A 30-Day Adjunct Wellness Intervention for the Management of Extra-Articular Symptoms of Rheumatoid Arthritis: A Formative Study.

Individuals with rheumatoid arthritis (RA) continually fall short of treatment targets using standard drug therapies alone. There is growing evidence that emphasizing physical and mental wellness is equally crucial for improving functioning among people with RA. The purpose of this formative study is to examine the feasibility of offering the wellness-based intervention ("KickStart30") in patients with RA. Thirteen individuals with RA on targeted immune modulators (a biologic or JAK inhibitor) enrolled in the KickStart30 program. Participants completed self-report measures of RA-specific disability (eg, pain) and other functional areas (eg, mood) in a pre- versus post- intervention design. Paired samples t-tests (and Related-Samples Wilcoxon Signed Rank Tests for non-normal distributions) detected statistically significant results for 10 of 12 measures, including reductions in pain (M = 4.54 to M = 3.54; p = .025; BPI), functional disability (M = 0.94 to M = 0.73, p = .032; HAQ-II), cognitive and physical dysfunction (M = 25.46 to M = 13.54, p < .001; CPFQ), depressive symptoms (M = 9.31 to M = 5.54, p = .003; PHQ-9), anxiety (M = 5.69 to M = 3.23, p = .005; GAD-7), insomnia (M = 11.62 to M = 17.32, p = .007; Note: higher scores on the SCI indicate less insomnia), stress-related eating (M = 75.46 to M = 84.54, p = .021; Note: higher scores on the EADES indicate less stress-related eating), along with significant increases in mindfulness (M = 62.54 to M = 67.85, p = .040; MAAS), mental wellness (M = 4.46 to M = 5.69; HERO), and well-being (Md = 8.00 to Md = 5.00, p = .004; WHO-5). All significant measures had medium to large effect sizes (Cohen's d). The study gives preliminary support for the possibility that the adjunct intervention may have an effect.

Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, and Electronic Health Records.

Importance: Half of the people who die by suicide make a health care visit within 1 month of their death. However, clinicians lack the tools to identify these patients. Objective: To predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems. Design, Setting, and Participants: This prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was performed from May 1, 2020, to November 19, 2021. Main Outcomes and Measures: Suicide attempts 1 and 6 months after presentation to the ED were defined by combining data from electronic health records (EHRs) with patient 1-month (n = 1102) and 6-month (n = 1220) follow-up surveys. Ensemble machine learning was used to develop predictive models and a risk score for suicide. Results: A total of 1818 patients participated in this study (1016 men [55.9%]; median age, 33 years [IQR, 24-46 years]; 266 Hispanic patients [14.6%]; 1221 non-Hispanic White patients [67.2%], 142 non-Hispanic Black patients [7.8%], 64 non-Hispanic Asian patients [3.5%], and 125 non-Hispanic patients of other race and ethnicity [6.9%]). A total of 137 of 1102 patients (12.9%; weighted prevalence) attempted suicide within 1 month, and a total of 268 of 1220 patients (22.0%; weighted prevalence) attempted suicide within 6 months. Clinicians' assessment alone was little better than chance at predicting suicide attempts, with externally validated area under the receiver operating characteristic curve (AUC) of 0.67 for the 1-month model and 0.60 for the 6-month model. Prediction accuracy was slightly higher for models based on EHR data (1-month model: AUC, 0.71; 6 month model: AUC, 0.65) and was best using patient self-reports (1-month model: AUC, 0.76; 6-month model: AUC, 0.77), especially when patient self-reports were combined with EHR and/or clinician data (1-month model: AUC, 0.77; and 6 month model: AUC, 0.79). A model that used only 20 patient self-report questions and an EHR-based risk score performed similarly well (1-month model: AUC, 0.77; 6 month model: AUC, 0.78). In the best 1-month model, 30.7% (positive predicted value) of the patients classified as having highest risk (top 25% of the sample) made a suicide attempt within 1 month of their ED visit, accounting for 64.8% (sensitivity) of all 1-month attempts. In the best 6-month model, 46.0% (positive predicted value) of the patients classified at highest risk made a suicide attempt within 6 months of their ED visit, accounting for 50.2% (sensitivity) of all 6-month attempts. Conclusions and Relevance: This prognostic study suggests that the ability to identify patients at high risk of suicide attempt after an ED visit for psychiatric problems improved using a combination of patient self-reports and EHR data.