Work Fatigue Profiles: Nature, Implications, and Associations With Psychological Empowerment

Blais, Ann-Renée; Gillet, Nicolas; Houle, Simon A.; Comeau, Caitlin; Morin, Alexandre J. S.

doi:10.3389/fpsyg.2020.596206

Cited by 7 publications

(6 citation statements)

References 98 publications

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“…In the male sex, the endurance of the body will be stronger than that of the female [16]. This statement is directly proportional to the theory that men's endurance is stronger than that of women [17]. Compared with the results of the author's research now, results were found that were in line with the theory, namely the majority of male workers were 29 people and 7 other people with the female sex.…”

Section: B Gendermentioning

confidence: 56%

Effect of Work Climate on Labor Fatigue in Kediri Tofu Factory in 2021

Lahudin

Rachmaniyah

Khambali

et al. 2022

International Journal of Advanced Health Science and Technology

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This study aims to determine the effect of work climate on worker fatigue in Pabrik Tahu Kediri. This research is an observational study with a cross sectional approach. Data was collected by observation, interviews and measurements. The population in the study was 40 workers. The retrieval technique used is Ordinal Regression. The data obtained will be analyzed using the Ordinal Regression test. The variables in this study were labor fatigue as the dependent variable and hot work climate as the independent variable. From the statistical analysis, work fatigue is influenced by the characteristics of the workforce, namely age and gender (p 0.05). The results of the measurement of fatigue before work show that all workers experience low fatigue and 22.2% fatigue after work, 33.3% of workers who experience moderate fatigue and 44.4% of workers who experience high fatigue. The results of the measurement of the working climate in the production room are on average 32°C, which means it exceeds the NAV. Statistical test results show that there is a significant effect of work climate on labor fatigue at 0.001 0.05. Excessive hot work climate can cause body temperature to increase, sweating, which causes the body to lose fluids, salt and cause fatigue. Factors that influence labor fatigue are age, gender, and work climate. Based on the results of this study, the industry is advised to provide drinking places, adding ventilation to reduce heat exposure.

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Section: B Gendermentioning

confidence: 56%

Effect of Work Climate on Labor Fatigue in Kediri Tofu Factory in 2021

Lahudin

Rachmaniyah

Khambali

et al. 2022

International Journal of Advanced Health Science and Technology

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“…Work fatigue is composed of three different levels of fatigue: emotional, mental, and physical fatigue and may affect psychological and physical health of the workers leading to less efficient work recovery and negative work attitude. [34]. Therefore, an adequate physical demand is fundamental to preserve the mental state of the worker.…”

Section: Discussionmentioning

confidence: 99%

Optimal Biomechanical Performance in Upper-Limb Gestures Depends on Velocity and Carried Load

Brambilla

Malosio

Reni

et al. 2022

Biology

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In the last few years, there has been increased interest in the preservation of physical and mental health of workers that cooperate with robots in industrial contexts, such as in the framework of the European H2020 Mindbot Project. Since biomechanical analysis contributes to the characterization of the subject interacting with a robotic setup and platform, we tested different speed and loading conditions in a simulated environment to determine upper-limb optimal performance. The simulations were performed starting from laboratory data of people executing upper-limb frontal reaching movements, by scaling the motion law and imposing various carried loads at the hand. The simulated velocity ranged from 20% to 200% of the original natural speed, with step increments of 10%, while the hand loads were 0, 0.5, 1, and 2 kg, simulating carried objects. A 3D inverse kinematic and dynamic model was used to compute upper-limb kinematics and dynamics, including shoulder flexion, shoulder abduction, and elbow flexion. An optimal range of velocities was found in which the expended energy was lower. Interestingly, the optimal speed corresponding to lower exerted torque and energy decreased when the load applied increased. Lastly, we introduced a preliminary movement inefficiency index to evaluate the deviation of the power and expended energy for the shoulder flexion degree of freedom when not coinciding with the minimum energy condition. These results can be useful in human–robot collaboration to design minimum-fatigue collaborative tasks, tune setup parameters and robot behavior, and support physical and mental health for workers.

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“…Participant's levels of mental (six items; e.g., "Actually, I want to mentally shut down"; α = .94) and emotional (six items; e.g., "Actually, I want to avoid anything that took too much emotional energy"; α = .95) fatigue were measured at all occasions using the Work Fatigue Inventory (Frone & Tidwell, 2015; French version by Blais et al, 2020). Following Barling and Frone (2017), we rely on a global score of fatigue (α = .96).…”

Section: Fatigue (Outcome)mentioning

confidence: 99%

Nature, predictor, and outcomes of motivation trajectories during a professional training program

Sandrin

Morin

Fernet

et al. 2021

European Journal of Work and Organizational Psychology

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Trainees' motivation is an important factor to consider in order to strengthen their learning, wellbeing, and involvement in training sessions. Unfortunately, prior research has often adopted a static (cross-sectional) and unidimensional perspective of training motivation, been limited by the consideration of a very limited range of outcomes, and failed to consider the possible predictors of trainees' motivation. To address these limitations, the present study examines the shape, determinants (autonomy-supportive behaviors), and outcomes (positive and negative affect, fatigue, engagement, learning, and satisfaction) of autonomous and controlled motivation trajectories over the course of a professional training program. A sample of 43 employees completed the measures on four occasions (first day, three weeks, 10 weeks, and 14 weeks) over the course of a 14-week professional training program. This study also relies on a burst design, whereby employees completed each measure twice (with a half-day interval) at each measurement occasion to achieve a more accurate representation of occasion-specific ratings. Results from three-level growth analyses (with the two bursts at Level 1, four occasions at Level 2, and participants at Level 3) showed that autonomous motivation, negative affect, learning, and satisfaction appeared to follow curvilinear trajectories, whereas autonomy support and positive affect followed linear trajectories. In contrast, controlled motivation, fatigue, and engagement levels remained stable over time, consistent with an intercept-only model. Furthermore, higher levels of autonomy support were associated with higher levels of autonomous motivation, and lower levels of controlled motivation over time. Finally, higher initial levels of autonomous motivation predicted higher levels of positive affect, learning, satisfaction, and engagement, and lower levels of fatigue over time, whereas higher initial levels of controlled motivation predicted higher levels of fatigue over time.

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Work Fatigue Profiles: Nature, Implications, and Associations With Psychological Empowerment

Cited by 7 publications

References 98 publications

Effect of Work Climate on Labor Fatigue in Kediri Tofu Factory in 2021

Effect of Work Climate on Labor Fatigue in Kediri Tofu Factory in 2021

Optimal Biomechanical Performance in Upper-Limb Gestures Depends on Velocity and Carried Load

Nature, predictor, and outcomes of motivation trajectories during a professional training program

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