The relation between clinical characteristics and mental health in patients with Rheumatoid Arthritis

The relation between clinical characteristics and mental health in patients with Rheumatoid Arthritis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The relation between clinical characteristics and mental health in patients with Rheumatoid Arthritis Samantha Castro-Teixeira, Geraldo Rocha Castelar-Pinheiro, Jaqueline Carvalho Rodrigues This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6924681/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 23 You are reading this latest preprint version Abstract This study analyzed the influence of pain perception, functional capacity, quality of life, and disease activity on the mental health of patients with Rheumatoid Arthritis (RA). A quantitative cross-sectional cohort study was conducted with 461 adults ( M = 65.10; SD = 12.00), of whom 415 were women. Participants completed a sociodemographic and health conditions questionnaire, the Health Assessment Questionnaire Disability Index (HAQ-DI), the 12-item Short Form Health Survey (SF-12), and the Clinical Disease Activity Index (CDAI). Regression analyses revealed that CDAI (β = -0.066), fatigue (β = -0.143), joint pain (β = -0.079), HAQ-DI (β = 0.093), physical SF-12 (β = -0.222), poor sleep quality (β = -0.065), stress (β = -0.197), anxiety (β = -0.087), and depression (β = -0.312) significantly predicted mental health outcomes. Therefore, RA may negatively affect patients’ mental health, being associated with stress, poor sleep, depression, and anxiety, which in turn may exacerbate pain perception. Incorporating quality of life assessments into routine clinical consultations may provide a more comprehensive approach to care, addressing both physical and emotional dimensions of health in patients with RA. Biological sciences/Psychology Health sciences/Diseases Health sciences/Medical research Health sciences/Rheumatology Health sciences/Health care/Health services Health sciences/Health care/Quality of life pain chronic disease mental health Rheumatoid Arthritis Figures Figure 1 Figure 2 Introduction According to the World Health Organization [ 1 ] one person under the age of 70 dies every two seconds because of a chronic non-communicable disease characterized by slow development and long duration, with chronic pain being a common symptom [ 1 ]. Chronic pain usually persists for more than three months and can continue for more than a month after an acute or unhealed injury [ 2 ], being one of the symptoms of Rheumatoid Arthritis (RA). RA is an autoimmune, and systemic disease, which manifests itself mainly by inflammation in the peripheral joints and can cause progressive damage to bone and cartilage. As well as the joints, RA can have systemic manifestations, affecting organs such as the lungs, skin, and eyes [ 3 ]. In 2020, 17.6 million people had RA worldwide [ 4 ]. In 2019, according to IBGE (Brazilian Institute of Geography and Statistics) data[ 5 ] 7.9% of the Brazilian population reported having RA or Rheumatism. Therefore, it is important that healthcare professionals understand the clinical characteristics of this disease. RA is diagnosed based on clinical findings and complementary tests. Although the classification criteria proposed in 2010 by the American College of Rheumatology - ACR[ 6 ] and the European Alliance of Rheumatology Associations - EULAR[ 7 ] are useful in assessing patients, they should not be used as a diagnostic tool[ 7 ], [ 8 ]. Despite being a recognized disease with several treatment guidelines, RA has no specific blood markers, but the presence or absence of antibodies against citrullinated proteins/peptides (Anti-CCP) and Rheumatoid Factor (RF) together can corroborate the diagnosis [ 9 ], [ 10 ]. Pain and physical disability are known risk factors for symptoms of anxiety and depression in RA patients [ 11 ], [ 12 ], [ 13 ], [ 14 ], [ 15 ]. In this context, many patients with RA may experience low quality of life, depression, and anxiety [ 16 ], [ 17 ]. Furthermore, it has been identified that patients with more motor disability due to RA tend to have more depressive symptoms [ 18 ]. Concerning clinical analyses, RA and positive RF may be negatively associated with well-being in mental health, sleep, and cognition [ 12 ], [ 19 ]. In addition, there is a possible connection between stressful events, mental disorders, and the increased risk of triggering RA [ 17 ], [ 20 ], [ 21 ], [ 22 ]. One study showed that 86% of patients with rheumatic disease had experienced stressful events before the onset of the disease, relating psychological factors to the onset of RA. This occurs since chronic stress can have a negative influence on the immune system, thus increasing inflammatory processes which, in turn, are directly related to the onset of rheumatic diseases [ 23 ]. The association between RA activity and symptoms of anxiety and depression has previously been analyzed in the literature [ 24 ], using the Patient Global Assessment (PtGA) Severity and the Health Assessment Questionnaire Disability Index (HAQ-DI) as measures. According to the Uda et al. (2021), patients who were not in remission were more likely to have anxious and depressive symptoms. This result suggests that symptomatically active RA, characterized by chronic pain and physical limitations, may worsen an individual’s mental health. It is therefore important to consider including psychological care into treatment plans to improve patients' quality of life. Subsequently, Feng et al. (2024) investigated 314 patients, in whom RA activity was classified using the Disease Activity Score (DAS28), with the following criteria: clinical remission ( 5.1). The results showed that patients with moderate and high disease activity had higher levels of functional disability (HAQ-DI) and lower Health-Related Quality of Life (HRQoL) scores, when compared to patients in clinical remission. Multiple linear regression analysis revealed that mental health was one of the variables most impacted by disease activity. Moreover, evaluations using the 12-Item Health Survey (SF-12) showed that both physical and mental aspects were compromised by RA, with a more marked reduction in HRQoL in patients with more severe forms of the disease. These findings highlight the relevance of investigating how RA affects physical and psychological well-being, emphasizing the need for studies that can support interventions focused on improving patients' quality of life. This study aimed to analyze the influence of pain perception, functional capacity, quality of life, and disease activity on the mental health of patients with RA. The specific objectives were to analyze the relationship between the patient's mental health, measured by the Mental SF-12, and clinical variables, including the Clinical Disease Activity Index (CDAI), fatigue, joint pain, Functional Capacity (HAQ), physical health (Physical SF-12), specific mental health issues (depression, sleep, anxiety, stress) and symptom duration. Using network analysis, we initially sought to explore associations between pain intensity, quality of life, and RA activity and the influence of these variables on mental health. Then, through multiple linear regression, the study verified which variables best explained patients' mental health., the study verified which variables explained patients' mental health, providing a deeper understanding of the critical determinants in patients with this chronic condition. The main hypotheses of this study based on the literature were: 1) There is a negative relationship between the patient's mental health (Mental SF-12) and the Clinical Disease Activity Index (CDAI), fatigue, joint pain, depression, anxiety, stress and symptom time and positive with functional capacity (HAQ), physical health (Physical SF-12) and sleep quality [ 23 ], [ 24 ], [ 25 ]; 2) Variables such as depression, anxiety and stress will have a significant impact on measures of Quality of Life (QoL) and mental health [ 11 ], [ 12 ], [ 13 ], [ 14 ], [ 15 ]; 3) Physical health (Physical SF-12) will have a positive relationship with mental health (Mental SF-12), suggesting that both physical and mental health outcomes are associated [ 25 ]; 4) Symptom time and fatigue will be negatively correlated with mental health [ 11 ]. Understanding the QoL and mental health of these patients can be influenced by a complex interaction of biopsychosocial factors, providing important information to direct both health policies and personalized treatments. Method Design This research was part of a cohort designed to assess the predominant patterns of clinical management of Brazilian patients with RA in everyday practice. A cross-sectional study was carried out, using a quantitative description of trends in a sample of the population [26]. Participants We analyzed data from a larger study coordinated by the RA outpatient clinic of a public institution, between August 2015 and April 2016. The inclusion criteria for the study were: 1) meeting the 2010 American Rheumatism Association (ARA) or American College of Rheumatology (ACR)/ European League Against Rheumatism (EULAR) classification criteria for RA (Aletaha et al., 2010; Arnett et al., 1988); 2) age 18 years or older; and 3) documented medical record data from at least six months of follow-up at their health center before enrolling in the study. A total of 1115 participants were assessed, of whom 18 were excluded for not having RF data, 315 for not having Anti-CCP values, 318 for not having Mental SF-12 data, one for not having sleep data, one for not having depression data, and one for not having a CDAI, totaling 461 participants. Table 1 presents the sociodemographic data of the participants. INSERT TABLE 1 Data collection procedures The research was conducted in 11 Brazilian centers specializing in the treatment of patients diagnosed with RA. Most of the information was collected during medical consultations, while previous medical records served as secondary sources for biomarkers such as RF and Anti-CCP, which were tested prior to the patients’ arrival at the outpatient clinic. All data was stored in electronic medical records and compiled into a central database. There were three evaluation points. During the initial medical visit, sociodemographic information and lifestyle habits were collected. At this stage, the duration of the disease, RF positivity, and Anti-CCP levels were assessed. Additionally, participants were interviewed about how they managed stress, anxiety, depression, and sleep quality. Responses were measured on a questionnaire developed by the researchers, ranging from no difficulty, some difficulty, a lot of difficulty, to inability to perform, with scores ranging from -1 to 2. Pain perception was assessed using the Visual Analog Scale (VAS), with scores ranging from zero (no pain) to 100 (maximum pain). The following scales were also applied: the Health Assessment Questionnaire (HAQ), the Disability Index (DI), the 12-item Health Survey (SF-12), and the Clinical Disease Activity Index (CDAI). During the subsequent follow-up and final appointments, the previous collected data were reviewed to monitoring the progression of the disease. Instruments The following instruments were administered during the evaluations: 1) Sociodemographic and health conditions questionnaire The questionnaire aimed to collect data on socioeconomic profile, family history of rheumatoid arthritis, presence of other autoimmune diseases or associated conditions, personal history of comorbidities, and lifestyle habits (such as smoking, alcohol consumption, and physical activity) of the participants. It also included measures of anxiety, stress, non-restorative sleep, and depression, assessed using an instrument adapted from Sokka et al. (2009), based on the Multi-Dimensional Health Assessment Questionnaire (Pincus et al., n.d.). Response options were: “unable to do” (-1), “no difficulty’ (0), “some difficulty” (1), and “much difficulty” (2). In the present study, the Cronbach’s alpha coefficient was 0.811 (p < 0.001) for the total scale. 2) The Health Assessment Questionnaire (HAQ) Disability Index (DI) – HAQDI [27], [28] The HAQ-DI is used to monitor the progression of the disease and the effectiveness of the treatment, providing insight into the functionality of the patients. It is a self-assessment questionnaire made up of 20 questions related to daily activities, covering eight components that assess the musculoskeletal system. These components cover tasks such as dressing, getting up, eating, walking, personal care, reaching, grip strength, and other related activities. Each question has four answer options, ranging from zero to 3: “no difficulty at all” (0), “with some difficulty” (1), “with great difficulty” (2) and “unable to perform” (3)”. Higher scores mean greater disability. In the validation of the HAQ for Brazil (Ferraz et al., 1990), Cronbach's alpha coefficient was 0.905 (p<0.001), and the inter-observer correlation coefficient was 0.830 (p<0.001). Cronbach's alpha coefficient in this study was 0.811 (p<0,001). 3) 12-Item Health Survey (SF-12) [29], [30] The SF-12 is a questionnaire used to assess health-related QoL. It emerged as a simplified version of the SF-36 and can be administered in two minutes. The SF-12 consists of a combination of 12 closed and multiple-choice questions to calculate the three final scores for the physical, mental, and health-related QoL dimensions. The questionnaire ranges from zero to 100, with higher scores indicating better QoL. Scores approaching 50 reflect a situation like that of the general population, while values below 50 indicate a lower QoL than the population average. Cronbach's alpha coefficient in this study was 0.960 (p<0,001). 4) Clinical Disease Activity Index (CDAI) [31], [32] The CDAI is a measure of RA activity, which considers a series of parameters calculated by adding up the number of painful and swollen joints (28 joints), as well as the global assessment of disease activity by the patients and the doctors, both classified on a scale of zero to 10. The total CDAI score ranges from zero to 76 and is used to classify RA activity into four levels: remission (≤2.8), low (2.9-10), moderate (10.1-22), and high (>22). Dissanayake et al. (2022) found a Cronbach's alpha coefficient of 0.868 in their validation of the instrument. Ethical procedures Data collection procedures for this study were reviewed and approved by the National Research Ethics Committee of the Ministry of Health in Brazil (approval number: blind) in accordance with national regulations and ethical standards for research involving human participants. Prior to participation, all individuals received detailed information about the study and signed a Free and Informed Consent Form confirming their voluntary agreement to participate and to allow publication of the anonymized data. All participants were informed that their identities would remain confidential and that responses would be fully anonymized. The research team made sure that the entire data collection process respected participants’ privacy and followed ethical procedures, including the protection of sensitive information. Participants were also informed that the instruments used posed minimal risk to their physical or psychological health. Data analysis To explore the associations among the variables, a network analysis approach was used. It was performed using the EBICglasso method, aiming to remove spurious and weak correlations, examine the strength of the identified associations in the regression model, and explore their connections with clinical and mental health measures. The glasso method was estimated using a regularized solution based on the Extended Bayesian Information Criterion (EBIC). This approach enables an exploratory analysis of the association structure among variables, in which the relationships within the system are not pre-specified, allowing for the identification of emergent patterns based on empirical data [33]. This method allowed for a visual and statistical examination of the relationships between biological (e.g., rheumatoid factor, Anti-CCP), clinical (e.g., Clinical Disease Activity Index – CDAI, joint pain, fatigue, HAQ), and psychosocial variables (e.g., SF-12 Mental and Physical Health components: stress, anxiety, depression, and sleep disturbances). In network analysis, each variable is represented as a node, and the associations between variables are depicted as edges. The thickness and color of the edges reflect the strength and direction of the associations, respectively. Directionality was determined using partial correlations: blue edges indicate positive associations, red edges indicate negative associations, and the absence of an edge suggests that—after controlling for all other variables—there is no statistically significant relationship between the corresponding nodes. This method enables the simultaneous visualization of the interdependence among multiple variables, helping to identify interconnected structures and potential clusters of symptoms or psychological factors [34]. The relations identified in network analysis were included in a multiple linear regression model. The multiple linear regression analysis included as predictor variables the CDAI, fatigue, joint pain, HAQ, Physical SF-12, Multi-Dimensional Health Assessment Questionnaire (depression, sleep, anxiety, and stress), and as an outcome variable mental health (Mental SF-12). Therefore, the analyses sought to answer which variables have the greatest impact on mental health of the patients. Results Initially, a network analysis was conducted to examine the associations among clinical, and psychological variables. In the network model, RF was positively associated with anti-CCP antibodies, demonstrating the strongest connection in the network (0.65). However, no significant connections were found between these biomarkers and psychological variables or mental health indicators. In addition, pain showed a moderate positive association with CDAI (0.48) and a weaker positive connection with fatigue (0.23). Additionally, CDAI and fatigue were negatively associated with the SF-12 Physical and Mental Health components, although these associations were weak. Furthermore, among the psychological variables, stress demonstrated moderate positive associations with poor sleep quality (0.27), anxiety (0.49), and depression (0.37). Additionally, depression symptoms were negatively associated with mental health (−0.34), and stress also showed a negative association with mental health (−0.24). The network did not show any significant direct association between RF or anti-CCP and the mental health node. Overall, the network structure revealed clusters around mental health symptoms (stress, anxiety, depression) and disease activity (pain, CDAI, fatigue), as well as connections between functional and physical health indicators (HAQ, SF-12 Physical, SF-12 Mental), as illustrated in Figure 1. INSERT FIGURE 1 In terms of centrality, depressive symptoms stood out with the highest values of closeness and strength, indicating that this variable was the most interconnected and influential within the network. It also presented a high betweenness, suggesting that it plays a key role in linking different parts of the network. Anxiety, stress, and poor sleep also showed high centrality indices, reinforcing their importance in the network structure. On the other hand, RF and anti-CCP presented the lowest centrality values, showing tiniest integration with the rest of the network (Figure 2). INSERT FIGURE 2 Multiple regression analysis (Table 2) was carried out to examine the predictive capacity of the variables CDAI, fatigue, pain, HAQ, physical SF-12, poor sleep, stress, anxiety, and depression (independent variables) on mental SF-12 (dependent variable). Multicollinearity was assessed using the Variance Inflation Factor (VIF) and tolerance, with values falling within acceptable limits—VIF ranging from 1.01 to 2.28 and tolerance greater than 0.2. The Durbin-Watson test indicated independence of the residuals, with a value of 1.98. The regression model examining predictors of mental health (Mental SF-12) was statistically significant, F (1, 9) = 20.082, p < .001, indicating that the model reliably predicts mental health outcomes. The model accounted for approximately 53.6% of the variance in mental health scores (R² = .536), suggesting a moderate to strong explanatory power. Among the variables included, depressive and physical symptoms were found to be the variables that best explained poorer mental health among patients with RA. Levels of fatigue, stress, and the perception of lower QoL also contributed to greater mental health problems, as shown in Table 2. The level of fatigue and worse QoL also contributed to explaining greater mental health problems, as can be seen in Table 2. INSERT TABLE 2 Discussion This study investigated the relation between physical aspects, QoL, and mental health in patients with RA, aiming to assess the impact of these variables on psychological well-being. The combination of regression and network analysis reinforces the hypothesis that mental health in RA patients is not determined by a single factor but by a complex interplay between physical and emotional symptoms [23], [24], [25]. The results highlight the complexity of RA and their consequences, underscoring the importance of comprehensive interviews to understand the clinical manifestations in each patient. Network analysis revealed that greater RA severity was related to mental health outcomes, including fatigue, pain, perceived stress, anxiety, and depression symptoms. These results corroborate the findings of Feng et al. (2024), who demonstrated that RA compromises the mental health and QoL of patients with more severe forms of the disease, as joint pain, one of the primary symptoms of the disease, can be debilitating. Chronic pain is frequently associated with psychological stress, anxiety, and depression, directly affecting mental health [24], [35], [36]. The main predictors of mental health were fatigue, functional capacity, physical health, perceived stress, and depressive symptoms. These findings are consistent with previous research suggesting that psychological and physical factors interact in influencing the mental health of individuals living with chronic conditions such as rheumatoid arthritis (RA). Fatigue and depressive symptoms are not only prevalent in RA but are also among the strongest predictors of psychological distress and reduced quality of life [37], [38]. These findings also were further supported by network analysis, which provided an integrative perspective of the interactions among the variables. Rather than isolating relationships, the network model identified depressive symptoms as the most central node, with high strength, closeness, and betweenness values. This suggests that depression plays a central role in connecting and influencing various domains, including physical, emotional, and functional aspects. In individuals living with chronic conditions such as rheumatoid arthritis, depressive symptoms often emerge not only as a psychological response to the illness but also as a factor that intensifies pain perception, fatigue, and functional limitations [13], [39], [40]. Depression has been associated with greater disease burden and poorer treatment outcomes, acting as consequence and as influencer to reduced quality of life [41]. Its presence can worsen self-regulatory capacities, reduce engagement in coping strategies, and negatively impact motivation for self-care, thereby creating a reinforcing cycle between emotional distress and physical symptomatology [42], [43], [44]. These findings underscore the importance of addressing depressive symptoms as a key target in the comprehensive management of patients with chronic diseases. Other psychological variables, such as anxiety, stress, and sleep quality, also demonstrated high centrality, highlighting their relevance in the overall experience of living with RA. Fatigue, which emerged as a significant factor in regression analyses, must be considered a central component in the deterioration of emotional well-being. Research suggest that fatigue may disrupt the regulation of neurotransmitters such as serotonin and dopamine, which are critical for mood and motivation [45], [46]. Moreover, fatigue directly impacts the ability of the patients to function and maintain their routines, contributing to a cycle of physical and emotional exhaustion [24], [39], [47]. Similarly, functional limitation—another mental health predictor—can lead to frustration, feelings of helplessness, and reduced self-esteem, fostering symptoms of anxiety and depression. Sleep quality, positively associated with mental health in both analyses, is also a key component. Adequate sleep supports emotional regulation, reduces stress, and enhances coping abilities [48]. Conversely, pain disrupts sleep, thereby exacerbating psychological distress [49]. These findings suggest that interventions targeting fatigue management, pain reduction, and improved sleep may significantly impact on mental health of the patients. Perceived stress and depressive symptoms also emerged as relevant factors, in both regression and network analyses, supporting Hypothesis 2 of the study. These variables were not only significant predictors of mental health but also acted as links between different domains in the network structure, emphasizing their role in the dynamic interplay between physical and emotional states [41], [50], [51]. Chronic stress, through prolonged activation of the hypothalamic-pituitary-adrenal (HPA) axis and the resulting increase in cortisol levels, may sensitize pain circuits and impair mood regulation, contributing to the worsening of psychological symptoms [46], [52]. Thus, emotional suffering not only coexists with physical symptoms but also amplifies them, further compromising QoL. It is important to note that RF and anti-CCP levels did not show significant associations with mental health indicators in either analysis. These results suggest that while these biomarkers are critical for the diagnosis and prognosis of RA, they are not sufficient to identify problems of mental health in the patients. The subjective experience of the disease, shaped by factors such as pain, stress, and functional limitations, plays a more substantial role in psychological suffering [37], [53]. On the other hand, chronic pain and functional impairment remain directly linked to the development of depressive and anxious symptoms [11], [12]. Therefore, it is suggested that systematic assessments of QoL and psychological symptoms must be systematically evaluated in outpatient clinics for adults with RA. In summary, RA is a complex condition requiring multidisciplinary care. The strong relation between physical and psychological symptoms, if left unaddressed, may significantly impair the well-being of the patients. The impact of RA on psychological health suggests that early interventions are essential to reduce emotional distress and preserve the QoL. Therefore, clinical practice should address not only the biomedical aspects of the disease but also its psychosocial implications, promoting more humanized and effective care. Conclusions This study showed that the physical symptoms of RA can significantly impact the mental health of the patients. Therefore, assessing well-being has the potential to complement clinical care. It is suggested that including mental health evaluations in routine consultations can offer more comprehensive and humanized follow-up, addressing both physical and emotional aspects. In this context, the presence of mental health professionals (psychologists and psychiatrists) in outpatient services is essential to ensure continuous care for patients. These findings are highly relevant for recognize the psychological impact caused by RA and contribute to improving the well-being of the patients. This study highlights the importance of integrating psychological well-being into the treatment of chronic illnesses. Patients should also be informed about how RA can directly affect mental health, helping them understand the value of a model that addresses both physical and psychological health for overall well-being. As an alternative, the creation of emotional support groups for the patients with RA could be beneficial. One of the strengths of this study was the analysis of a large cohort to investigate the associations between clinical disease variables and mental health. However, despite its important findings, the study had some limitations. First, instead of formal psychiatric diagnoses, it relied on self-reported anxiety, stress, sleep, and depression symptoms. Therefore, it is recommended that future studies use formal clinical diagnoses and explore potential correlations, in addition to employing more comprehensive measures of mental health Declarations Authors Contribution Declaration Samantha Castro Teixeira: Conceptualization, Methodology, Formal Analysis, Writing – Original Draft, Visualization. Geraldo da Rocha Castelar Pinheiro: Data Collection, Methodology – Review & Editing. Jaqueline de Carvalho Rodrigues: Project Administration, Writing – Review & Editing, Resources. All authors reviewed and approved the final version of the manuscript. Data Availability Statement The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Due to the sensitive nature of the data and confidentiality agreements with participants, anonymized data may be shared with qualified researchers for non-commercial academic purposes, following institutional approval. Funding Declaration No funds, grants, or other support was received. Competing interests The authors declare no competing interests. References World Health Organization - WHO, “On the road to 2025,” Noncommunicable Diseases, Rehabilitation and Disability. Accessed: Oct. 21, 2024. [Online]. Available: https://www.who.int/teams/noncommunicable-diseases/on-the-road-to-2025 S. N. 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Dou, “Correlation between disease activity and patient-reported health-related quality of life in rheumatoid arthritis: a cross-sectional study,” BMJ Open , vol. 14, p. 82020, 2024, doi: 10.1136/bmjopen-2023-082020. J. W. Creswell and D. J. Creswell, Projeto de pesquisa: Métodos qualitativo, quantitativo e misto , 2nd ed. 2010. M. B. Ferraz, L. M. Oliveira, P. M. P. Araujo, E. Atra, and P. Tugwell, “Crosscultural reliability of the physical ability dimension of the health assessment questionnaire.,” J Rheumatol , vol. 17, no. 6, pp. 813–817, Jun. 1990, Accessed: Oct. 21, 2024. [Online]. Available: https://europepmc.org/article/med/2388204 J. F. Fries, “The Health Assessment Questionnaire (HAQ) Article in Clinical and Experimental Rheumatology,” 2005, Accessed: Oct. 21, 2024. [Online]. Available: https://www.researchgate.net/publication/7494006 M. F. Silveira, J. C. Almeida, R. S. Freire, D. S. Haikal, and A. E. de B. L. Martins, “Propriedades psicométricas do instrumento de avaliação da qualidade de vida- 12-item health survey (SF-12),” 2013, Accessed: Oct. 21, 2024. [Online]. Available: https://www.scielosp.org/pdf/csc/2013.v18n7/1923-1931/pt J. E. Ware, M. Kosinski, and S. D. Keller, “A 12-Item Short-Form Health Survey: Construction of Scales and Preliminary Tests of Reliability and Validity,” Med Care , vol. 34, no. 3, 1996, doi: 10.1097/00005650-199603000-00003. D. Aletaha and J. Smolen, “The Simplified Disease Activity Index (SDAI) and the Clinical Disease Activity Index (CDAI): A review of their usefulness and validity in rheumatoid arthritis,” 2005. K. Dissanayake, C. Jayasinghe, P. Wanigasekara, J. Dissanayake, and A. Sominanda, “Validity of clinical disease activity index (CDAI) to evaluate the disease activity of rheumatoid arthritis patients in Sri Lanka: A prospective follow up study based on newly diagnosed patients,” PLoS One , vol. 17, no. 11, p. e0278285, Nov. 2022, doi: 10.1371/JOURNAL.PONE.0278285. S. Epskamp, L. J. Waldorp, R. Mõttus, and D. Borsboom, “The Gaussian Graphical Model in Cross-Sectional and Time-Series Data,” Multivariate Behav Res , vol. 53, no. 4, pp. 453–480, Jul. 2018, doi: 10.1080/00273171.2018.1454823. D. Borsboom and A. O. J. Cramer, “Network analysis: An integrative approach to the structure of psychopathology,” Annu Rev Clin Psychol , vol. 9, no. Volume 9, 2013, pp. 91–121, Mar. 2013, doi: 10.1146/ANNUREV-CLINPSY-050212-185608/CITE/REFWORKS. Y. Huang, T. Loux, X. Huang, and X. Feng, “The relationship between chronic diseases and mental health: A cross-sectional study,” Ment Health Prev , vol. 32, p. 200307, Dec. 2023, doi: 10.1016/J.MHP.2023.200307. A. H. Rogers and S. G. Farris, “A meta-analysis of the associations of elements of the fear-avoidance model of chronic pain with negative affect, depression, anxiety, pain-related disability and pain intensity,” European Journal of Pain , vol. 26, no. 8, pp. 1611–1635, Sep. 2022, doi: 10.1002/EJP.1994. F. Matcham, L. Rayner, S. Steer, and M. Hotopf, “The prevalence of depression in rheumatoid arthritis: a systematic review and meta-analysis,” 2020, doi: 10.1093/rheumatology/ket169. F. Matcham et al. , “The impact of rheumatoid arthritis on quality-of-life assessed using the SF-36: A systematic review and meta-analysis,” Semin Arthritis Rheum , vol. 44, no. 2, pp. 123–130, Oct. 2014, doi: 10.1016/J.SEMARTHRIT.2014.05.001. S. Golubović, T. Ilić, B. Golubović, M. Gajić, and Z. Gajić, “The occurrence of depressive symptoms in rheumatoid arthritis: a cross-sectional study,” Vojnosanit Pregl , vol. 80, no. 02, pp. 128–135, Apr. 2023, doi: 10.2298/VSP211125019G. S. Brandstetter, G. Riedelbeck, M. Steinmann, B. Ehrenstein, J. Loss, and C. Apfelbacher, “Pain, social support and depressive symptoms in patients with rheumatoid arthritis: testing the stress-buffering hypothesis,” Rheumatol Int , vol. 37, no. 6, 2017, doi: 10.1007/s00296-017-3651-3. A. Khan, V. Pooja, S. Chaudhury, V. Bhatt, and D. Saldanha, “Assessment of Depression, Anxiety, Stress, and quality of life in rheumatoid arthritis patients and comparison with healthy individuals,” Ind Psychiatry J , vol. 30, no. Suppl 1, pp. S195–S200, Oct. 2021, doi: 10.4103/0972-6748.328861. R. Sarfraz, M. Aqeel, J. Lactao, S. Khan, and J. Abbas, “Coping Strategies, Pain Severity, Pain Anxiety, Depression, Positive and Negative Affect in Osteoarthritis Patients; A Mediating and Moderating Model,” Nature-Nurture Journal of Psychology , 2020, doi: 10.47391/NNJP.03. A. Kołtuniuk and J. Rosińczuk, “The Levels of Depression, Anxiety, Acceptance of Illness, and Medication Adherence in Patients with Multiple Sclerosis - Descriptive and Correlational Study,” Int J Med Sci , vol. 18, no. 1, p. 216, 2021, doi: 10.7150/IJMS.51172. T. Covic, G. Tyson, D. Spencer, and G. Howe, “Depression in rheumatoid arthritis patients: demographic, clinical, and psychological predictors,” J Psychosom Res , vol. 60, no. 5, pp. 469–476, May 2006, doi: 10.1016/j.jpsychores.2005.09.011. Y. Cao, D. Fan, and Y. Yin, “Pain Mechanism in Rheumatoid Arthritis: From Cytokines to Central Sensitization,” 2020, Hindawi Limited . doi: 10.1155/2020/2076328. A. Trautmann, “Mechanisms underlying chronic fatigue, a symptom too often overlooked II- From deregulated immunity to neuroinflammation and its consequences,” médecine/sciences , vol. 37, no. 11, pp. 1047–1054, Nov. 2021, doi: 10.1051/MEDSCI/2021170. C. A. Isnardi et al. , “Depression Is a Major Determinant of Functional Capacity in Rheumatoid Arthritis,” Journal of Clinical Rheumatology , vol. 27, pp. S180–S185, Sep. 2021, doi: 10.1097/RHU.0000000000001506. B. Adroa Afiya, “The Multifaceted Nature of Sleep: Understanding Physiology, Disorders, and Optimal Practices for Health and Well-Being,” Journal of Research in Medical Sciences , vol. 3, pp. 52–57, 2024, Accessed: Mar. 10, 2025. [Online]. Available: https://rijournals.com/wp-content/uploads/2024/06/RIJRMS-3152-57-2024.pdf N. Kontodimopoulos, E. Stamatopoulou, G. Kletsas, and A. Kandili, “Disease activity and sleep quality in rheumatoid arthritis: a deeper look into the relationship,” Expert Rev Pharmacoecon Outcomes Res , vol. 20, no. 6, pp. 595–602, Nov. 2020, doi: 10.1080/14737167.2020.1677156. K. Aschbacher, A. O’Donovan, O. M. Wolkowitz, F. S. Dhabhar, Y. Su, and E. Epel, “Good stress, bad stress and oxidative stress: Insights from anticipatory cortisol reactivity,” Psychoneuroendocrinology , vol. 38, no. 9, pp. 1698–1708, Sep. 2013, doi: 10.1016/J.PSYNEUEN.2013.02.004. T. Louwies, A. Orock, and B. Greenwood-Van Meerveld, “Stress-induced visceral pain in female rats is associated with epigenetic remodeling in the central nucleus of the amygdala,” Neurobiol Stress , vol. 15, p. 100386, Nov. 2021, doi: 10.1016/J.YNSTR.2021.100386. J. E. Pope, “Management of Fatigue in Rheumatoid Arthritis,” 2020, doi: 10.1136/rmdopen-2019-001084. E. T. Craig et al. , “What Does the Patient Global Health Assessment in Rheumatoid Arthritis Really Tell Us? Contribution of Specific Dimensions of Health-Related Quality of Life,” Arthritis Care Res (Hoboken) , vol. 72, no. 11, pp. 1571–1578, Nov. 2020, doi: 10.1002/ACR.24073. Tables Table 1 Sociodemographic data of the Participants N % Mean Standard deviation Minimum Maximum Age 65.10 12.00 32 98 Gender (Male/Female) 46/415 10/90 Years of study 8.04 4.18 0 18 Months of symptoms 153 113 8 678 Marital status Widowed 40 9.6 Single 83 20.0 Living together 14 3.4 Divorced 39 9.4 Married 227 55.0 Separated 12 2.9 Employment status Retired 154 37.1 Homemaker 81 19.5 Employed with a formal work contract 76 18.3 On sick leave/receiving social security disability benefits 37 8.9 Unemployed 22 5.3 Working without a formal contract or registration 21 5.0 Self-employed with official registration 20 4.82 Unemployed, seeking a job 3 0.72 Not informed 1 0.24 Table 2 Predictors of mental health (Mental SF-12). Predictor β Standard error F p R 2 Intercept 324.253 20.082 < .001 CDAI -0.066 0.041 2.659 0.104 0.536 Fatigue -0.143 0.016 11.729 < .001* 0.536 Pain -0.079 0.015 3.499 0.062 0.536 HAQ 0.093 0.333 6.209 0.013* 0.536 Physical SF-12 -0.223 0.067 38.735 < .001* 0.536 Not getting a good night's sleep -0.065 0.572 2.621 0.106 0.536 Stress -0.197 0.757 16.326 < .001* 0.536 Anxiety -0.087 0.713 3.549 0.060 0.536 Depression -0.312 0.650 53.183 < .001* 0.536 Note. CDAI = Clinical Disease Activity Index; HAQ = Health Assessment Questionnaire; SF-12 = 12-Item Health Survey. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6924681","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":485407762,"identity":"3b599de4-0ec0-4a10-8921-52cbd6bc384b","order_by":0,"name":"Samantha Castro-Teixeira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYAiAAwz8ICqhAK8qxgYEO+EAgySIm2BAihaDAyAGHi387cefP66osGGQbz+d+Lnwxx154/OrEz88MGCQ5xc7gFWLxJkcw8YzZ9IYDM7kbpaekfDMcNuNt5slgA4znDk7AasWA4YcxsbGtsNARu4GaZ6Ew4zbbpzdANKSYHAbhxb+5w/BWuT7327+DdRiv3nG2c0/8GqRSDAEa2G4kbsNZEviBv7ebXhtkbjxxnBmw5k0HoMbb7dZ86QdTp5xg3ebRYKBBE6/8PenP/jYUGEjJ9+fu/k2j81h2/7+s5tv/qiwkeeXxq4FBniQLAarlMCrHN3iA6SoHgWjYBSMghEAALxoZgg2HtuPAAAAAElFTkSuQmCC","orcid":"","institution":"Pontifical Catholic University of Rio de Janeiro (PUC-Rio)","correspondingAuthor":true,"prefix":"","firstName":"Samantha","middleName":"","lastName":"Castro-Teixeira","suffix":""},{"id":485407763,"identity":"260854fa-2117-4c55-bc26-41d5ddc30115","order_by":1,"name":"Geraldo Rocha Castelar-Pinheiro","email":"","orcid":"","institution":"Rio de Janeiro State University","correspondingAuthor":false,"prefix":"","firstName":"Geraldo","middleName":"Rocha","lastName":"Castelar-Pinheiro","suffix":""},{"id":485407764,"identity":"26316e65-5dad-41e7-a2e3-6464b37f3b8f","order_by":2,"name":"Jaqueline Carvalho Rodrigues","email":"","orcid":"","institution":"Pontifical Catholic University of Rio de Janeiro (PUC-Rio)","correspondingAuthor":false,"prefix":"","firstName":"Jaqueline","middleName":"Carvalho","lastName":"Rodrigues","suffix":""}],"badges":[],"createdAt":"2025-06-18 15:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6924681/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6924681/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-22155-3","type":"published","date":"2025-11-03T15:57:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87028081,"identity":"bf58d6d4-3754-40d5-9815-61d30ec3213c","added_by":"auto","created_at":"2025-07-18 12:29:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":186162,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork Analyse\u003c/p\u003e\n\u003cp\u003eNote. RF= Rheumatoid Factor; Anti-CCP= anti-cyclic citrullinated peptide antibodies; CDAI= Clinical Disease Activity Index; HAQ= Health Assessment Questionnaire; SF-12= 12-Item Health Survey; Depressive= Depressive Symptoms.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6924681/v1/c619185dc26994da78c2bb10.png"},{"id":87028078,"identity":"284c6554-0f13-451b-bbe5-3d8fe8a6bde4","added_by":"auto","created_at":"2025-07-18 12:29:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90994,"visible":true,"origin":"","legend":"\u003cp\u003eCentrality Graphic\u003c/p\u003e\n\u003cp\u003eNote. RF= Rheumatoid Factor; Anti-CCP= anti-cyclic citrullinated peptide antibodies; CDAI= Clinical Disease Activity Index; HAQ= Health Assessment Questionnaire; SF-12= 12-Item Health Survey; Depressive: Depressive Symptoms.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6924681/v1/907fffa46f2fa6865ec184d6.png"},{"id":95564438,"identity":"83270019-f5a6-4e29-b04e-6a69f1628412","added_by":"auto","created_at":"2025-11-10 16:09:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":849921,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6924681/v1/d61ff98c-35f9-4931-bf96-6e49dab91dcf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The relation between clinical characteristics and mental health in patients with Rheumatoid Arthritis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the World Health Organization [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] one person under the age of 70 dies every two seconds because of a chronic non-communicable disease characterized by slow development and long duration, with chronic pain being a common symptom [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Chronic pain usually persists for more than three months and can continue for more than a month after an acute or unhealed injury [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], being one of the symptoms of Rheumatoid Arthritis (RA).\u003c/p\u003e\u003cp\u003eRA is an autoimmune, and systemic disease, which manifests itself mainly by inflammation in the peripheral joints and can cause progressive damage to bone and cartilage. As well as the joints, RA can have systemic manifestations, affecting organs such as the lungs, skin, and eyes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In 2020, 17.6\u0026nbsp;million people had RA worldwide [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In 2019, according to IBGE (Brazilian Institute of Geography and Statistics) data[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] 7.9% of the Brazilian population reported having RA or Rheumatism. Therefore, it is important that healthcare professionals understand the clinical characteristics of this disease.\u003c/p\u003e\u003cp\u003eRA is diagnosed based on clinical findings and complementary tests. Although the classification criteria proposed in 2010 by the American College of Rheumatology - ACR[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and the European Alliance of Rheumatology Associations - EULAR[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] are useful in assessing patients, they should not be used as a diagnostic tool[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Despite being a recognized disease with several treatment guidelines, RA has no specific blood markers, but the presence or absence of antibodies against citrullinated proteins/peptides (Anti-CCP) and Rheumatoid Factor (RF) together can corroborate the diagnosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePain and physical disability are known risk factors for symptoms of anxiety and depression in RA patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this context, many patients with RA may experience low quality of life, depression, and anxiety [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, it has been identified that patients with more motor disability due to RA tend to have more depressive symptoms [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConcerning clinical analyses, RA and positive RF may be negatively associated with well-being in mental health, sleep, and cognition [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, there is a possible connection between stressful events, mental disorders, and the increased risk of triggering RA [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. One study showed that 86% of patients with rheumatic disease had experienced stressful events before the onset of the disease, relating psychological factors to the onset of RA. This occurs since chronic stress can have a negative influence on the immune system, thus increasing inflammatory processes which, in turn, are directly related to the onset of rheumatic diseases [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe association between RA activity and symptoms of anxiety and depression has previously been analyzed in the literature [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], using the Patient Global Assessment (PtGA) Severity and the Health Assessment Questionnaire Disability Index (HAQ-DI) as measures. According to the Uda et al. (2021), patients who were not in remission were more likely to have anxious and depressive symptoms. This result suggests that symptomatically active RA, characterized by chronic pain and physical limitations, may worsen an individual\u0026rsquo;s mental health. It is therefore important to consider including psychological care into treatment plans to improve patients' quality of life.\u003c/p\u003e\u003cp\u003eSubsequently, Feng et al. (2024) investigated 314 patients, in whom RA activity was classified using the Disease Activity Score (DAS28), with the following criteria: clinical remission (\u0026lt;\u0026thinsp;2.6), low (2.6\u0026ndash;3.2), moderate (3.2\u0026ndash;5.1), and high (\u0026gt;\u0026thinsp;5.1). The results showed that patients with moderate and high disease activity had higher levels of functional disability (HAQ-DI) and lower Health-Related Quality of Life (HRQoL) scores, when compared to patients in clinical remission. Multiple linear regression analysis revealed that mental health was one of the variables most impacted by disease activity. Moreover, evaluations using the 12-Item Health Survey (SF-12) showed that both physical and mental aspects were compromised by RA, with a more marked reduction in HRQoL in patients with more severe forms of the disease. These findings highlight the relevance of investigating how RA affects physical and psychological well-being, emphasizing the need for studies that can support interventions focused on improving patients' quality of life.\u003c/p\u003e\u003cp\u003eThis study aimed to analyze the influence of pain perception, functional capacity, quality of life, and disease activity on the mental health of patients with RA. The specific objectives were to analyze the relationship between the patient's mental health, measured by the Mental SF-12, and clinical variables, including the Clinical Disease Activity Index (CDAI), fatigue, joint pain, Functional Capacity (HAQ), physical health (Physical SF-12), specific mental health issues (depression, sleep, anxiety, stress) and symptom duration. Using network analysis, we initially sought to explore associations between pain intensity, quality of life, and RA activity and the influence of these variables on mental health. Then, through multiple linear regression, the study verified which variables best explained patients' mental health., the study verified which variables explained patients' mental health, providing a deeper understanding of the critical determinants in patients with this chronic condition.\u003c/p\u003e\u003cp\u003eThe main hypotheses of this study based on the literature were: 1) There is a negative relationship between the patient's mental health (Mental SF-12) and the Clinical Disease Activity Index (CDAI), fatigue, joint pain, depression, anxiety, stress and symptom time and positive with functional capacity (HAQ), physical health (Physical SF-12) and sleep quality [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; 2) Variables such as depression, anxiety and stress will have a significant impact on measures of Quality of Life (QoL) and mental health [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; 3) Physical health (Physical SF-12) will have a positive relationship with mental health (Mental SF-12), suggesting that both physical and mental health outcomes are associated [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; 4) Symptom time and fatigue will be negatively correlated with mental health [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Understanding the QoL and mental health of these patients can be influenced by a complex interaction of biopsychosocial factors, providing important information to direct both health policies and personalized treatments.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was part of a cohort designed to assess the predominant patterns of clinical management of Brazilian patients with RA in everyday practice. A cross-sectional study was carried out, using a quantitative description of trends in a sample of the population\u0026nbsp;[26].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed data from a larger study coordinated by the RA outpatient clinic of a public institution, between August 2015 and April 2016. The inclusion criteria for the study were: 1) meeting the 2010 American Rheumatism Association (ARA) or American College of Rheumatology (ACR)/ European League Against Rheumatism (EULAR) classification criteria for RA (Aletaha et al., 2010; Arnett et al., 1988); 2) age 18 years or older; and 3) documented medical record data from at least six months of follow-up at their health center before enrolling in the study. A total of 1115 participants were assessed, of whom 18 were excluded for not having RF data, 315 for not having Anti-CCP values, 318 for not having Mental SF-12 data, one for not having sleep data, one for not having depression data, and one for not having a CDAI, totaling 461 participants. Table 1 presents the sociodemographic data of the participants.\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 1\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was conducted in 11 Brazilian centers specializing in the treatment of patients diagnosed with RA. Most of the information was collected during medical consultations, while previous medical records served as secondary sources for biomarkers such as RF and Anti-CCP, which were tested prior to the patients’ arrival at the outpatient clinic. All data was stored in electronic medical records and compiled into a central database. There were three evaluation points.\u003c/p\u003e\n\u003cp\u003eDuring the initial medical visit, sociodemographic information and lifestyle habits were collected. At this stage, the duration of the disease, RF positivity, and Anti-CCP levels were assessed. Additionally, participants were interviewed about how they managed stress, anxiety, depression, and sleep quality. Responses were measured on a questionnaire developed by the researchers, ranging from no difficulty, some difficulty, a lot of difficulty, to inability to perform, with scores ranging from -1 to 2. Pain perception was assessed using the Visual Analog Scale (VAS), with scores ranging from zero (no pain) to 100 (maximum pain). The following scales were also applied: the Health Assessment Questionnaire (HAQ), the Disability Index (DI), the 12-item Health Survey (SF-12), and the Clinical Disease Activity Index (CDAI). During the subsequent follow-up and final appointments, the previous collected data were reviewed to monitoring the progression of the disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstruments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following instruments were administered during the evaluations:\u003c/p\u003e\n\u003cp\u003e1)\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sociodemographic and health conditions questionnaire\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe questionnaire aimed to collect data on socioeconomic profile, family history of rheumatoid arthritis, presence of other autoimmune diseases or associated conditions, personal history of comorbidities, and lifestyle habits (such as smoking, alcohol consumption, and physical activity) of the participants. It also included measures of anxiety, stress, non-restorative sleep, and depression, assessed using an instrument adapted from Sokka et al. (2009), based on the Multi-Dimensional Health Assessment Questionnaire (Pincus et al., n.d.). Response options were: “unable to do” (-1), “no difficulty’ (0), “some difficulty” (1), and “much difficulty” (2). In the present study, the Cronbach’s alpha coefficient was 0.811 (p \u0026lt; 0.001) for the total scale.\u003c/p\u003e\n\u003cp\u003e2)\u0026nbsp; The Health Assessment Questionnaire (HAQ) Disability Index (DI) – HAQDI [27], [28]\u003c/p\u003e\n\u003cp\u003eThe HAQ-DI is used to monitor the progression of the disease and the effectiveness of the treatment, providing insight into the functionality of the patients. It is a self-assessment questionnaire made up of 20 questions related to daily activities, covering eight components that assess the musculoskeletal system. These components cover tasks such as dressing, getting up, eating, walking, personal care, reaching, grip strength, and other related activities. Each question has four answer options, ranging from zero to 3: “no difficulty at all” (0), “with some difficulty” (1), “with great difficulty” (2) and “unable to perform” (3)”. \u0026nbsp;Higher scores mean greater disability. In the validation of the HAQ for Brazil (Ferraz et al., 1990), Cronbach's alpha coefficient was 0.905 (p\u0026lt;0.001), and the inter-observer correlation coefficient was 0.830 (p\u0026lt;0.001). Cronbach's alpha coefficient in this study was 0.811 (p\u0026lt;0,001).\u003c/p\u003e\n\u003cp\u003e3) \u0026nbsp;12-Item Health Survey (SF-12)\u0026nbsp;[29], [30]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SF-12 is a questionnaire used to assess health-related QoL. It emerged as a simplified version of the SF-36 and can be administered in two minutes. The SF-12 consists of a combination of 12 closed and multiple-choice questions to calculate the three final scores for the physical, mental, and health-related QoL dimensions. The questionnaire ranges from zero to 100, with higher scores indicating better QoL. Scores approaching 50 reflect a situation like that of the general population, while values below 50 indicate a lower QoL than the population average. Cronbach's alpha coefficient in this study was 0.960 (p\u0026lt;0,001).\u003c/p\u003e\n\u003cp\u003e4) Clinical Disease Activity Index (CDAI) [31], [32]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe CDAI is a measure of RA activity, which considers a series of parameters calculated by adding up the number of painful and swollen joints (28 joints), as well as the global assessment of disease activity by the patients and the doctors, both classified on a scale of zero to 10. The total CDAI score ranges from zero to 76 and is used to classify RA activity into four levels: remission (≤2.8), low (2.9-10), moderate (10.1-22), and high (\u0026gt;22). Dissanayake et al. (2022) found a Cronbach's alpha coefficient of 0.868 in their validation of the instrument.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection procedures for this study were reviewed and approved by the National Research Ethics Committee of the Ministry of Health in Brazil (approval number: blind) in accordance with national regulations and ethical standards for research involving human participants.\u003c/p\u003e\n\u003cp\u003ePrior to participation, all individuals received detailed information about the study and signed a Free and Informed Consent Form confirming their voluntary agreement to participate and to allow publication of the anonymized data. All participants were informed that their identities would remain confidential and that responses would be fully anonymized.\u003c/p\u003e\n\u003cp\u003eThe research team made sure that the entire data collection process respected participants’ privacy and followed ethical procedures, including the protection of sensitive information. Participants were also informed that the instruments used posed minimal risk to their physical or psychological health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the associations among the variables, a network analysis approach was used. It was performed using the EBICglasso method, aiming to remove spurious and weak correlations, examine the strength of the identified associations in the regression model, and explore their connections with clinical and mental health measures. The glasso method was estimated using a regularized solution based on the Extended Bayesian Information Criterion (EBIC). This approach enables an exploratory analysis of the association structure among variables, in which the relationships within the system are not pre-specified, allowing for the identification of emergent patterns based on empirical data\u0026nbsp;[33]. This method allowed for a visual and statistical examination of the relationships between biological (e.g., rheumatoid factor, Anti-CCP), clinical (e.g., Clinical Disease Activity Index – CDAI, joint pain, fatigue, HAQ), and psychosocial variables (e.g., SF-12 Mental and Physical Health components: stress, anxiety, depression, and sleep disturbances).\u003c/p\u003e\n\u003cp\u003eIn network analysis, each variable is represented as a node, and the associations between variables are depicted as edges. The thickness and color of the edges reflect the strength and direction of the associations, respectively. Directionality was determined using partial correlations: blue edges indicate positive associations, red edges indicate negative associations, and the absence of an edge suggests that—after controlling for all other variables—there is no statistically significant relationship between the corresponding nodes. This method enables the simultaneous visualization of the interdependence among multiple variables, helping to identify interconnected structures and potential clusters of symptoms or psychological factors\u0026nbsp;[34].\u003c/p\u003e\n\u003cp\u003eThe relations identified in network analysis were included in a multiple linear regression model. The multiple linear regression analysis included as predictor variables the CDAI, fatigue, joint pain, HAQ, Physical SF-12, Multi-Dimensional Health Assessment Questionnaire (depression, sleep, anxiety, and stress), and as an outcome variable mental health (Mental SF-12). Therefore, the analyses sought to answer which variables have the greatest impact on mental health of the patients.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eInitially, a network analysis was conducted to examine the associations among clinical, and psychological variables. In the network model, RF was positively associated with anti-CCP antibodies, demonstrating the strongest connection in the network (0.65). However, no significant connections were found between these biomarkers and psychological variables or mental health indicators.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, pain showed a moderate positive association with CDAI (0.48) and a weaker positive connection with fatigue (0.23). Additionally, CDAI and fatigue were negatively associated with the SF-12 Physical and Mental Health components, although these associations were weak.\u003c/p\u003e\n\u003cp\u003eFurthermore, among the psychological variables, stress demonstrated moderate positive associations with poor sleep quality (0.27), anxiety (0.49), and depression (0.37). Additionally, depression symptoms were negatively associated with mental health (−0.34), and stress also showed a negative association with mental health (−0.24). The network did not show any significant direct association between RF or anti-CCP and the mental health node.\u003c/p\u003e\n\u003cp\u003eOverall, the network structure revealed clusters around mental health symptoms (stress, anxiety, depression) and disease activity (pain, CDAI, fatigue), as well as connections between functional and physical health indicators (HAQ, SF-12 Physical, SF-12 Mental), as illustrated in Figure 1.\u003c/p\u003e\n\u003cp\u003eINSERT FIGURE 1\u003c/p\u003e\n\u003cp\u003eIn terms of centrality, depressive symptoms stood out with the highest values of closeness and strength, indicating that this variable was the most interconnected and influential within the network. It also presented a high betweenness, suggesting that it plays a key role in linking different parts of the network. Anxiety, stress, and poor sleep also showed high centrality indices, reinforcing their importance in the network structure. On the other hand, RF and anti-CCP presented the lowest centrality values, showing tiniest integration with the rest of the network (Figure 2).\u003c/p\u003e\n\u003cp\u003eINSERT FIGURE 2\u003c/p\u003e\n\u003cp\u003eMultiple regression analysis (Table 2) was carried out to examine the predictive capacity of the variables CDAI, fatigue, pain, HAQ, physical SF-12, poor sleep, stress, anxiety, and depression (independent variables) on mental SF-12 (dependent variable). Multicollinearity was assessed using the Variance Inflation Factor (VIF) and tolerance, with values falling within acceptable limits—VIF ranging from 1.01 to 2.28 and tolerance greater than 0.2. The Durbin-Watson test indicated independence of the residuals, with a value of 1.98. The regression model examining predictors of mental health (Mental SF-12) was statistically significant, F (1, 9) = 20.082, p \u0026lt; .001, indicating that the model reliably predicts mental health outcomes. The model accounted for approximately 53.6% of the variance in mental health scores (R² = .536), suggesting a moderate to strong explanatory power. Among the variables included, depressive and physical symptoms were found to be the variables that best explained poorer mental health among patients with RA. Levels of fatigue, stress, and the perception of lower QoL also contributed to greater mental health problems, as shown in Table 2. The level of fatigue and worse QoL also contributed to explaining greater mental health problems, as can be seen in Table 2.\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 2\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the relation between physical aspects, QoL, and mental health in patients with RA, aiming to assess the impact of these variables on psychological well-being. The combination of regression and network analysis reinforces the hypothesis that mental health in RA patients is not determined by a single factor but by a complex interplay between physical and emotional symptoms [23], [24], [25]. The results highlight the complexity of RA and their consequences, underscoring the importance of comprehensive interviews to understand the clinical manifestations in each patient.\u003c/p\u003e\n\u003cp\u003eNetwork analysis revealed that greater RA severity was related to mental health outcomes, including fatigue, pain, perceived stress, anxiety, and depression symptoms. These results corroborate the findings of Feng et al. (2024), who demonstrated that RA compromises the mental health and QoL of patients with more severe forms of the disease, as joint pain, one of the primary symptoms of the disease, can be debilitating. Chronic pain is frequently associated with psychological stress, anxiety, and depression, directly affecting mental health [24], [35], [36].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe main predictors of mental health were fatigue, functional capacity, physical health, perceived stress, and depressive symptoms. These findings are consistent with previous research suggesting that psychological and physical factors interact in influencing the mental health of individuals living with chronic conditions such as rheumatoid arthritis (RA). Fatigue and depressive symptoms are not only prevalent in RA but are also among the strongest predictors of psychological distress and reduced quality of life [37], [38].\u003c/p\u003e\n\u003cp\u003eThese findings also were further supported by network analysis, which provided an integrative perspective of the interactions among the variables. Rather than isolating relationships, the network model identified depressive symptoms as the most central node, with high strength, closeness, and betweenness values. This suggests that depression plays a central role in connecting and influencing various domains, including physical, emotional, and functional aspects. In individuals living with chronic conditions such as rheumatoid arthritis, depressive symptoms often emerge not only as a psychological response to the illness but also as a factor that intensifies pain perception, fatigue, and functional limitations [13], [39], [40]. Depression has been associated with greater disease burden and poorer treatment outcomes, acting as consequence and as influencer to reduced quality of life [41]. Its presence can worsen self-regulatory capacities, reduce engagement in coping strategies, and negatively impact motivation for self-care, thereby creating a reinforcing cycle between emotional distress and physical symptomatology [42], [43], [44]. These findings underscore the importance of addressing depressive symptoms as a key target in the comprehensive management of patients with chronic diseases.\u003c/p\u003e\n\u003cp\u003eOther psychological variables, such as anxiety, stress, and sleep quality, also demonstrated high centrality, highlighting their relevance in the overall experience of living with RA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFatigue, which emerged as a significant factor in regression analyses, must be considered a central component in the deterioration of emotional well-being. Research suggest that fatigue may disrupt the regulation of neurotransmitters such as serotonin and dopamine, which are critical for mood and motivation [45], [46]. Moreover, fatigue directly impacts the ability of the patients to function and maintain their routines, contributing to a cycle of physical and emotional exhaustion [24], [39], [47]. Similarly, functional limitation—another mental health predictor—can lead to frustration, feelings of helplessness, and reduced self-esteem, fostering symptoms of anxiety and depression.\u003c/p\u003e\n\u003cp\u003eSleep quality, positively associated with mental health in both analyses, is also a key component. Adequate sleep supports emotional regulation, reduces stress, and enhances coping abilities [48]. Conversely, pain disrupts sleep, thereby exacerbating psychological distress [49]. These findings suggest that interventions targeting fatigue management, pain reduction, and improved sleep may significantly impact on mental health of the patients.\u003c/p\u003e\n\u003cp\u003ePerceived stress and depressive symptoms also emerged as relevant factors, in both regression and network analyses, supporting Hypothesis 2 of the study. These variables were not only significant predictors of mental health but also acted as links between different domains in the network structure, emphasizing their role in the dynamic interplay between physical and emotional states [41], [50], [51]. Chronic stress, through prolonged activation of the hypothalamic-pituitary-adrenal (HPA) axis and the resulting increase in cortisol levels, may sensitize pain circuits and impair mood regulation, contributing to the worsening of psychological symptoms [46], [52]. Thus, emotional suffering not only coexists with physical symptoms but also amplifies them, further compromising QoL.\u003c/p\u003e\n\u003cp\u003eIt is important to note that RF and anti-CCP levels did not show significant associations with mental health indicators in either analysis. These results suggest that while these biomarkers are critical for the diagnosis and prognosis of RA, they are not sufficient to identify problems of mental health in the patients. The subjective experience of the disease, shaped by factors such as pain, stress, and functional limitations, plays a more substantial role in psychological suffering [37], [53]. On the other hand, chronic pain and functional impairment remain directly linked to the development of depressive and anxious symptoms [11], [12]. Therefore, it is suggested that systematic assessments of QoL and psychological symptoms must be systematically evaluated in outpatient clinics for adults with RA.\u003c/p\u003e\n\u003cp\u003eIn summary, RA is a complex condition requiring multidisciplinary care. The strong relation between physical and psychological symptoms, if left unaddressed, may significantly impair the well-being of the patients. The impact of RA on psychological health suggests that early interventions are essential to reduce emotional distress and preserve the QoL. Therefore, clinical practice should address not only the biomedical aspects of the disease but also its psychosocial implications, promoting more humanized and effective care.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study showed that the physical symptoms of RA can significantly impact the mental health of the patients. Therefore, assessing well-being has the potential to complement clinical care. It is suggested that including mental health evaluations in routine consultations can offer more comprehensive and humanized follow-up, addressing both physical and emotional aspects. In this context, the presence of mental health professionals (psychologists and psychiatrists) in outpatient services is essential to ensure continuous care for patients.\u003c/p\u003e\u003cp\u003eThese findings are highly relevant for recognize the psychological impact caused by RA and contribute to improving the well-being of the patients. This study highlights the importance of integrating psychological well-being into the treatment of chronic illnesses. Patients should also be informed about how RA can directly affect mental health, helping them understand the value of a model that addresses both physical and psychological health for overall well-being. As an alternative, the creation of emotional support groups for the patients with RA could be beneficial.\u003c/p\u003e\u003cp\u003eOne of the strengths of this study was the analysis of a large cohort to investigate the associations between clinical disease variables and mental health. However, despite its important findings, the study had some limitations. First, instead of formal psychiatric diagnoses, it relied on self-reported anxiety, stress, sleep, and depression symptoms. Therefore, it is recommended that future studies use formal clinical diagnoses and explore potential correlations, in addition to employing more comprehensive measures of mental health\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors Contribution Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSamantha Castro Teixeira: Conceptualization, Methodology, Formal Analysis, Writing \u0026ndash; Original Draft, Visualization.\u003c/p\u003e\n\u003cp\u003eGeraldo da Rocha Castelar Pinheiro: Data Collection, Methodology \u0026ndash; Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eJaqueline de Carvalho Rodrigues: Project Administration, Writing \u0026ndash; Review \u0026amp; Editing, Resources.\u003c/p\u003e\n\u003cp\u003eAll authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Due to the sensitive nature of the data and confidentiality agreements with participants, anonymized data may be shared with qualified researchers for non-commercial academic purposes, following institutional approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funds, grants, or other support was received.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization - WHO, \u0026ldquo;On the road to 2025,\u0026rdquo; Noncommunicable Diseases, Rehabilitation and Disability. Accessed: Oct. 21, 2024. [Online]. Available: https://www.who.int/teams/noncommunicable-diseases/on-the-road-to-2025\u003c/li\u003e\n \u003cli\u003eS. N. Raja \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;The Revised IASP definition of pain: concepts, challenges, and compromises HHS Public Access,\u0026rdquo; \u003cem\u003ePain\u003c/em\u003e, vol. 161, no. 9, 2020, doi: 10.1097/j.pain.0000000000001939.\u003c/li\u003e\n \u003cli\u003eJ. S. Smolen, D. Aletaha, and I. B. McInnes, \u0026ldquo;Rheumatoid arthritis,\u0026rdquo; \u003cem\u003eThe Lancet\u003c/em\u003e, vol. 388, no. 10055, pp. 2023\u0026ndash;2038, Oct. 2016, doi: 10.1016/S0140-6736(16)30173-8.\u003c/li\u003e\n \u003cli\u003eR. J. Black \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Global, regional, and national burden of rheumatoid arthritis, 1990\u0026ndash;2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021,\u0026rdquo; \u003cem\u003eLancet Rheumatol\u003c/em\u003e, vol. 5, no. 10, pp. e594\u0026ndash;e610, Oct. 2023, doi: 10.1016/S2665-9913(23)00211-4.\u003c/li\u003e\n \u003cli\u003eInstituto Brasileiro de Geografia e Estat\u0026iacute;stica - IBGE, \u0026ldquo;Pesquisa Nacional de Sa\u0026uacute;de 2019: Percep\u0026ccedil;\u0026atilde;o do estado de sa\u0026uacute;de, estilos de vida, doen\u0026ccedil;as cr\u0026ocirc;nicas e sa\u0026uacute;de bucal,\u0026rdquo; 2019.\u003c/li\u003e\n \u003cli\u003eL. Fraenkel \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;2021 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis,\u0026rdquo; \u003cem\u003eArthritis Care Res (Hoboken)\u003c/em\u003e, vol. 73, no. 7, 2021, doi: 10.1002/acr.24596.\u003c/li\u003e\n \u003cli\u003eD. Aletaha \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative,\u0026rdquo; \u003cem\u003eAnn Rheum Dis\u003c/em\u003e, vol. 69, no. 9, pp. 1580\u0026ndash;1588, Sep. 2010, doi: 10.1136/ARD.2010.138461.\u003c/li\u003e\n \u003cli\u003eF. C. Arnett \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;The american rheumatism association 1987 revised criteria for the classification of rheumatoid arthritis,\u0026rdquo; \u003cem\u003eArthritis Rheum\u003c/em\u003e, vol. 31, no. 3, pp. 315\u0026ndash;324, Mar. 1988, doi: 10.1002/ART.1780310302.\u003c/li\u003e\n \u003cli\u003eJ. R\u0026ouml;nnelid, C. Turesson, and A. Kastbom, \u0026ldquo;Autoantibodies in Rheumatoid Arthritis \u0026ndash; Laboratory and Clinical Perspectives,\u0026rdquo; May 14, 2021, \u003cem\u003eFrontiers Media S.A.\u003c/em\u003e doi: 10.3389/fimmu.2021.685312.\u003c/li\u003e\n \u003cli\u003eM. V Sokolova, G. Schett, and U. Steffen, \u0026ldquo;Autoantibodies in Rheumatoid Arthritis: Historical Background and Novel Findings,\u0026rdquo; \u003cem\u003eClin Rev Allergy Immunol\u003c/em\u003e, vol. 63, pp. 138\u0026ndash;151, 2022, doi: 10.1007/s12016-021-08890-1.\u003c/li\u003e\n \u003cli\u003eH. Morf, G. da Rocha Castelar-Pinheiro, A. B. Vargas-Santos, C. Baerwald, and O. Seifert, \u0026ldquo;Impact of clinical and psychological factors associated with depression in patients with rheumatoid arthritis: comparative study between Germany and Brazil,\u0026rdquo; \u003cem\u003eClin Rheumatol\u003c/em\u003e, vol. 40, no. 5, pp. 1779\u0026ndash;1787, May 2021, doi: 10.1007/S10067-020-05470-0/TABLES/4.\u003c/li\u003e\n \u003cli\u003eC. Dickens, L. McGowan, D. Clark-Carter, and F. Crreed, \u0026ldquo;Depression in Rheumatoid Arthritis: A Systematic Review of the Literature With Meta-Analysis,\u0026rdquo; \u003cem\u003ePsychosomatic Medicine\u003c/em\u003e, vol. 64, pp. 52\u0026ndash;60, 2002, doi: 10.1097/00006842-200201000-00008.\u003c/li\u003e\n \u003cli\u003eE. Fakra and H. Marotte, \u0026ldquo;Rheumatoid arthritis and depression,\u0026rdquo; \u003cem\u003eJoint Bone Spine\u003c/em\u003e, vol. 88, no. 5, p. 105200, Oct. 2021, doi: 10.1016/J.JBSPIN.2021.105200.\u003c/li\u003e\n \u003cli\u003eS. Odegard, A. Finset, P. Mowinckel, T. K. Kvien, and T. Uhlig, \u0026ldquo;Pain and psychological health status over a 10-year period in patients with recent onset rheumatoid arthritis,\u0026rdquo; \u003cem\u003eAnn Rheum Dis\u003c/em\u003e, vol. 66, no. 9, pp. 1195\u0026ndash;1201, Mar. 2007, doi: 10.1136/ard.2006.064287.\u003c/li\u003e\n \u003cli\u003eD. A. Walsh and D. F. McWilliams, \u0026ldquo;Mechanisms, impact and management of pain in rheumatoid arthritis,\u0026rdquo; \u003cem\u003eNature Reviews Rheumatology 2014 10:10\u003c/em\u003e, vol. 10, no. 10, pp. 581\u0026ndash;592, May 2014, doi: 10.1038/nrrheum.2014.64.\u003c/li\u003e\n \u003cli\u003eA. Beşirli, J. \u0026Ouml;. Alptekin, D. Kaymak, and \u0026Ouml;. A. \u0026Ouml;zer, \u0026ldquo;The Relationship Between Anxiety, Depression, Suicidal Ideation and Quality of Life in Patients with Rheumatoid Arthritis,\u0026rdquo; \u003cem\u003ePsychiatric Quarterly\u003c/em\u003e, vol. 91, no. 1, pp. 53\u0026ndash;64, Mar. 2020, doi: 10.1007/S11126-019-09680-X/TABLES/6.\u003c/li\u003e\n \u003cli\u003eW. Tański, A. Szalonka, and B. Tomasiewicz, \u0026ldquo;Quality of Life and Depression in Rheumatoid Arthritis Patients Treated with Biologics \u0026ndash; A Single Centre Experience,\u0026rdquo; \u003cem\u003ePsychol Res Behav Manag\u003c/em\u003e, vol. 15, pp. 491\u0026ndash;501, 2022, doi: 10.2147/PRBM.S352984.\u003c/li\u003e\n \u003cli\u003eT. Muhammad, M. Rashid, and P. P. Zanwar, \u0026ldquo;Examining the Association of Pain and Pain Frequency With Self-Reported Difficulty in Activities of Daily Living and Instrumental Activities of Daily Living Among Community-Dwelling Older Adults: Findings From the Longitudinal Aging Study in India,\u0026rdquo; \u003cem\u003eThe Journals of Gerontology: Series B\u003c/em\u003e, vol. 78, no. 9, pp. 1545\u0026ndash;1554, Aug. 2023, doi: 10.1093/GERONB/GBAD085.\u003c/li\u003e\n \u003cli\u003eI. Stanciu, J. Anderson, S. Siebert, D. Mackay, and D. M. Lyall, \u0026ldquo;Associations of rheumatoid arthritis and rheumatoid factor with mental health, sleep and cognition characteristics in the UK Biobank,\u0026rdquo; \u003cem\u003eScientific Reports 2022 12:1\u003c/em\u003e, vol. 12, no. 1, pp. 1\u0026ndash;7, Nov. 2022, doi: 10.1038/s41598-022-22021-6.\u003c/li\u003e\n \u003cli\u003eA. W. M. Evers \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Does stress affect the joints? Daily stressors, stress vulnerability, immune and HPA axis activity, and short-term disease and symptom fluctuations in rheumatoid arthritis,\u0026rdquo; \u003cem\u003eAnn Rheum Dis\u003c/em\u003e, vol. 73, no. 9, pp. 1683\u0026ndash;1688, Sep. 2014, doi: 10.1136/ANNRHEUMDIS-2012-203143.\u003c/li\u003e\n \u003cli\u003eY. C. Lee \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Posttraumatic Stress Disorder and Risk for Incident Rheumatoid Arthritis,\u0026rdquo; \u003cem\u003eArthritis Care Res (Hoboken)\u003c/em\u003e, vol. 68, no. 3, p. 292, Mar. 2016, doi: 10.1002/ACR.22683.\u003c/li\u003e\n \u003cli\u003eI. A. Vallerand, S. B. Patten, and C. Barnabe, \u0026ldquo;Depression and the risk of rheumatoid arthritis,\u0026rdquo; \u003cem\u003eCurr Opin Rheumatol\u003c/em\u003e, vol. 31, no. 3, p. 279, May 2019, doi: 10.1097/BOR.0000000000000597.\u003c/li\u003e\n \u003cli\u003eS. C. Conway, F. H. Creed, and D. P. M. Symmons, \u0026ldquo;Life events and the onset of rheumatoid arthritis,\u0026rdquo; \u003cem\u003eJ Psychosom Res\u003c/em\u003e, vol. 38, no. 8, pp. 837\u0026ndash;847, Nov. 1994, doi: 10.1016/0022-3999(94)90071-X.\u003c/li\u003e\n \u003cli\u003eM. Uda \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Factors associated with anxiety and depression in rheumatoid arthritis patients: a cross-sectional study,\u0026rdquo; \u003cem\u003eAdvances in Rheumatology\u003c/em\u003e, vol. 61, no. 1, pp. 1\u0026ndash;10, Dec. 2021, doi: 10.1186/S42358-021-00223-2/TABLES/4.\u003c/li\u003e\n \u003cli\u003eJ. Feng, L. Yu, Y. Fang, X. Zhang, S. Li, and L. Dou, \u0026ldquo;Correlation between disease activity and patient-reported health-related quality of life in rheumatoid arthritis: a cross-sectional study,\u0026rdquo; \u003cem\u003eBMJ Open\u003c/em\u003e, vol. 14, p. 82020, 2024, doi: 10.1136/bmjopen-2023-082020.\u003c/li\u003e\n \u003cli\u003eJ. W. Creswell and D. J. 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Sominanda, \u0026ldquo;Validity of clinical disease activity index (CDAI) to evaluate the disease activity of rheumatoid arthritis patients in Sri Lanka: A prospective follow up study based on newly diagnosed patients,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 17, no. 11, p. e0278285, Nov. 2022, doi: 10.1371/JOURNAL.PONE.0278285.\u003c/li\u003e\n \u003cli\u003eS. Epskamp, L. J. Waldorp, R. M\u0026otilde;ttus, and D. Borsboom, \u0026ldquo;The Gaussian Graphical Model in Cross-Sectional and Time-Series Data,\u0026rdquo; \u003cem\u003eMultivariate Behav Res\u003c/em\u003e, vol. 53, no. 4, pp. 453\u0026ndash;480, Jul. 2018, doi: 10.1080/00273171.2018.1454823.\u003c/li\u003e\n \u003cli\u003eD. Borsboom and A. O. J. Cramer, \u0026ldquo;Network analysis: An integrative approach to the structure of psychopathology,\u0026rdquo; \u003cem\u003eAnnu Rev Clin Psychol\u003c/em\u003e, vol. 9, no. Volume 9, 2013, pp. 91\u0026ndash;121, Mar. 2013, doi: 10.1146/ANNUREV-CLINPSY-050212-185608/CITE/REFWORKS.\u003c/li\u003e\n \u003cli\u003eY. Huang, T. Loux, X. Huang, and X. Feng, \u0026ldquo;The relationship between chronic diseases and mental health: A cross-sectional study,\u0026rdquo; \u003cem\u003eMent Health Prev\u003c/em\u003e, vol. 32, p. 200307, Dec. 2023, doi: 10.1016/J.MHP.2023.200307.\u003c/li\u003e\n \u003cli\u003eA. H. Rogers and S. G. Farris, \u0026ldquo;A meta-analysis of the associations of elements of the fear-avoidance model of chronic pain with negative affect, depression, anxiety, pain-related disability and pain intensity,\u0026rdquo; \u003cem\u003eEuropean Journal of Pain\u003c/em\u003e, vol. 26, no. 8, pp. 1611\u0026ndash;1635, Sep. 2022, doi: 10.1002/EJP.1994.\u003c/li\u003e\n \u003cli\u003eF. Matcham, L. Rayner, S. Steer, and M. Hotopf, \u0026ldquo;The prevalence of depression in rheumatoid arthritis: a systematic review and meta-analysis,\u0026rdquo; 2020, doi: 10.1093/rheumatology/ket169.\u003c/li\u003e\n \u003cli\u003eF. Matcham \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;The impact of rheumatoid arthritis on quality-of-life assessed using the SF-36: A systematic review and meta-analysis,\u0026rdquo; \u003cem\u003eSemin Arthritis Rheum\u003c/em\u003e, vol. 44, no. 2, pp. 123\u0026ndash;130, Oct. 2014, doi: 10.1016/J.SEMARTHRIT.2014.05.001.\u003c/li\u003e\n \u003cli\u003eS. Golubović, T. Ilić, B. Golubović, M. Gajić, and Z. Gajić, \u0026ldquo;The occurrence of depressive symptoms in rheumatoid arthritis: a cross-sectional study,\u0026rdquo; \u003cem\u003eVojnosanit Pregl\u003c/em\u003e, vol. 80, no. 02, pp. 128\u0026ndash;135, Apr. 2023, doi: 10.2298/VSP211125019G.\u003c/li\u003e\n \u003cli\u003eS. Brandstetter, G. Riedelbeck, M. Steinmann, B. Ehrenstein, J. Loss, and C. Apfelbacher, \u0026ldquo;Pain, social support and depressive symptoms in patients with rheumatoid arthritis: testing the stress-buffering hypothesis,\u0026rdquo; \u003cem\u003eRheumatol Int\u003c/em\u003e, vol. 37, no. 6, 2017, doi: 10.1007/s00296-017-3651-3.\u003c/li\u003e\n \u003cli\u003eA. Khan, V. Pooja, S. Chaudhury, V. Bhatt, and D. Saldanha, \u0026ldquo;Assessment of Depression, Anxiety, Stress, and quality of life in rheumatoid arthritis patients and comparison with healthy individuals,\u0026rdquo; \u003cem\u003eInd Psychiatry J\u003c/em\u003e, vol. 30, no. Suppl 1, pp. S195\u0026ndash;S200, Oct. 2021, doi: 10.4103/0972-6748.328861.\u003c/li\u003e\n \u003cli\u003eR. Sarfraz, M. Aqeel, J. Lactao, S. Khan, and J. Abbas, \u0026ldquo;Coping Strategies, Pain Severity, Pain Anxiety, Depression, Positive and Negative Affect in Osteoarthritis Patients; A Mediating and Moderating Model,\u0026rdquo; \u003cem\u003eNature-Nurture Journal of Psychology\u003c/em\u003e, 2020, doi: 10.47391/NNJP.03.\u003c/li\u003e\n \u003cli\u003eA. Kołtuniuk and J. Rosińczuk, \u0026ldquo;The Levels of Depression, Anxiety, Acceptance of Illness, and Medication Adherence in Patients with Multiple Sclerosis - Descriptive and Correlational Study,\u0026rdquo; \u003cem\u003eInt J Med Sci\u003c/em\u003e, vol. 18, no. 1, p. 216, 2021, doi: 10.7150/IJMS.51172.\u003c/li\u003e\n \u003cli\u003eT. Covic, G. Tyson, D. Spencer, and G. Howe, \u0026ldquo;Depression in rheumatoid arthritis patients: demographic, clinical, and psychological predictors,\u0026rdquo; \u003cem\u003eJ Psychosom Res\u003c/em\u003e, vol. 60, no. 5, pp. 469\u0026ndash;476, May 2006, doi: 10.1016/j.jpsychores.2005.09.011.\u003c/li\u003e\n \u003cli\u003eY. Cao, D. Fan, and Y. Yin, \u0026ldquo;Pain Mechanism in Rheumatoid Arthritis: From Cytokines to Central Sensitization,\u0026rdquo; 2020, \u003cem\u003eHindawi Limited\u003c/em\u003e. doi: 10.1155/2020/2076328.\u003c/li\u003e\n \u003cli\u003eA. Trautmann, \u0026ldquo;Mechanisms underlying chronic fatigue, a symptom too often overlooked II- From deregulated immunity to neuroinflammation and its consequences,\u0026rdquo; \u003cem\u003em\u0026eacute;decine/sciences\u003c/em\u003e, vol. 37, no. 11, pp. 1047\u0026ndash;1054, Nov. 2021, doi: 10.1051/MEDSCI/2021170.\u003c/li\u003e\n \u003cli\u003eC. A. Isnardi \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Depression Is a Major Determinant of Functional Capacity in Rheumatoid Arthritis,\u0026rdquo; \u003cem\u003eJournal of Clinical Rheumatology\u003c/em\u003e, vol. 27, pp. S180\u0026ndash;S185, Sep. 2021, doi: 10.1097/RHU.0000000000001506.\u003c/li\u003e\n \u003cli\u003eB. Adroa Afiya, \u0026ldquo;The Multifaceted Nature of Sleep: Understanding Physiology, Disorders, and Optimal Practices for Health and Well-Being,\u0026rdquo; \u003cem\u003eJournal of Research in Medical Sciences\u003c/em\u003e, vol. 3, pp. 52\u0026ndash;57, 2024, Accessed: Mar. 10, 2025. [Online]. Available: https://rijournals.com/wp-content/uploads/2024/06/RIJRMS-3152-57-2024.pdf\u003c/li\u003e\n \u003cli\u003eN. Kontodimopoulos, E. Stamatopoulou, G. Kletsas, and A. Kandili, \u0026ldquo;Disease activity and sleep quality in rheumatoid arthritis: a deeper look into the relationship,\u0026rdquo; \u003cem\u003eExpert Rev Pharmacoecon Outcomes Res\u003c/em\u003e, vol. 20, no. 6, pp. 595\u0026ndash;602, Nov. 2020, doi: 10.1080/14737167.2020.1677156.\u003c/li\u003e\n \u003cli\u003eK. Aschbacher, A. O\u0026rsquo;Donovan, O. M. Wolkowitz, F. S. Dhabhar, Y. Su, and E. Epel, \u0026ldquo;Good stress, bad stress and oxidative stress: Insights from anticipatory cortisol reactivity,\u0026rdquo; \u003cem\u003ePsychoneuroendocrinology\u003c/em\u003e, vol. 38, no. 9, pp. 1698\u0026ndash;1708, Sep. 2013, doi: 10.1016/J.PSYNEUEN.2013.02.004.\u003c/li\u003e\n \u003cli\u003eT. Louwies, A. Orock, and B. Greenwood-Van Meerveld, \u0026ldquo;Stress-induced visceral pain in female rats is associated with epigenetic remodeling in the central nucleus of the amygdala,\u0026rdquo; \u003cem\u003eNeurobiol Stress\u003c/em\u003e, vol. 15, p. 100386, Nov. 2021, doi: 10.1016/J.YNSTR.2021.100386.\u003c/li\u003e\n \u003cli\u003eJ. E. Pope, \u0026ldquo;Management of Fatigue in Rheumatoid Arthritis,\u0026rdquo; 2020, doi: 10.1136/rmdopen-2019-001084.\u003c/li\u003e\n \u003cli\u003eE. T. Craig \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;What Does the Patient Global Health Assessment in Rheumatoid Arthritis Really Tell Us? Contribution of Specific Dimensions of Health-Related Quality of Life,\u0026rdquo; \u003cem\u003eArthritis Care Res (Hoboken)\u003c/em\u003e, vol. 72, no. 11, pp. 1571\u0026ndash;1578, Nov. 2020, doi: 10.1002/ACR.24073.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cem\u003eSociodemographic data of the Participants\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"566\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e65.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e12.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 197px;\"\u003e\n \u003cp\u003eGender (Male/Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e46/415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e10/90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYears of study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e8.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eMonths of symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e678\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eLiving together\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e55.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eEmployment status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e37.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eHomemaker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eEmployed with a formal work contract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eOn sick leave/receiving social security disability benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eWorking without a formal contract or registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eSelf-employed with official registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e4.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eUnemployed, seeking a job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNot informed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u003cem\u003ePredictors of mental health (Mental SF-12).\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"539\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e324.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e20.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eCDAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e11.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003ePain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eHAQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e6.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.013*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003ePhysical SF-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e38.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eNot getting a good night\u0026apos;s sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e16.326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e53.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 539px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eCDAI = Clinical Disease Activity Index; HAQ = Health Assessment Questionnaire; SF-12 = 12-Item Health Survey.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"pain, chronic disease, mental health, Rheumatoid Arthritis","lastPublishedDoi":"10.21203/rs.3.rs-6924681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6924681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study analyzed the influence of pain perception, functional capacity, quality of life, and disease activity on the mental health of patients with Rheumatoid Arthritis (RA). A quantitative cross-sectional cohort study was conducted with 461 adults (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;65.10; \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.00), of whom 415 were women. Participants completed a sociodemographic and health conditions questionnaire, the Health Assessment Questionnaire Disability Index (HAQ-DI), the 12-item Short Form Health Survey (SF-12), and the Clinical Disease Activity Index (CDAI). Regression analyses revealed that CDAI (β = -0.066), fatigue (β = -0.143), joint pain (β = -0.079), HAQ-DI (β\u0026thinsp;=\u0026thinsp;0.093), physical SF-12 (β = -0.222), poor sleep quality (β = -0.065), stress (β = -0.197), anxiety (β = -0.087), and depression (β = -0.312) significantly predicted mental health outcomes. Therefore, RA may negatively affect patients\u0026rsquo; mental health, being associated with stress, poor sleep, depression, and anxiety, which in turn may exacerbate pain perception. Incorporating quality of life assessments into routine clinical consultations may provide a more comprehensive approach to care, addressing both physical and emotional dimensions of health in patients with RA.\u003c/p\u003e","manuscriptTitle":"The relation between clinical characteristics and mental health in patients with Rheumatoid Arthritis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 12:29:51","doi":"10.21203/rs.3.rs-6924681/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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Reports","date":"2025-06-18T15:45:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f118bd19-f393-41ef-ad4e-bdf32615f7d0","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51529230,"name":"Biological sciences/Psychology"},{"id":51529231,"name":"Health sciences/Diseases"},{"id":51529232,"name":"Health sciences/Medical research"},{"id":51529233,"name":"Health sciences/Rheumatology"},{"id":51529234,"name":"Health sciences/Health care/Health services"},{"id":51529235,"name":"Health sciences/Health care/Quality of life"}],"tags":[],"updatedAt":"2025-11-10T16:08:28+00:00","versionOfRecord":{"articleIdentity":"rs-6924681","link":"https://doi.org/10.1038/s41598-025-22155-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-03 15:57:50","publishedOnDateReadable":"November 3rd, 2025"},"versionCreatedAt":"2025-07-18 12:29:51","video":"","vorDoi":"10.1038/s41598-025-22155-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-22155-3","workflowStages":[]},"version":"v1","identity":"rs-6924681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6924681","identity":"rs-6924681","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}