Objective: Cognitive impairment is common in patients with Parkinson’s disease (PD), and few pharmacological options are available for treating this condition. We evaluated the effects of a digital cognitive training program (SUPERBRAIN), which was previously shown to be effective in populations at risk of Alzheimer’s disease, on cognitive function in individuals with PD. Methods: Twenty-three individuals with PD and mild cognitive impairment (PD-MCI) from four clinics were randomized to the intervention (n=16) or control (n=7) groups. The intervention group completed a 12-week, home-based, tablet-based cognitive training program (25–30 min/day, 7 days/week). Cognitive outcomes were assessed using the Seoul Neuropsychological Screening Battery pre- and post-intervention. Results: The adherence rate was 79.36%. The intervention group showed significant improvements in the Seoul Verbal Learning Test (SVLT) delayed recall and the Controlled Oral Word Association Test, while no changes were observed in the control group. Analysis of covariance confirmed greater SVLT improvement in the intervention group (F statistic=7.15, p=0.015, partial η2=0.28). Conclusion SUPERBRAIN is feasible and can improve cognitive function in individuals with PD-MCI.

Objective: This study evaluated the effectiveness of a virtual reality (VR) based stress reduction program tailored for healthcare and information technology (IT) professionals during the coronavirus disease-2019 pandemic. Methods: The 2-week program, based on forest healing principles, was designed to alleviate occupational stress and improve sleep quality. Participants (n=54; 46 healthcare, 8 IT professionals) underwent pre- and post-intervention assessments using validated psychological scales and physiological measurements. Results: Results showed significant reductions in stress (Perceived Stress Scale [PSS], p=0.001) and anxiety (Hospital Anxiety and Depression Scale [HADS] anxiety, p=0.002) across all participants. Healthcare professionals demonstrated significant decreases in depression (Patient Health Questionnaire-9, p=0.015), anxiety (HADS anxiety, p<0.001), and stress (PSS, p=0.001). Unexpectedly, weekday sleep quality (Pittsburgh Sleep Quality Index) worsened in the healthcare group (p=0.013). The IT group showed no significant changes, possibly due to the small sample size. Physiological measurements revealed significant differences between groups post-intervention, including melatonin levels (p=0.001) and electrocardiogram values (p=0.031), suggesting occupation-specific responses to VR interventions. Conclusion Despite limitations such as unequal sample sizes, this study provides valuable insights into the potential of VR-based stress management programs. The findings underscore the need for occupation-specific approaches and further research with larger, balanced samples to validate these results and explore long-term effects.

Objective: This study evaluated the effectiveness of a virtual reality (VR) based stress reduction program tailored for healthcare and information technology (IT) professionals during the coronavirus disease-2019 pandemic. Methods: The 2-week program, based on forest healing principles, was designed to alleviate occupational stress and improve sleep quality. Participants (n=54; 46 healthcare, 8 IT professionals) underwent pre- and post-intervention assessments using validated psychological scales and physiological measurements. Results: Results showed significant reductions in stress (Perceived Stress Scale [PSS], p=0.001) and anxiety (Hospital Anxiety and Depression Scale [HADS] anxiety, p=0.002) across all participants. Healthcare professionals demonstrated significant decreases in depression (Patient Health Questionnaire-9, p=0.015), anxiety (HADS anxiety, p<0.001), and stress (PSS, p=0.001). Unexpectedly, weekday sleep quality (Pittsburgh Sleep Quality Index) worsened in the healthcare group (p=0.013). The IT group showed no significant changes, possibly due to the small sample size. Physiological measurements revealed significant differences between groups post-intervention, including melatonin levels (p=0.001) and electrocardiogram values (p=0.031), suggesting occupation-specific responses to VR interventions. Conclusion Despite limitations such as unequal sample sizes, this study provides valuable insights into the potential of VR-based stress management programs. The findings underscore the need for occupation-specific approaches and further research with larger, balanced samples to validate these results and explore long-term effects.

In recent years, artificial intelligence (AI), a collection of core technologies leading the 4th Industrial Revolution, is playing an important role in national innovation. AI is not just a new technology, but an innovative technology that brings about widespread changes in industrial and social structures and is a key driving force that will lead to strengthening the quality of life and national competitiveness of the people. The aviation safety sector also expects AI technology to be used as an error prevention and risk management tool in aircraft design and operation, aircraft production and maintenance, environmental problems, and airport operation. The national strategies of advanced countries for AI include securing professional manpower, securing their own AI technology, establishing an ecosystem and establishing ethics for human-centered AI development. However, most AI-related strategic plans and operational guidelines in the public sectors, including aviation, are focused on technology development and services, so they do not consider essential items such as reliability and ethics when developing and applying AI in the public sector. Therefore, this study aims to present guidelines that should be considered and applied when developing and introducing systems using the latest AI technology in the aviation safety and public sector.

Objective: This study evaluated the effectiveness of a virtual reality (VR) based stress reduction program tailored for healthcare and information technology (IT) professionals during the coronavirus disease-2019 pandemic. Methods: The 2-week program, based on forest healing principles, was designed to alleviate occupational stress and improve sleep quality. Participants (n=54; 46 healthcare, 8 IT professionals) underwent pre- and post-intervention assessments using validated psychological scales and physiological measurements. Results: Results showed significant reductions in stress (Perceived Stress Scale [PSS], p=0.001) and anxiety (Hospital Anxiety and Depression Scale [HADS] anxiety, p=0.002) across all participants. Healthcare professionals demonstrated significant decreases in depression (Patient Health Questionnaire-9, p=0.015), anxiety (HADS anxiety, p<0.001), and stress (PSS, p=0.001). Unexpectedly, weekday sleep quality (Pittsburgh Sleep Quality Index) worsened in the healthcare group (p=0.013). The IT group showed no significant changes, possibly due to the small sample size. Physiological measurements revealed significant differences between groups post-intervention, including melatonin levels (p=0.001) and electrocardiogram values (p=0.031), suggesting occupation-specific responses to VR interventions. Conclusion Despite limitations such as unequal sample sizes, this study provides valuable insights into the potential of VR-based stress management programs. The findings underscore the need for occupation-specific approaches and further research with larger, balanced samples to validate these results and explore long-term effects.

In recent years, artificial intelligence (AI), a collection of core technologies leading the 4th Industrial Revolution, is playing an important role in national innovation. AI is not just a new technology, but an innovative technology that brings about widespread changes in industrial and social structures and is a key driving force that will lead to strengthening the quality of life and national competitiveness of the people. The aviation safety sector also expects AI technology to be used as an error prevention and risk management tool in aircraft design and operation, aircraft production and maintenance, environmental problems, and airport operation. The national strategies of advanced countries for AI include securing professional manpower, securing their own AI technology, establishing an ecosystem and establishing ethics for human-centered AI development. However, most AI-related strategic plans and operational guidelines in the public sectors, including aviation, are focused on technology development and services, so they do not consider essential items such as reliability and ethics when developing and applying AI in the public sector. Therefore, this study aims to present guidelines that should be considered and applied when developing and introducing systems using the latest AI technology in the aviation safety and public sector.

Objective: This study evaluated the effectiveness of a virtual reality (VR) based stress reduction program tailored for healthcare and information technology (IT) professionals during the coronavirus disease-2019 pandemic. Methods: The 2-week program, based on forest healing principles, was designed to alleviate occupational stress and improve sleep quality. Participants (n=54; 46 healthcare, 8 IT professionals) underwent pre- and post-intervention assessments using validated psychological scales and physiological measurements. Results: Results showed significant reductions in stress (Perceived Stress Scale [PSS], p=0.001) and anxiety (Hospital Anxiety and Depression Scale [HADS] anxiety, p=0.002) across all participants. Healthcare professionals demonstrated significant decreases in depression (Patient Health Questionnaire-9, p=0.015), anxiety (HADS anxiety, p<0.001), and stress (PSS, p=0.001). Unexpectedly, weekday sleep quality (Pittsburgh Sleep Quality Index) worsened in the healthcare group (p=0.013). The IT group showed no significant changes, possibly due to the small sample size. Physiological measurements revealed significant differences between groups post-intervention, including melatonin levels (p=0.001) and electrocardiogram values (p=0.031), suggesting occupation-specific responses to VR interventions. Conclusion Despite limitations such as unequal sample sizes, this study provides valuable insights into the potential of VR-based stress management programs. The findings underscore the need for occupation-specific approaches and further research with larger, balanced samples to validate these results and explore long-term effects.

In recent years, artificial intelligence (AI), a collection of core technologies leading the 4th Industrial Revolution, is playing an important role in national innovation. AI is not just a new technology, but an innovative technology that brings about widespread changes in industrial and social structures and is a key driving force that will lead to strengthening the quality of life and national competitiveness of the people. The aviation safety sector also expects AI technology to be used as an error prevention and risk management tool in aircraft design and operation, aircraft production and maintenance, environmental problems, and airport operation. The national strategies of advanced countries for AI include securing professional manpower, securing their own AI technology, establishing an ecosystem and establishing ethics for human-centered AI development. However, most AI-related strategic plans and operational guidelines in the public sectors, including aviation, are focused on technology development and services, so they do not consider essential items such as reliability and ethics when developing and applying AI in the public sector. Therefore, this study aims to present guidelines that should be considered and applied when developing and introducing systems using the latest AI technology in the aviation safety and public sector.

In recent years, artificial intelligence (AI), a collection of core technologies leading the 4th Industrial Revolution, is playing an important role in national innovation. AI is not just a new technology, but an innovative technology that brings about widespread changes in industrial and social structures and is a key driving force that will lead to strengthening the quality of life and national competitiveness of the people. The aviation safety sector also expects AI technology to be used as an error prevention and risk management tool in aircraft design and operation, aircraft production and maintenance, environmental problems, and airport operation. The national strategies of advanced countries for AI include securing professional manpower, securing their own AI technology, establishing an ecosystem and establishing ethics for human-centered AI development. However, most AI-related strategic plans and operational guidelines in the public sectors, including aviation, are focused on technology development and services, so they do not consider essential items such as reliability and ethics when developing and applying AI in the public sector. Therefore, this study aims to present guidelines that should be considered and applied when developing and introducing systems using the latest AI technology in the aviation safety and public sector.

Objective: This study evaluated the effectiveness of a virtual reality (VR) based stress reduction program tailored for healthcare and information technology (IT) professionals during the coronavirus disease-2019 pandemic. Methods: The 2-week program, based on forest healing principles, was designed to alleviate occupational stress and improve sleep quality. Participants (n=54; 46 healthcare, 8 IT professionals) underwent pre- and post-intervention assessments using validated psychological scales and physiological measurements. Results: Results showed significant reductions in stress (Perceived Stress Scale [PSS], p=0.001) and anxiety (Hospital Anxiety and Depression Scale [HADS] anxiety, p=0.002) across all participants. Healthcare professionals demonstrated significant decreases in depression (Patient Health Questionnaire-9, p=0.015), anxiety (HADS anxiety, p<0.001), and stress (PSS, p=0.001). Unexpectedly, weekday sleep quality (Pittsburgh Sleep Quality Index) worsened in the healthcare group (p=0.013). The IT group showed no significant changes, possibly due to the small sample size. Physiological measurements revealed significant differences between groups post-intervention, including melatonin levels (p=0.001) and electrocardiogram values (p=0.031), suggesting occupation-specific responses to VR interventions. Conclusion Despite limitations such as unequal sample sizes, this study provides valuable insights into the potential of VR-based stress management programs. The findings underscore the need for occupation-specific approaches and further research with larger, balanced samples to validate these results and explore long-term effects.