Older people with depression exhibit better response to electroconvulsive therapy (ECT). We aimed to measure the total effect of age on ECT response and investigate whether this effect is mediated by psychotic features, psychomotor retardation, psychomotor agitation, age of onset, and episode duration.

We pooled data from four prospective Irish studies where ECT was administered for a major depressive episode (unipolar or bipolar) with baseline score ≥21 on the 24-item Hamilton Depression Rating Scale (HAM-D). The primary outcome was change in HAM-D between baseline and end of treatment. The estimands were total effect of age, estimated using linear regression, and the indirect effects for each putative mediator, estimated using causal mediation analyses.

A total of 256 patients (mean age 57.8 [SD = 14.6], 60.2% female) were included. For every additional 10 years of age, HAM-D was estimated to decrease by a further 1.74 points over the ECT period (p < 0.001). Age acted on all putative mediators. Mechanistic theories, whereby a mediator drives treatment response, were confirmed for all putative mediators except age of onset. Consequently, mediation of the effect of age on change in HAM-D could be demonstrated for psychotic features, psychomotor retardation, psychomotor agitation, and episode duration but not for age of onset.

A total of 43.1% of the effect of older age on increased ECT response was explained by the mediators. Treatment planning could be improved by preferentially offering ECT to older adults, especially if presenting with psychotic features, greater severity of psychomotor disturbance, and earlier in the episode.

Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk.

Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11–36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones.

Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20).

Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

Poor mental health is a state of psychological distress that is influenced by lifestyle factors such as sleep, diet, and physical activity. Compulsivity is a transdiagnostic phenotype cutting across a range of mental illnesses including obsessive–compulsive disorder, substance-related and addictive disorders, and is also influenced by lifestyle. Yet, how lifestyle relates to compulsivity is presently unknown, but important to understand to gain insights into individual differences in mental health. We assessed (a) the relationships between compulsivity and diet quality, sleep quality, and physical activity, and (b) whether psychological distress statistically contributes to these relationships.

We collected harmonized data on compulsivity, psychological distress, and lifestyle from two independent samples (Australian n = 880 and US n = 829). We used mediation analyses to investigate bidirectional relationships between compulsivity and lifestyle factors, and the role of psychological distress.

Higher compulsivity was significantly related to poorer diet and sleep. Psychological distress statistically mediated the relationship between poorer sleep quality and higher compulsivity, and partially statistically mediated the relationship between poorer diet and higher compulsivity.

Lifestyle interventions in compulsivity may target psychological distress in the first instance, followed by sleep and diet quality. As psychological distress links aspects of lifestyle and compulsivity, focusing on mitigating and managing distress may offer a useful therapeutic approach to improve physical and mental health. Future research may focus on the specific sleep and diet patterns which may alter compulsivity over time to inform lifestyle targets for prevention and treatment of functionally impairing compulsive behaviors.

The present study explored the influence of romantic love on the expression of several obsessive–compulsive disorder (OCD) characteristics, including symptom severity, symptom dimensions, age at onset, sensory phenomena (SP), and developmental course, as well as other related comorbid disorders. It was hypothesized that love-precipitated OCD would be associated with a set of distinct characteristics and exhibit greater rates of comorbid disorders.

The analyses were performed using a large sample (n = 981) of clinical patients with a primary diagnosis of OCD (Females = 67.3%, M age = 35.31).

Love-precipitated OCD was associated with greater severity of SP and later age at onset of obsessions. However, symptom severity, symptom dimension, developmental course, and psychiatric comorbidities were not associated with love-precipitated OCD.

It was concluded that romantic love does shape the expression of OCD, especially with regard to SP and onset age. These findings encourage further exploration to determine its clinical significance as a phenotype.

The extent to which obsessive–compulsive and related disorders (OCRDs) are impulsive, compulsive, or both requires further investigation. We investigated the existence of different clusters in an online nonclinical sample and in which groups DSM-5 OCRDs and other related psychopathological symptoms are best placed.

Seven hundred and seventy-four adult participants completed online questionnaires including the Cambridge–Chicago Compulsivity Trait Scale (CHI-T), the Barratt Impulsiveness Scale (BIS-15), and a series of DSM-5 OCRDs symptom severity and other psychopathological measures. We used K-means cluster analysis using CHI-T and BIS responses to test three and four factor solutions. Next, we investigated whether different OCRDs symptoms predicted cluster membership using a multinomial regression model.

The best solution identified one “healthy” and three “clinical” clusters (ie, one predominantly “compulsive” group, one predominantly “impulsive” group, and one “mixed”—“compulsive and impulsive group”). A multinomial regression model found obsessive–compulsive, body dysmorphic, and schizotypal symptoms to be associated with the “mixed” and the “compulsive” clusters, and hoarding and emotional symptoms to be related, on a trend level, to the “impulsive” cluster. Additional analysis showed cognitive-perceptual schizotypal symptoms to be associated with the “mixed” but not the “compulsive” group.

Our findings suggest that obsessive–compulsive disorder; body dysmorphic disorder and schizotypal symptoms can be mapped across the “compulsive” and “mixed” clusters of the compulsive–impulsive spectrum. Although there was a trend toward hoarding being associated with the “impulsive” group, trichotillomania, and skin picking disorder symptoms did not clearly fit to the demarcated clusters.