Epidemiological data offer conflicting views of the natural course of binge-eating disorder (BED), with large retrospective studies suggesting a protracted course and small prospective studies suggesting a briefer duration. We thus examined changes in BED diagnostic status in a prospective, community-based study that was larger and more representative with respect to sex, age of onset, and body mass index (BMI) than prior multi-year prospective studies.

Probands and relatives with current DSM-IV BED (n = 156) from a family study of BED (‘baseline’) were selected for follow-up at 2.5 and 5 years. Probands were required to have BMI > 25 (women) or >27 (men). Diagnostic interviews and questionnaires were administered at all timepoints.

Of participants with follow-up data (n = 137), 78.1% were female, and 11.7% and 88.3% reported identifying as Black and White, respectively. At baseline, their mean age was 47.2 years, and mean BMI was 36.1. At 2.5 (and 5) years, 61.3% (45.7%), 23.4% (32.6%), and 15.3% (21.7%) of assessed participants exhibited full, sub-threshold, and no BED, respectively. No participants displayed anorexia or bulimia nervosa at follow-up timepoints. Median time to remission (i.e. no BED) exceeded 60 months, and median time to relapse (i.e. sub-threshold or full BED) after remission was 30 months. Two classes of machine learning methods did not consistently outperform random guessing at predicting time to remission from baseline demographic and clinical variables.

Among community-based adults with higher BMI, BED improves with time, but full remission often takes many years, and relapse is common.

While adolescent-onset schizophrenia (ADO-SCZ) and adolescent-onset bipolar disorder with psychosis (psychotic ADO-BPD) present a more severe clinical course than their adult forms, their pathophysiology is poorly understood. Here, we study potentially state- and trait-related white matter diffusion-weighted magnetic resonance imaging (dMRI) abnormalities along the adolescent-onset psychosis continuum to address this need.

Forty-eight individuals with ADO-SCZ (20 female/28 male), 15 individuals with psychotic ADO-BPD (7 female/8 male), and 35 healthy controls (HCs, 18 female/17 male) underwent dMRI and clinical assessments. Maps of extracellular free-water (FW) and fractional anisotropy of cellular tissue (FAT) were compared between individuals with psychosis and HCs using tract-based spatial statistics and FSL's Randomise. FAT and FW values were extracted, averaged across all voxels that demonstrated group differences, and then utilized to test for the influence of age, medication, age of onset, duration of illness, symptom severity, and intelligence.

Individuals with adolescent-onset psychosis exhibited pronounced FW and FAT abnormalities compared to HCs. FAT reductions were spatially more widespread in ADO-SCZ. FW increases, however, were only present in psychotic ADO-BPD. In HCs, but not in individuals with adolescent-onset psychosis, FAT was positively related to age.

We observe evidence for cellular (FAT) and extracellular (FW) white matter abnormalities in adolescent-onset psychosis. Although cellular white matter abnormalities were more prominent in ADO-SCZ, such alterations may reflect a shared trait, i.e. neurodevelopmental pathology, present across the psychosis spectrum. Extracellular abnormalities were evident in psychotic ADO-BPD, potentially indicating a more dynamic, state-dependent brain reaction to psychosis.

Despite evidence of gender differences in bipolar disorder characteristics and comorbidity, there is little research on the differences in treatment and service use between men and women with bipolar disorder.

To use routine data to describe specialist mental health service contact for bipolar disorder, including in-patient, community and support service contacts; to compare clinical characteristics and mental health service use between men and women in contact with secondary services for bipolar disorder.

Cross-sectional analysis of mental health patients with bipolar disorder in New Zealand, based on complete national routine health data.

A total of 3639 individuals were in contact with specialist mental health services with a current diagnosis of bipolar disorder in 2015. Of these 58% were women and 46% were aged 45 and over. The 1-year prevalence rate of bipolar disorder leading to contact with specialist mental health services was 1.56 (95% CI 1.50–1.63) per 100 000 women and 1.20 (95% CI 1.14–1.26) per 100 000 men. Rates of bipolar disorder leading to service contact were 30% higher in women than men (rate ratio 1.30, 95% CI 1.22–1.39). The majority (68%) had a diagnosis of bipolar I disorder. Women were more likely to receive only out-patient treatment and have comorbid anxiety whereas more men had substance use disorder, were convicted for crimes when unwell, received compulsory treatment orders and received in-patient treatment.

Although the prevalence of bipolar disorder is equal between men and women in the population, women were more likely to have contact with specialist services for bipolar disorder but had a lower intensity of service interaction.

Psychiatric disorders, including eating disorders (EDs), have clinical outcomes that range widely in severity and chronicity. The ability to predict such outcomes is extremely limited. Machine-learning (ML) approaches that model complexity may optimize the prediction of multifaceted psychiatric behaviors. However, the investigations of many psychiatric concerns have not capitalized on ML to improve prognosis. This study conducted the first comparison of an ML approach (elastic net regularized logistic regression) to traditional regression to longitudinally predict ED outcomes.

Females with heterogeneous ED diagnoses completed demographic and psychiatric assessments at baseline (n = 415) and Year 1 (n = 320) and 2 (n = 277) follow-ups. Elastic net and traditional logistic regression models comprising the same baseline variables were compared in ability to longitudinally predict ED diagnosis, binge eating, compensatory behavior, and underweight BMI at Years 1 and 2.

Elastic net models had higher accuracy for all outcomes at Years 1 and 2 [average Area Under the Receiving Operating Characteristics Curve (AUC) = 0.78] compared to logistic regression (average AUC = 0.67). Model performance did not deteriorate when the most important predictor was removed or an alternative ML algorithm (random forests) was applied. Baseline ED (e.g. diagnosis), psychiatric (e.g. hospitalization), and demographic (e.g. ethnicity) characteristics emerged as important predictors in exploratory predictor importance analyses.

ML algorithms can enhance the prediction of ED symptoms for 2 years and may identify important risk markers. The superior accuracy of ML for predicting complex outcomes suggests that these approaches may ultimately aid in advancing precision medicine for serious psychiatric disorders.

This study compared the best available treatment for bulimia nervosa, cognitive–behavioural therapy (CBT) augmented by fluoxetine if indicated, with a stepped-care treatment approach in order to enhance treatment effectiveness.

To establish the relative effectiveness of these two approaches.

This was a randomised trial conducted at four clinical centres (Clinicaltrials.gov registration number: NCT00733525). A total of 293 participants with bulimia nervosa were randomised to one of two treatment conditions: manual-based CBT delivered in an individual therapy format involving 20 sessions over 18 weeks and participants who were predicted to be non-responders after 6 sessions of CBT had fluoxetine added to treatment; or a stepped-care approach that began with supervised self-help, with the addition of fluoxetine in participants who were predicted to be non-responders after six sessions, followed by CBT for those who failed to achieve abstinence with self-help and medication management.

Both in the intent-to-treat and completer samples, there were no differences between the two treatment conditions in inducing recovery (no binge eating or purging behaviours for 28 days) or remission (no longer meeting DSM–IV criteria). At the end of 1-year follow-up, the stepped-care condition was significantly superior to CBT.

Therapist-assisted self-help was an effective first-level treatment in the stepped-care sequence, and the full sequence was more effective than CBT suggesting that treatment is enhanced with a more individualised approach.