(1) Background: The cognitive reserve (CR) concept has not been precisely defined in severe mental disorders and has been estimated using heterogeneous methods. This study aims to investigate and develop the psychometric properties of the Cognitive Reserve Assessment Scale in Health (CRASH), an instrument designed to measure CR in people with severe mental illness; (2) Methods: 100 patients with severe mental illness (non-affective psychoses and affective disorders) and 66 healthy controls were included. The internal consistency and convergent validity of CRASH were assessed. Spearman’s correlations coefficients were also performed to examine the relationship between CRASH and neuropsychological tests, psychosocial functioning, and clinical course; (3) Results: The internal consistency was high (Cronbach’s alpha coefficient = 0.903). The CRASH global score had a large positive correlation with the Cognitive reserve questionnaire total score (r = 0.838, p < 0.001), demonstrating good convergent validity. The correlation coefficients between the CRASH total scores and clinical, functional, and neuropsychological performance were different between groups. In order to provide clinical interpretation, severity classification based on diagnosis (non-affective psychotic disorders, affective disorders, and healthy controls) have been created; (4) Conclusions: CRASH is the first CR measure developed specifically for patients with severe mental illness, facilitating reliable and valid measurement of this construct. The scale may aid in the stratification of patients and the implementation of personalized interventions.

Introduction: Early recognition of bipolar disorder improves the prognosis and decreases the burden of the disease. However, there is a significant delay in diagnosis. Multiple risk factors for bipolar disorder have been identified and a population at high-risk for the disorder has been more precisely defined. These advances have allowed the development of risk calculators to predict individual risk of conversion to bipolar disorder. This review aims to identify the risk calculators for bipolar disorder and assess their clinical applicability. Methods: A systematic review of original studies on the development of risk calculators in bipolar disorder was performed. The studies’ quality was evaluated with the Newcastle-Ottawa Quality Assessment Form for Cohort Studies and according to recommendations of the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis Initiative. Results: Three studies met the inclusion criteria; one developed a risk calculator of conversion from major depressive episode to bipolar disorder; one of conversion to new-onset bipolar spectrum disorders in offspring of parents with bipolar disorder; and the last one of conversion in youths with bipolar disorder not-otherwise-specified. Conclusions: The calculators reviewed in this article present good discrimination power for bipolar disorder, although future replication and validation of the models is needed.

Being able to predict functional outcomes after First-Episode Psychosis (FEP) is a major goal in psychiatry. Thus, we aimed to identify trajectories of psychosocial functioning in a FEP cohort followed-up for 2 years in order to find premorbid/baseline predictors for each trajectory. Additionally, we explored diagnosis distribution within the different trajectories. A total of 261 adults with FEP were included. Latent class growth analysis identified four distinct trajectories: Mild impairment-Improving trajectory (Mi-I) (38.31% of the sample), Moderate impairment-Stable trajectory (Mo-S) (18.39%), Severe impairment-Improving trajectory (Se-I) (12.26%), and Severe impairment-Stable trajectory (Se-S) (31.03%). Participants in the Mi-I trajectory were more likely to have higher parental socioeconomic status, less severe baseline depressive and negative symptoms, and better premorbid adjustment than individuals in the Se-S trajectory. Participants in the Se-I trajectory were more likely to have better baseline verbal learning and memory and better premorbid adjustment than those in the Se-S trajectory. Lower baseline positive symptoms predicted a Mo-S trajectory vs. Se-S trajectory. Diagnoses of Bipolar disorder and Other psychoses were more prevalent among individuals falling into Mi-I trajectory. Our findings suggest four distinct trajectories of psychosocial functioning after FEP. We also identified social, clinical, and cognitive factors associated with more resilient trajectories, thus providing insights for early interventions targeting psychosocial functioning.

Objective: This study was aimed at identifying differences in the prodromal symptoms and their duration, risk factors and markers of vulnerability in patients presenting a first episode mania (FEM) or psychosis (FEP) with onset in late adolescence or adulthood in order to guide tailored treatment strategies.Methods: Patients with a FEM or FEP underwent a clinical assessment. Prodromes were evaluated with the Bipolar Prodrome Symptom Scale‐Retrospective (BPSS‐R). Chi‐squared tests were conducted to assess specific prodromal symptoms, risk factors or markers of vulnerability between groups. Significant prodromal symptoms were entered in a stepwise forward logistic regression model. The probabilities of a gradual versus rapid onset pattern of the prodromes were computed with logistic regression models.Results: The total sample included 108 patients (FEM = 72, FEP = 36). Social isolation was associated with the prodromal stage of a FEP whilst Increased energy or goal‐directed activity with the prodrome to a FEM. Physically slowed down presented the most gradual onset whilst Increased energy presented the most rapid. The presence of obstetric complications and difficulties in writing and reading during childhood were risk factors for FEP. As for markers of vulnerability, impairment in premorbid adjustment was characteristic of FEP patients. No specific risk factor or marker of vulnerability was identified for FEM.Conclusion: Early characteristics differentiating FEP from FEM were identified. These findings might help shape early identification and preventive intervention programmes.

Objective: The use of electroconvulsive therapy (ECT) in the treatment of bipolar disorder (BD) remains poorly described. Based on data from Danish registries with complete nationwide coverage, this study of patients with incident BD aimed to describe when, how, and for whom ECT is used in the context of BD.Methods: We identified patients receiving their first diagnosis of BD in the period from 2008 to 2018, who subsequently received ECT. Descriptive statistics were used to clarify when, how, and for whom ECT is used.Results: We identified 1338 patients with incident BD who subsequently received ECT. The median age at the first ECT session was 50.6 years (interquartile range [IQR]: 26.4), and 62% of those treated with ECT were female. The median time from the diagnosis of BD to the first ECT treatment was 0.6 years (IQR: 2.6), and 58% of the patients receiving ECT had the first treatment within the first year after being diagnosed with BD. The most common indication for the first ECT treatment was depression (mainly non‐psychotic depression), followed by mania (mainly psychotic mania). The first ECT session was typically provided to inpatients (97%), upon patient consent (98%) and with bilateral electrode placement (60%).Conclusions: A substantial proportion of the patients with incident BD who receive ECT require this treatment within the first year after the diagnosis. The most common indication for ECT is depression followed by (psychotic) mania. Inpatient voluntary ECT using bilateral electrode placement is the most common form of administration.