Anxiety, depression, and brain overwork in the general population of Mongolia

Lkhagvasuren, Battuvshin; Hiramoto, Tetsuya; Bat-Erdene, Enkhjin; Tumurbaatar, Enkhnaran; Tumur-Ochir, Gantsetseg; Amartuvshin, Tsolmontuya; Dashtseren, Myagmartseren; Lai, Edward; Viswanath, Vijay; Oka, Takakazu; Jadamba, Tsolmon

doi:10.1038/s41598-024-52779-w

Cited by 2 publications

References 32 publications

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Early Detection and Prevention of Occupational Diseases Related to 'Excessive Workload': Analyzing of Scientific Researchers' Data in Universities Utilizing Deep Learning Models

Yang,

Yu,

Wei

et al. 2024

Preprint

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As a typical representative of a high-stress occupational group, university researchers are exposed to significant risks associated with ‘excessive workload’. Continuous engagement in intense mental labor leads to the accumulation of physical and mental fatigue, which ultimately increases the susceptibility to cardiovascular and heart diseases. Identifying and monitoring sensitive physiological indicators associated with ‘excessive workload’ is considered an effective strategy to reduce the risks. In this study, an experiment was conducted to build a dataset for researchers using a selection of physiologically sensitive indicators. The dataset including photoplethysmography (PPG) signals, facial behavioral attributes and head posture feature parameters. Six deep learning models and three machine learning models were used in this study for analysis. The results show that all constructed models exhibit excellent performance. Notably, the PSO-CNN-LSTM and MFO-CNN-BiLSTM models show unrivalled accuracy and robustness in the classification task, with prediction accuracies of 99.62% and 99.76%. Respectively, along with a stable AUC value of over 0.99. This highlights their ability to accurately predict the risk of ‘excessive workload’ related diseases in humans. This study provides new insights into the prevention and management of occupational diseases, enhancing occupational health management.

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Early Detection and Prevention of Occupational Diseases Related to 'Excessive Workload': Analyzing of Scientific Researchers' Data in Universities Utilizing Deep Learning Models

Yang,

Yu,

Wei

et al. 2024

Preprint

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The mediator role of the feeling of personal unaccomplishment in the effect of unemployment anxiety on depression: a research on business faculty students in Türkiye

Yumusak

2024

Front. Public Health

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BackgroundThis study aims to determine how the unemployment anxiety of university students affects their depression level. It also examines the mediating role of the feeling of personal unaccomplishment between these effects.MethodsThe data was analyzed using the PROCESS method. The research was conducted on 843 students attending different public or foundation (private) universities in Türkiye. Random sampling was used to select the participants.ResultsAs a result of the analysis, it was determined that there is a positive, significant, moderate (R = 0.509, p < 0.01) relationship between unemployment anxiety and depression and a positive, significant and weak relationship between unemployment anxiety and feeling of personal unaccomplishment (R = 0.102, p < 0.01), there is a positive, significant, and weak (R = 0.184, p < 0.01) relationship between feeling of personal unaccomplishment and depression. Unemployment anxiety of university students had significant and positive effects on their depression level and significant and positive effects on feelings of personal unaccomplishment of students.ConclusionAs a result of the mediating variable analysis, it was determined that the feeling of personal unaccomplishment has a partial mediator role in the relationship between unemployment anxiety and depression.

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Anxiety, depression, and brain overwork in the general population of Mongolia

Cited by 2 publications

References 32 publications

Early Detection and Prevention of Occupational Diseases Related to 'Excessive Workload': Analyzing of Scientific Researchers' Data in Universities Utilizing Deep Learning Models

Early Detection and Prevention of Occupational Diseases Related to 'Excessive Workload': Analyzing of Scientific Researchers' Data in Universities Utilizing Deep Learning Models

The mediator role of the feeling of personal unaccomplishment in the effect of unemployment anxiety on depression: a research on business faculty students in Türkiye

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