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: 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.

Objective: This study explores whether cancer patients’ dysfunctional self-focus is a significant contributor to their fear of progression. In addition, we investigated whether their psychiatric symptoms such as depression, anxiety, and dysfunctional beliefs about sleep may mediate the relationship between these factors. Methods: We conducted a retrospective medical records review of 196 cancer patients who visited the Stress Management Clinic for the first time from March to September 2022. Their demographic information and responses to rating scales such as the Fear of Progression Questionnaire-Short Form (FoP-Q-SF), Dysfunctional Self-focus Attribution Scale (DSAS), Patient Health Questionnaire-9 Items (PHQ-9), State subcategory of the State and Trait of Anxiety Inventory (STAI-S), Insomnia Severity Index (ISI), Cancer-related Dysfunctional Beliefs about Sleep scale (C-DBS), and numeric rating scales of pain and fatigue were collected. Results: A high FoP-Q-SF score was significantly correlated with high PHQ-9 (r=0.60), STAI-S (r=0.38), ISI (r=0.34), C-DBS (r=0.47), pain (r=0.24), fatigue (r=0.37), and DSAS (r=0.58, all p<0.001). A linear regression analysis showed that the FoP-Q-SF score was significantly predicted by younger age (β=-0.13, p=0.011), PHQ-9 (β=0.36, p<0.001), STAI-S (β=0.18, p=0.001), C-DBS (β=0.22, p<0.001), and DSAS (β=0.25, p<0.001). A mediation analysis showed that dysfunctional self-focus directly influenced patients’ fear of progression. In addition, cancer patients’ depression, anxiety, and cancer-related dysfunctional beliefs about sleep mediated this relationship. Conclusion We observed that dysfunctional self-focus may influence cancer patients’ fear of progression, mediated by depression, anxiety, and cancer-related dysfunctional beliefs about sleep.

Objective: Coronavirus disease-2019 (COVID-19) had a significant impact on the mental health of healthcare workers. Related assessments should be included in plans for future pandemics. We investigated the connections between grief, viral anxiety, depression, and preoccupation in the context of COVID-19 in healthcare workers, to determine which factors will need to be incorporated. Methods: A total of 267 healthcare workers who had experienced the death of at least one patient during the COVID-19 pandemic were asked to respond to questionnaires assessing grief, viral anxiety, depression, loneliness, and preoccupation with COVID-19, based on their emotional state during the 2 weeks immediately after the death. Multivariate linear regression, causal mediation analysis and structural equation modeling were used to examine the psychological processes underlying grief. Results: Linear regression showed that viral anxiety (β=0.287, 95% confidence interval [CI]: 0.235–0.338, p<0.001) and depression (β= 0.157, 95% CI: 0.073–0.241, p<0.001) had independent associations with preoccupation with COVID-19. Causal mediation analysis revealed that both viral anxiety (proportion mediated: 0.51, 95% CI: 0.37–0.66, p<0.001) and depression (proportion mediated: 0.77, 95% CI: 0.50–1.08, p<0.001) were mediators between grief and preoccupation with COVID-19. In a structural equation model, viral anxiety and depression mediated most of the effects of grief on preoccupation with COVID-19, and loneliness was a mediator between grief and depression. Conclusion Contingency plans for the next pandemic are being formulated. Effective measures to protect the mental health of healthcare workers should be included, and such measures should consist of assessments for grief, viral anxiety, depression, and loneliness.

Objective: This study investigated whether the discrepancy between desired time in bed and desired total sleep time (DBST) index could be a meaningful indicator for assessing insomnia severity in a clinical sample of patients with insomnia. Furthermore, we sought to identify the mediators of the association between DBST and insomnia severity in individuals with insomnia. Methods: We collected the medical records of 127 patients with insomnia. Each participant’s DBST index was calculated using sleep indices, including time and duration variables. Psychological symptoms were investigated using the Insomnia Severity Index (ISI), Patients Health Questionnaire-9 items (PHQ-9), Generalized Anxiety Disorder-7, Dysfunctional Beliefs and Attitudes about Sleep-16 items (DBAS-16), and Epworth Sleepiness Scale. Results: The DBST index was significantly correlated with the ISI (r=0.20, p<0.05), desired total sleep time (r=-0.52, p<0.001), and desired time in bed (r=0.32, p<0.01). Linear regression analysis revealed that insomnia severity was associated with age (β=-0.18, p=0.018), DBST (β=0.23, p=0.003), PHQ-9 (β=0.23, p=0.031), and DBAS-16 (β=0.42, p<0.001). The DBST directly influenced insomnia severity, although indirect effects of mediators were not significant. Conclusion The DBST index directly influenced insomnia severity regardless of the mediating effects of psychological factors among a clinical sample of patients with insomnia. This finding implies that the DBST index can be a simple measure of insomnia severity, even among patients with insomnia.

Background: Lung cancer is associated with significant psychological distress, including fear of progression (FoP). Because insomnia and depression are highly prevalent and associated with FoP, we examined the association between FoP, insomnia, and depression in cancer patients. Furthermore, we tested the mediation effect of cancer-related dysfunctional beliefs about sleep (C-DBS) on this association. Methods: We analyzed data collected from patients with surgically resected non-small cell lung cancer from a single-center randomized controlled study investigating digital healthcare applications. Baseline demographic and clinical variables were collected. In addition, selfreported questionnaires including the Fear of Progression Questionnaire-Short Form, Patients Health Questionnaire-9 items (PHQ-9), Insomnia Severity Index, and C-DBS were administered. Results: Among the 320 enrolled patients with lung cancer, a regression model showed that FoP was predicted by age (β = −0.13, P = 0.007), PHQ-9 (β = 0.35, P < 0.001), and C-DBS (β = 0.28, P < 0.001). Insomnia did not directly influence FoP, but C-DBS mediated the association. Depression directly influenced FoP, but C-DBS did not mediate this association. Conclusion Among patients with surgically resected lung cancer, C-DBS mediated the effects of severity of insomnia on FoP. Depression directly influenced FoP, but C-DBS did not influence this association. To reduce FoP among patients with lung cancer, C-DBS should be addressed in the cognitive behavioral therapy module.