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.

Objective: This study aimed to investigate how shift-working nursing professionals perceive the current lights-off time in wards as early, appropriate, or late and how their perceptions can be influenced when considering people’s usual bedtimes. Methods: An online survey was conducted comprising queries about the current lights-off time in wards and respondents’ opinions, self-rated psychological status, and perceptions of the current lights-off time considering others’ usual bedtimes. Psychological status was evaluated using the Insomnia Severity Index, the Patient Health Questionnaire-9, the Dysfunctional Beliefs and Attitudes about Sleep-16, and the Discrepancy between Desired Time in Bed and Desired Total Sleep Time (DBST) Index, along with the expected DBST Index of others. Results: Of 159 nursing professionals, 88.7% regarded the current lights-off time of 9:46±0:29 PM as appropriate. However, when considering others’ usual bedtimes, the proportion perceiving the lights-off time as too early rose from 6.9% to 28.3%. Participants recommended delaying the lights-off time to 10:06±0:42 PM for patients’ sleep and 10.22±0:46 PM for nursing care activities. Nursing professionals’ insomnia severity was significantly higher among who responded that current light off time is too early after considering usual bedtime of other people. Conclusion This study underscores the need to reassess lights-off times in wards given individuals’ typical bedtimes. The findings emphasize the need to address nursing professionals’ perspectives and insomnia severity when optimizing lights-off schedules in healthcare settings.

Objective: This study aimed to investigate how shift-working nursing professionals perceive the current lights-off time in wards as early, appropriate, or late and how their perceptions can be influenced when considering people’s usual bedtimes. Methods: An online survey was conducted comprising queries about the current lights-off time in wards and respondents’ opinions, self-rated psychological status, and perceptions of the current lights-off time considering others’ usual bedtimes. Psychological status was evaluated using the Insomnia Severity Index, the Patient Health Questionnaire-9, the Dysfunctional Beliefs and Attitudes about Sleep-16, and the Discrepancy between Desired Time in Bed and Desired Total Sleep Time (DBST) Index, along with the expected DBST Index of others. Results: Of 159 nursing professionals, 88.7% regarded the current lights-off time of 9:46±0:29 PM as appropriate. However, when considering others’ usual bedtimes, the proportion perceiving the lights-off time as too early rose from 6.9% to 28.3%. Participants recommended delaying the lights-off time to 10:06±0:42 PM for patients’ sleep and 10.22±0:46 PM for nursing care activities. Nursing professionals’ insomnia severity was significantly higher among who responded that current light off time is too early after considering usual bedtime of other people. Conclusion This study underscores the need to reassess lights-off times in wards given individuals’ typical bedtimes. The findings emphasize the need to address nursing professionals’ perspectives and insomnia severity when optimizing lights-off schedules in healthcare settings.

Objective: This study aimed to investigate how shift-working nursing professionals perceive the current lights-off time in wards as early, appropriate, or late and how their perceptions can be influenced when considering people’s usual bedtimes. Methods: An online survey was conducted comprising queries about the current lights-off time in wards and respondents’ opinions, self-rated psychological status, and perceptions of the current lights-off time considering others’ usual bedtimes. Psychological status was evaluated using the Insomnia Severity Index, the Patient Health Questionnaire-9, the Dysfunctional Beliefs and Attitudes about Sleep-16, and the Discrepancy between Desired Time in Bed and Desired Total Sleep Time (DBST) Index, along with the expected DBST Index of others. Results: Of 159 nursing professionals, 88.7% regarded the current lights-off time of 9:46±0:29 PM as appropriate. However, when considering others’ usual bedtimes, the proportion perceiving the lights-off time as too early rose from 6.9% to 28.3%. Participants recommended delaying the lights-off time to 10:06±0:42 PM for patients’ sleep and 10.22±0:46 PM for nursing care activities. Nursing professionals’ insomnia severity was significantly higher among who responded that current light off time is too early after considering usual bedtime of other people. Conclusion This study underscores the need to reassess lights-off times in wards given individuals’ typical bedtimes. The findings emphasize the need to address nursing professionals’ perspectives and insomnia severity when optimizing lights-off schedules in healthcare settings.

Objective: This study aimed to investigate how shift-working nursing professionals perceive the current lights-off time in wards as early, appropriate, or late and how their perceptions can be influenced when considering people’s usual bedtimes. Methods: An online survey was conducted comprising queries about the current lights-off time in wards and respondents’ opinions, self-rated psychological status, and perceptions of the current lights-off time considering others’ usual bedtimes. Psychological status was evaluated using the Insomnia Severity Index, the Patient Health Questionnaire-9, the Dysfunctional Beliefs and Attitudes about Sleep-16, and the Discrepancy between Desired Time in Bed and Desired Total Sleep Time (DBST) Index, along with the expected DBST Index of others. Results: Of 159 nursing professionals, 88.7% regarded the current lights-off time of 9:46±0:29 PM as appropriate. However, when considering others’ usual bedtimes, the proportion perceiving the lights-off time as too early rose from 6.9% to 28.3%. Participants recommended delaying the lights-off time to 10:06±0:42 PM for patients’ sleep and 10.22±0:46 PM for nursing care activities. Nursing professionals’ insomnia severity was significantly higher among who responded that current light off time is too early after considering usual bedtime of other people. Conclusion This study underscores the need to reassess lights-off times in wards given individuals’ typical bedtimes. The findings emphasize the need to address nursing professionals’ perspectives and insomnia severity when optimizing lights-off schedules in healthcare settings.

Objective: The aim of this study was to explore the psychometric properties of the Insomnia Severity Index (ISI) based on modern test theory, such as item response theory (IRT) and Rasch analysis, with shortened versions of the ISI among the general population. Methods: We conducted two studies to evaluate the reliability and validity of the shortened versions of the ISI in a Korean population. In Study I, conducted via online survey, we performed an exploratory factor analysis (n=400). In Study II, confirmatory factor analysis (CFA) was conducted (n=400). IRT and Rasch analysis were performed on all samples. Participants symptoms were rated using the ISI, Dysfunctional Beliefs and Attitudes about Sleep–16 items, Dysfunctional Beliefs about Sleep–2 items, Patient Health Questionnaire–9 items, and discrepancy between desired time in bed and desired total sleep time. Results: CFA showed a good fit for the 2-factor model of the ISI (comparative fit index=0.994, Tucker–Lewis index=0.990, root-meansquare-error of approximation=0.039, and standardized root-mean-square residual=0.046). The 3-item versions also showed a good fit for the model. All scales showed good internal consistency reliability. The scale information curve of the 2-item scale was similar to that of the full-scale ISI. The Rasch analysis outputs suggested a good model fit. Conclusion The shortened 2-factor ISI is a reliable and valid model for assessing the severity of insomnia in the Korean population. The results are needed to be explored further among the clinical sample of insomnia.