Objective: We investigated the sleep parameters and clinical factors related to short sleep onset latency (SL) in cancer patients. Methods: We retrospectively reviewed the medical records of 235 cancer patients. Patient Health Questionnaire-9, State and Trait Anxiety Inventory (State subcategory), Insomnia Severity Index (ISI), Cancer-related Dysfunctional Beliefs about Sleep, and Fear of Progression scale scores and sleep related parameters including sleeping pill ingestion time, bedtime, sleep onset time, and wake-up time were collected. We also calculated the duration from sleeping pill ingestion to bedtime, sleep onset time, and wake-up time; duration from wake-up time to bedtime and sleep onset time; and time spent in bed over a 24 hours period. Results: Among patients not taking sleeping pills (n = 145), early wake-up time (adjusted odds ratio [OR]: 0.39, 95% confidence interval [CI] 0.19−0.78), early sleep onset time (OR: 0.50, 95% CI 0.27−0.93), and low ISI score (OR: 0.82, 95% CI 0.71−0.93) were identified as expecting variables for SL ≤ 30 minutes. Longer duration from wake-up time to bedtime (OR: 2.49, 95% CI 1.48−4.18) predicted SL ≤ 30 minutes. Among those taking sleeping pills (n = 90), early sleep onset time (OR: 0.54, 95% CI 0.39−0.76) and short duration from pill ingestion to sleep onset time (OR: 0.05, 95% CI 0.02−0.16) predicted SL ≤ 30 minutes. Conclusion Cancer patients who fell asleep quickly spent less time in bed during the day. Thus, before cancer patients with insomnia are prescribed sleeping pills, their sleep parameters should be examined to improve their SL.

Nonalcoholic fatty liver disease (NAFLD) is one of the causes of fatty liver, occurring when fat is accumulated in the liver without alcohol consumption. NAFLD is the most common liver disorder in advanced countries. NAFLD is a spectrum of pathology involving hepatic steatosis with/without inflammation and nonalcoholic steatohepatitis with accumulation of hepatocyte damage and hepatic fibrosis. Recent studies have revealed that NAFLD results in the progression of cryptogenic cirrhosis that leads to hepatocarcinoma and cardiovascular diseases such as heart failure. The main causes of NAFLD have not been revealed yet, metabolic syndromes including obesity and insulin resistance are widely accepted for the critical risk factors for the pathogenesis of NAFLD. Nuclear receptors (NRs) are transcriptional factors that sense environmental or hormonal signals and regulate expression of genes, involved in cellular growth, development, and metabolism. Several NRs have been reported to regulate genes involved in energy and xenobiotic metabolism and inflammation. Among various NRs, farnesoid X receptor (FXR) is abundantly expressed in the liver and a key regulator to control various metabolic processes in the liver. Recent studies have shown that NAFLD is associated with inappropriate function of FXR. The impact of FXR transcriptional activity in NAFLD is likely to be potential therapeutic strategy, but still requires to elucidate underlying potent therapeutic mechanisms of FXR for the treatment of NAFLD. This article will focus the physiological roles of FXR and establish the correlation between FXR transcriptional activity and the pathogenesis of NAFLD.
Alcohol Drinking ; Bile Acids and Salts ; Bile* ; Cardiovascular Diseases ; Fatty Liver ; Fibrosis ; Heart Failure ; Hepatocytes ; Inflammation ; Insulin Resistance ; Liver ; Metabolism ; Non-alcoholic Fatty Liver Disease* ; Obesity ; Pathology ; Receptors, Cytoplasmic and Nuclear ; Risk Factors

Purpose: Cancer-related fatigue is a common and distressing symptom that occurs during cancer treatment. This study aimed to find factors that are related to cancer-related fatigue, and its effect on patients’ quality of life. Materials and Methods: This study included 159 patients who completed questionnaires and interviews during their initial examination at the sleep clinic for cancer patients, Asan Medical Center, between December 2018 and January 2020. Their medical reports were reviewed retrospectively. Questionnaire data about depression, anxiety, insomnia, fear of disease progression, and dysfunctional beliefs about sleep, pain, and quality of life, were reviewed. Additionally, patient sleep structure data were analyzed. Results: Factors such as depression (p < 0.001), anxiety (p < 0.001), fear of cancer progression (p < 0.001), fatigue (p=0.027), and time in bed during 24 hours (p=0.037) were significant expecting variables for low quality of life from logistic regression analysis. In pathway analysis, depression (p < 0.001), not cancer-related fatigue (p=0.537), act as a direct risk factor on quality of life. And also, depression was an overall risk factor for insomnia, fatigue, and daily activity of cancer patients. Conclusion Cancer-related fatigue did not show significant effect on patient’s quality of life in this study. However, the result of pathway analysis highlights the importance of assessing depression in the process of cancer treatment and providing appropriate interventions.

Purpose: Cancer-related fatigue is a common and distressing symptom that occurs during cancer treatment. This study aimed to find factors that are related to cancer-related fatigue, and its effect on patients’ quality of life. Materials and Methods: This study included 159 patients who completed questionnaires and interviews during their initial examination at the sleep clinic for cancer patients, Asan Medical Center, between December 2018 and January 2020. Their medical reports were reviewed retrospectively. Questionnaire data about depression, anxiety, insomnia, fear of disease progression, and dysfunctional beliefs about sleep, pain, and quality of life, were reviewed. Additionally, patient sleep structure data were analyzed. Results: Factors such as depression (p < 0.001), anxiety (p < 0.001), fear of cancer progression (p < 0.001), fatigue (p=0.027), and time in bed during 24 hours (p=0.037) were significant expecting variables for low quality of life from logistic regression analysis. In pathway analysis, depression (p < 0.001), not cancer-related fatigue (p=0.537), act as a direct risk factor on quality of life. And also, depression was an overall risk factor for insomnia, fatigue, and daily activity of cancer patients. Conclusion Cancer-related fatigue did not show significant effect on patient’s quality of life in this study. However, the result of pathway analysis highlights the importance of assessing depression in the process of cancer treatment and providing appropriate interventions.

Background: This study explores whether the intolerance of uncertainty among healthcare workers prompts viral anxiety, and whether this association is mediated by their reassuranceseeking behavior and preoccupation with the coronavirus disease 2019 (COVID-19) in Korea. Methods: An online survey was conducted among healthcare workers in Asan Medical Center, on November 29, 2021. Demographic characteristics and responses to items from rating scales were collected, including Stress and Anxiety to Viral Epidemics-9, Coronavirus Reassurance-Seeking Behaviors Scale (CRBS), Obsession with COVID-19 Scale (OCS), Patient Health Questionnaire-9, Insomnia Severity Scale, and Intolerance of Uncertainty-12 (IUS-12). Results: Among the 329 participants, viral anxiety of healthcare workers was predicted by being female (β = 0.14, P = 0.002), CRBS (β = 0.30, P < 0.001), OCS (β = 0.32, P < 0.001), and IUS-12 (β = 0.15, P = 0.002) scores (adjusted R2 = 0.43, F = 31.1, P < 0.001). Mediation analysis showed that the intolerance of uncertainty directly influenced viral anxiety, and reassuranceseeking behavior and obsession with COVID-19 partially mediated the association. Conclusion The intolerance of uncertainty among healthcare workers directly influenced their viral anxiety, and reassurance-seeking behavior and obsession with COVID-19 mediated this association in this era of “living with coronavirus” in Korea.

Objective: We aimed to explore the influence of public workers’ distress or viral anxiety on their level of depression and work engagement during the coronavirus disease (COVID-19) pandemic. Additionally, we ascertain the mediation effect of resilience and public service motivation on this association. Methods: A total of 300 public workers participated in this online survey. Their demographic characteristics and responses to survey items were collected using the Stress and Anxiety to Viral Epidemics–6 items Scale, the Patient Health Questionnaire–9 items Scale, the Public Service Motivation (PSM) Scale, the Nine-item Utrecht Work Engagement Scale, the Korean Occupational Stress Scale–Short Form, and the Brief Resilience Scale. Results: Work engagement of public workers was expected by PSM (β=0.28, p<0.001), resilience (β=0.30, p<0.001), and work-related stress (β=-0.40, p<0.001) (F=57.4, p<0.001). Depression was expected by fewer years of employment (β=-0.12, p=0.02), viral anxiety (β= 0.21, p<0.001), and low resilience (β=-0.42, p<0.001) (F=22.1, p<0.001). Resilience and PSM partially mediated the effects of work-related stress on work engagement. Depression was influenced by COVID-19–induced viral anxiety, and their resilience—but not PSM—mediated the association. Conclusion Public workers’ resilience and PSM partially mediated the effects of work-related stress on work engagement. The influence of viral anxiety on public workers’ depression was mediated by their resilience but not PSM.

Background: This study aimed to explore clinical correlates of fear of progression (FoP) among patients with cancer during the coronavirus disease 2019 (COVID-19) pandemic and examine the mediation effect of cancer-related dysfunctional beliefs about sleep (C-DBS). Methods: Medical charts of patients with cancer who visited a psycho-oncology clinic between July and November 2021 were reviewed. Baseline socio-demographic and cancer-related variables were collected. Patients’ self-report questionnaires, regarding FoP, depression (Patient Health Questionnaire-9 items; PHQ-9), viral anxiety (Stress and Anxiety to Viral Epidemics-6 items; SAVE-6), C-DBS, and other distress, were investigated. Pearson’s correlation and linear regression were performed to examine the risk factors of FoP. Mediation effect analysis with the bootstrap method with 2,000 resamples was implemented. Results: A total of 231 patients were included in the analysis. Linear regression revealed that FoP was predicted by age (β = −0.14, P = 0.003), PHQ-9 (β = 0.48, P < 0.001), SAVE-6 (β = 0.34, P < 0.001), and C-DBS (β = 0.15, P = 0.005). FoP was directly influenced by SAVE-6 and mediated by C-DBS, while it was directly influenced by PHQ-9 with no mediation effect. Conclusion During the COVID-19 pandemic, the FoP of patients with cancer was associated with younger age, depression, viral anxiety, and C-DBS. Depression and viral anxiety directly influenced FoP, while C-DBS mediated the association between viral anxiety and FoP.Therefore, oncology healthcare professionals are recommended to assess C-DBS of their patients when they are highly distressed from FoP.

Objective: The aim of this study was to explore the factors that can influence the severity of insomnia in the general population. We also aimed to examine whether sleep effort mediates the association between dysfunctional beliefs about sleep or the discrepancy between desired time in bed and desired total sleep time (DBST) and insomnia severity in individuals. Methods: A total of 387 participants enrolled in this e-survey study. The symptoms were rated using the insomnia severity index (ISI), Patients Health Questionnaire-9 items, Dysfunctional Beliefs about Sleep-2 items, Glasgow Sleep Effort Scale, and Stress and Anxiety to Viral Epidemics-6 items. In addition, we defined a new sleep index named the DBST index. A linear regression analysis was performed to explore the factors predicting ISI scores, and mediation analysis was implemented to explore whether persistent preoccupation with sleep mediated the influence of dysfunctional beliefs about sleep and DBST on insomnia severity. Results: A linear regression analysis investigated depression (β=0.17, p<0.001), sleep effort (β=0.50, p<0.001), dysfunctional beliefs about sleep (β=0.13, p=0.001), and DBST (β=0.09, p=0.014) (adjusted R2=0.50, F=65.7, p<0.001). Additionally, we observed that persistent preoccupation with sleep partially mediated the influence of dysfunctional beliefs about sleep and DBST on insomnia severity. Conclusion Depression, preoccupation with sleep, dysfunctional beliefs about sleep, and DBST influenced the insomnia severity of the general population. We also observed that a persistent preoccupation with sleep partially mediated the influence of dysfunctional beliefs about sleep and the DBST index on insomnia severity.

Background: The coronavirus disease 2019, or COVID-19, has had a major psychological impact on healthcare workers. However, very few scales are available to specifically assess work-related stress and anxiety in healthcare workers responding to a viral epidemic. This study developed a new assessment tool, the Stress and Anxiety to Viral Epidemics-9 (SAVE-9) and aimed to validate it among healthcare workers directly affected by COVID-19 in Korea. Methods: A total of 1,019 healthcare workers responded through anonymous questionnaires during April 20–30, 2020. Exploratory factor analysis (EFA) was conducted to explore the construct validity, and the reliability was assessed using internal consistency measures of Cronbach's alpha coefficients. Receiver operating characteristic analysis was conducted to define the most appropriate cut-off point of SAVE-9 using the Generalized Anxiety Disorder-7 scale (GAD-7; ≥ 5). Second, Spearman's rank correlation coefficient was used to establish convergent validity for the SAVE-9 questionnaire with GAD-7 and the Patient Health Questionnaire-9. Results: The nine-item scale had satisfactory internal consistency (Cronbach's α = 0.795). It adopted a two-factor structure: 1) anxiety regarding viral epidemics and 2) work-related stress associated with viral epidemics. A cut-off score of 22 for the SAVE-9 ascertained levels of stress and anxiety in response to a viral epidemic in healthcare workers that warranted clinical attention. Correlations between the SAVE-9 and the other scales were statistically significant (P < 0.05). Conclusion The results suggest that the SAVE-9 is a useful, reliable, and valid tool to evaluate stress and anxiety responses in healthcare workers during viral epidemics.

Objective: We aimed to investigate the effect of nursing professionals’ resilience on their mental health, work-related stress, and anxiety in response to the COVID-19 pandemic. Methods: We conducted an online survey in the Asan Medical Center and Ulsan University Hospital, South Korea. We extracted data of 824 nursing professionals who consented to participate, including demographic variables and the Stress and Anxiety to Viral Epidemics-9 (SAVE-9), PHQ-9, GAD-7, and Brief Resilience Scale scores. Results: Resilience was negatively correlated with Patient Health Questionnaire-9 (PHQ-9) (rho=-0.23), Generalized Anxiety Scale-7 items (GAD-7) (rho=-0.25), Stress and Anxiety to Viral Epidem-ics-6 items (SAVE-6) (rho=-0.15), and Stress And anxiety to Viral Epidemics-3 items (SAVE-3) (rho=-0.13, all, p<0.001). Logistic regression analysis adjusting age, marital status, and years of employment revealed that high level of general anxiety [adjusted odds ratio (aOR)=1.40, 95% confidence interval (CI)=1.31–1.50], work-related stress during viral epidemics (aOR=1.16, 95% CI=1.03–1.29), and a low level of resilience (aOR=0.91, 95% CI=0.85–0.97) were expecting variables for the depression of healthcare workers. Conclusion Nursing professionals’ level of resilience may be associated with low level of work-related stress and anxiety induced by a viral epidemic. We need to explore further the possibility of resilience as coping strategy of healthcare workers in this pandemic era.