Objectives: Large language models (LLMs) demonstrate remarkable potential in healthcare communication. However, whether they can process complex, high-volume medical information, such as stroke-related content, remains insufficiently validated. This study aimed to evaluate the natural language processing capabilities of LLMs in handling such content and to develop an evaluation instrument. Methods: A survey compared educational materials generated by two LLMs (ChatGPT 4.0 and Claude 3) with neurologist-authored content on stroke. The materials were based on two clinical scenarios representing distinct stroke etiologies: cardioembolism and large-artery atherosclerosis. They were evaluated in terms of accuracy, legality, ethics, comprehensiveness, and information delivery. Scores for comprehensiveness and information delivery were compared according to participants’ agreement with the use of LLMs in healthcare. Results: ChatGPT received the highest scores across all domains, except for legality in Scenario 2. In Scenario 1, the ranking for accuracy and summarization of clinical information was, from highest to lowest, ChatGPT, Claude, and the neurologist (η2 = 0.140, p < 0.001; η2 = 0.175, p < 0.001). The same hierarchy was observed in Scenario 2 for accuracy (η2 = 0.077, p < 0.001) and summarization (η2 = 0.194, p < 0.001). Participants who agreed with the use of LLMs in healthcare assigned higher scores for the comprehensiveness (Scenario 1, p = 0.005; Scenario 2, p = 0.007) and information delivery (Scenario 1, p = 0.003; Scenario 2, p = 0.026) of ChatGPT-generated materials than participants who did not agree. Conclusions LLMs demonstrated adequate capability to convey complex content, such as stroke-related information, in an accessible and understandable manner for non-experts.

Objective: This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required. Methods: An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed. Results: PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator. Conclusion PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.

Objective: This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required. Methods: An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed. Results: PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator. Conclusion PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.

Objective: This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required. Methods: An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed. Results: PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator. Conclusion PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.

Objective: This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required. Methods: An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed. Results: PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator. Conclusion PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.

Objective: This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required. Methods: An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed. Results: PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator. Conclusion PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.

Background: We aimed to explore whether the dysfunctional pandemic grief of nursing professionals who experienced a patient’s death may be related with their suicidal ideation and examine whether their interpersonal problems and dysfunctional self-focus mediate this association. Methods: An anonymous online survey was conducted on November 16–18, 2023 among nurses in a tertiary hospital who witnessed people’s death. Their psychological states were assessed using the Pandemic Grief Scale (PGS) for healthcare workers, Dysfunctional Selffocus Attributes Scale (DSAS), Interpersonal Needs Questionnaire (INQ), and Depressive Symptom Inventory-Suicidality Subscale (DSI-SS). Linear regression analysis was conducted to explore the expecting variables for the DSI-SS. Mediation analysis was performed to examine the mediating effects of self-focus and interpersonal problems between grief reaction and suicidal ideation. Results: The PGS (β = 0.18, P = 0.005), INQ-Perceived Burdensomeness (INQ-PB; β = 0.51, P < 0.001), and DSAS-Negatively Biased Focus (DSAS-NBF; β = 0.17, P = 0.021) were significantly associated with the DSI-SS. Mediation analysis using these variables showed that the PGS directly influenced the DSI-SS, and the INQ-PB and DSAS-NBF partially mediated the influence of the PGS on DSI-SS. Conclusion Dysfunctional grief experienced by nurses following the loss of patients during the pandemic exacerbated suicidal ideation by fostering a greater focus on negative outcomes and heightened feelings of being a burden. These findings underscore the need for targeted interventions to address these specific cognitive and emotional vulnerabilities to mitigate the risk of suicidal ideation.

Objective: This study aims to explore the association between work-related stress of healthcare workers in response to the coronavirus disease-2019 (COVID-19) pandemic and their depressive symptoms. Additionally, it focuses on the impact of insomnia symptoms, interpersonal factors, and resilience on depressive symptoms. Methods: The results of an anonymous survey of 329 healthcare workers were analyzed, including the Stress and Anxiety to Viral Epidemics-3 items, Insomnia Severity Index, Interpersonal Needs Questionnaire, Connor–Davidson Resilience Scale-2 items, and Patient Health Questionnaire-9 items. Mediation analysis assessed whether insomnia symptoms, resilience, and interpersonal factors mediate the association between work-related stress and depressive symptoms. Results: Work-related stress directly influenced depressive symptoms (standardized estimator=0.11, p=0.010, 95% confidence interval [CI] 0.03–0.19). The association between the former and latter was positively mediated by insomnia symptoms (standardized estimator=0.10, p<0.001, 95% CI 0.05–0.14), thwarted belongingness (standardized estimator=0.04, p=0.006, 95% CI 0.01–0.07), and perceived burdensomeness (standardized estimator=0.05, p=0.002, 95% CI 0.02–0.08) and was negatively mediated by resilience (standardized estimator=0.02, p=0.041, 95% CI 0.0001–0.04). Conclusion This study highlights the connection between heightened work-related stress experienced by healthcare workers amid the COVID-19 pandemic and the subsequent development of depressive symptoms mediated by insomnia, interpersonal factors, and resilience. Interventions that focus on building resilience could be pivotal in mitigating the detrimental mental health consequences of workplace stress among healthcare workers in a viral epidemic.

Objective: This study aims to explore the association between work-related stress of healthcare workers in response to the coronavirus disease-2019 (COVID-19) pandemic and their depressive symptoms. Additionally, it focuses on the impact of insomnia symptoms, interpersonal factors, and resilience on depressive symptoms. Methods: The results of an anonymous survey of 329 healthcare workers were analyzed, including the Stress and Anxiety to Viral Epidemics-3 items, Insomnia Severity Index, Interpersonal Needs Questionnaire, Connor–Davidson Resilience Scale-2 items, and Patient Health Questionnaire-9 items. Mediation analysis assessed whether insomnia symptoms, resilience, and interpersonal factors mediate the association between work-related stress and depressive symptoms. Results: Work-related stress directly influenced depressive symptoms (standardized estimator=0.11, p=0.010, 95% confidence interval [CI] 0.03–0.19). The association between the former and latter was positively mediated by insomnia symptoms (standardized estimator=0.10, p<0.001, 95% CI 0.05–0.14), thwarted belongingness (standardized estimator=0.04, p=0.006, 95% CI 0.01–0.07), and perceived burdensomeness (standardized estimator=0.05, p=0.002, 95% CI 0.02–0.08) and was negatively mediated by resilience (standardized estimator=0.02, p=0.041, 95% CI 0.0001–0.04). Conclusion This study highlights the connection between heightened work-related stress experienced by healthcare workers amid the COVID-19 pandemic and the subsequent development of depressive symptoms mediated by insomnia, interpersonal factors, and resilience. Interventions that focus on building resilience could be pivotal in mitigating the detrimental mental health consequences of workplace stress among healthcare workers in a viral epidemic.

Objective: This study aims to explore the association between work-related stress of healthcare workers in response to the coronavirus disease-2019 (COVID-19) pandemic and their depressive symptoms. Additionally, it focuses on the impact of insomnia symptoms, interpersonal factors, and resilience on depressive symptoms. Methods: The results of an anonymous survey of 329 healthcare workers were analyzed, including the Stress and Anxiety to Viral Epidemics-3 items, Insomnia Severity Index, Interpersonal Needs Questionnaire, Connor–Davidson Resilience Scale-2 items, and Patient Health Questionnaire-9 items. Mediation analysis assessed whether insomnia symptoms, resilience, and interpersonal factors mediate the association between work-related stress and depressive symptoms. Results: Work-related stress directly influenced depressive symptoms (standardized estimator=0.11, p=0.010, 95% confidence interval [CI] 0.03–0.19). The association between the former and latter was positively mediated by insomnia symptoms (standardized estimator=0.10, p<0.001, 95% CI 0.05–0.14), thwarted belongingness (standardized estimator=0.04, p=0.006, 95% CI 0.01–0.07), and perceived burdensomeness (standardized estimator=0.05, p=0.002, 95% CI 0.02–0.08) and was negatively mediated by resilience (standardized estimator=0.02, p=0.041, 95% CI 0.0001–0.04). Conclusion This study highlights the connection between heightened work-related stress experienced by healthcare workers amid the COVID-19 pandemic and the subsequent development of depressive symptoms mediated by insomnia, interpersonal factors, and resilience. Interventions that focus on building resilience could be pivotal in mitigating the detrimental mental health consequences of workplace stress among healthcare workers in a viral epidemic.