Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven shortened version from a machine learning approach

BACKGROUND

The Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) is a widely used self-report instrument for identifying sleep-related cognition. However, its length can be cumbersome in clinical practice. This study aims to develop a data-driven shortened version of the DBAS-16 that efficiently predicts the DBAS-16 total score among the general population.

METHODS

We collected 1000 responses to the DBAS-16 from the general population through three separate surveys, each focusing on different aspects of insomnia severity and related factors. Using Exploratory Factor Analysis (EFA) on the survey responses, we grouped DBAS-16 items based on response pattern similarities. The most representative item from each group, showing the highest regression performance with eXtreme Gradient Boosting (XGBoost) in predicting the DBAS-16 total score, was selected to create a shortened version of the DBAS-16.

RESULTS

Through EFA and XGBoost, we categorized the DBAS-16 items into six distinct groups. Selecting one item from each group, based on the highest coefficient of determination R2 values in predicting the DBAS-16 total score. After measuring the R2 values for all possible combinations of six items, items 4, 5, 7, 11, 13, and 15 were chosen, exhibiting the highest R2 value. Based on these six items, we developed the DBAS-6, a data-driven shortened version of the DBAS-16. The DBAS-6 exhibited outstanding predictive ability, achieving the highest R2 value of 0.90 for predicting the DBAS-16 total score, surpassing that of a previously developed shortened version. Notably, the DBAS-6 efficiently encapsulates the core aspects of the DBAS-16 and demonstrates robust predictive power over heterogeneous test data samples with distinct statistical characteristics from the training data.

CONCLUSION

With its concise format and high predictive accuracy, the DBAS-6 offers a practical tool for assessing dysfunctional beliefs about sleep in clinical settings.

Dysfunctional Self-Focus and Fear of Progression in Cancer Patients Mediated by Depression, Anxiety, and Dysfunctional Sleep Beliefs

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.

Efficacy and safety of digital therapeutic application of Sleep Index-Based Treatment for Insomnia (dSIBT-I): a pilot study

The aim of this study was to evaluate the safety and efficacy of digital therapeutic application of Sleep Index-Based Treatment for Insomnia (dSIBT-I) and compare them with those of digital application of Cognitive Behavioural Therapy for Insomnia (dCBT-I). This randomised prospective pilot study was conducted at the Asan Medical Center. A total of 50 patients with insomnia were recruited between December 2022 and January 2023 and randomly allocated to the dSIBT-I or dCBT-I group. The study was carried out for one month. The primary outcome was the significant reduction in Insomnia Severity Index score at Week 4 compared to baseline, while the secondary outcome was proportion of participants whose Insomnia Severity Index scores were reduced to <15 at Week 4. We performed linear mixed model and generalised estimating equation analyses. Both dSIBT-I and dCBT-I groups showed significant improvements in Insomnia Severity Index scores at Week 4. There was no significant difference between two groups in terms of Insomnia Severity Index scores at Week 4 (group × time effect, F = 1.07, p = 0.382) and proportion of participants whose Insomnia Severity Index scores were reduced to <15 at Week 4 (group × time effects, F = 1.80, p = 0.615). However, at Week 2, the dSIBT-I group showed better results than the dCBT-I group in terms of both Insomnia Severity Index scores (p = 0.044) and proportion of participants whose Insomnia Severity Index scores were reduced to <15 (82.6% vs. 48.0%, p = 0.017). No treatment-emergent adverse events were reported in either group. The dSIBT-I is a safe and effective therapy for insomnia, with rapid treatment effects.

Catastrophizing Maladaptive Coping Affects the Association Between Viral Anxiety and Fear of Progression in Cancer Patients During COVID-19 Pandemic

OBJECTIVE

The aim of the present study was to explore whether or not cancer patients' viral anxiety and depression during the coronavirus-2019 (COVID-19) pandemic were associated with a fear of cancer progression. We also assessed whether coping strategies affected the relationship.

METHODS

The present cross-sectional survey included cancer patients who visited Ulsan University Hospital in Ulsan, Korea. The participants' demographic information and responses to the following symptoms rating scales were collected: Stress and Anxiety to Viral Epidemic-6; Patient Health Questionnaire-9; Cognitive Emotion Regulation Questionnaire-short version; or Fear of Progression Questionnaire-short version.

RESULTS

Of the 558 cancer patients surveyed, 25 (4.5%) reported that their treatment schedule was delayed during the COVID-19 pandemic. The patients' fear of progression was found to be related to age (β=-0.08; p=0.011), viral anxiety (β=0.40; p<0.001), depression (β=0.26; p<0.001), and catastrophizing coping strategies (β=0.15; p=0.004), for an overall adjusted R2 of 0.46 (F=66.8; p<0.001). Mediation analysis showed that viral anxiety and depression were directly associated with fear of progression, while catastrophizing mediated this relationship.

CONCLUSION

Fear of progression in cancer patients was associated with viral anxiety, depression, and maladaptive coping techniques, such as catastrophizing, during the COVID-19 pandemic.

Adherence to Physical Distancing and Health Beliefs About COVID-19 Among Patients With Cancer

BACKGROUND

This study aimed to validate questionnaires on adherence to physical distancing and health beliefs about coronavirus disease 2019 (COVID-19) among patients with cancer and explore their interaction with depression or viral anxiety among them.

METHODS

Through an online survey, data from 154 cancer patients (female: 82.5%, breast cancer: 66.2%, current cancer treatment, presence: 65.6%) were collected from March to June 2022. The survey gathered responses to questionnaires on adherence to physical distancing, health beliefs about COVID-19, perceived social norms, Stress and Anxiety to Viral Epidemics-6 items, and Patient Health Questionnaire-2. Confirmatory factor analysis (CFA) for construct validity and structural equation model (SEM) were performed.

RESULTS

The CFA showed a good model fit for adherence to physical distancing (comparative fit index [CFI] = 1.000, Tucker-Lewis index [TLI] = 0.930, root-mean-square-error of approximation [RMSEA] = 0.000, and standardized root-mean-square residual [SRMR] = 0.050) and a satisfactory model fit for health beliefs about COVID-19 (CFI = 0.978, TLI = 0.971, RMSEA = 0.061, and SRMR = 0.089). Through SEM, we found that personal injunctive norms were the main mediators linking health beliefs with physical distancing in patients with cancer. Depression also mediated the effects of viral anxiety and perceived severity on physical distancing (χ² = 20.073, df = 15, P = 0.169; CFI = 0.984; RMSEA = 0.047).

CONCLUSION

The questionnaires are reliable and valid. Patients with cancer may be able to adhere to physical distancing by addressing perceived severity, viral anxiety, perceived benefits, self-efficacy, perceived barriers, as well as personal injunctive norms.

Mediating Effect of Intolerance of Uncertainty and Cancer-Related Dysfunctional Beliefs About Sleep on Psychological Symptoms and Fear of Progression Among Cancer Patients

OBJECTIVE

This study aimed to explore the mediating effects of cancer-related dysfunctional beliefs regarding sleep and intolerance of uncertainty on the effect of depression, insomnia, and anxiety on fear of progression (FoP).

METHODS

We retrospectively reviewed medical records of patients with cancer who visited the Sleep Clinic for cancer patients in Asan Medical Center for the first time between December 2021 and March 2022. Data collected included age, sex, types of cancer, staging, current treatment modalities, and history of surgical procedures. In addition, psychological symptoms were rated using the Insomnia Severity Scale (ISI), Patient Health Questionnaire-9 items (PHQ-9), State subcategory of the State and Trait of Anxiety Inventory (STAI-S), Short form of Fear of Progression Questionnaire, Cancer-related Dysfunctional Beliefs about Sleep scale (C-DBS), single item of pain and fatigue, Connor Davidson Resilience Scale 2-item (CD-RISC2), and Intolerance of Uncertainty-12 (IUS-12). The predictive variables for FoP were determined by linear regression analysis.

RESULTS

The FoP was significantly correlated with age (r=-0.289), ISI (r=0.178), PHQ-9 (r=0.703), STAI-S (r=0.377), fatigue (r=0.452), CD-RISC2 (r=-0.270), IUS-12 (r=0.585), and C-DBS (r=0.427, all p<0.01). A mediation analysis showed that intolerance of uncertainty and dysfunctional beliefs about sleep mediated the relationship of FoP with insomnia, depression, or anxiety.

CONCLUSION

Psychological support for intolerance of uncertainty and cancer-related dysfunctional beliefs about sleep in patients with cancer may be beneficial to reduce their FoP.

Cancer-Related Dysfunctional Beliefs About Sleep Mediate the Influence of Sleep Disturbance on Fear of Progression Among Patients With Surgically Resected Lung Cancer

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, self-reported 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.

Discrepancy between desired time in bed and desired total sleep time in patients with cancer: The DBST index and its relationship with insomnia severity and sleep onset latency

Patients with cancer can often experience insomnia or sleep disturbances. This study aimed to explore whether the discrepancy between a patient's desired time in bed and desired total sleep time (DBST index) can be used as a measurement tool for insomnia severity or sleep onset latency [SOL] in patients with cancer. This retrospective medical records review study gathered clinical information and scores from scales and indices such as the Insomnia Severity Index (ISI), Cancer-related Dysfunctional Beliefs about Sleep (C-DBS) scale, Patient Health Questionnaire-9 items (PHQ-9), State subcategory of State and Trait Anxiety Inventory, and the short form of the Fear of Progression Questionnaire. Sleep indices of time variables (bedtime, sleep onset time, and wake-up time), duration variables [SOL, time in bed (TIB), time in bed over 24 hours (TIB/d), and duration from wake-up time to bedtime (WTB)], and DBST index were calculated. ISI scores were predicted by the PHQ-9 (β = 0.34, P < 0.001), C-DBS scale (β = 0.17, P = 0.034), and DBST indices (β = 0.22, P = 0.004). Long SOL value was predicted by early bedtimes (β = -0.18, P = 0.045), short WTB durations (β = -0.26, P = 0.004), and high DBST index values (β = 0.19, P = 0.013). The DBST index was significantly correlated with both insomnia severity and SOL in patients with cancer.

Effect of Cancer-Related Dysfunctional Beliefs About Sleep on Fear of Cancer Progression in the Coronavirus Pandemic

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.

Prevalence of Sleep Disturbance in Patients With Cancer: A Systematic Review and Meta-Analysis

Sleep disturbance is one of the most common and troubling symptoms that harm the quality of life throughout all phases of treatment and stages of the illness among patients with cancer. The aim of this meta-analysis is to examine the present status of sleep disturbance prevalence in patients with cancer. The following databases were searched: PubMed, CINAHL, MEDLINE, EMBASE, PsycINFO, from inception to April 2021. Prevalence rates were pooled with meta-analysis using a random-effects model. A total of 160 studies (N = 46,279) published between 1998 and 2021 met the inclusion criteria. The overall prevalence of sleep disturbance was 60.7% (26,448/46,279 participants, 95% CI 58.1-63.3%) with significant heterogeneity between studies (p < .000, τ2 = .0000, I2 = 96.4%). This meta-analysis highlights the importance of developing optimal monitoring strategies to reduce sleep disturbance and improve the quality of life of cancer patients.

Assessing the Sleep-wake Pattern in Cancer Patients for Predicting a Short Sleep Onset Latency

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.

Mechanisms of Cognitive Behavioral Therapy and Light Therapy for Cancer-Related Insomnia: A Randomized Clinical Trial during Chemotherapy for Breast Cancer

STUDY OBJECTIVES

This study aimed to investigate the mechanisms of a combined brief cognitive behavioral plus bright light therapy (CBT-I+Light) in women receiving chemotherapy.

METHODS

Women (N = 101) were randomly assigned to CBT-I+Light or treatment as usual plus relaxation audios (TAU+). Participants completed sleep diaries and wore an actigraph during the 6-week intervention period. Patient-reported outcomes were assessed at baseline, mid-point (week 3), and later (week 6). Cognitive (i.e., dysfunctional sleep beliefs, pre-sleep cognitions, and arousal) and behavioral (i.e., time in bed awake and day-to-day out-of-bedtime variability) mechanisms were examined.

RESULTS

Cognitively, both groups declined significantly in overall dysfunctional sleep beliefs from pre- to post-intervention (both p< .04); however, they did not differ on sleep-related beliefs nor pre-sleep cognitions and arousal at post-intervention (both p> .50). Dysfunctional beliefs sleep expectations subscale was lower in CBT-I+Light versus TAU+ (p= .01). Behaviorally, CBT-I+Light reported less overall time in bed awake after the start of the intervention (p< .05) and significantly less time in bed during the morning until the final week of the intervention period. Out-of-bedtime day-to-day variability was lower in the CBT-+Light vs TAU+ at the final intervention day.

CONCLUSION

Mechanisms of CBT-I+Light during chemotherapy remain to be shown. Our results suggest that changes in behavioral mechanisms may be associated with sleep improvements within this cohort. Future studies should assess the role of additional mechanisms (e.g., sleep effort) within larger samples. Whilst intervention brevity is important, more potent interventions may be required to achieve robust changes in target mechanisms.

Discrepancy Between Desired Time in Bed and Desired Total Sleep Time, Insomnia, Depression, and Dysfunctional Beliefs About Sleep Among the General Population

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.

Functional Impairments in the Mental Health, Depression and Anxiety Related to the Viral Epidemic, and Disruption in Healthcare Service Utilization Among Cancer Patients in the COVID-19 Pandemic Era

Purpose

Literature is scarce regarding cancer care utilization during the massive outbreak of coronavirus disease 2019 (COVID-19) in the Republic of Korea. We investigated functional impairments in mental health and their relationships with depression, anxiety regarding the viral epidemic, and disruptions in healthcare service utilization among cancer patients in the COVID-19 pandemic era.

Materials and Methods

We used an online survey with questions related to the disturbances faced by patients with cancer in utilizing healthcare services in the pandemic era. Current mental health status was assessed using the Work and Social Adjustment Scale (WSAS), Stress and Anxiety to Viral Epidemics-6 (SAVE-6) scale, Patient Health Questionnaire-9 (PHQ-9), Insomnia Severity Index (ISI), Brief Resilience Scale (BRS), Cancer-Related Dysfunctional Beliefs about Sleep Scale (C-DBS), and Fear of COVID-19 over Cancer (FCC).

Results

Among the 221 responders, 95 (43.0%) reported disruptions in healthcare service utilization during the COVID-19 pandemic. Logistic regression analysis revealed that functional impairment in the mental health of these patients was expected due to disruptions in healthcare service utilization, high levels of depression, anxiety regarding the viral epidemic, fear of COVID over cancer, and low resilience. Mediation analysis showed that patient resilience and cancer-related dysfunctional beliefs about sleep partially mediated the effects of viral anxiety on functional impairment.

Conclusion

In this pandemic era, patients with cancer experience depression, anxiety regarding the viral epidemic, and disruptions in healthcare service utilization, which may influence their functional impairments in mental health.

Depression, Rather Than Cancer-Related Fatigue or Insomnia, Decreased the Quality of Life of Cancer Patients

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.

Development of Dysfunctional Beliefs and Attitude about Sleep Scale for Cancer Patients

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.Abbreviations: CBT: cognitive behavioral therapy; C-DBAS-14: Cancer-Related Dysfunctional Beliefs and Attitude about Sleep; C-DBS: Cancer-Related Dysfunctional Beliefs about Sleep; DBAS-16: Dysfunctional Beliefs and Attitudes about Sleep; ISI: Insomnia Severity Index.

Time to Take Sleeping Pills and Subjective Satisfaction among Cancer Patients

OBJECTIVE

We investigated the influence of the time to take hypnotics and daytime activity on patient satisfaction with sleeping pills.

METHODS

Ninety-six cancer patients who were currently taking benzodiazepine or z-drug as hypnotics were grouped into satisfied and dissatisfied groups. The subjects' symptoms, time to take sleeping pills, bedtime, sleep onset time, wake up time, and time in bed within 24 hours (TIB/d) were obtained.

RESULTS

The satisfied group had significantly late sleeping pill ingestion time (p=0.04); significantly early wake up time (p=0.01); and significantly shorter sleep latency, TIB/d, duration from the administration of pills to sleep onset, and duration from the administration of pills to wake up time (PTW). Logistic regression analysis revealed that the significant predictors of patient satisfaction to hypnotics were less severity of insomnia [odds ratio (OR)=0.91] and the time variables, including late sleeping pill administration time (OR=1.53) and early wake up time (OR=0.57). Among the duration variables, short PTW (OR=0.30) and short TIB/d (OR=0.64) were significantly related with the satisfaction to hypnotics.

CONCLUSION

Reducing the duration from the administration of hypnotics to wake up time and TIB/d can influence the satisfaction to sleeping pills.