Irremediability is a key requirement for euthanasia and assisted suicide for psychiatric disorders (psychiatric EAS). Countries like the Netherlands and Belgium ask clinicians to assess irremediability in light of the patient's diagnosis and prognosis and ‘according to current medical understanding’. Clarifying the relevance of a default objective standard for irremediability when applied to psychiatric EAS is crucial for solid policymaking. Yet so far, a thorough examination of this standard is lacking.

Using treatment-resistant depression (TRD) as a test case, through a scoping review in PubMed, we analyzed the state-of-the-art evidence for whether clinicians can accurately predict individual long-term outcome and single out irremediable cases, by examining the following questions: (1) What is the definition of TRD; (2) What are group-level long-term outcomes of TRD; and (3) Can clinicians make accurate individual outcome predictions in TRD?

A uniform definition of TRD is lacking, with over 150 existing definitions, mostly focused on psychopharmacological research. Available yet limited studies about long-term outcomes indicate that a majority of patients with long-term TRD show significant improvement over time. Finally, evidence about individual predictions in TRD using precision medicine is growing, but methodological shortcomings and varying predictive accuracies pose important challenges for its implementation in clinical practice.

Our findings support the claim that, as per available evidence, clinicians cannot accurately predict long-term chances of recovery in a particular patient with TRD. This means that the objective standard for irremediability cannot be met, with implications for policy and practice of psychiatric EAS.

Use of intensive longitudinal methods (e.g. ecological momentary assessment, passive sensing) and machine learning (ML) models to predict risk for depression and suicide has increased in recent years. However, these studies often vary considerably in length, ML methods used, and sources of data. The present study examined predictive accuracy for depression and suicidal ideation (SI) as a function of time, comparing different combinations of ML methods and data sources.

Participants were 2459 first-year training physicians (55.1% female; 52.5% White) who were provided with Fitbit wearable devices and assessed daily for mood. Linear [elastic net regression (ENR)] and non-linear (random forest) ML algorithms were used to predict depression and SI at the first-quarter follow-up assessment, using two sets of variables (daily mood features only, daily mood features + passive-sensing features). To assess accuracy over time, models were estimated iteratively for each of the first 92 days of internship, using data available up to that point in time.

ENRs using only the daily mood features generally had the best accuracy for predicting mental health outcomes, and predictive accuracy within 1 standard error of the full 92 day models was attained by weeks 7–8. Depression at 92 days could be predicted accurately (area under the curve >0.70) after only 14 days of data collection.

Simpler ML methods may outperform more complex methods until passive-sensing features become better specified. For intensive longitudinal studies, there may be limited predictive value in collecting data for more than 2 months.

Relapse from drug abuse (DA) is common, but has rarely been studied in general population samples using a wide range of objective predictors.

Using nationwide registries, we ascertained 44 523 subjects first registered for DA between the ages of 15 and 40 in 1998 to 2004 and followed for 8 years. We predicted relapse in subjects defined as a second DA registration. We also predicted DA relapse in relative pairs concordant for DA but discordant for relapse.

In multivariate regression analyses, the strongest predictors for relapse were prior criminal behavior, male sex, being on social welfare, low school achievement, prior alcoholism, and a high-risk father. A risk index trained from these analyses on random split-halves demonstrated a risk ratio of 1.11 [95% confidence intervals (CIs) 1.10–1.11] per decile and an ROC value of 0.70 (0.69–0.71). Co-relative analyses indicated that a modest proportion of this association was causal, with the remainder arising from familial confounders. A developmental structural equation model revealed a complex interviewing of risk pathways to DA with three key mediational hubs: low educational attainment, early age at first registration, and being on social welfare.

In a general population sample, using objective registry information, DA relapse is substantially predictable. However, the identified risk factors may not be valid targets for interventions because many index familial risk and may not impact causally on probability of relapse. Risk for DA relapse may reflect an inter-weaving, over developmental time, of genetic–temperamental vulnerability, indices of externalizing behaviors and social factors reflecting deprivation.

Self-efficacy is a pivotal factor in the etiology and prognosis of major depression. However, longitudinal studies on the relationship between self-efficacy and major depressive disorder (MDD) are scarce. The objectives were to investigate: (1) the associations between self-efficacy and the 1-year and 2-year risks of first onset of MDD and (2) the associations between self-efficacy and the 1-year and 2-year risks of the persistence/recurrence of MDD, in a sample of first-year university students.

We followed 8079 first-year university students for 2 years from April 2018 to October 2020. MDD was ascertained by the Chinese version of the Composite International Diagnostic Interview (CIDI-3.0) based on self-report. Self-efficacy was measured by the 10-item General Self-efficacy (GSE) scale. Random effect logistic regression modeling was used to estimate the associations.

Among participants without a lifetime MDD, the data showed that participants with high baseline GSE scores were associated with a higher risk of first onset of MDD over 2 years [odds ratio (OR) 1.04, 95% confidence interval (CI) 1.01–1.08]. Among those with a lifetime MDD, participants with high baseline GSE scores were less likely to have had a MDD over 2 years (OR 0.93, 95% CI 0.88–0.99) compared to others.

A high level of GSE may be protective of the risk of persistent or recurrent MDD. More longitudinal studies in university students are needed to further investigate the impact of GSE on the first onset of MDD.

Sleep disturbances are important symptoms to monitor in people with bipolar disorder (BD) but the precise longitudinal relationships between sleep and mood remain unclear. We aimed to examine associations between stable and dynamic aspects of sleep and mood in people with BD, and assess individual differences in the strength of these associations.

Participants (N = 649) with BD-I (N = 400) and BD-II (N = 249) provided weekly self-reports of insomnia, depression and (hypo)mania symptoms using the True Colours online monitoring tool for 21 months. Dynamic structural equation models were used to examine the interplay between weekly reports of insomnia and mood. The effects of clinical and demographic characteristics on associations were also assessed.

Increased variability in insomnia symptoms was associated with increased mood variability. In the sample as a whole, we found strong evidence of bidirectional relationships between insomnia and depressive symptoms but only weak support for bidirectional relationships between insomnia and (hypo)manic symptoms. We found substantial variability between participants in the strength of prospective associations between insomnia and mood, which depended on age, gender, bipolar subtype, and a history of rapid cycling.

Our results highlight the importance of monitoring sleep in people with BD. However, researchers and clinicians investigating the association between sleep and mood should consider subgroup differences in this relationship. Advances in digital technology mean that intensive longitudinal data on sleep and mood are becoming increasingly available. Novel methods to analyse these data present an exciting opportunity for furthering our understanding of BD.

The relationship between schizophrenia and violence is complex. The aim of this multicentre case–control study was to examine and compare the characteristics of a group of forensic psychiatric patients with a schizophrenia spectrum disorders and a history of significant interpersonal violence to a group of patients with the same diagnosis but no lifetime history of interpersonal violence.

Overall, 398 patients (221 forensic and 177 non-forensic patients) were recruited across five European Countries (Italy, Germany, Poland, Austria and the United Kingdom) and assessed using a multidimensional standardised process.

The most common primary diagnosis in both groups was schizophrenia (76.4%), but forensic patients more often met criteria for a comorbid personality disorder, almost always antisocial personality disorder (49.1 v. 0%). The forensic patients reported lower levels of disability and better social functioning. Forensic patients were more likely to have been exposed to severe violence in childhood. Education was a protective factor against future violence as well as higher levels of disability, lower social functioning and poorer performances in cognitive processing speed tasks, perhaps as proxy markers of the negative syndrome of schizophrenia. Forensic patients were typically already known to services and in treatment at the time of their index offence, but often poorly compliant.

This study highlights the need for general services to stratify patients under their care for established violence risk factors, to monitor patients for poor compliance and to intervene promptly in order to prevent severe violent incidents in the most clinically vulnerable.

Traumatic experiences are associated with a higher risk of psychotic illnesses, but little is known about potentially modifiable mechanisms underlying this relationship. This study aims to examine whether post-traumatic stress disorder (PTSD) symptoms mediate the relationship between trauma and psychotic experiences (PEs).

We used data from the Avon Longitudinal Study of Parents and Children to examine whether: PTSD symptoms mediate the relationships between (a) childhood trauma and adolescent PEs (study of adolescent PEs; n = 2952), and (b) childhood/adolescent trauma and PEs in early adulthood (study of adult PEs; n = 2492). We examined associations between variables using logistic regression, and mediation using the parametric g-computation formula.

Exposure to trauma was associated with increased odds of PEs (adolescent PEs: ORadjusted 1.48, 95% CI 1.23–1.78; adult PEs: ORadjusted 1.57, 95% CI 1.25–1.98) and PTSD symptoms (adolescent PTSD: ORadjusted 1.59, 95% CI 1.31–1.93; adult PTSD: ORadjusted 1.50, 95% CI 1.36–1.65). The association between PTSD symptoms and PE was stronger in adolescence (ORadjusted 4.63, 95% CI 2.34–9.17) than in adulthood (ORadjusted 1.62, 95% CI 0.80–3.25). There was some evidence that PTSD symptoms mediated the relationship between childhood trauma and adolescent PEs (proportion mediated 14%), though evidence of mediation was weaker for adult PEs (proportion mediated 8%).

These findings are consistent with the hypothesis that PTSD symptoms partly mediate the association between trauma exposure and PEs. Targeting PTSD symptoms might help prevent the onset of psychotic outcomes.

Evidence on neonatal withdrawal syndrome following antidepressant intrauterine exposure is limited, particularly for antidepressants other than selective serotonin reuptake inhibitor (SSRIs).

In our case/non-case pharmacovigilance study, based on VigiBase®, the WHO database of suspected adverse drug reactions, we estimated reporting odds ratio (ROR) and the Bayesian information component (IC) with 95% confidence/credibility intervals (CI) as measures of disproportionate reporting of antidepressant-related neonatal withdrawal syndrome. Antidepressants were first compared to all other medications, then to methadone, and finally within each class of antidepressants: SSRIs, tricyclics (TCA) and other antidepressants. Antidepressants were ranked in terms of clinical priority, based on semiquantitative score ratings. Serious v. non-serious reports were compared.

A total of 406 reports of neonatal withdrawal syndrome in 379 neonates related to 15 antidepressants were included. Disproportionate reporting was detected for antidepressants as a group as compared to all other drugs (ROR: 6.18, 95% CI 5.45–7.01, IC: 2.07, 95% CI 1.92–2.21). Signals were found for TCAs (10.55, 95% CI 8.02–13.88), followed by other antidepressants (ROR: 5.90, 95% CI 4.74–7.36) and SSRIs (ROR: 4.68, 95% CI 4.04–5.42). Significant disproportionality emerged for all individual antidepressants except for bupropion, whereas no disproportionality for any antidepressant was detected v. methadone. Eleven antidepressants had a moderate clinical priority score and four had a weak one. Most frequent symptoms included respiratory symptoms (n = 106), irritability/agitation (n = 75), tremor (n = 52) and feeding problems (n = 40).

Most antidepressants are associated with moderate signals of disproportionate reporting for neonatal withdrawal syndrome, which should be considered when prescribing an antidepressant during pregnancy, irrespective of class.

The course of Bipolar Disorder (BD) is highly variable, with marked inter and intra-individual differences in symptoms and functioning. In this study, we identified illness trajectories across major clinical domains that could have etiological, prognostic, and therapeutic relevance.

Using the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we performed univariate and multivariate trajectory modeling of depressive symptoms, manic symptoms, and psychosocial functioning. Multinomial regression was performed to identify baseline variables associated with poor outcome trajectories.

Depressive symptoms predominated, with most subjects being found in trajectories characterized by various degrees of depressive symptoms and 13% of subjects being classified in a poor outcome ‘persistently depressed’ trajectory. Most subjects experienced few manic symptoms, although approximately 10% of subjects followed a trajectory of persistently manic symptoms. Trajectory analysis of psychosocial functioning showed impairment in most of the sample, with little improvement during follow up. Multi-trajectory analyses highlighted significant impairment in subjects with persistently mixed and persistently depressed trajectories of illness. In general, poor outcome trajectories were marked by lower educational attainment, higher unemployment and disability, and a greater likelihood of adverse clinical features (rapid cycling and suicide attempts) and comorbid diagnoses (anxiety disorders, PTSD, and substance abuse/dependence disorders).

Subjects with BD can be classified into several trajectories of clinically relevant domains that are prognostically relevant and show differing degrees of associations with a broad range of negative clinical risk factors. The highest level of psychosocial disability was found in subjects with chronic mixed and depressive symptoms, who show limited improvement despite guideline-based treatment.

The attributional theory of paranoia suggests that paranoid beliefs may protect individuals from low self-esteem and distress (Bentall et al. 2001). The current study tested this theory by investigating a hypothesis that paranoid beliefs in combination with low perceived deservedness of persecution (poor-me beliefs) confer protection against the distress caused by social but not activity related stress.

Paranoid symptoms, perceived deservedness of persecution, self-esteem, mood, and stress levels of individuals diagnosed with schizophrenia spectrum disorders (N = 91) and healthy controls (N = 52) were assessed in the context of daily life using the experience sampling method.

Individuals holding poor-me beliefs (poor-me individuals) showed blunted sensitivity to social but not activity stress. In contrast, individuals holding paranoid beliefs in combination with high perceived deservedness of persecution (bad-me individuals) showed heightened sensitivity to social stress. No consistent differences in reactions to activity stress emerged. Although both poor-me and bad-me individuals reported low self-esteem, this disturbance was particularly characteristic of bad-me individuals.

The results suggest that poor-me paranoid beliefs may protect individuals against the distress associated with unpleasant social situations. The specificity of reactions to social stress is discussed in the context of wider literature. Future directions for research are suggested.

Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes.

This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent major depressive disorder (MDD; N = 623). Participants completed app-based self-reported and performance-based cognitive function assessments alongside validated measures of depression, functional disability, and self-esteem every 3 months. Participants were followed-up for a maximum of 2-years. Multilevel hierarchically nested modelling was employed to explore between- and within-participant variation over time to identify whether persistent cognitive difficulties are related to levels of depression and functional impairment during follow-up.

508 individuals (81.5%) provided data (mean age: 46.6, s.d.: 15.6; 76.2% female). Increasing persistence of self-reported cognitive difficulty was associated with higher levels of depression and functional impairment throughout the follow-up. In comparison to low persistence of objective cognitive difficulty (<25% of timepoints), those with high persistence (>75% of timepoints) reported significantly higher levels of depression (B = 5.17, s.e. = 2.21, p = 0.019) and functional impairment (B = 4.82, s.e. = 1.79, p = 0.002) over time. Examination of the individual cognitive modules shows that persistently impaired executive function is associated with worse functioning, and poor processing speed is particularly important for worsened depressive symptoms.

We replicated previous findings of greater persistence of cognitive difficulty with increasing severity of depression and further demonstrate that these cognitive difficulties are associated with pervasive functional disability. Difficulties with cognition may be an indicator and target for further treatment input.

There are many barriers to engaging in current psychological treatments, including time, cost, and availability. Ultra-brief treatments overcome some of these barriers by delivering therapeutic information and skills using significantly less time than standard-length treatments. We developed a therapist-guided online ultra-brief treatment for depression and anxiety and compared it to an existing 8-week, 5-lesson therapist-guided standard-length treatment and a waitlist control.

In a randomized controlled trial, adults with self-reported depression or anxiety were randomized (1:1:1) to the ultra-brief treatment, standard-length treatment, or waitlist control. The primary outcomes were depression symptoms and anxiety symptoms assessed at baseline, 5-weeks later, 9-weeks later (primary timepoint), and 3-months later. The trial was prospectively registered.

Between 7 February 2022, and 16 August 2022, 242 participants were enrolled in the ultra-brief treatment (n = 85), standard-length treatment (n = 80), and waitlist control (n = 77). Participants were mostly women with an average age of 48.56 years. At 9-weeks post-baseline, participants in the ultra-brief treatment group reported significantly lower depression (between groups d = 0.41) and anxiety (d = 0.53) than the waitlist control. The ultra-brief treatment was non-inferior for anxiety at both 9-weeks and 3-months follow-up. Non-inferiority for depression was observed at 9-weeks.

The online ultra-brief treatment resulted in significant reductions in depression and anxiety that were non-inferior to a longer treatment course after 9-weeks. Remotely delivered ultra-brief treatments have the potential to provide accessible and effective care for those who cannot, or would prefer not to, access longer psychological interventions.

Little is known about the childhood antecedents and adult correlates of adolescent dual-harm (i.e. co-occurring self- and other-harm). We examine the longitudinal associations between (a) social and psychological risk factors in childhood and adolescent dual-harm and (b) adolescent dual-harm and social and mental health impairments in early adulthood.

Participants (N = 1482) are from a prospective longitudinal community-representative study. Dual-, self-, and other-harm were self-reported at ages 13, 15, and 17. Social and psychological risk factors in childhood were assessed between 7 and 11; early adult correlates at age 20. Groups with dual-harm, self-harm only, other-harm only, and no harm were compared.

Between 13 and 17, 7.2% of adolescents reported dual-harm (self-harm only: 16.2%; other-harm only: 13.3%). Some childhood risk factors (e.g. sensation-seeking, parental divorce, victimization by peers) characterized all harm groups; others were common to the dual- and self-harm (anxiety/depressive symptoms, relational aggression) or dual- and other-harm groups only (low self-control, substance use, delinquency). Adolescents with dual-harm had reported more physical aggression and harsh parenting, and lower school bonding in childhood than any other group. In early adulthood, they reported more anxiety/depressive symptoms, psychopathy symptoms, homicidal ideations, delinquency, and victimization experiences than any other group.

Adolescent dual-harm follows psychological problems and social disconnection in childhood and signals risk of psychopathology and isolation in early adulthood. To curb the burden from dual-harm, interventions must target adolescents, families, peer networks, and school environments. Differentiating youth with dual-harm from those with single-harm is important for developing personalized treatments.