Correlation of internalized stigma with self-esteem, social support and coping styles in patients with rheumatoid arthritis: A cross-sectional study.

AIM: To understand the status of internalized stigma in patients with rheumatoid arthritis (RA) and explore its relationship with self-esteem, social support, and coping style. METHODS: This cross-sectional study selected patients with RA who visited the Rheumatology and Immunology Department of a tertiary hospital from May 2022 to May 2023. The Chinese versions of the Internalized Stigma of Mental Illness Scale-Rheumatoid Arthritis (ISMI-RA), Social Support Rating Scale, Rosenberg Self-Esteem Scale, and Medical Coping Style Questionnaire were administered to assess the internalized stigma, social support, self-esteem, and coping styles, respectively. The Pearson correlation test or Spearman rank correlation was then used to analyze the correlation between these measures. RESULTS: Overall, 69.5% participants reported high level of internalized stigma. The average age of the 174 participants was 52.67 ± 12.24 years, with 87.36 per cent female patients. The mean ISMI-RA score was 54.49 ± 9.62, and the ISMI-RA subscale with the highest average score was alienation. The Pearson's correlations show that internalized stigma was positively associated with the coping styles of avoidance (r = .212, p < .01) and acceptance (r = .560, p < .01), and that internalized stigma was negatively associated with the coping styles of confrontation (r = -.479, p < .01), social support (r = -.570, p < .01), and self-esteem(r = -.512, p < .05). CONCLUSION: The high level of internalized stigma in RA patients suggests that we should develop interventions to improve patients' self-esteem, encourage them to adopt positive coping styles, and gain more social support for them, so as to alleviate their internalized stigma.

Latent characteristics and influencing factors of stigma in rheumatoid arthritis: A latent class analysis.

To explore the latent classes of stigma in patients with rheumatoid arthritis, we analyzed the characteristics of the different categories. Adopting a convenient sampling method, socio-demographic and disease-related information from the outpatient clinics and wards of 3 tertiary care hospitals in China was collected. The Chinese version of the Internalized Stigma of Mental Illness scale-Rheumatoid Arthritis was used in this survey. Rheumatoid arthritis stigma was divided into 3 potential categories: Low Stigma-Strong Resistance (83, 41.5%), Medium Stigma-Strong Alienation (78, 39.0%), and High Stigma-Weak Resistance (39, 19.5%). Unordered multinomial logistic regression analysis showed that pain (OR = 1.540, P = .005; OR = 1.797, P < .001), elementary school education and below (OR = 4.051, P = .037), and duration of morning stiffness (OR = 0.267, P = .032) were risk factors for stigma, whereas family history was a protective factor against stigma (OR = 0.321, P = .046). Patients with longer morning stiffness, more severe pain, and less education have a greater risk of heavier stigma. Strong alienation is an early warning of heavy stigma. Resistance to stigma and family support can help patients overcome their psychological obstacles. More attention should be paid to constructing family centered support systems to help resist stigma.

Self-reported sleep disturbance is significantly associated with depression, anxiety, self-efficacy, and stigma in Chinese patients with rheumatoid arthritis.

The objective of this article is to assess self-reported sleep disturbance and identify psychological, clinical, and sociodemographic factors that might influence sleep disturbance in patients with rheumatoid arthritis (RA). The study included 141 patients with confirmed RA (84.4% women, mean age 56.87 years). The Pittsburgh Sleep Quality Index, the Chinese version of rheumatoid arthritis self-efficacy scale, the Chinese version of Anxiety Depression Distress Inventory-27, the Chinese version of Stigma Scale for Chronic Illness, Visual Analogue Scale-Pain, disease activity index were used. Sleep disturbance was positively correlated with age, pain, disease activity, depression and anxiety, and stigma, while self-efficacy was correlated negatively with sleep disturbance. Multiple linear regression analysis revealed that depression, anxiety, self-efficacy, and stigma explained 77.4% of sleep quality variance. The data has demonstrated a suggestive relationship between low sleep quality and anxiety, depression, self-efficacy, and stigma. Patients reporting poor sleep, fatigue, and pain might have particular psychological intervention needs focusing on distress or anxiety symptoms, low self-efficacy, and high stigma.

Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease with depression as one of its most common symptoms. The aim of this study is to establish a nomogram prediction model to assess the occurrence of depression in patients with SLE. Based on the Hospital Anxiety and Depression Scale cutoff of 8, 341 patients with SLE, recruited between June 2017 and December 2019, were divided into depressive and non-depressive groups. Data on socio-demographic characteristics, medical history, sociopsychological factors, and other risk factors were collected. Between-group differences in clinical characteristics were assessed with depression as the dependent variable and the variables selected by logistic multiple regression as predictors. The model was established using R language. Marital status, education, social support, coping, and anxiety predicted depression (p < 0.05). The nomogram prediction model showed that the risk rate was from 0.01 to 0.80, and the receiver operating characteristic curve analysis showed that the area under the curve was 0.891 (p < 0.001). The calibration curve can intuitively show that the probability of depression predicted by the nomogram model is consistent with the actual comparison. The designed nomogram provides a highly predictive assessment of depression in patients with SLE, facilitating more comprehensive depression evaluation in usual clinical care.

A Structural Equation Model of Health-Related Quality of Life in Chinese Patients With Rheumatoid Arthritis.

Background: The aim of this study was to examine how body image, Disease Activity Score in 28 joints, the feeling of being anxious, depression, fatigue, quality of sleep, and pain influence the quality of life (QoL) in patients with rheumatoid arthritis (RA). Methods: A multicenter cross-sectional survey with convenience sampling was conducted from March 2019 and December 2019, 603 patients with RA from five hospitals were evaluated using the Body Image Disturbance Questionnaire, Disease Activity Score in 28 joints, Hospital Anxiety and Depression Scale, Fatigue Severity Scale, Pittsburgh Sleep Quality Index, Short Form 36 Health Survey, and Global Pain Scale. The relationship between quality of life and other variables was evaluated by using the structural equation model (SEM). Results: A total of 580 patients were recruited. SEM fitted the data very well with a root mean square error of approximation (RMSEA) of 0.072. Comparative fit index of 0.966, and Tucker-Lewis index of 0.936. The symptoms and the normalized factor load of six variables showed that the normalized factor load of pain was 0.99. Conclusions: The QoL model was used to fit an SEM to systematically verify and analyze the population disease data, biological factors, and the direct and indirect effects of the symptom group on the QoL, and the interactions between the symptoms. Therefore, the diagnosis, treatment and rehabilitation of RA is a long-term, dynamic, and complex practical process. Patients' personal symptoms, needs, and experiences also vary greatly. Comprehensive assessment of patients' symptoms, needs, and experiences, as well as the role of social support cannot be ignored, which can help to meet patients' nursing needs, improve their mood and pain-based symptom management, and ultimately improve patients' QoL.

microRNA-23 inhibits inflammation to alleviate rheumatoid arthritis via regulating CXCL12.

Rheumatoid arthritis (RA) is a common systemic, inflammatory and autoimmune disorder. MicroRNAs (miRs) are strongly associated with the initiation and progression of RA. However, the functions and mechanisms underlying miR-23 in RA are not completely understood. Therefore, the present study aimed to investigate the molecular mechanisms underlying miR-23 in RA. A bioinformatics tool (StarBase) and a wide range of experimental assays, including reverse transcription-quantitative PCR, western blotting, luciferase reporter assays and ELISAs, were performed to investigate the biological role of miR-23 in RA. The results indicated that miR-23 was downregulated and chemokine C-X-C motif ligand 12 (CXCL12) was upregulated in RA samples compared with healthy samples. Furthermore, miR-23 overexpression suppressed inflammation via reducing TNF-α, IL-1ß and IL-8 expression levels compared with the NC mimic group. Regarding the underlying mechanism, compared with NC mimic, miR-23 mimic decreased CXCL12 mRNA expression by binding to its 3'-untranslated region. Additionally, CXCL12 overexpression reversed miR-23 mimic-mediated effects on inflammation. NF-κB signaling is associated with inflammation. Therefore, the present study indicated that CXCL12 promoted inflammation by activating NF-κB signaling. In conclusion, miR-23 inhibited inflammation to alleviate RA by regulating CXCL12 via the NF-κB signaling pathway, which may serve as a potential target for the diagnosis and treatment of RA.