ABSTRACT Objectives Traditional measures of well‐being in bipolar disorder (BD) often equate well‐being with the absence of mood symptoms, overlooking strengths‐based indicators like acceptance, agency, and positive emotion that individuals with BD identify as central to their lived experience of wellness. To address this misalignment, we developed and psychometrically validated a new well‐being measure, the Well‐being Evaluation for Living with Bipolar (WELL‐B), grounded in the concept of thriving. Methods The WELL‐B was co‐designed with individuals with BD and caregivers through a collaborative learning health system and piloted in the Prechter Longitudinal Study for Bipolar Disorder (PLS‐BD). Participants ( N = 192) completed the WELL‐B twice over 2 months. The WELL‐B captured personalized, qualitative examples of well‐being across eight domains and corresponding quantitative ratings using four overarching prompts. Using both Classical Test Theory and Modern Test Theory frameworks, we evaluated factor structure, internal consistency, item‐level properties, test–retest reliability, and convergent and divergent validity. Results Exploratory factor analysis revealed a stable three‐factor solution: general well‐being, time availability, and work‐related well‐being factors. All factors showed strong internal consistency (alphas > 0.85), and item response theory analyses indicated moderate to high item discrimination. The well‐being factor was strongly associated with better mental health functioning and lower depression, anxiety, and alcohol use. Most participants rated the WELL‐B as acceptable, feasible, and meaningful for reflecting on their wellness. Conclusions The WELL‐B offers a strengths‐based, patient‐centered approach to assessing well‐being in BD. Future directions include refinement, broader validation, and testing clinical utility for treatment planning and monitoring.
ABSTRACT Introduction While bipolar disorder is associated with significant comorbidity, little is known about the musculoskeletal health of individuals with bipolar disorder. Thus, we aimed to investigate the association between bipolar disorder and muscle strength, mass, quality and sarcopenia. Methods Women with bipolar disorder ( n = 106) were recruited from healthcare settings and age‐matched to controls ( n = 300), without bipolar disorder, from the Geelong Osteoporosis Study. Both groups, aged ≥ 20 years. were drawn from South‐Eastern Australia. Bipolar disorder was identified using a clinical interview (SCID‐I/NP). Maximum handgrip strength (HGS) was measured using a Jamar dynamometer, appendicular lean mass (ALM) using a Lunar densitometer and body mass index (BMI, kg/m 2 ) was calculated. Foundation for the National Institute of Health (FNIH) and European Working Group on Sarcopenia in Older People (EWGSOP2) algorithms were used to determine low HGS, ALM, probable and confirmed sarcopenia. Socioeconomic status (SES) was determined and information on lifestyle obtained via questionnaire. Results Higher proportion of women with bipolar disorder met criteria for low HGS and ALM compared to those without bipolar disorder. Using FNIH and EWGSOP2 criteria, 36 (8.9%; 34 probable and 2 confirmed) and 46 (11.4%; 43 probable and 3 confirmed) women met criteria for sarcopenia, respectively. Women with bipolar disorder were twice as likely to have sarcopenia (FNIH; OR 2.24, 95% CI: 1.11–4.55 and EWGSOP2; OR 2.78, 95% CI: 1.47–5.20), independent of age, smoking, activity, alcohol, diet and SES. Conclusion These data suggest women with bipolar disorder have an increased likelihood of sarcopenia. Replication and research into underlying mechanisms are next necessary steps.
ABSTRACT Background The global prevalence of major depressive disorder and bipolar depression (BD) has increased, with BD often underdiagnosed and mismanaged. This study aims to identify key biomarkers from demographic and laboratory indicators to differentiate unipolar depression (UD) from BD, aiding early diagnosis and personalized treatment. Methods This study was conducted at the Second Affiliated Hospital of Xinxiang Medical University between January 2022 and December 2024. A total of 174 inpatients were included, with 87 diagnosed with UD and 87 with BD. Demographic and laboratory data were collected. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors. Receiver operating characteristic (ROC) curve analysis was used to evaluate discriminatory ability. Results BD exhibited a higher male proportion ( p = 0.004) and significantly elevated total bilirubin (TBIL), creatinine, and creatine kinase (CK) levels, along with lower thyroxine (T4) levels, compared to UD ( p < 0.05). Multivariate analysis identified platelets, TBIL, T4, and CK as independent risk factors ( p < 0.05). ROC analysis revealed TBIL (Area Under the Curve [AUC] = 0.609) and CK (AUC = 0.621) as key discriminators, with a combined model achieving an AUC of 0.724, sensitivity of 75.9%, and specificity of 59.8%. Conclusions Key metabolic and muscular biomarkers, including TBIL, CK, PLT, and T4, were identified as potential differentiators between UD and BD. These findings demonstrated diagnostic potential and underscored the need for further validation in larger studies.
ABSTRACT Background In clinics, major depressive episodes (MDE) in adolescents and early adults with mood disorders are a prevalent manifestation with limited treatment efficacy. Previous studies have suggested that early‐stage treatment response is an important predictor of patients' final clinical outcome. Finding clinical features related to early‐stage treatment response is crucial for optimizing interventions and understanding outcome determinants. Methods We conducted a study involving 218 inpatients aged 13–25 years with mood disorders currently in MDE. We evaluated patients' multi‐dimensional clinical features both at baseline and after 2 weeks of treatment; the main outcome measure was the reduction rate of total the 17‐item Hamilton Depression Rating Scale (HAMD‐17) scores between baseline and 2 weeks of treatment. Logistic regression analysis was applied to identify baseline predictive clinical factors. Results Baseline HAMD total score (OR = 1.10, 95% CI [1.00, 1.20], p = 0.045) and thought disorder factor scores of Brief Psychiatric Rating Scale (BPRS) (OR = 0.79, 95% CI [0.70, 0.91], p < 0.001) were significantly associated with early‐stage treatment response. Conclusion Our study contributes to predicting early‐stage treatment response in adolescents and young adults with MDE based on baseline clinical features. Baseline HAMD total score and thought disorder factor scores of BPRS are potential clinical predictors. Understanding such factors enhances treatment decision‐making and efficacy.
BACKGROUND:Lithium has long been associated with reduced suicide risk in bipolar disorder; however, evidence from real-world clinical populations remains susceptible to confounding, and the behavioral correlates related to this association are not well characterized. METHODS:In this multicenter cross-sectional study, 616 individuals aged 12-45 years with bipolar disorder were recruited from 14 psychiatric centers, of whom 585 had complete data for the present analyses. Lithium exposure within the past year was determined from clinical records. The primary outcome was a composite of suicide-related behaviors, including suicidal ideation, suicide attempts, and non-suicidal self-injury. A pre-specified analytical framework was applied, with multivariable logistic regression as the primary analysis and propensity score matching (PSM) as the principal approach to improve covariate balance. Regression-based decomposition analyses were conducted to examine whether aggression was statistically associated with the exposure-outcome relationship, and restricted cubic spline models were used to characterize the dose-response association between aggression and suicide-related behaviors. Robustness analyses included inverse probability of treatment weighting (IPTW), alternative matching specifications, E-value analyses, cluster-robust standard errors, and exploratory age-stratified analyses. RESULTS:Lithium exposure was associated with lower odds of suicide-related behaviors in both the fully adjusted model (OR = 0.55, 95% CI: 0.34-0.89) and the propensity score-matched sample (OR = 0.53, 95% CI: 0.33-0.86). Higher aggression scores were linearly associated with increased suicide-related risk. Exploratory regression-based decomposition analyses indicated that approximately 20.93% of the observed lithium-outcome association was statistically accounted for by aggression. Results from robustness analyses were directionally consistent with the primary findings. CONCLUSIONS:In this multicenter clinical sample, lithium exposure was consistently associated with lower odds of suicide-related behaviors across multiple analytic approaches. Aggression was independently associated with suicide-related risk and statistically accounted for part of the observed association between lithium exposure and suicide-related outcomes. However, causal inference is limited by the cross-sectional design, and residual confounding-particularly confounding by indication-remains a key concern. Prospective longitudinal studies are required to clarify temporal relationships and disentangle treatment effects from selection processes.
