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.

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.

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.

Background: As South Korea experiences rapid population aging, preventing early retirement has become a critical concern. Ill health contributes to early retirement, and educational level moderates this relationship. Although well-studied in Europe, it remains less explored in Northeast Asia, where labor markets and educational attainment differ significantly. This study investigated the moderating role of education in the relationship between chronic diseases and labor force non-participation in South Korea, considering disease severity, type, and employment status. Methods: Using data from the Korean Longitudinal Study of Elderly Employment, this study analyzed 5,758 individuals born between 1964 and 1976. Chronic diseases were categorized by severity and type. Labor force participation and retirement from lifetime primary occupation were measured. Education was categorized as low (≤high school) or high (≥college). Logistic regression analyses were conducted, adjusting for sociodemographic and lifestyle covariates, with stratification by education level, employment status, severity, and disease characteristics. Results: Chronic diseases were significantly associated with labor market non-participation and early retirement, with stronger associations among individuals with lower educational levels. Educational disparities were particularly evident for severe and psychiatric disorders. Among wage workers, those with lower education were more likely to exit the labor market due to chronic diseases, whereas those with higher education generally maintained employment, except in cases of musculoskeletal diseases. Low-educated individuals with chronic diseases were also more likely to retire early from their lifetime primary occupations. Conclusions Education moderates the relationship between chronic diseases and labor non-participation, with greater disparities in severe or psychiatric illnesses and among wage workers. Low-educated workers are more vulnerable to early retirement due to ill health, highlighting the need for targeted policy interventions to support this group and prevent early exit from the workforce.

This retrospective study aimed to implement cognitive behavioral therapy for insomnia (CBTi) within the Metaverse, exploring its feasibility as an alternative to traditional face-to-face CBTi sessions. Methods: A total of 49 individuals (41 females) participated in the study, predominantly young adults, with 42.9% in their twenties and 42.9% in their thirties. The Metaverse-based program consisted of a single-session designed to educate participants about healthy sleep habits in line with CBTi principles and guide behaviors conducive to better sleep. The participants reported on their sleep patterns at two intervals: the day following the intervention and again 2 weeks later. Results: The findings revealed that after participating in the Metaverse-based program, there was a reported increase in sleep satisfaction (74.5%) and a reduction in sleep latency (64.4%). Comparison of follow-up results to immediate post-program outcomes revealed no significant differences between the two time points in sleep onset latency (t (34)=1.71, p=0.096), number of wakings (t (34)=0.53, p=0.597), or feeling refreshed upon waking (t (34)=1.89, p=0.067). However, there were significant differences between the two time points in sleep satisfaction (t (34)=2.77, p=0.009). Conclusions: Despite certain limitations, the study highlights the promising potential of the Metaverse as an innovative platform for delivering CBTi, indicating its potential effectiveness in enhancing sleep quality among individuals with sleep disturbances.

This retrospective study aimed to implement cognitive behavioral therapy for insomnia (CBTi) within the Metaverse, exploring its feasibility as an alternative to traditional face-to-face CBTi sessions. Methods: A total of 49 individuals (41 females) participated in the study, predominantly young adults, with 42.9% in their twenties and 42.9% in their thirties. The Metaverse-based program consisted of a single-session designed to educate participants about healthy sleep habits in line with CBTi principles and guide behaviors conducive to better sleep. The participants reported on their sleep patterns at two intervals: the day following the intervention and again 2 weeks later. Results: The findings revealed that after participating in the Metaverse-based program, there was a reported increase in sleep satisfaction (74.5%) and a reduction in sleep latency (64.4%). Comparison of follow-up results to immediate post-program outcomes revealed no significant differences between the two time points in sleep onset latency (t (34)=1.71, p=0.096), number of wakings (t (34)=0.53, p=0.597), or feeling refreshed upon waking (t (34)=1.89, p=0.067). However, there were significant differences between the two time points in sleep satisfaction (t (34)=2.77, p=0.009). Conclusions: Despite certain limitations, the study highlights the promising potential of the Metaverse as an innovative platform for delivering CBTi, indicating its potential effectiveness in enhancing sleep quality among individuals with sleep disturbances.

This retrospective study aimed to implement cognitive behavioral therapy for insomnia (CBTi) within the Metaverse, exploring its feasibility as an alternative to traditional face-to-face CBTi sessions. Methods: A total of 49 individuals (41 females) participated in the study, predominantly young adults, with 42.9% in their twenties and 42.9% in their thirties. The Metaverse-based program consisted of a single-session designed to educate participants about healthy sleep habits in line with CBTi principles and guide behaviors conducive to better sleep. The participants reported on their sleep patterns at two intervals: the day following the intervention and again 2 weeks later. Results: The findings revealed that after participating in the Metaverse-based program, there was a reported increase in sleep satisfaction (74.5%) and a reduction in sleep latency (64.4%). Comparison of follow-up results to immediate post-program outcomes revealed no significant differences between the two time points in sleep onset latency (t (34)=1.71, p=0.096), number of wakings (t (34)=0.53, p=0.597), or feeling refreshed upon waking (t (34)=1.89, p=0.067). However, there were significant differences between the two time points in sleep satisfaction (t (34)=2.77, p=0.009). Conclusions: Despite certain limitations, the study highlights the promising potential of the Metaverse as an innovative platform for delivering CBTi, indicating its potential effectiveness in enhancing sleep quality among individuals with sleep disturbances.