tasks.
OBJECTIVE: The broad objective of this study was to investigate the direct and indirect effects of behavioral factors on the psychological and physiological health of workers.
METHODS: The latest, second generation technique, which is structural equation modeling, is used to identify the relationships between behavioral antecedents and health outcomes. A total of 277 technical workers participated, aged between 20 and 49 and were healthy in all aspects.
RESULTS: The study results showed quantitative demands, emotional demands, work-family conflict, and job insecurity were significantly associated with both psychological (stress) and physiological (Body Mass Index) factors. The social support of colleagues produced mixed findings with direct and indirect paths. Stress also significantly mediates the psychosocial factors and burnout of the workers.
CONCLUSION: The study concluded that workers were physically available, but they experienced distractions as members of social systems, affecting their physiological and psychological health.