Hallucinations are common and distressing symptoms in Parkinson’s disease (PD). Treatment response in clinical trials is measured using validated questionnaires, including the Scale for Assessment of Positive Symptoms-Hallucinations (SAPS-H) and University of Miami PD Hallucinations Questionnaire (UM-PDHQ). The minimum clinically important difference (MCID) has not been determined for either scale. This study aimed to estimate a range of MCIDs for SAPS-H and UM-PDHQ using both consensus-based and statistical approaches.

A Delphi survey was used to seek opinions of researchers, clinicians, and people with lived experience. We defined consensus as agreement ≥75%. Statistical approaches used blinded data from the first 100 PD participants in the Trial for Ondansetron as Parkinson’s Hallucinations Treatment (TOP HAT, NCT04167813). The distribution-based approach defined the MCID as 0.5 of the standard deviation of change in scores from baseline at 12 weeks. The anchor-based approach defined the MCID as the average change in scores corresponding to a 1-point improvement in clinical global impression-severity scale (CGI-S).

Fifty-one researchers and clinicians contributed to three rounds of the Delphi survey and reached consensus that the MCID was 2 points on both scales. Sixteen experts with lived experience reached the same consensus. Distribution-defined MCIDs were 2.6 points for SAPS-H and 1.3 points for UM-PDHQ, whereas anchor-based MCIDs were 2.1 and 1.3 points, respectively.

We used triangulation from multiple methodologies to derive the range of MCID estimates for the two rating scales, which was between 2 and 2.7 points for SAPS-H and 1.3 and 2 points for UM-PDHQ.

Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have a major impact. This study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms.

Two datasets were studied: (A) one consisted of n = 54 subjects with an anxiety diagnosis, who received 12 weeks of CBT, and (B) one consisted of n = 15 subjects treated for 8 weeks. Connectome predictive modeling (CPM) was used to predict treatment response, as assessed with the PARS. The main analysis included network edges positively correlated with treatment outcome and age, sex, and baseline anxiety severity as predictors. Results from alternative models and analyses are also presented. Model assessments utilized 1000 bootstraps, resulting in a 95% CI for R2, r, and mean absolute error (MAE).

The main model showed a MAE of approximately 3.5 (95% CI: [3.1–3.8]) points, an R2 of 0.08 [−0.14–0.26], and an r of 0.38 [0.24–0.511]. When testing this model in the left-out sample (B), the results were similar, with an MAE of 3.4 [2.8–4.7], R2−0.65 [−2.29–0.16], and r of 0.4 [0.24–0.54]. The anatomical metrics showed a similar pattern, where models rendered overall low R2.

The analysis showed that models based on earlier promising results failed to predict clinical outcomes. Despite the small sample size, this study does not support the extensive use of CPM to predict outcomes in pediatric anxiety.

Borderline personality disorder (BPD) is a severe mental disorder characterized by emotional dysregulation, impulsive behaviors, and difficulties in interpersonal relationships. Despite the poor understanding of the underlying biological processes, the oxytocin (OXT) system may be involved in and mediate some of BPD’s symptomatic and behavioral aspects. To clarify OXT’s role in BPD, we assessed its plasma levels and modulations induced by psychotherapies in patients.

Fifty BPD patients and 28 healthy controls (HC) participated in the study; patients were randomly assigned to two psychotherapeutic treatments: metacognitive interpersonal therapy and structured clinical management. Clinical and psychometric measures were assessed, and plasma was collected at baseline (T0) and in patients after 6 (T6) and 12 (T12) months of treatment. OXT was quantified by a radioimmunoassay technique.

BPD patients showed lower plasma OXT at T0 than HC (p = 0.002), and a correlation was observed (r = −0.36, p = 0.017) between low OXT concentrations and high Attachment Style Questionnaire – Italian Version–Preoccupation with Relationships subscale scores. OXT changed significantly over time in patients (p = 0.049) with an increase particularly evident from baseline to T6 (p = 0.022), without significant difference between treatment groups. OXT changes (T0 − T12) inversely correlated with symptom improvement as changes in the Zanarini Rating Scale for borderline personality disorder (r = 0.387, p = 0.006) and the Difficulties in Emotion Regulation Scale (r = 0.387, p = 0.005) scores during treatment.

OXT alteration in BPD patients and the regularizing effect of long-term psychotherapies support an involvement of the OXT system in the disease and in treatment impact. More research is needed to fully understand the underlying causal mechanisms linking OXT with pathogenesis and psychotherapy outcomes.

Childhood and adolescence are vulnerable periods for mental disorders, and the COVID-19 pandemic has exacerbated mental health challenges in this population. We aimed to estimate changes in the global burden of mental disorders among children and adolescents before and during the pandemic.

Using data from the Global Burden of Diseases Study 2021, we analyzed incidence, prevalence, and years lived with disability (YLDs) for mental disorders in individuals aged 5–24. Annual percent changes in age-standardized rates were calculated, and a Bayesian age–period–cohort model estimated the expected and additional burden based on pre-pandemic trends.

In 2021, an estimated 123.0 million new cases of mental disorders were reported among children and adolescents, with an 11.8% average annual increase in the age-standardized incidence rate during the pandemic. Anxiety disorders, which previously ranked third, became the leading cause of nonfatal disability (12.9 million [8.0–19.3] YLDs), while depressive disorders rose to fourth place (10.9 million [6.8–16.5] YLDs). The burden grew in most regions, especially among females, those aged 15–24, and in high sociodemographic index (SDI) areas. Based on pre-pandemic data, we estimated an additional burden of 795.0, 165.9, and 622.8 new cases per 100,000 population for total mental disorders, anxiety disorders, and depressive disorders globally in 2021, respectively. Spearman correlation analysis showed a significant positive correlation between additional burden and SDI levels.

These findings highlight the increased burden of mental disorders among children and adolescents during the pandemic, emphasizing the need for targeted post-pandemic mental health support.

Access to “big data” is a boon for researchers, fostering collaboration and resource-sharing to accelerate advancements across fields. Yet, disentangling complex datasets has been hindered by methodological limitations, calling for alternative, interdisciplinary approaches to parse manifold multi-directional pathways between clinical features, particularly for highly heterogeneous autism spectrum disorder (ASD). Despite a long history of male-bias in ASD prevalence, no consensus has been reached regarding mechanisms underlying sex-related discrepancies.

Applying a novel network-theory-based approach, we extracted data-driven, clinically-relevant insights from a well-characterized sample (http://sfari.org/simons-simplex-collection) of autistic males (N = 2175, Age = 8.9 ± 3.5 years) and females (N = 334, Age = 9.2 ± 3.7 years). Expert clinical review of exploratory factor analysis (EFA) results yielded factors of interest in sensory, social, and restricted and repetitive behavior domains. To offset inherent confounds of sample imbalance, we identified a comparison subgroup of males (N = 331) matched to females (by age, IQ). We applied data-driven causal discovery analysis (CDA) using Greedy Fast Causal Inference (GFCI) on three groups (all females, all males, matched males). Structural equation modeling (SEM) extracted measures of model-fit and effect sizes for causal relationships between sex, age-at-enrollment, and IQ on EFA-determined factors.

We identified potential targets for intervention at nodes with mediating or indirect effects. For example, in the female and matched male groups, analyses suggest mitigating RRB domain behaviors may lead to downstream reductions in oppositional and self-injurious behaviors.

Our investigation unveiled sex-specific directional relationships that inform our understanding of differing needs and outcomes associated with biological sex in autism and may serve to further development of targeted interventions.

Obsessive-compulsive symptoms (OCS) emerge in a significant proportion of clozapine-treated schizophrenia patients, affecting social functioning and increasing depressive symptoms. This study investigates the underexplored cognitive mechanisms of clozapine-induced OCS, particularly focusing on dysfunctional checking behavior.

Clinical and cognitive profiles of OCS and their relationship to dysfunctional checking were investigated using a novel checking paradigm (image verification task or IVT) in four groups: clozapine-treated schizophrenia patients with clozapine-induced OCS (SCZ-OCS, n = 21) and without (SCZ-only, n = 15), patients with obsessive-compulsive disorder (OCD, n = 32) and IQ-matched healthy volunteers (HV, n = 30).

Only SCZ-OCS patients showed a distinctive pattern of dysfunctional checking on the IVT. Compared with SCZ-OCS, SCZ-only patients exhibited functional checking while having equivalent deficits in executive cognition, clozapine dose, and treatment duration, though with less severe positive and depressive symptoms. In SCZ-OCS, dysfunctional checking was positively correlated with clozapine dose and working memory performance. By contrast, OCD patients’ checking was positively related to intolerance of uncertainty. Checking in the OCD and SCZ-OCS groups was positively correlated with YBOCS-compulsion.

This study is the first to compare the distinct cognitive and clinical profiles of SCZ-OCS, SCZ-only, and OCD, with a focus on checking behavior, a major symptom in clozapine-treated patients. We introduced a novel and sensitive measure for checking, which showed dysfunctional checking only in SCZ-OCS patients treated with clozapine. These findings indicate that a subset of patients with schizophrenia with more severe positive symptoms and cognitive deficits are especially susceptible to OCD symptoms when treated with clozapine.

Major depressive disorder (MDD) is marked by significant changes to the local synchrony of spontaneous neural activity across various brain regions. However, many methods for assessing this local connectivity use fixed or arbitrary neighborhood sizes, resulting in a decreased capacity to capture smooth changes to the spatial gradient of local correlations. A newly developed method sensitive to classical anatomo-functional boundaries, Iso-Distant Average Correlation (IDAC), was therefore used to examine depression associated alterations to the local functional connectivity of the brain.

One-hundred and forty-seven adolescents and young adults with MDD and 94 healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI) scan. Whole-brain functional connectivity maps of intracortical neural activity within iso-distant local areas (5–10, 15–20, and 25–30 mm) were generated to characterize local fMRI signal similarities.

Across all spatial distances, MDD participants demonstrated greater local functional connectivity of the bilateral posterior hippocampus, retrosplenial cortex, dorsal insula, fusiform gyrus, and supplementary motor area. Local connectivity alterations in short and medium distances (5–10 and 15–20 mm) in the mid insula cortex were additionally associated with expressive suppression use, independent of depressive symptom severity.

Our study identified increased synchrony of the neural activity in several regions commonly implicated in the neurobiology of depression. These effects were relatively consistent across the three distances examined. Longitudinal investigation of this altered local connectivity will clarify whether these differences are also found in other age groups and if this relationship is modified by increased disease chronicity.

Population-level preventive interventions are urgently needed and may be effective for psychosis due to social determinants. We tested three syndemic models along pathways from childhood adversity (CA) to psychotic spectrum disorder (PSD) and their implications for prevention.

Cross-sectional data from 7461 British men surveyed in 5 population subgroups. We tested interactions on both additive and multiplicative scales for a syndemic of violence/criminality (VC), sexual behavior (SH), and substance misuse (SM) according to the presence of CA and adult traumatic life events; mediation analysis of path models; and partial least squares path modeling, with PSD as outcome.

Multiplicative synergistic interactions were found between VC, SH, and SM among men, who experienced CA and traumatic adult life events. However, when disaggregated, only SM mediated the pathway from CA to PSD. Path modeling showed traumatic life events acted on PSD through the syndemic and had no direct effect on PSD. Higher syndemic scores and living in areas of deprivation characterized men with PSD and CA.

Our findings support a broad division of PSD into cases due to (i) biological/inherent causes, and (ii) social determinants, the latter including a syndemic pathway determined by CA. Preventive strategies should focus primarily on preventing adverse effects of CA on developmental pathways which result in PSD. Single component prevention strategies may prevent triggering effects of SM on PSD during adolescence/early adulthood among vulnerable individuals due to CA. Future research should determine applicability and transferability of interventions based on these findings to different populations, specifically those experiencing syndemics.

Data from an RCT of IAPT Norway (“Prompt Mental Health Care” [PMHC]) were linked to several administrative registers up to five years following the intervention. The aims were to (1) examine the effects of PMHC compared to treatment-as-usual (TAU) on work-related outcomes and health care use, (2) estimate the cost–benefit of PMHC, and (3) examine whether clinical outcomes at six-month follow-up explained the effects of PMHC on work−/cost–benefit-related outcomes.

RCTs with parallel assignment were conducted at two PMHC sites (N = 738) during 2016/2017. Eligible participants were considered for admission due to anxiety and/or depression. We used Bayesian estimation with 90% credibility intervals (CI) and posterior probabilities (PP) of effects in favor of PMHC. Primary outcome years were 2018–2022. The cost–benefit analysis estimated the overall economic gain expressed in terms of a benefit–cost ratio and the differences in overall public sector spending.

The PMHC group was more likely than the TAU group to be in regular work without receiving welfare benefits in 2019–2022 (1.27 ≤ OR ≤ 1.43). Some evidence was found that the PMHC group spent less on health care. The benefit–cost ratio in terms of economic gain relative to intervention costs was estimated at 5.26 (90%CI $ - $1.28, 11.8). The PP of PMHC being cost-beneficial for the economy as a whole was 85.9%. The estimated difference in public sector spending was small. PMHC effects on work participation and cost–benefit were largely explained by PMHC effects on mental health.

The results support the societal economic benefit of investing in IAPT-like services.

In major depressive disorder (MDD), only ~35% achieve remission after first-line antidepressant therapy. Using UK Biobank data, we identify sociodemographic, clinical, and genetic predictors of antidepressant response through self-reported outcomes, aiming to inform personalized treatment strategies.

In UK Biobank Mental Health Questionnaire 2, participants with MDD reported whether specific antidepressants helped them. We tested whether retrospective lifetime response to four selective serotonin reuptake inhibitors (SSRIs) (N = 19,516) – citalopram (N = 8335), fluoxetine (N = 8476), paroxetine (N = 2297) and sertraline (N = 5883) – was associated with sociodemographic (e.g. age, gender) and clinical factors (e.g. episode duration). Genetic analyses evaluated the association between CYP2C19 variation and self-reported response, while polygenic score (PGS) analysis assessed whether genetic predisposition to psychiatric disorders and antidepressant response predicted self-reported SSRI outcomes.

71%–77% of participants reported positive responses to SSRIs. Non-response was significantly associated with alcohol and illicit drug use (OR = 1.59, p = 2.23 × 10−20), male gender (OR = 1.25, p = 8.29 × 10−08), and lower-income (OR = 1.35, p = 4.22 × 10−07). The worst episode lasting over 2 years (OR = 1.93, p = 3.87 × 10−16) and no mood improvement from positive events (OR = 1.35, p = 2.37 × 10−07) were also associated with non-response. CYP2C19 poor metabolizers had nominally higher non-response rates (OR = 1.31, p = 1.77 × 10−02). Higher PGS for depression (OR = 1.08, p = 3.37 × 10−05) predicted negative SSRI outcomes after multiple testing corrections.

Self-reported antidepressant response in the UK Biobank is influenced by sociodemographic, clinical, and genetic factors, mirroring clinical response measures. While positive outcomes are more frequent than remission reported in clinical trials, these self-reports replicate known treatment associations, suggesting they capture meaningful aspects of antidepressant effectiveness from the patient’s perspective.

To improve early intervention and personalise treatment for individuals early on the psychosis continuum, a greater understanding of symptom dynamics is required. We address this by identifying and evaluating the movement between empirically derived attenuated psychotic symptomatic substates—clusters of symptoms that occur within individuals over time.

Data came from a 90-day daily diary study evaluating attenuated psychotic and affective symptoms. The sample included 96 individuals aged 18–35 on the psychosis continuum, divided into four subgroups of increasing severity based on their psychometric risk of psychosis, with the fourth meeting ultra-high risk (UHR) criteria. A multilevel hidden Markov modelling (HMM) approach was used to characterise and determine the probability of switching between symptomatic substates. Individual substate trajectories and time spent in each substate were subsequently assessed.

Four substates of increasing psychopathological severity were identified: (1) low-grade affective symptoms with negligible psychotic symptoms; (2) low levels of nonbizarre ideas with moderate affective symptoms; (3) low levels of nonbizarre ideas and unusual thought content, with moderate affective symptoms; and (4) moderate levels of nonbizarre ideas, unusual thought content, and affective symptoms. Perceptual disturbances predominantly occurred within the third and fourth substates. UHR individuals had a reduced probability of switching out of the two most severe substates.

Findings suggest that individuals reporting unusual thought content, rather than nonbizarre ideas in isolation, may exhibit symptom dynamics with greater psychopathological severity. Individuals at a higher risk of psychosis exhibited persistently severe symptom dynamics, indicating a potential reduction in psychological flexibility.

Sustained attention is integral to goal-directed tasks in everyday life. It is a demanding and effortful process prone to failure. Deficits are particularly prevalent in mood disorders. However, conventional methods of assessment, rooted in overall measures of performance, neglect the nuanced temporal dimensions inherent in sustained attention, necessitating alternative analytical approaches.

This study investigated sustained attention deficits and temporal patterns of attentional fluctuation in a large clinical cohort of patients with bipolar depression (BPd, n = 33), bipolar euthymia (BPe, n = 84), major depression (MDd, n = 38) and controls (HC, n = 138) using a continuous performance task (CPT). Longitudinal and spectral analyses were employed to examine trial-level reaction time (RT) data.

Longitudinal analysis revealed a significant worsening of performance over time (vigilance decrement) in BPd, whilst spectral analysis unveiled attentional fluctuations concentrated in the frequency range of 0.077 Hz (1/12.90 s)–0.049 Hz (1/20.24 s), with BPd and MDd demonstrating greater spectral power compared to BPe and controls.

Although speculative, the increased variability in this frequency range may have an association with the dysfunctional activity of the Default Mode Network, which has been shown to oscillate at a similar timescale. These findings underscore the importance of considering the temporal dimensions of sustained attention and show the potential of spectral analysis of RT in future clinical research.

It is unknown whether there is a general factor that accounts for the propensity for both physical and mental conditions in different age groups and how it is associated with lifestyle and well-being.

We analyzed health conditions data from the Millennium Cohort Study (MCS) (age = 17; N = 19,239), the National Child Development Study (NCDS) (age = 44; N = 9293), and the English Longitudinal Study of Ageing (ELSA) (age ≥ 50; N = 7585). The fit of three Confirmatory Factor models was used to select the optimal solution by Comparative Fit Index, Tucker-Lewis Index, and Root Mean Square Error of Approximation. The relationship among d factor, lifestyles, and well-being was further explored.

Supporting the existence of the d factor, the bi-factor model showed the best model fit in 17-year-olds (MCS:CFI = 0.97, TFI = 0.96, RMSEA = 0.01), 44-year-olds (NCDS:CFI = 0.96, TFI = 0.95, RMSEA = 0.02), and 50+ year-olds (ELSA:CFI = 0.97, TFI = 0.96, RMSEA = 0.02). The d factor scores significantly correlated with lifestyle and well-being, suggesting healthier lifestyles were associated with a reduced likelihood of physical and mental health comorbidities, which in turn improved well-being.

Contrary to the traditional dichotomy between mental and physical conditions, our study showed a general factor underlying the comorbidity across mental and physical diseases, related to lifestyle and well-being. Our results inform the conceptualization of mental and physical illness as well as future research assessing risk and pathways of disease transmission, intervention, and prevention. Our results also provide a strong rationale for a systematic screening for mental disorders in individuals with physical conditions and vice versa, and for integrated services addressing multimorbidity.

Schizophrenia is a chronic and complex mental disorder resulting from interactions between cumulative and synergistic genetic and environmental factors. Viral infection during the prenatal stage constitutes one of the most relevant risk factors for the development of schizophrenia later in adulthood.

A narrative review was conducted to explore the link between viral infections and schizophrenia, as well as the neuropsychiatric effects of antiviral drugs, particularly in the context of this specific mental condition. Literature searches were performed using the PubMed, Scopus, and Web of Science databases.

Several viral infections, such as herpesviruses, influenza virus, Borna disease virus, and coronaviruses, can directly or indirectly disrupt normal fetal brain development by modifying gene expression in the maternal immune system, thereby contributing to the pathophysiological symptoms of schizophrenia. In addition, neuropsychiatric effects caused by antiviral drugs are frequent and represent significant adverse outcomes for viral treatment.

Epidemiological evidence suggests a potential relationship between viruses and schizophrenia. Increases in inflammatory cytokine levels and changes in the expression of key genes observed in several viral infections may constitute potential links between these viral infections and schizophrenia. Furthermore, antivirals may affect the central nervous system, although for most drugs, their mechanisms of action are still unclear, and a strong relationship between antivirals and schizophrenia has not yet been established.