Objectives: Bedtime procrastination (BP) is defined as the behavior of voluntarily postponing bedtime without having external reasons for doing so. According to previous studies, people with reduced use of active emotion regulation strategies may use BP to cope with negative emotions. However, research about the relationship among active emotional regulation strategies, BP, and insomnia is lacking. This study aimed to investigate the mediating effect of BP between active emotional regulation strategies and insomnia severity. Methods: In total, 597 adults (female, 81.9%; mean age, 23.18±2.80 years) completed the Emotional Regulation Strategies Checklist, Insomnia Severity Index, and Bedtime Procrastination Scale. Results: There was a significant association between active emotional regulation strategies and BP (r=-0.152, p<0.01), between BP and insomnia severity (r=0.259, p<0.01), and between active emotional regulation strategies and insomnia severity (r=-0.128, p<0.01). BP significantly mediated the relationship between active emotional regulation strategies and insomnia severity (B=-0.024; 95% confidence interval [CI], -0.04 to -0.01). Conclusions BP may be considered in the relationship between active emotional regulation strategies and insomnia severity. Understanding the mediating role of BP may help prevent insomnia.

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.

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.

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.

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.

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.

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.