Timely outpatient follow-up and readmission after discharge are common quality indicators in psychiatric care, but their association varies in previous research. We aimed to examine whether the impact of outpatient follow-up and other factors on readmission risk evolves over time in people with non-affective psychotic disorder (NAP).

The Finnish Quality of Care Register includes all people diagnosed with NAP since January 2010. Here, we followed patients with a hospital discharge between 2017 and 2021 until readmission, death, or up to 365 days. Time of the first outpatient follow-up appointment, length of stay (LOS), number of previous hospitalizations, psychosis diagnosis, substance use disorder (SUD), residential status, economic activity, gender, age, year, and region were included. Follow-up time was divided into five periods: week 1, weeks 2–4, weeks 5–13, weeks 14–25, and weeks 26–52, and each period was analyzed separately with Cox regression.

Of the 29 858 discharged individuals, 54.1% had an outpatient follow-up within a week. A total of 10 623 (35.6%) individuals were readmitted. Short LOS increased the readmission risk in the first four weeks, whereas lack of outpatient follow-up raised the risk (adjusted HRs between 1.15 (95% CI 1.04–1.26) and 1.53 (1.37–1.71) in weeks 5–52. The number of previous hospitalizations remained a consistent risk factor throughout the follow-up, while SUD increased risk after 4 weeks and living without family after 13 weeks.

Risk factors of readmission vary over time. These temporal patterns must be considered when developing outpatient treatment programs.

Neurocognitive deficits are a core feature of psychosis and depression. Despite commonalities in cognitive alterations, it remains unclear if and how the cognitive deficits in patients at clinical high risk for psychosis (CHR) and those with recent-onset psychosis (ROP) are distinct from those seen in recent-onset depression (ROD).

This study was carried out within the European project ‘Personalized Prognostic Tools for Early Psychosis Management’, and aimed to characterise the cognitive profiles of patients with psychosis or depression.

We examined cognitive profiles for patients with ROP (n = 105), patients with ROD (n = 123), patients at CHR (n = 116) and healthy controls (n = 372) across seven sites in five European countries. Confirmatory factor analysis identified four cognitive factors independent of gender, education and site: speed of processing, attention and working memory, verbal learning and spatial learning.

Patients with ROP performed worse than healthy controls in all four domains (P < 0.001), whereas performance of patients with ROD was not affected (P > 0.05). Patients at CHR performed worse than healthy controls in speed of processing (P = 0.001) and spatial learning (P = 0.003), but better than patients with ROP across all cognitive domains (all P ≤ 0.01). CHR and ROD groups did not significantly differ in any cognitive domain. These findings were independent of comorbid depressive symptoms, substance consumption and illness duration.

These results show that neurocognitive abilities are affected in CHR and ROP, whereas ROD seems spared. Although our findings may support the notion that those at CHR have a specific vulnerability to psychosis, future studies investigating broader transdiagnostic risk cohorts in longitudinal designs are needed.

Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.

A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15–41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1–2 s.d. below or above HC, respectively) for each cognitive test.

Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.

These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning.

We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample.

Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD).

Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD.

Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

The aim of the current study was to explore the effect of gender, age at onset, and duration on the long-term course of schizophrenia.

Twenty-nine centers from 25 countries representing all continents participated in the study that included 2358 patients aged 37.21 ± 11.87 years with a DSM-IV or DSM-5 diagnosis of schizophrenia; the Positive and Negative Syndrome Scale as well as relevant clinicodemographic data were gathered. Analysis of variance and analysis of covariance were used, and the methodology corrected for the presence of potentially confounding effects.

There was a 3-year later age at onset for females (P < .001) and lower rates of negative symptoms (P < .01) and higher depression/anxiety measures (P < .05) at some stages. The age at onset manifested a distribution with a single peak for both genders with a tendency of patients with younger onset having slower advancement through illness stages (P = .001). No significant effects were found concerning duration of illness.

Our results confirmed a later onset and a possibly more benign course and outcome in females. Age at onset manifested a single peak in both genders, and surprisingly, earlier onset was related to a slower progression of the illness. No effect of duration has been detected. These results are partially in accord with the literature, but they also differ as a consequence of the different starting point of our methodology (a novel staging model), which in our opinion precluded the impact of confounding effects. Future research should focus on the therapeutic policy and implications of these results in more representative samples.

Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure.

We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry.

(i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains ‘emotional neglect’ and ‘emotional abuse’ were most predictive for CHR and ROP, while in ROD ‘physical abuse’ and ‘sexual abuse’ were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found.

These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.

It is unclear whether there is a direct link between economic crises and changes in suicide rates.

The Lopez-Ibor Foundation launched an initiative to study the possible impact of the economic crisis on European suicide rates.

Data was gathered and analysed from 29 European countries and included the number of deaths by suicide in men and women, the unemployment rate, the gross domestic product (GDP) per capita, the annual economic growth rate and inflation.

There was a strong correlation between suicide rates and all economic indices except GPD per capita in men but only a correlation with unemployment in women. However, the increase in suicide rates occurred several months before the economic crisis emerged.

Overall, this study confirms a general relationship between the economic environment and suicide rates; however, it does not support there being a clear causal relationship between the current economic crisis and an increase in the suicide rate.

Decline in social functioning occurs in individuals who later develop psychosis.

To investigate whether baseline differences in disability are present in those who do and those who do not make a transition to psychosis in a group clinically at high risk and whether disability is a risk factor for transition.

Prospective multicentre, naturalistic field study with an 18-month follow-up period on 245 help-seeking individuals clinically at high risk. Disability was assessed with the Disability Assessment Schedule of the World Health Organization (WHODAS–II).

At baseline, the transition group displayed significantly greater difficulties in making new friends (z =−3.40, P = 0.001), maintaining a friendship (z =−3.00, P = 0.003), dealing with people they do not know (z =−2.28, P = 0.023) and joining community activities (z =−2.0, P = 0.05) compared with the non-transition group. In Cox regression, difficulties in getting along with people significantly contributed to the prediction of transition to psychosis in our sample (β = 0.569, s.e. = 0.184, Wald = 9.548, P = 0.002, hazard ratio (HR) = 1.767, 95% CI 1.238–2.550).

Certain domains of social disability might contribute to the prediction of psychosis in a sample clinically at high risk.

There are numerous instruments for screening for depression. A feasible screen is good at both recognising and predicting depression.

To study the ability of the Depression Scale and its items to recognise and predict a depressive episode.

A sample of patients attending primary care was examined in 1991–1992 and again 7 years later. The accuracy of the Depression Scale at baseline and at follow-up was tested against the Short Form of the Composite International Diagnostic Interview (CIDI-SF) diagnosis of depression at follow-up. The sensitivity and specificity of the Depression Scale and its items were assessed.

Both baseline and follow-up Depression Scale scores were consistent with the CIDI–SF diagnoses. It was possible to find single items efficient at both recognising and predicting depression.

The Depression Scale is a useful screening instrument for depression, with both diagnostic and predictive validity.