Psychometric properties of fatigue severity scale in Chinese systemic lupus erythematosus patients

Exploring Psychoneurological Symptom Clusters in Acute Stroke Patients: A Latent Class Analysis

Purpose

To identify latent classes of acute stroke patients with distinct experiences with the symptom clusters of depression, anxiety, fatigue, sleep disturbance, and pain symptoms and assess, if the selected variables determine a symptom-cluster experience in acute stroke patients.

Participants and Methods

A sample of 690 participants were collected from July 2020 to December 2020 in a cross-sectional descriptive study. Latent class analysis was conducted to distinguish different clusters of acute stroke participants who experienced five patient-reported symptoms. Furthermore, multinomial logistic regression was selected to verify the influencing indicators of each subgroup, with selected socio-demographic variables, clinical characteristics, self-efficacy, and perceived social support as independent variables and the different latent classes as the dependent variable.

Results

Three latent classes, named “all high symptom,” “high psychological disorder,” and “all low symptom,” were identified, accounting for 9.6%, 26.3%, and 64.1% of symptom clusters, respectively. Patients in the “all high symptom” and “high psychological disorder” classes reported significantly lower quality of life (F=40.21, p <0.05). Female gender, younger age, higher National Institutes of Health Stroke Scale scores, and lower self-efficacy and perceived social support were risk factors associated with the “high psychological disorder” class. Younger patients with lower self-efficacy and perceived social support were more likely to be in the “all high symptom” class.

Conclusion

This study identified latent classes of acute stroke patients that can be used in predicting symptom-cluster experiences following a stroke. Also, the ability to characterize subgroups of patients with distinct symptom experiences helps identify high-risk patients. Focusing on symptom clusters in clinical practice can inspire us to create effective targeted interventions for subgroups of stroke patients suffering from the same symptom cluster.

Quality of life measures in Systemic Lupus Erythematosus: A systematic review

In this study we systematically investigated the health-related quality of life (HRQoL) tools, which have been most often used over the last five years to evaluate the QoL in patients with systemic lupus erythematosus (SLE), focusing on their items and applications. A detailed literature search was conducted: the inclusion criteria were as follows: 1) studies including at least 50 patients; 2) studies including at least 25 patients with SLE; 3) quality of life testing with validated measures. The systematic review was based on 119 studies for a total of 32,449 SLE patients and 3092 controls. A total of 35 different patients-reported quality of life measures, applied in cohorts of patients with SLE, were retrieved with the 36-item Medical Outcome Short Form (SF-36) (63 studies of 119 =52.95%), Lupus Quality of Life (LupusQoL) (17 studies =14.3%) and Lupus Patient-Reported Outcome (LupusPRO) (12 studies =10%) being the most commonly used tools. Overall, this systematic review of the literature indicated that quality of life in patients with SLE appears to be poor and generally lower compared to both the general population and patients with other chronic conditions, as was shown by a few studies that used SF-36 and LupusPRO. The use of HRQoL scoring in SLE is gaining increasing interest and is used both in randomized controlled trials and in real-life. Future efforts are needed to improve the understanding of the impact of the disease burden on quality of life from the patient’s perspective.

Mental Health Differences in Healthcare Workers Exposed to Different Risks During the Coronavirus Disease 2019 Pandemic

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has caused a significant impact on the physical and mental health of healthcare workers. This study assessed the psychological status of healthcare workers who were exposed to different risk-levels in China and explored the factors that affected their mental health.

METHODS

Demographic, occupational characteristics, and mental health measurements were collected from 810 workers in 41 hospitals in China, through online questionnaires from February 11 to March 3, 2020. The degree of symptoms for fatigue, anxiety, and insomnia were assessed using the Chinese versions of the Fatigue Severity Scale, 7-item Generalized Anxiety Disorder Scale, and Insomnia Severity Index, respectively. Binary logistic regression analysis was performed to identify factors associated with mental health symptoms.

RESULTS

All 810 participants completed the relevant questionnaires without missing data. The prevalence of fatigue, anxiety, and insomnia symptoms was 74.3, 73.7, and 61.7%, respectively. Nurses, women, and workers exposed to high-risk areas were more likely to report mental health problems (P < 0.05). After controlling for confounders, exposure to high-risk areas was independently associated with increased symptoms of fatigue, anxiety, and insomnia (fatigue among high-risk areas: OR, 3.87; 95% CI, 2.26-6.61; P < 0.001; anxiety among high-risk areas: OR, 2.66; 95% CI, 1.58-4.51; P < 0.001; insomnia among high-risk areas: OR, 2.83; 95% CI, 1.68-4.79, P < 0.001).

CONCLUSION

The study demonstrated significant differences in psychological symptoms among healthcare workers exposed to different levels of risk, and those in high-risk areas were more vulnerable to experiencing mental health symptoms. These findings emphasize the importance of giving due attention to healthcare workers, especially women, nurses, and those working in high-risk settings during the COVID-19 pandemic.

Validation of a three-item Fatigue Severity Scale for patients with substance use disorder: a cohort study from Norway for the period 2016-2020

BACKGROUND

Little attention has been paid to customising fatigue questionnaires for patients with Substance Use Disorders (SUDs). The present study aims to validate and shorten the nine-item Fatigue Severity Scale (FSS-9) and Visual Analogue Fatigue Scale (VAFS) for use with this population.

METHODS

We used data from a nested cohort with annual health assessments with responses on the FSS-9 and VAFS. During the period 2016-2020, 917 health assessments were collected from 655 patients with SUD in Bergen and Stavanger, Norway. A total of 225 patients answered the health assessment at least twice. We defined baseline as the first annual health assessment when the health assessments were sorted chronologically per patient. We checked for internal consistency, and we used longitudinal confirmatory factor analysis (CFA) and linear mixed model (LMM) analysis to validate and shorten the FSS-9 and VAFS.

RESULTS

The internal consistency of the FSS-9 was excellent with a Cronbach's α of 0.94 at baseline and 0.93 at the second annual health assessment. When shortening the FSS-9 to a three-item FSS (FSS-3, items 5-7), the Cronbach's α was 0.87 at baseline and 0.84 at the second health assessment. The internal consistency was not affected when the VAFS was added to the FSS-3 and the FSS-9. The longitudinal CFA model showed a well-fitting model for the FSS-3 (χ² = 13.33, degree of freedom = 8, P = 0.101). The LMM analysis showed equal linear changes at the individual level for the FSS-3 (slope: 0.00, P > 0.05) and FSS-9 (slope: 0.01, P > 0.05) between the health assessments.

CONCLUSION

The FSS-9 could be shortened to the FSS-3 with high validity and reliability for patients with SUDs and the addition of VAFS did not provide much added variability.