Objectives: ：Among the various risk factors for suicide, geographic factors have different effects on males and females. This study aimed to identify differences between genders in spatiotemporal dependence and spatiotemporal patterns of suicide mortality over the preceding decade. Methods: ：This research analyzed the age-adjusted suicide mortality rate per 100,000 population, spanning from 2012 to 2021, for intentional suicides across each administrative district (229 Si, Gun, Gu) in Korea. Data were sourced from the National Statistical Office of the Korean Statistical Information Service. The Moran’s I in-dex for spatial autocorrelation of the suicide mortality rates was computed. An emerging hot spot analysis was conducted to examine the community-level spatiotemporal distribution patterns, thus providing insight into the re-gional clustering characteristics that reflect the temporal-spatial clusters of suicide mortality rates. Results: ：TIn males, the Moran’s I indices were almost above 0 (p-value<0.05) for most years, indicating sig-nificant spatial autocorrelation. Conversely, no significant regional clustering was observed among females dur-ing the same period. The emerging hot spot analysis, focusing on the temporal trends in the spatial distributionof male suicide mortality rates from 2012 to 2021, identified two distinct time series patterns and a total of 12 hot spot areas: seven new spots and five sporadic spots. Conclusions ：This study is the first to intuitively demonstrate the disparities in spatiotemporal dependencies and patterns of suicide mortality rates in Korea between genders. The findings highlight the necessity for tailoredsuicide prevention strategies that are sensitive to gender differences.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objectives: ：Among the various risk factors for suicide, geographic factors have different effects on males and females. This study aimed to identify differences between genders in spatiotemporal dependence and spatiotemporal patterns of suicide mortality over the preceding decade. Methods: ：This research analyzed the age-adjusted suicide mortality rate per 100,000 population, spanning from 2012 to 2021, for intentional suicides across each administrative district (229 Si, Gun, Gu) in Korea. Data were sourced from the National Statistical Office of the Korean Statistical Information Service. The Moran’s I in-dex for spatial autocorrelation of the suicide mortality rates was computed. An emerging hot spot analysis was conducted to examine the community-level spatiotemporal distribution patterns, thus providing insight into the re-gional clustering characteristics that reflect the temporal-spatial clusters of suicide mortality rates. Results: ：TIn males, the Moran’s I indices were almost above 0 (p-value<0.05) for most years, indicating sig-nificant spatial autocorrelation. Conversely, no significant regional clustering was observed among females dur-ing the same period. The emerging hot spot analysis, focusing on the temporal trends in the spatial distributionof male suicide mortality rates from 2012 to 2021, identified two distinct time series patterns and a total of 12 hot spot areas: seven new spots and five sporadic spots. Conclusions ：This study is the first to intuitively demonstrate the disparities in spatiotemporal dependencies and patterns of suicide mortality rates in Korea between genders. The findings highlight the necessity for tailoredsuicide prevention strategies that are sensitive to gender differences.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objectives: ：Among the various risk factors for suicide, geographic factors have different effects on males and females. This study aimed to identify differences between genders in spatiotemporal dependence and spatiotemporal patterns of suicide mortality over the preceding decade. Methods: ：This research analyzed the age-adjusted suicide mortality rate per 100,000 population, spanning from 2012 to 2021, for intentional suicides across each administrative district (229 Si, Gun, Gu) in Korea. Data were sourced from the National Statistical Office of the Korean Statistical Information Service. The Moran’s I in-dex for spatial autocorrelation of the suicide mortality rates was computed. An emerging hot spot analysis was conducted to examine the community-level spatiotemporal distribution patterns, thus providing insight into the re-gional clustering characteristics that reflect the temporal-spatial clusters of suicide mortality rates. Results: ：TIn males, the Moran’s I indices were almost above 0 (p-value<0.05) for most years, indicating sig-nificant spatial autocorrelation. Conversely, no significant regional clustering was observed among females dur-ing the same period. The emerging hot spot analysis, focusing on the temporal trends in the spatial distributionof male suicide mortality rates from 2012 to 2021, identified two distinct time series patterns and a total of 12 hot spot areas: seven new spots and five sporadic spots. Conclusions ：This study is the first to intuitively demonstrate the disparities in spatiotemporal dependencies and patterns of suicide mortality rates in Korea between genders. The findings highlight the necessity for tailoredsuicide prevention strategies that are sensitive to gender differences.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objectives: ：Among the various risk factors for suicide, geographic factors have different effects on males and females. This study aimed to identify differences between genders in spatiotemporal dependence and spatiotemporal patterns of suicide mortality over the preceding decade. Methods: ：This research analyzed the age-adjusted suicide mortality rate per 100,000 population, spanning from 2012 to 2021, for intentional suicides across each administrative district (229 Si, Gun, Gu) in Korea. Data were sourced from the National Statistical Office of the Korean Statistical Information Service. The Moran’s I in-dex for spatial autocorrelation of the suicide mortality rates was computed. An emerging hot spot analysis was conducted to examine the community-level spatiotemporal distribution patterns, thus providing insight into the re-gional clustering characteristics that reflect the temporal-spatial clusters of suicide mortality rates. Results: ：TIn males, the Moran’s I indices were almost above 0 (p-value<0.05) for most years, indicating sig-nificant spatial autocorrelation. Conversely, no significant regional clustering was observed among females dur-ing the same period. The emerging hot spot analysis, focusing on the temporal trends in the spatial distributionof male suicide mortality rates from 2012 to 2021, identified two distinct time series patterns and a total of 12 hot spot areas: seven new spots and five sporadic spots. Conclusions ：This study is the first to intuitively demonstrate the disparities in spatiotemporal dependencies and patterns of suicide mortality rates in Korea between genders. The findings highlight the necessity for tailoredsuicide prevention strategies that are sensitive to gender differences.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objectives: ：Among the various risk factors for suicide, geographic factors have different effects on males and females. This study aimed to identify differences between genders in spatiotemporal dependence and spatiotemporal patterns of suicide mortality over the preceding decade. Methods: ：This research analyzed the age-adjusted suicide mortality rate per 100,000 population, spanning from 2012 to 2021, for intentional suicides across each administrative district (229 Si, Gun, Gu) in Korea. Data were sourced from the National Statistical Office of the Korean Statistical Information Service. The Moran’s I in-dex for spatial autocorrelation of the suicide mortality rates was computed. An emerging hot spot analysis was conducted to examine the community-level spatiotemporal distribution patterns, thus providing insight into the re-gional clustering characteristics that reflect the temporal-spatial clusters of suicide mortality rates. Results: ：TIn males, the Moran’s I indices were almost above 0 (p-value<0.05) for most years, indicating sig-nificant spatial autocorrelation. Conversely, no significant regional clustering was observed among females dur-ing the same period. The emerging hot spot analysis, focusing on the temporal trends in the spatial distributionof male suicide mortality rates from 2012 to 2021, identified two distinct time series patterns and a total of 12 hot spot areas: seven new spots and five sporadic spots. Conclusions ：This study is the first to intuitively demonstrate the disparities in spatiotemporal dependencies and patterns of suicide mortality rates in Korea between genders. The findings highlight the necessity for tailoredsuicide prevention strategies that are sensitive to gender differences.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.