Fatigue is associated with depression independent of excessive daytime sleepiness in the general population

Current situation and related factors of fatigue among doctors and nurses in tertiary general hospitals in Northeast China

Fatigue has gradually become an important factor affecting the health and work quality of healthcare workers. However, the occurrence of fatigue and related factors in the context of heavy workloads and strained doctor-patient relationships have not been adequately studied in Northeast China. The current study aims to assess the situation of fatigue among healthcare workers in tertiary general hospitals in Northeast China, and to further analyze the influencing factors of fatigue among healthcare workers (doctors and nurses as a whole), doctors and nurses from various perspectives. A cross-sectional survey was conducted among healthcare workers who met the inclusion criteria in two tertiary general hospitals in Dalian, Liaoning Province, Northeast China. The survey data collected in the structured questionnaire include fatigue, general demographic characteristics, work situation, perceived stress, insomnia symptoms, workplace violence, anxiety symptoms, depressive symptoms, family function, and doctor-patient relationship. A binary logistic regression model was applied to analyze the independent influencing factors of fatigue. A total of 1004 healthcare workers were included in this study (503 doctors and 501 nurses). The prevalence of fatigue was 53.9% for healthcare workers, with rates of 52.3% for doctors, and 55.5% for nurses. Binary logistic regression analysis showed that health status, perceived stress, insomnia symptoms, anxiety symptoms, and doctor-patient relationship were influencing factors of fatigue among healthcare workers, doctors, and nurses. Chronic pain was an influencing factor for fatigue among healthcare workers and nurses. Depressive symptoms were an influencing factor for fatigue for healthcare workers and doctors. Night shift frequency was an influencing factor for fatigue for nurses. In Northeast China, tertiary general hospitals have a relatively high prevalence of fatigue among healthcare workers, especially among nurses. Fatigue was influenced by various factors such as health status, perceived stress, insomnia symptoms, anxiety symptoms, and doctor-patient relationships. It is necessary to raise awareness of fatigue among healthcare workers, particularly healthcare workers with risk factors, and to develop targeted and effective intervention measures aimed at reducing fatigue.

A Comparison of Patient Self-Reported Fatigue in the FRAIL Scale With a Validated Fatigue Measure

RATIONALE

The FRAIL scale is a self-administered tool used to screen for frailty in clinical, community and long-term nursing settings. Patient's self-reporting of fatigue in the FRAIL scale may raise concerns of subjectivity and accuracy in frailty assessment.

OBJECTIVE

To assess the performance of the patient-reported fatigue measure in the FRAIL scale in comparison to a validated fatigue measure, the Fatigue Severity Scale (FSS).

METHODS

We conducted a cross-sectional study involving interviews and medical records review. Participants were 55 years and older seen at an ambulatory geriatric osteoporosis clinic. Participants were administered the FRAIL scale and the FSS over the phone or in person. Patient self-reported fatigue was derived from the first item (Are you fatigued?) on the FRAIL scale while the FSS provided a validated fatigue measure. Clinical and demographic data were obtained by review of medical records. Sensitivity, specificity, negative and positive predictive values, and AUC were estimated for patient self-reported fatigue from the FRAIL scale using the FSS as the gold standard. Logistic regression analysis was used to investigate independent associations between the items on the FRAIL scale and fatigue assessed by the FSS, adjusting for demographic and clinical characteristics.

RESULTS

We interviewed 126 participants, mean age was 77.2 ± 8.5 years, 91.3% (116) were female and 69.3% (88) were Caucasian/White. The prevalence of fatigue assessed by the FSS and the FRAIL scale were 24% and 34.6%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of patient-reported fatigue were 0.67, 0.75, 0.45, and 0.88, respectively. The AUC was 0.71. Depression (OR = 2.41, 95% CI = 1.14-10.25) and patient self-reported fatigue (OR = 4.74, 95% CI = 1.74-12.9) were significantly associated with FSS fatigue measure.

CONCLUSION

Patient-reported fatigue largely reflects validated measure of fatigue. Physicians should therefore be encouraged to use the FRAIL scale to assess frailty.

High fatigue levels among psychiatric outpatients - the validity of the Danish Patient Reported Outcomes Measurement Information System Fatigue Short-Form (PROMISF-SF)

BACKGROUND

Patient Reported Outcomes Measurement Information System Fatigue Short-Form (PROMIS-F-SF) is a self-administered, patient reported outcome (PRO) designed to assess fatigue in healthy and clinical populations and for tracking progress during treatment for disorders complicated with fatigue.

METHODS

Patients in the Mental Health Service Outpatient Clinics and healthy volunteers were invited to complete a survey, which included the Danish translation of the PROMIS-F-SF, the Chalder Fatigue Scale (CFS-11), and measures of depression and anxiety. We conducted a confirmatory factor analysis of the previously suggested single-factor structure of the instrument. We furthermore evaluated the construct validity of the PROMIS-F-SF by means of its relationship with the CFS-11. Finally, we evaluated the utility of the PROMIS-F-SF to identify patient-status by conducting receiver operating characteristic curves.

RESULTS

70 healthy volunteers and 62 patients completed the instruments. The PROMIS-F-SF had a average fit to the previously reported single-factor structure. Cronbach's alpha and McDonald's omega showed good internal reliability (α = 0.96, ωtotal = 0.97). PROMIS-F-SF score was positively correlated with the CFS-11 (r =.76) and it correlated highly with depression (r =.78) and anxiety (r =.74) score. The optimal cut-off point in the ROC-analyses was 15, which yielded a sensitivity of 89% and a specificity of 67% in the prediction of patient status.

CONCLUSIONS

Level of fatigue among psychiatric outpatients is high in patients with psychiatric illness, compared to levels measured in healthy volunteers. The Danish PROMIS-F-SF shows good psychometric properties in this combined sample of healthy adults and psychiatric patients with non-psychotic disorders and it is recommended as PRO measure for psychiatric populations. Examination of psychometric properties in patient populations with somatic disorder could be a natural next step.

The relationship between fatigue, sleep quality, and sleep deprivation

BACKGROUND

Fatigue, sleep disorders, and daytime sleepiness are interconnected, posing significant risks to occupational health and workplace safety. However, the literature on their relationships remains fragmented, with notable gaps, particularly concerning working populations. This descriptive cross-sectional study aimed to evaluate sleep quality (SQ), daily sleep time in hours (DST), daytime sleepiness, fatigue levels among employees in an automotive workplace, and their interrelationships.

METHODS

This study assessed fatigue, DST, SQ, and daytime sleepiness (DTS) among employees aged 21-51 years working under the same conditions. Data were collected using questionnaires and two validated scales: the Check Individual Strength Scale (CIS) for fatigue and the Epworth Sleepiness Scale (ESS) for excessive daytime sleepiness.

RESULTS

None of the Check Individual Strength Scale (CIS), or SQ points, mean values or DST hours values significantly differ due to any sociodemographic independent variables. Epworth Sleepiness Scale (ESS) points mean values differ significantly due to BMI values. However, statistically significant relationships were identified among CIS, ESS, SQ points, and DST hours. Additionally, a positive correlation was observed between ESS and CIS scores. These findings suggest reciprocal effects among fatigue, SQ, DST, and daytime sleepiness.

CONCLUSION

While sleep problems cause fatigue also chronic fatigue syndrome may be the reason of worse SQ. Further research is necessary to emphasize the importance of addressing the interplay between fatigue, excessive daytime sleepiness, SQ, and DST in hours to improve workplace safety and employee well-being.

Fatigue or excessive daytime sleepiness: which is more closely related to depression?

OBJECTIVE/BACKGROUND

This study investigated fatigue and excessive daytime sleepiness to determine which was more closely related to depression in the general population.

PATIENTS/METHODS

Participants were investigated across 15 South Korean districts. Excessive daytime sleepiness, fatigue, and depression were evaluated using the Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), and Patient Health Questionnaire-9 (PHQ-9), respectively. Depression was defined as PHQ-9 ≥ 10. The authors classified the combination of excessive daytime sleepiness and fatigue as excessive daytime sleepiness with fatigue (E+F+, ESS ≥ 11, FSS ≥ 36), fatigue without excessive daytime sleepiness (E-F+, ESS < 11, FSS ≥ 36), excessive daytime sleepiness without fatigue (E+F-, ESS ≥ 11, FSS < 36), and no fatigue and excessive daytime sleepiness (E-F-, ESS < 11, FSS < 36).

RESULTS

Among 2,493 participants (1,257 women), mean age was 47.9 ± 0.3 years. The prevalence of depression, fatigue, and excessive daytime sleepiness was 8.4% (n = 210), 30.8% (n = 767), and 15.3% (n = 382), respectively. The frequency of the four categories with depression (vs. controls) was as follows.: E+F+ (n = 67, 31.9% vs. 7.3%) (P < 0.001), E-F+ (n = 71, 33.8% vs. 20.3%) (P < 0.001), E+F-( n = 16, 7.6% vs. 5.8%) (P = 0.294), and E-F- (n = 56, 26.7% vs. 66.6%) (P < 0.001). After adjusting for covariates, depression was associated with E+F+ (odds ratio, OR 8.804, 95% confidence interval (CI) 5.818-13.132), E-F+ (OR 3.942, 95% CI 2.704-5.747), E+F- (OR 2.812, 95% CI 1.542-5.131), and E-F- (reference). Additionally, we performed logistic regression according to two categories. There was no significant difference in the association of depression between E+F- (reference) and E-F+ (OR 1.399, 95% CI 0.760-2.575).

CONCLUSION

Although fatigue and excessive daytime sleepiness were associated with depression regardless of the presence of each other, we could not clarify which was more closely related to depression.

Factors affecting physical and mental fatigue in adults from South Korea: A cross-sectional study

In modern society, demanding and stressful events contribute to increased fatigue in adults. Moreover, fatigue is the most prevalent symptom of long coronavirus disease 2019. Fatigue is a subjective feeling of tiredness that can be attributed to various causes. This cross-sectional study investigated factors affecting physical and mental fatigue in adults living in South Korea. Self-reported data were collected through an online survey conducted between July 11 and July 17, 2021. The final sample comprised 362 participants, excluding those with uncertain responses. The collected data were analyzed using IBM SPSS version 27.0. General characteristics and variables of the participants were examined through descriptive statistical analysis. Differences in fatigue level according to the general characteristics of the participants were analyzed using t tests and one-way analysis of variance. The correlation between variables was analyzed using Pearson correlation coefficients. To investigate factors affecting fatigue, stepwise multiple regression analysis was conducted. The overall level of fatigue according to participants' general characteristics differed significantly based on alcohol use, economic status, number of chronic diseases, stress, depression, and sleep problems. Factors affecting physical fatigue were depression, sleep problems, General Health Questionnaire (GHQ-12) scores, and number of chronic diseases. The factors affecting mental fatigue were depression, GHQ-12 score, and alcohol use. The variables that had the most significant impact on overall fatigue were alcohol consumption, the number of chronic illnesses, depression, and GHQ-12, in that order. This emphasizes the importance of lifestyle improvement and dietary management in adults for preventing chronic diseases and managing mental health. The results of this study should be considered when planning health services to provide fatigue interventions for Korean adults.

Distinct Profiles of Morning and Evening Fatigue Co-Occurrence in Patients During Chemotherapy

BACKGROUND

Morning and evening fatigue are distinct and distressing symptoms experienced during chemotherapy that demonstrate a large amount of interindividual variability.

OBJECTIVES

The objectives of this study were to identify subgroups of patients with distinct morning and evening fatigue co-occurrence profiles and evaluate for differences among these subgroups in demographic, clinical, and symptom characteristics and quality of life.

METHODS

Oncology patients ( n = 1,334) completed the Lee Fatigue Scale to self-report morning and evening fatigue, six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct morning and evening physical fatigue profiles.

RESULTS

Four distinct morning and evening fatigue profiles were identified (i.e., Both Low, Low Morning + Moderate Evening, Both Moderate, and Both High). Compared to the Both Low profile, the Both High profile was significantly younger, less likely to be married or partnered, more likely to live alone, had a higher comorbidity burden, and lower functional status. The Both High profile had higher levels of anxiety, depressive symptoms, sleep disturbance, and pain and lower levels of quality of life.

DISCUSSION

The variability in the morning and evening severity scores among the four profiles supports the hypothesis that morning and evening fatigue are distinct but related symptoms. Clinically meaningful levels of both morning and evening fatigue were reported by 50.4% of our sample, which suggests that the co-occurrence of these two symptoms is relatively common. Patients in Both Moderate and Both High profiles experienced an extremely high symptom burden that warrants ongoing assessments and aggressive symptom management interventions.

Evaluating the psychometric properties of the fatigue severity scale using item response theory

BACKGROUND

Fatigue is a common daily experience and a symptom of various disorders. While scholars have discussed the use of the Fatigue Severity Scale (FSS) using item response theory (IRT), the characteristics of the Japanese version are not yet examined. This study evaluated the psychometric properties of the FSS using IRT and assessed its reliability and concurrent validity with a general sample in Japan.

METHODS AND MEASURES

A total of 1,007 Japanese individuals participated in an online survey, with 692 of them providing valid data. Of these, 125 participants partook in a re-test after approximately 18 days and had their longitudinal data analyzed. In addition, the graded response model (GRM) was used to assess the FSS items' characteristics.

RESULTS

The GRM's results recommended using seven items and a 6-point scale. The FSS's reliability was acceptable. Furthermore, the validity was adequate from the results of correlation and regression analyses. The synchronous effects models demonstrated that the Multidimensional Fatigue Inventory (MFI) enhanced depression, and depression enhanced FSS.

CONCLUSION

This study suggested that the Japanese version of the FSS should be a 7-item scale with a 6-point response scale. Further investigations may reveal the different aspects of fatigue assessed by the analyzed fatigue measures.

Multivariate patterns of disrupted sleep longitudinally predict affective vulnerability to psychosis in 22q11.2 Deletion Syndrome

22q11.2 deletion syndrome (22q11DS) contributes dramatically to increased genetic risk for psychopathology, and in particular schizophrenia. Sleep disorders, including obstructive sleep apnea (OSA), are also highly prevalent, making 22q11DS a unique model to explore their impact on psychosis vulnerability. Still, the contribution of sleep disturbances to psychosis vulnerability remains unclear. We characterized the sleep phenotype of 69 individuals with 22q11DS and 38 healthy controls with actigraphy and sleep questionnaires. Psychiatric symptoms were measured concomitantly with the baseline sleep assessment and at longitudinal follow-up, 3.58±0.85 years later. We used a novel multivariate partial-least-square-correlation (PLSC) approach to identify sleep patterns combining objective and subjective variables, which correlated with psychiatric symptoms. We dissected longitudinal pathways linking sleep disturbances to psychosis, using multi-layer-network-analysis. 22q11DS was characterized by a non-restorative sleep pattern, combining increased daytime fatigue despite longer sleep duration. Non-restorative sleep combined with OSA symptoms correlated with both emotional and psychotic symptoms. Moreover, a sleep pattern evocative of OSA predicted longitudinal worsening of positive and negative symptoms, by accentuating the effects of emotional dysregulation. These results suggest that sleep disturbances could significantly increase psychosis risk, along an affective pathway. If confirmed, this suggests that systematic screening of sleep quality could mitigate psychosis vulnerability in 22q11DS.

The impact of sleep quality, fatigue and social well-being on depressive symptomatology in autistic older adolescents and young adults

Depression and poor sleep quality commonly co-occur with autism, and depression has been associated with loneliness and reduced social support. In non-autistic samples, poor sleep quality and daytime fatigue also contribute to depression. However, the contribution of sleep quality and fatigue to depressive symptoms, and how they interact with social factors to influence depression in autism remain unexplored. Our aim was to examine these relationships in 114 young autistic adults aged 15-25 years (57% male) from the SASLA online, longitudinal study (baseline and 2-year follow-up). Hierarchical multiple regression models examined the association between social well-being (social integration and social contribution; T1), sleep quality (T1, T2), and fatigue (T1, T2) on depression (T1, T2). Two mediation models were conducted on T1 data predicting depression from sleep quality though fatigue and sleep quality through social well-being. Depression and fatigue scores did not change over 2 years, but sleep quality worsened. The T1 regression model was significant (R² = 36%) with fatigue and social contribution individually predicting depression symptomatology. The longitudinal regression model was also significant (adjusted R² = 57%) with social contribution (T1) as the only significant predictor of depression (T2). Fatigue trended towards mediating the sleep quality-depression relationship, while social well-being was a significant partial mediator of this relationship. Results highlight that sleep quality, fatigue, and social well-being contribute to depression among young autistic adults. Interestingly, fatigue and social well-being were independently associated with depression. Thus, addressing sleep quality and associated fatigue, and social well-being is important when treating depression in autistic individuals.

Subjective sleep quality and fatigue assessment in Polish adult patients with primary immunodeficiencies: A pilot study

Introduction

Primary immunodeficiencies (PIDs) are clinically heterogeneous disorders caused by abnormalities in the immune system. However, PIDs are genetically determined and may occur at any age from early childhood to elderly age. Due to chronic patterns, the risk of malignancy and organ damage in patients with PIDs may affect any aspect of life, including sleep patterns. To our knowledge, the prevalence of insomnia and subjective sleep quality have not been investigated in patients with PIDs. Therefore, this pilot study was conducted to investigate sleep quality, the prevalence of sleep disturbances, and fatigue in adult patients with PIDs in Poland.

Methods

All participants were surveyed using the Athens Insomnia Scale, Pittsburgh Sleep Quality Index, Fatigue Severity Scale, and a questionnaire concerning general health and demographic data. We included 92 participants: 48 women (52.2%) and 44 men (47.8%).

Results

Participants' mean age was 41.9 ± 13.9 years. The mean sleep duration was 7.0 ± 1.5 hours, and the mean sleep latency was 41.2 ± 53.1 minutes. Additionally, 44.6% of patients (n=41) had symptoms of insomnia and 44.6% (n=42) had poor sleep quality. Less than one-fourth (n=22; 23.9%) of the patients reported the use of sleeping pills; moreover, clinically significant fatigue was reported in 52.2% (n=48).

Discussion

Our investigation provides insight into the problem of sleep disturbances in patients with PIDs. Data have demonstrated that sleeping disorders with concomitant fatigue are common in patients with PID. Further studies are needed to determine the determinants of poor sleep quality in this specific group of patients.

Relationships among pulmonary function, anxiety and depression in mild asthma: An exploratory study

In a secondary analysis of data from a prior study, we calculated the relationships among depression (PHQ-8), anxiety (GAD-7), and measures of asthma in 69 steroid-naïve patients with mild and moderate symptomatic asthma. Average levels of pulmonary function, depression and anxiety tended to be in the normal range, and asthma tended to be well controlled (Asthma Control Test). Nevertheless, PHQ-8 scores were significantly correlated with forced oscillation (FO) measures of airway reactance (AX) and resistance at a low frequency of stimulation (Rrs_5Hz). GAD-7 scores also were significantly related to Rrs_5Hz. Exploratory analyses in supplementary data provide no evidence for vagal mediation of the association. Further research is necessary to discover mechanisms for the associations found here. Future studies might examine the utility of assessing and treating mild anxiety and depression in mild to moderate asthma.