Three types of university students with subthreshold depression characterized by distinctive cognitive behavioral skills.

Subthreshold depression impairs young people's quality of life and places them at greater risk of developing major depression. Cognitive behavioral therapy (CBT) is an evidence-based approach for addressing such depressive states. This study identified subtypes of university students with subthreshold depression and revealed discrete profiles of five CBT skills: self-monitoring, cognitive restructuring, behavioral activation, assertive communication, and problem solving. Using data from the Healthy Campus Trial (registration number: UMINCTR-000031307), a hierarchical clustering analysis categorized 1,080 students into three clusters: Reflective Low-skilled, Non-reflective High-skilled, and Non-reflective Low-skilled students. Non-reflective Low-skilled students were significantly more depressed than other students (p < .001). The severity of depression seemed to be related to the combination of self-monitoring skills and other CBT skills. Considering the high prevalence of poor self-monitoring skills in persons with autism, the most severe depression was observed in the significant association between Non-reflective Low-skilled students and autistic traits (p = .008). These findings suggest that subthreshold depression can be categorized into three subtypes based on CBT skill profiles. The assessment of autistic traits is also suggested when we provide CBT interventions for Non-reflective Low-skilled students.

Training in neuropsychiatry: views of early career psychiatrists from across the world.

BACKGROUND: Training and practice in neuropsychiatry varies across the world. However, little is known about the experiences and opinions of early career psychiatrists (ECPs) across different countries regarding neuropsychiatry. AIMS AND METHOD: To investigate neuropsychiatry training experiences, practices and opinions among ECPs across different countries. An online survey was distributed to ECPs in 35 countries across the world. RESULTS: A total of 522 participants took part in this study. Responses show that neuropsychiatry is integrated to a variable extent in psychiatric training curricula across the world. Most respondents were not aware of the existence of neuropsychiatric training or of neuropsychiatric units. Most agreed that training in neuropsychiatry should be done during or after the psychiatry training period. Lack of interest among specialty societies, lack of time during training, and political and economic reasons are regarded as the main barriers. CLINICAL IMPLICATIONS: These findings call for an improvement in the extent and in the quality of neuropsychiatry training across the world.

Prognostic factors and effect modifiers for personalisation of internet-based cognitive behavioural therapy among university students with subthreshold depression: A secondary analysis of a factorial trial.

BACKGROUND: Internet-cognitive behavioural therapy (iCBT) for depression can include multiple components. This study explored depressive symptom improvement prognostic factors (PFs) and effect modifiers (EMs) for five common iCBT components including behavioural activation, cognitive restructuring, problem solving, self-monitoring, and assertion training. METHODS: We used data from a factorial trial of iCBT for subthreshold depression among Japanese university students (N = 1093). The primary outcome was the change in PHQ-9 scores at 8 weeks from baseline. Interactions between each component and various baseline characteristics were estimated using a mixed-effects model for repeated measures. We calculated multiplicity-adjusted p-values at 5 % false discovery rate using the Benjamini-Hochberg procedure. RESULTS: After multiplicity adjustment, the baseline PHQ-9 total score emerged as a PF and exercise habits as an EM for self-monitoring (adjusted p-values <0.05). The higher the PHQ-9 total score at baseline (range: 5-14), the greater the decrease after 8 weeks. For each 5-point increase at baseline, the change from baseline to 8 weeks was bigger by 2.8 points. The more frequent the exercise habits (range: 0-2 points), the less effective the self-monitoring component. The difference in PHQ-9 change scores between presence or absence of self-monitoring was smaller by 0.94 points when the participant exercised one level more frequently. Additionally, the study suggested seven out of 36 PFs and 14 out of 160 EMs examined were candidates for future research. LIMITATIONS: Generalizability is limited to university students with subthreshold depression. CONCLUSIONS: These results provide some helpful information for the future development of individualized iCBT algorithms for depression.

Validation of the Japanese Big Five Scale Short Form in a University Student Sample.

The Japanese Big Five Scale Short Form (JBFS-SF), a 29-item self-report scale, has recently been used to measure the Big Five personality traits. However, the scale lacks psychometric validation. This study examined the validity and reliability of the JBFS-SF with data collected from 1,626 Japanese university students participating in a randomized controlled clinical trial. Structural validity was tested with exploratory and confirmatory factor analysis and measurement invariance tests were conducted across sex. Internal consistency was evaluated with McDonald's omega. Additionally, construct validity was estimated across factors using the PHQ-9, GAD-7, AQ-J-10, and SSQ. EFA results showed that the JBFS-SF can be classified according to the expected five-factor structure, while three items had small loadings. Therefore, we dropped these three items and tested the reliability and validity of the 26-item version. CFA results found that a 26-item JBFS-FS has adequate structural validity (GFI = 0.907, AGFI = 0.886, CFI = 0.907, and RMSEA = 0.057). The omega of each factor was 0.74-0.85. Each JBFS-SF factor was specifically correlated with the PHQ-9, GAD-7, and SSQ. This research has shown that the JBFS-SF can be a clinically useful measure for assessing personality characteristics.

Providing Brief Personalized Therapies for Insomnia Among Workers Using a Sleep Prompt App: Randomized Controlled Trial.

BACKGROUND: Insomnia is the most common sleep disorder and the foremost health concern among workers. We developed a new sleep prompt app (SPA) for smartphones to positively alter the users' consciousness and behavior by sending timely short messages for mild sleep problems at an early stage. OBJECTIVE: The aim of this study is to investigate the effectiveness of the SPA in providing brief personalized therapy for insomnia among workers. METHODS: We conducted a 2-arm parallel randomized controlled trial. The intervention group used the SPA, and the control group received no intervention. Participants were recruited between November 2020 and January 2021. The researcher sent emails for recruitment to more than 3000 workers of 2 companies and 1 university in Japan. The SPA provided personalized prompt messages, sleep diaries, sleep hygiene education, stimulus control therapy, and sleep restriction therapy. The prompt messages were sent automatically to the participants to encourage them to improve their sleep habits and sleep status and were optimized to the individual's daily rhythm. The intervention program duration was 4 weeks. The primary outcome was a change in the Insomnia Severity Index (ISI) for the study period. The ISI was obtained weekly using a web questionnaire. RESULTS: A total of 116 Japanese workers (intervention group n=60, control group n=56) with sleep disorders were recruited. Two participants in the intervention group were excluded from the analyses because of challenges in installing the SPA. The mean ISI scores at baseline were 9.2 for both groups; however, after 4 weeks, the mean ISI scores declined to 6.8 and 8.0 for the intervention and control groups, respectively. Primary analysis using a linear mixed model showed a significant improvement in the temporal trends of the ISI in the SPA group and in the total population (P=.03). Subgroup analyses of ISI-8-insomniacs revealed a significant improvement in the temporal trends of ISI in the SPA group (P=.01), and the CFS score for physical condition significantly improved following the intervention (P=.02). CONCLUSIONS: This study demonstrates the effectiveness of the SPA in providing brief personalized therapy for insomnia among Japanese workers with mild insomnia. The physical fatigue score significantly improved in ISI-8-insomniacs. Thus, SPA could play an important role in reducing the adverse effects of sleep disorders in workers. To promote the wide use of the SPA in the future, further studies are required to examine its effectiveness in other age groups and individuals with health problems. TRIAL REGISTRATION: University Medical Information Network Clinical Trials Registry (UMIN-CTR) UMIN000042263; https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000046295.

Machine Learning Algorithm-Based Prediction Model for the Augmented Use of Clozapine with Electroconvulsive Therapy in Patients with Schizophrenia.

The augmentation of clozapine with electroconvulsive therapy (ECT) has been an optimal treatment option for patients with treatment- or clozapine-resistant schizophrenia. Using data from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics survey, which was the largest international psychiatry research collaboration in Asia, our study aimed to develop a machine learning algorithm-based substantial prediction model for the augmented use of clozapine with ECT in patients with schizophrenia in terms of precision medicine. A random forest model and least absolute shrinkage and selection operator (LASSO) model were used to develop a substantial prediction model for the augmented use of clozapine with ECT. Among the 3744 Asian patients with schizophrenia, those treated with a combination of clozapine and ECT were characterized by significantly greater proportions of females and inpatients, a longer duration of illness, and a greater prevalence of negative symptoms and social or occupational dysfunction than those not treated. In the random forest model, the area under the curve (AUC), which was the most preferred indicator of the prediction model, was 0.774. The overall accuracy was 0.817 (95% confidence interval, 0.793−0.839). Inpatient status was the most important variable in the substantial prediction model, followed by BMI, age, social or occupational dysfunction, persistent symptoms, illness duration > 20 years, and others. Furthermore, the AUC and overall accuracy of the LASSO model were 0.831 and 0.644 (95% CI, 0.615−0.672), respectively. Despite the subtle differences in both AUC and overall accuracy of the random forest model and LASSO model, the important variables were commonly shared by the two models. Using the machine learning algorithm, our findings allow the development of a substantial prediction model for the augmented use of clozapine with ECT in Asian patients with schizophrenia. This substantial prediction model can support further studies to develop a substantial prediction model for the augmented use of clozapine with ECT in patients with schizophrenia in a strict epidemiological context.

Components of smartphone cognitive-behavioural therapy for subthreshold depression among 1093 university students: a factorial trial.

BACKGROUND: Internet-based cognitive-behavioural therapy (iCBT) is effective for subthreshold depression. However, which skills provided in iCBT packages are more effective than others is unclear. Such knowledge can inform construction of more effective and efficient iCBT programmes. OBJECTIVE: To examine the efficacy of five components of iCBT for subthreshold depression. METHODS: We conducted an factorial trial using a smartphone app, randomly allocating presence or absence of five iCBT skills including self-monitoring, behavioural activation (BA), cognitive restructuring (CR), assertiveness training (AT) and problem-solving. Participants were university students with subthreshold depression. The primary outcome was the change on the Patient Health Questionnaire-9 (PHQ-9) from baseline to week 8. Secondary outcomes included changes in CBT skills. FINDINGS: We randomised a total of 1093 participants. In all groups, participants had a significant PHQ-9 reduction from baseline to week 8. Depression reduction was not significantly different between presence or absence of any component, with corresponding standardised mean differences (negative values indicate specific efficacy in favour of the component) ranging between -0.04 (95% CI -0.16 to 0.08) for BA and 0.06 (95% CI -0.06 to 0.18) for AT. Specific CBT skill improvements were noted for CR and AT but not for the others. CONCLUSIONS: There was significant reduction in depression for all participants regardless of the presence and absence of the examined iCBT components. CLINICAL IMPLICATION: We cannot yet make evidence-based recommendations for specific iCBT components. We suggest that future iCBT optimisation research should scrutinise the amount and structure of components to examine. TRIAL REGISTRATION NUMBER: UMINCTR-000031307.

Development of a classifier for gambling disorder based on functional connections between brain regions.

AIM: Recently, a machine-learning (ML) technique has been used to create generalizable classifiers for psychiatric disorders based on information of functional connections (FCs) between brain regions at resting state. These classifiers predict diagnostic labels by a weighted linear sum (WLS) of the correlation values of a small number of selected FCs. We aimed to develop a generalizable classifier for gambling disorder (GD) from the information of FCs using the ML technique and examine relationships between WLS and clinical data. METHODS: As a training dataset for ML, data from 71 GD patients and 90 healthy controls (HCs) were obtained from two magnetic resonance imaging sites. We used an ML algorithm consisting of a cascade of an L1-regularized sparse canonical correlation analysis and a sparse logistic regression to create the classifier. The generalizability of the classifier was verified using an external dataset. This external dataset consisted of six GD patients and 14 HCs, and was collected at a different site from the sites of the training dataset. Correlations between WLS and South Oaks Gambling Screen (SOGS) and duration of illness were examined. RESULTS: The classifier distinguished between the GD patients and HCs with high accuracy in leave-one-out cross-validation (area under curve (AUC = 0.89)). This performance was confirmed in the external dataset (AUC = 0.81). There was no correlation between WLS, and SOGS and duration of illness in the GD patients. CONCLUSION: We developed a generalizable classifier for GD based on information of functional connections between brain regions at resting state.

The validity and reliability of the Japanese version of RU-SATED.

OBJECTIVE: We developed a Japanese version of RU-SATED (RU-SATED-J), a simple self-rated scale for measurement of multidimensional sleep health, and examined its reliability and psychometric validity. METHOD: The RU-SATED-J was developed by a rigorous reverse translation process. It consists of six questions, each with three Likert-type response options. The total score (range 0-12) was calculated by summing the item scores. Psychometric characteristics were tested in an observational cross-sectional study involving factory workers in Japan (n = 177, mean age 42.8 ± 11.6 years, range 19-65 years). The distribution and reliability of the scale scores were examined in terms of Cronbach's alpha coefficient. The convergent and divergent validity of the scale score were assessed by examining the correlations of various factors with the Insomnia Severity Index (ISI) and the Epworth Sleepiness Scale (ESS). RESULTS: The distribution of scores was left-skewed, with a mean of 8.21 ± 2.72 points, and range of 0-12. The internal reliability of the scale was α = 0.758. The total score showed a significant negative correlation with the ISS (rs = -0.542, P < 0.001) and the ESS (rs = -0.178, P = 0.018). Exploratory factor analysis (EFA) demonstrated a two-factor structure. Confirmatory factor analysis (CFA) showed that the goodness of fit of the higher-order factor model had a Root Mean Square Error of Approximation (RMSEA) of <0.001 and a Comparative Fit Index (CFI) of 1.00, confirming its factorial validity. CONCLUSION: The RU-SATED is a promising new instrument for measuring multi-dimensional sleep health perception among Japanese adults. Further general population studies using this Japanese version of the questionnaire should be considered.

Network Analysis-Based Disentanglement of the Symptom Heterogeneity in Asian Patients with Schizophrenia: Findings from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics.

The symptom heterogeneity of schizophrenia is consistent with Wittgenstein's analogy of a language game. From the perspective of precision medicine, this study aimed to estimate the symptom presentation and identify the psychonectome in Asian patients, using data obtained from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics. We constructed a network structure of the Brief Psychiatric Rating Scale (BPRS) items in 1438 Asian patients with schizophrenia. Furthermore, all the BPRS items were considered to be an ordered categorical variable ranging in value from 1-7. Motor retardation was situated most centrally within the BPRS network structure, followed by depressive mood and unusual thought content. Contrastingly, hallucinatory behavior was situated least centrally within the network structure. Using a community detection algorithm, the BPRS items were organized into positive, negative, and general symptom clusters. Overall, DSM symptoms were not more central than non-DSM symptoms within the symptom network of Asian patients with schizophrenia. Thus, motor retardation, which results from the unmet needs associated with current antipsychotic medications for schizophrenia, may be a tailored treatment target for Asian patients with schizophrenia. Based on these findings, targeting non-dopamine systems (glutamate, γ-aminobutyric acid) may represent an effective strategy with respect to precision medicine for psychosis.

A Call for a Rational Polypharmacy Policy: International Insights From Psychiatrists.

OBJECTIVE: Recently, rational polypharmacy approaches have been proposed, regardless of the lower risk and cost of monotherapy. Considering monotherapy as first-line treatment and polypharmacy as rational treatment, a balanced attitude toward polypharmacy is recommended. However, the high prevalence of polypharmacy led the Japanese government to establish a polypharmacy reduction policy. Based on this, the association between the policy and psychiatrists' attitude toward polypharmacy has been under debate. METHODS: We developed an original questionnaire about Psychiatrists' attitudes toward polypharmacy (PAP). We compared the PAP scores with the treatment decision-making in clinical case vignettes. Multiple regression analyses were performed to quantify associations of explanatory variables including policy factors and PAP scores. The anonymous questionnaires were administered to psychiatrists worldwide. RESULTS: The study included 347 psychiatrists from 34 countries. Decision-making toward polypharmacy was associated with high PAP scores. Multiple regression analysis revealed that low PAP scores were associated with the policy factor (ß=-0.20, p=0.004). The culture in Korea was associated with high PAP scores (ß=0.34, p<0.001), whereas the culture in India and Nepal were associated with low scores (ß=-0.15, p=0.01, and ß=-0.17, p=0.006, respectively). CONCLUSION: Policy on polypharmacy may influence psychiatrists' decision-making. Thus, policies considering rational polypharmacy should be established.

Factors associated with anxiety and depression in rheumatoid arthritis patients: a cross-sectional study.

BACKGROUND: The management of anxiety and depression symptoms in rheumatoid arthritis (RA) patients is vital. Previous study findings on this topic are conflicting, and the topic remains to be thoroughly investigated. This study aimed to clarify the association of RA disease activity with anxiety and depression symptoms after controlling for physical disability, pain, and medication. METHODS: We conducted a cross-sectional study of RA patients from the XXX Rheumatoid Arthritis Management Alliance cohort. We assessed patients using the Disease Activity Score (DAS28), Health Assessment Questionnaire Disability Index (HAQ-DI), and Hospital Anxiety and Depression Scale (HADS). Anxiety and depression symptoms were defined by a HADS score ≥ 8. We analyzed the data using multivariable logistic regression analyses. RESULTS: Of 517 participants, 17.6% had anxiety symptoms and 27.7% had depression symptoms. The multivariable logistic regression analysis demonstrated that DAS28 was not independently associated with anxiety symptoms (odds ratio [OR] [95% confidence interval; CI] 0.93 [0.48-1.78]; p = 0.82) and depression symptoms (OR [95% CI] 1.45 [0.81-2.61]; p = 0.22). However, DAS28 patient global assessment (PtGA) severity was associated with anxiety symptoms (OR [95% CI] 1.15 [1.02-1.29]; p = 0.03) and depression symptoms (OR [95% CI] 1.21 [1.09-1.35]; p < 0.01). Additionally, HAQ-DI scores ≤ 0.5 were associated with anxiety symptoms (OR [95% CI] 3.51 [1.85-6.64]; p < 0.01) and depression symptoms (OR [95% CI] 2.65 [1.56-4.50]; p < 0.01). Patients using steroids were more likely to have depression than those not using steroids (OR [95% CI] 1.66 [1.03-2.67]; p = 0.04). CONCLUSIONS: No association was found between RA disease activity and anxiety and depression symptoms in the multivariable logistic regression analysis. Patients with high PtGA scores or HAQ-DI scores ≤ 0.5 were more likely to experience anxiety and depression symptoms, irrespective of disease activity remission status. Rather than focusing solely on controlling disease activity, treatment should focus on improving or preserving physical function and the patient's overall sense of well-being.

Development and validation of the Cognitive Behavioural Therapy Skills Scale among college students.

BACKGROUND: There are many different skill components used in cognitive behavioural therapy (CBT). However, there is currently no comprehensive way of measuring these skills in patients. OBJECTIVE: To develop a comprehensive and brief measure of five main CBT skills: self-monitoring, behavioural activation, cognitive restructuring, assertiveness training and problem-solving. METHODS: University students (N=847) who participated in a fully factorial randomised controlled trial of smartphone CBT were assessed with the CBT Skills Scale, the Patient Health Questionnaire-9 (PHQ-9), the Generalised Anxiety Disorder-7 (GAD-7) and the short form of the Japanese Big Five Scale. Structural validity was estimated with exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), and internal consistency evaluated with Cronbach's α coefficients. Construct validity was evaluated with the correlations between each factor of the CBT Skills Scale, the PHQ-9, the GAD-7 and the Big Five Scale. FINDINGS: The EFA supported a five-factor solution based on the original instruments assessing each CBT skill component. The CFA showed sufficient goodness-of-fit indices for the five-factor structure. The Cronbach's α of each factor was 0.75-0.81. Each CBT skills factor was specifically correlated to the PHQ-9, GAD-7, and the Big Five Scale. CONCLUSIONS: The CBT Skills Scale has a stable structural validity and internal consistency with a five-factor solution and appropriate content validity concerning the relationship with depression, anxiety and personality. CLINICAL IMPLICATIONS: The CBT Skills Scale will be potential predictor and effect modifier in studying the optimisation of CBT interventions. TRIAL REGISTRATION: CTR-000031307.

Factors associated with anxiety and depression in rheumatoid arthritis patients: a cross-sectional study

Abstract Background: The management of anxiety and depression symptoms in rheumatoid arthritis (RA) patients is vital. Previous study findings on this topic are conflicting, and the topic remains to be thoroughly investigated. This study aimed to clarify the association of RA disease activity with anxiety and depression symptoms after controlling for physical disability, pain, and medication. Methods: We conducted a cross-sectional study of RA patients from the XXX Rheumatoid Arthritis Management Alliance cohort. We assessed patients using the Disease Activity Score (DAS28), Health Assessment Questionnaire Disability Index (HAQ-DI), and Hospital Anxiety and Depression Scale (HADS). Anxiety and depression symptoms were defined by a HADS score ≥ 8. We analyzed the data using multivariable logistic regression analyses. Results: Of 517 participants, 17.6% had anxiety symptoms and 27.7% had depression symptoms. The multivariable logistic regression analysis demonstrated that DAS28 was not independently associated with anxiety symptoms (odds ratio [OR] [95% confidence interval; CI] 0.93 [0.48-1.78]; p = 0.82) and depression symptoms (OR [95% CI] 1.45 [0.81-2.61]; p = 0.22). However, DAS28 patient global assessment (PtGA) severity was associated with anxiety symptoms (OR [95% CI] 1.15 [1.02-1.29]; p = 0.03) and depression symptoms (OR [95% CI] 1.21 [1.09-1.35]; p < 0.01). Additionally, HAQ-DI scores ≤ 0.5 were associated with anxiety symptoms (OR [95% CI] 3.51 [1.85-6.64]; p < 0.01) and depression symptoms (OR [95% CI] 2.65 [1.56-4.50]; p < 0.01). Patients using steroids were more likely to have depression than those not using steroids (OR [95% CI] 1.66 [1.03-2.67]; p = 0.04). Conclusions: No association was found between RA disease activity and anxiety and depression symptoms in the multivariable logistic regression analysis. Patients with high PtGA scores or HAQ-DI scores ≤ 0.5 were more likely to experience anxiety and depression symptoms, irrespective of disease activity remission status. Rather than focusing solely on controlling disease activity, treatment should focus on improving or preserving physical function and the patient's overall sense of well-being.

Anti-PDHA1 antibody is detected in a subset of patients with schizophrenia.

Autoantibodies have been implicated in schizophrenia aetiology. Here, novel autoantibodies were isolated from patients with schizophrenia. Autoantibody candidates were searched using two-dimensional gel electrophoresis and western blotting with rat brain proteins as antigens and two sera pools (25 schizophrenia patients versus 25 controls) as antibodies. Immunoreactive antigens were identified by mass spectrometry. Antibody prevalence were evaluated by western blotting using human recombinant proteins. Furthermore, brain magnetic resonance imaging data (regional brain volumes and diffusion tensor imaging measures) were compared. Two proteins of the mitochondrial respiration pathway were identified as candidate antigens. Three patients with schizophrenia, but no controls, expressed antibodies targeting one of the candidate antigens, i.e., pyruvate dehydrogenase E1 component subunit alpha, somatic form, mitochondrial (PDHA1, EC 1.2.4.1), which is related to mitochondrial energy production. Anti-PDHA1 antibody-positive patients (n = 3) had increased volumes in the left occipital fusiform gyrus compared to both controls (n = 23, p = 0.017) and antibody-negative patients (n = 16, p = 0.009), as well as in the left cuneus compared to antibody-negative patients (n = 16, p = 0.018). This is the first report of an anti-PDHA1 antibody in patients with schizophrenia. Compatible with recent findings of mitochondrial dysfunction in schizophrenia, this antibody may be involved in the pathogenesis of a specific subgroup of schizophrenia.

Effect of Physical State on Pain Mediated Through Emotional Health in Rheumatoid Arthritis.

OBJECTIVE: Pain is one of the main symptoms of patients with rheumatoid arthritis (RA). Pain in RA is caused by specific physical changes, such as joint destruction, and is therefore used as a disease activity marker. Although pain can also be influenced by emotional factors, neither the effect of emotional health nor the indirect effect of the physical state mediated by emotional health on pain has been quantified. METHODS: A total of 548 patients with RA participated. Emotional health was assessed using the Hospital Anxiety and Depression Scale (HADS). Measures routinely used in practice were used to evaluate the physical state and pain. To quantify the effects of the physical state on emotional health, and the effects of both physical and emotional health on pain, we used structural equation modeling, with emotional health, physical state, and pain as latent variables. RESULTS: The prevalence of anxiety and depression (HADS score ≥8 for each) among patients with RA was 18.7% and 29.4%, respectively. Emotional health was significantly influenced by the physical state (ß = 0.21). Pain was affected by physical (ß = 0.54) and emotional health (ß = 0.29). The effect of the physical state on pain was mediated by emotional health, with this mediation effect (ß = 0.06) accounting for 10.2% of the total effect. CONCLUSION: The magnitude of pain in RA is determined by the mediation effect of emotional health as well as the direct physical state. Our findings suggest that emotional factors should be taken into account when assessing RA disease activity.