Study objectives: This study aimed to develop a scale utilizing the original Dysfunctional Beliefs and Attitudes about Sleep (DBAS) scale that measured maladaptive cognitions associated with sleep that is especially sensitive to cancer patients. In addition to the original scale, we added two additional items that reflected cancer-specific dysfunctional beliefs about sleep. Methods: Participants consisted of 337 cancer patients (mean age 54.0 +/- 11.8 years, 32.0% men). All participants completed the DBAS-16, two cancer specific items, and the Insomnia Severity Index. Item-to-total-score correlations, internal consistency, item selection, and factor structure were examined. Results: The DBAS-16 was found to be reliable, and internal consistency was also adequate when adding two cancer-specific questions (Cronbach's alpha = 0.89). A total of 14 items were selected, and a four-factor model was selected using exploratory factor analysis (Tucker-Lewis index = 0.86, root mean square error of approximation = 0.08). The four factors were (a) sleep expectations, (b) worry about insomnia, (c) perceived consequences of insomnia and medication, and (d) two cancer-related items. The modified 14 items of the Cancer-related DBAS (C-DBAS-14) well differentiated cancer patients with and without insomnia. Conclusions: The C-DBAS-14 is a promising measure that has adequate internal consistency. It is also sensitive to sleep-related cognitions in cancer patients and can discriminate patients with cancer who are experiencing insomnia from those who are good sleepers. The enhanced utility of the shortened 14-item scale tailored specifically to cancer patients may be useful in both clinical practice and research settings.

Objective The aim of this study was to estimate the progress of insomnia prevalence and incidence over the past several years. Also, this study compared survival rates between individuals with and without insomnia.Methods The National Health Insurance Service-National Sample Cohort (NHIS-NSC) from 2002–2013 was used for this study. Prevalent cases of insomnia were defined using ICD-10 codes F51.0 or G47.0, or a prescription of sedatives. Cox’s proportional hazard analysis was conducted to compare survival rates between insomnia patients and people without insomnia.Results In 2013, there were 46,167 (5.78%) insomnia patients over 20 years old in this cohort. Insomnia was more common among women and the elderly. Annual incidence over the past several years remained steady but the prevalence increased. The survival of insomnia patients was lower than that of people without insomnia, and the hazard ratio for overall mortality was 1.702 (p<0.001).Conclusion This large-scale population-based cohort study provided current epidemiologic indicators of insomnia in the Korean general population.

Objective We aim to present a clinical guideline for the diagnosis and treatment of insomnia in adults by reviewing and integrating existing clinical guidelines. The purpose of this guideline is to assist clinicians who perform evidence-based insomnia treatment.Methods We selected literature that may be appropriate for use in guideline development from evidence-based practice guidelines that have been issued by an academic or governmental institution within the last five years. The core question of this guideline was made in sentence form including Patient/Problem, Intervention, Comparison, Outcome (PICO) elements. After searching PubMed, EMBASE, and medical guideline issuing agencies, three guidelines were judged to be the most appropriately reviewed, up-to-date, and from trusted sources.Results The Appraisal of Guidelines for Research and Evaluation (AGREE) II tool was used to evaluate the quality of the three clinical guidelines. The final outcome of the guideline development process is a total of 15 recommendations that report the strength of the recommendation, the quality of evidence, a summary of content, and considerations in applying the recommendation.Conclusion It is vital for clinical guidelines for insomnia to be developed and continually updated in order to provide more accurate evidence-based treatments to patients.

OBJECTIVE:We aimed to investigate whether the sleep education and hypnotics reduction program (the i-sleep program), developed for all hospitalized patients and medical personnel, help reducing the hypnotics prescriptions rate among hospitalized cancer patients in a general hospital.METHODS:Patient data such as hypnotics prescribed at the time of admission and discharge during prior to (year of 2014) and after (year of 2015) initiation of the i-sleep program were collected and compared. Also, hypnotics prescription rate at the first day of each month of 2014 and 2015 were estimated and compared.RESULTS:All of 12,382 patients in 2014 and 12,313 patients in 2015 were admitted to the Department of Oncology of the hospital. In 2014, 782 (6.3%) of 12,382 inpatients were already taking hypnotics at the time of admission, and 594 (76.0%) of the 782 patients were still taking sleeping pills at the time of discharge. Following initiation of the i-sleep program (2015), 792 (6.4%) of 12,313 inpatients were already taking hypnotics at the time of admission, and 553 (69.8%) of the 792 inpatients were still taking them at the time of discharge (relative risk, 0.92; 95% confidence interval, 0.87-0.98). On the first day of each month of 2014, 7.3% to 12.6% (mean, 10.0%) of inpatients had prescriptions for hypnotics. Following initiation of the program, the rate of hypnotic prescription was significantly reduced (3.2-10.8%; mean, 8.0%; p = 0.03).CONCLUSION:Our date showed that the i-sleep program may help to reduce the hypnotic prescription rate in hospitalized cancer patients.

Background and ObjectiveaaDepression is one of the major causes of insomnia among cancer patients, and should be explored among cancer patients who are suffering from insomnia. The objective of this study was to explore whether dysfunctional beliefs about sleep among cancer patients were associated with insomnia independent of depression. MethodsaaMedical records of patients who visited Asan Medical Center sleep clinic for cancer were reviewed retrospectively from January to November of 2017. The data included the patient’s psychiatric symptoms and assessment of sleep disorders Insomnia Severity Index (ISI), Patient’s Health Questionnaire-9 (PHQ-9), State-Trait Anxiety Inventory (STAI), Fear of Progression (FoP), and Cancer-related Dysfunctional Beliefs about Sleep (C-DBS) and a clinical interview. ResultsaaResults indicated that ISI score was significantly correlated with PHQ-9, FoP, and CDBS scores, and C-DBS score was significantly correlated with ISI, PHQ-9, and FoP scores all, p < 0.01). The ISI and C-DBS scores were not significantly correlated with age and the STAI-State scale. Linear regression analysis revealed that C-DBS (β = 0.40, p < 0.001) and PHQ-9 scores (β = 0.30, p < 0.01) predicted ISI scores among all participants. Among participants who were not depressed (PHQ-9 score ≤ 9), C-DBS scores were the only predictor for ISI scores (β = 0.46, p < 0.001). ConclusionsaaDysfunctional beliefs about sleep in cancer patients were significantly associated with severity of insomnia, independent of depression. Sleep Med Res 2019;10(1):31-35

Objective We aimed to develop the clinical guideline for headache by the systematic review and synthesis of existing evidence-based guidelines. The purpose of developing the guideline was to improve the appropriateness of diagnosis and treatment of headache disorder, and consequently, to improve patients pain control and quality of life. The guideline broadly covers the differential diagnosis and treatment of tension-type headache, migraine, cluster headache, and medication-overuse headache. Methods This is a methodological study based on the ADAPTE methodology, including a systematic review of the literature, quality assessment of the guidelines using the Appraisal of Clinical Guidelines for REsearch & Evaluation II (AGREE II) Instrument, as well as an external review using a Delphi technique. The inclusion criteria for systematic search were as follows: topic-relevant, up-to-date guidelines including evidence from within 5 years, evidence-based guidelines, guidelines written in English or Korean, and guidelines issued by academic institutions or government agencies. Results We selected five guidelines and conducted their quality assessment using the AGREE II Instrument. As a result, one guideline was found to be eligible for adaptation. For 13 key questions, a total of 39 recommendations were proposed with the grading system and revised using the nominal group technique. Conclusion Recommendations should be applied to actual clinical sites to achieve the ultimate goal of this guideline; therefore, follow-up activities, such as monitoring of guideline usage and assessment of applicability of the recommendations, should be performed in the future. Further assessment of the effectiveness of the guideline in Korea is needed.

Background Although distress screening is crucial for cancer survivors, it is not easy for clinicians to recognize distress. Physical activity (PA) data collected by mobile devices such as smart bands and smartphone apps have the potential to be used to screen distress in breast cancer survivors. Objective The aim of this study was to assess data collection rates of smartphone apps and smart bands in terms of PA data, investigate the correlation between PA data from mobile devices and distress-related questionnaires from smartphone apps, and demonstrate factors associated with data collection with smart bands and smartphone apps in breast cancer survivors. Methods In this prospective observational study, patients who underwent surgery for breast cancer at Asan Medical Center, Seoul, Republic of Korea, between June 2017 and March 2018 were enrolled and asked to use both a smartphone app and smart band for 6 months. The overall compliance rates of the daily PA data collection via the smartphone walking apps and wearable smart bands were analyzed in a within-subject manner. The longitudinal daily collection rates were calculated to examine the dropout pattern. We also performed multivariate linear regression analysis to examine factors associated with compliance with daily collection. Finally, we tested the correlation between the count of daily average steps and distress level using Pearson correlation analysis. Results A total of 160 female patients who underwent breast cancer surgeries were enrolled. The overall compliance rates for using a smartphone app and smart bands were 88.0% (24,224/27,513) and 52.5% (14,431/27,513), respectively. The longitudinal compliance rate for smartphone apps was 77.8% at day 180, while the longitudinal compliance rate for smart bands rapidly decreased over time, reaching 17.5% at day 180. Subjects who were young, with other comorbidities, or receiving antihormonal therapy or targeted therapy showed significantly higher compliance rates to the smartphone app. However, no factor was associated with the compliance rate to the smart band. In terms of the correlation between the count of daily steps and distress level, step counts collected via smart band showed a significant correlation with distress level. Conclusions Smartphone apps or smart bands are feasible tools to collect data on the physical activity of breast cancer survivors. PA data from mobile devices are correlated with participants’ distress data, which suggests the potential role of mobile devices in the management of distress in breast cancer survivors. Trial Registration ClinicalTrials.gov NCT03072966; https://clinicaltrials.gov/ct2/show/NCT03072966

OBJECTIVE:We applied a program of sleep education and hypnotics reduction for inpatients (the i-sleep program). This study explored whether the i-sleep program is effective for reducing the prescription rate of sleeping pills to inpatients in a general hospital. METHODS:We estimated the proportion of inpatients prescribed hypnotics at admission to and discharge from the hospital, excluding pediatric care units, before (2014) and after (2015) the program. In addition, we estimated the proportion of inpatients prescribed sleeping pills among all inpatients on the first day of each month of 2014 and 2015. RESULTS:The proportion of inpatients prescribed hypnotics as discharge medication among inpatients who had been prescribed them at the time of admission decreased significantly, from 57.0% to 46.8%, after the i-sleep program (RR=0.82, 95% CI: 0.79-0.86). The proportion of inpatients newly prescribed sleeping pills after admission to the hospital did not significantly decrease (1.97% to 2.00%; RR=1.01, 95% CI: 0.96-1.07). The mean prescription rate of sleeping pills per day was 8.18% in 2014 and 7.78% in 2015. CONCLUSION:The i-sleep program reduced the proportion of inpatients who continued to take sleeping pills from admission until discharge, although it did't reduce the prescription rate per day.

Background The aim of this study was to evaluate the use of the Diagnostic Drawing Series (DDS) as a screening tool for the breast cancer patients with psychological distress. Methods All of 64 patients with breast cancer participated in this study. Patients' depressive and anxiety symptoms were assessed using Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) when the DDS was applied to the partipicants. Results Depressed patients used more enclosure in the Feeling drawings (P = 0.002) and tilt in Free drawings (P = 0.048). Patients with anxiety drew a picture over 67% of the paper (P = 0.015) in Tree drawing and more medium pressure (P = 0.049) in Feeling drawings. Thirty four subjects (77.3%) of unstable emotion group used over 67% of the space (P = 0.002). More Landscapes were observed in the Feeling drawings of unstable patients (P = 0.042). Conclusion These results suggested that DDS could be used as a supplemental screening tool for psychological distress in breast cancer patients.

A few patients diagnosed with insomnia attempt going to bed earlier to obtain adequate sleep and fall asleep less than 30 min, although they often complain about their inability to fall asleep easily. The aim of this study was to explore the association between short sleep latency and patients’ sleepwake pattern. All the 99 patients with primary insomnia who were under treatment with benzodiazepine or non-benzodiazepine gamma-aminobutyric acid (GABA) agonists as sleeping pills were selected. The time to take hypnotics, bedtime, sleep onset, and wake-up times were determined from medical records. Subjects who showed sleep latency of less than 30 min (SL ≤ 30, n = 56) were treated with hypnotics (10:46 pm) before going to bed (11:00 pm) later compared with subjects with sleep latency greater than 30 min (SL > 30 min, n = 43, hypnotic ingestion time, 9:46 pm; bedtime 10:10 pm). Duration from wake-up time to bedtime (WTB) was significantly longer in SL ≤ 30 group (16.5 ± 1.1 h) compared to SL > 30 group (15.8 ± 1.5 h). Long sleep latency was significantly correlated with old age, earlier ingestion of sleeping pills, earlier bedtime, and short duration of WTB (all, p < 0.01). Early bed time in the evening was not associated with short sleep latency. Patients with insomnia may find that delayed bedtime may promote faster sleep.

Background and ObjectiveaaIn South Korea, numerous people have died of lung injury from humidifier disinfectant. The objective of this study was to explore the association between cognitive emotion regulation strategies for victims of humidifier disinfectant accidents in Korea and their insomnia and other psychiatric problems. MethodsaaAmong 196 subjects experiencing humidifier disinfectant-related interstitial pneumonitis, 40 subjects were assessed for their psychological states between June 2015 and May 2016. Their psychiatric symptoms were assessed using Insomnia Severity Index, Hospital Anxiety and Depression Scales, Patient Health Questionnaire-9, posttraumatic stress disorder Checklist for DSM-5, and Cognitive Emotion Regulation Questionnaire. resultsaaSubjects’ adaptive cognitive emotion regulation strategies were not correlated with rating scale scores. However, total score of maladaptive cognitive emotion regulation strategy was significantly correlated with all rating scale scores (all p < 0.01). Among maladaptive strategies, rumination and catastrophizing strategies were significantly correlated with severity of insomnia and other psychiatric symptoms. ConclusionsaaThere was an association between victims’ maladaptive coping strategies and insomnia or other psychiatric symptoms. Thus, managing their coping strategies is necessary to help them survive in their current environment. Sleep Med res 2018;9(1):26-31

Background and Objective Insomnia is very common in depression and especially medical students are easy to experience sleep disturbance because of their studies. Also depressive symptoms are closely related to stress. Stress is an interaction between an individual and the environment, involving subjective perception and assessment of stressors, thus constituting a highly personalized process. Different personality traits can create different levels of stress. In this study, we tried to explore the relationship between insomnia and depressive symptoms or stress of medical students, and whether their personality may play a role on this relationship or not. Methods We enrolled 154 medical students from University of Ulsan College of Medicine. We used the Medical Stress Scale, the Multidimensional Perfectionism Scale, the Patient Health Questionnaire-9, the Academic Motivation Scale, the Insomnia Severity Index, and The revised NEO Personality Inventory (PI). Results Insomnia severity, amotivation, medical stress, mental health index and neuroticism traits of NEO-PI significantly correlated with depressive symptom severity (p < 0.001). And stepwise linear regression analysis indicated insomnia, amotivation and neuroticism traits of NEO-PI are expecting factors for students’ depressive symptoms is related to (p < 0.001). Conclusions Student who tend to be perfect feel more academic stress. The high level of depressive symptom is associated with insomnia, amotivation, academic stress in medical student. Moreover, personality trait also can influence their depressive symptoms.

Smartphone applications have recently been used as a breakthrough technology for monitoring mental health conditions in cancer outpatient settings. However, the use of electronic patient-reported outcomes (ePROs) on mental conditions through smartphone applications raises new concerns, which includes the question of the accuracy of depression screening. Thus, research is essential for improving the depression-screening performance. This study aims to (1) test whether deep-learning-based algorithms can overcome the limitations of traditional statistical methods in terms of depression screening accuracy. In addition, the study aims to (2) explore ePRO patterns that adversely affect depression screening accuracy. As a deep learning-based algorithm, a feedforward neural network algorithm was used. As a traditional statistical method, a random intercept logistic regression was employed. To explore the ePRO patterns that negatively impact model accuracy, mental fluctuations, missing data, and compounding effects between mental fluctuations and missing data were tested. The performances of the algorithms and the effects of the ePRO patterns were measured through the receiver operating characteristic comparison test. The results of the study show that the performance of the deep-learning-based models was superior to that of the traditional statistical approach. The study found that mental fluctuations statistically reduced the accuracy of depression-screening models. A weak association between ePRO omissions and screening accuracy was found. Moreover, the compounding effects that had a negative effect on the depression screening accuracy were statistically significant. Although well-trained deep-learning-based models exhibit excellent performance, they still have some limitations. Thus, it is very important to focus on data quality to predict health outcomes when using data that is difficult to quantify, such as mental conditions.

Dysfunctional beliefs about sleep may be associated with chronic sleep disturbance in patients afflicted with cancer over the trajectory of their battle with cancer. The objective of this study was exploration of the utility of assessing the sleep disturbances suffered by cancer patients possibly emanating from two cancer-related informationally valid but nonetheless dysfunctional beliefs: “My immune system will have serious problems if I don’t go to sleep at a certain time (question 1)” and “If I don’t sleep well at night, my cancer can recur or metastasize (question 2).” The scores for these beliefs were significantly correlated with insomnia severity [measured using the Insomnia Severity Index (p < 0.01)] and fear of disease progression [measured using the Fear of Progression Questionnaire (p < 0.01)]. The question 2 score also correlated with younger age (p = 0.01) and high depression scores assessed using the Patient Health Questionnaire-9 (p = 0.04). We believe the scores for these two cancer-related dysfunctional beliefs can be used to help evaluate sleep disturbances in cancer patients.

Many patients claim that they cannot sleep well despite ingestion of sleeping pills. In such cases, the physician should explore the reason why sleep disturbance persisted in patients despite administration of sleeping pills. We should consider patients’ age, gender, medical or psychiatric diseases, workplace, or sleep environment that may influence patients’ sleep and satisfaction with their hypnotics. However, prior to prescribing a hypnotic agent for patients with sleep disturbance, good sleep hygiene education should be provided first. Cognitive-behavioral therapy for insomnia is an important and effective treatment modality to improve patients’ sleep quality and reduce dosage of sleeping pills, but it is not easy for most general practitioners to learn and practice this modality. Therefore, we need to consider how to optimize the prescription of hypnotics for treating insomnia in order to prescribe hypnotics safely and appropriately at the lowest dosage. Physician should consider the mechanism of action of each hypnotic agent and prescribe proper hypnotics according to patients’ comorbid illness, insomnia types, or other underlying sleep disorders. Also, we should instruct the patients about when they should take their sleeping pills and we should monitor whether they have followed the instructions or not. Hospitalized patients are in a different sleep environment compared to outpatients, and therefore, we should also prepare modified management strategies for inpatients. In this review, strategies for optimizing the prescription of sleeping pills for insomnia patients will be discussed.

Objective Among the various psychiatric disorders, depression is a common comorbid condition in cancer patients. Due to the distinct and diverse nature of cancer, the prevalence of depression may be assumed to be affected by differences in primary cancer sites. In this study, we explored the prevalence rates of depression among the ten most prevalent cancers in South Korea using a national patient sample.Methods This was a 1-year cross-sectional study using a national patient sample provided by the South Korean National Health Insurance in 2011. We selected all patients who had received ICD-10 codes of the 10 most prevalent cancers and major depressive disorder. Afterwards, the cancer and depression groups were merged and analyzed.Results The MDD prevalence rate was highest in lung cancer (11.0%), followed by non-Hodgkin's lymphoma (9.2%), prostate (9.1%), bladder (8.8%), breast (7.8%), cervix (7.8%), colorectal (7.7%), stomach (6.9%), liver (6.5%), and thyroid cancer (5.6%). Within all cancer groups, patients with a MDD diagnosis were significantly older (p<0.05) than non-MDD patients. Colorectal, stomach, and thyroid cancer displayed a higher female proportion in the MDD group than the non-MDD group. In the subgroup analysis, the prevalence rate differed by age and sex.Conclusion The prevalence of depression varied according to cancer types. Patients with lung cancer were the most prone to experience depression. Because clinical and psychological factors may influence MDD prevalence, these factors will need to be studied more closely in the future.

IntroductionIn Korean culture, co-sleeping of parents and children are quite common, which is different from the Western culture where solitary sleeping of children is preferred. In this study, we evaluate the sleep environment factors that effect on children sleep disorder, and parent's parenting stress and mental health.MethodsSurveys were conducted to 115 participating parents of preschool children sleeping behaviour lecture. Seventy-one completed surveys were analyzed for the study. The mean age of target children was 53 ± 23 months. Parents’ mental health was evaluated by using several forms such as Insomnia Severity Index, Korean-Parenting Stress Index short form, and The Patient Health Questionnaire-9. Children's sleeping environment and quality were assessed by Child Sleep Habit Questionnaire and Sleep environment survey.ResultsPearson correlation analysis (P < 0.05) was conducted to evaluate the relationship between the sleep disorder of children, and the parent's parenting stress and mental health. Analyzing the data through the partial least square path modeling, co-sharing would have negative effect; bed-sharing could have negative effect on the depressing emotion of parents (P = 0.065). Solitary sleeping of children could have positive effect on parent's mental health (P < 0.01).ConclusionPreschool children's sleeping disorder occurs more often in co-sleeping children with parents than solitary sleeping children. Parents’ parenting stress is related to the parent's age and depression, further related to the children sleeping disorder and their sleep environment. Although, it is difficult to generalize the exact cause, evaluation and improvement of children's sleep environment would help to reduce the parent's parenting stress.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Insomnia disorder is common in patients undergoing cancer treatment. There is compelling evidence demonstrating that cognitive-behavioral therapy for insomnia (CBT-I) should be the initial treatment, but there has been insufficient research has been conducted among cancer patients. This population presents with unique physical and psychosocial health issues that may interfere with standard CBT-I and addressing these issues can play a role in improving treatment adherence and efficacy. We explore potential adaptations that can be made to standard CBT-I for cancer patients. Further research for this growing population is essential.