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.

Mentalizing—our ability to make inferences about the mental states of others—is impaired across psychiatric disorders and robustly associated with functional outcomes. Mentalizing deficits have been prominently linked to aberrant activity in cortical regions considered to be part of the “social brain network” (e.g., dorsomedial prefrontal cortex, temporoparietal junction), yet emerging evidence also suggests the importance of cerebellar dysfunction. In the present study—using a transdiagnostic, clinical psychiatric sample spanning the psychosis-autism-social anxiety spectrums—we examined the role of the cerebellum in mentalizing and its unique contributions to broader social functioning.

Sixty-two participants (38 with significant social dysfunction secondary to psychiatric illness and 24 nonclinical controls without social dysfunction) completed a mentalizing task during functional magnetic resonance imaging. General linear model analysis, latent variable modeling, and regression analyses were used to examine the contribution of cerebellum activation to the prediction of group status and social functioning.

Mentalizing activated a broad set of social cognitive brain regions, including cerebral mentalizing network (MN) nodes and posterior cerebellum. Higher posterior cerebellum activation significantly predicted clinical status (i.e., individuals with psychiatric disorders versus nonclinical controls). Finally, cerebellar activation accounted for significant variance in social functioning independent of all other cerebral MN brain regions identified in a whole-brain analysis.

Findings add to an accumulating body of evidence establishing the unique role of the posterior cerebellum in mentalizing deficits and social dysfunction across psychiatric illnesses. Collectively, our results suggest that the posterior cerebellum should be considered – alongside established cerebral regions – as part of the mentalizing network.

Although cognitive remediation (CR) improves cognition and functioning, the key features that promote or inhibit its effectiveness, especially between cognitive domains, remain unknown. Discovering these key features will help to develop CR for more impact.

To identify interrelations between cognition, symptoms, and functioning, using a novel network analysis approach and how CR affects these recovery outcomes.

A secondary analysis of randomized controlled trial data (N = 165) of CR in early psychosis. Regularized partial correlation networks were estimated, including symptoms, cognition, and functioning, for pre-, post-treatment, and change over time. Pre- and post-CR networks were compared on global strength, structure, edge invariance, and centrality invariance.

Cognition, negative, and positive symptoms were separable constructs, with symptoms showing independent relationships with cognition. Negative symptoms were central to the CR networks and most strongly associated with change in functioning. Verbal and visual learning improvement showed independent relationships to improved social functioning and negative symptoms. Only visual learning improvement was positively associated with personal goal achievement. Pre- and post-CR networks did not differ in structure (M = 0.20, p = 0.45) but differed in global strength, reflecting greater overall connectivity in the post-CR network (S = 0.91, p = 0.03).

Negative symptoms influenced network changes following therapy, and their reduction was linked to improvement in verbal and visual learning following CR. Independent relationships between visual and verbal learning and functioning suggest that they may be key intervention targets to enhance social and occupational functioning.

There is currently no definitive method for identifying individuals with psychosis in secondary care on a population-level using administrative healthcare data from England.

To develop various algorithms to identify individuals with psychosis in the Mental Health Services Data Set (MHSDS), guided by national estimates of the prevalence of psychosis.

Using a combination of data elements in the MHSDS for financial years 2017–2018 and 2018–2019 (mental health cluster (a way to describe and classify a group of individuals with similar characteristics), Health of the Nation Outcome Scale (HoNOS) scores, reason for referral, primary diagnosis, first-episode psychosis flag, early intervention in psychosis team flag), we developed 12 unique algorithms to detect individuals with psychosis seen in secondary care. The resulting numbers were then compared with national estimates of the prevalence of psychosis to ascertain whether they were reasonable or not.

The 12 algorithms produced 99 204–138 516 and 107 545–134 954 cases of psychosis for financial years 2017–2018 and 2018–2019, respectively, in line with national prevalence estimates. The numbers of cases of psychosis identified by the different algorithms differed according to the type and number (3–6) of data elements used. Most algorithms identified the same core of patients.

The MHSDS can be used to identify individuals with psychosis in secondary care in England. Users can employ several algorithms to do so, depending on the objective of their analysis and their preference regarding the data elements employed. These algorithms could be used for surveillance, research and/or policy purposes.

There is evidence that attachment, trauma, and voice appraisals individually impact voice hearing in psychosis, but their intersectional relationship has not been examined. The aim of this study was to identify subgroups of individuals from the intersectional relationship between these factors and examine differences between subgroups on clinical outcomes.

A latent profile analysis was conducted on baseline data from the AVATAR2 trial (n = 345), to identify statistically distinct subgroups of individuals with psychosis who hear distressing voices based on co-occurring patterns of trauma, fearful attachment, and voice appraisals. The association between profile membership and demographic characteristics, voice severity, posttraumatic stress disorder symptoms, emotional distress, and difficulties with motivation and pleasure was then examined. Experts by experience were consulted throughout the process.

Four profiles were identified: ‘adverse voices and relational trauma’, ‘low malevolent and omnipotent voices’, ‘adverse voices yet low relational trauma’, and ‘high benevolent voices’. Negative voice appraisals occurred in the presence of high and low trauma and attachment adversities. The first profile was associated with being female and/or other non-male genders and had worse voice severity and emotional distress. High adversities and worse emotional distress occurred in the presence of voice benevolence and engagement. Black and South Asian ethnicities were not associated with specific profiles.

The identified profiles had negative and positive voice appraisals associated with higher and lower occurrence of adversities, and different clinical outcomes. These profiles could inform detailed case formulations that could tailor interventions for voice hearers.

Complex post-traumatic stress disorder (cPTSD) is a newly recognized condition characterized by core PTSD symptoms and disturbances in self-organization (DSO) that has been associated with psychotic-like experiences (PLEs). This study employs two psychopathology network approaches to identify which post-traumatic symptoms are related to PLEs in a sample of late adolescents. We propose that cPTSD symptoms play a crucial role in explaining the co-occurrence of trauma and PLEs.

A sample of 1010 late adolescents provided measures of post-traumatic symptomatology and PLEs. We estimated the Gaussian graphical network structure of PTSD/cPTSD symptoms and PLEs and assessed their bridge centrality indices. Bayesian network analysis was then used to estimate a directed acyclic graph (DAG). Gender was set as a moderator in both Gaussian and Bayesian models.

Results show that affect dysregulation, a cPTSD domain, presented the highest bridge connection with the PLE cluster. Bayesian network analysis identified a pathway going from cPTSD items of worthlessness and relational dysregulation, to PLE items of paranoia and social anxiety. Additionally, we found relevant gender differences in network connectivity, with females showing higher connectivity compared to males.

Our findings highlight the central role of affect dysregulation and negative self-concept in linking cPTSD to PLE symptoms, with specific differences according to gender. These insights underscore the need for targeted, gender-sensitive approaches in the prevention and treatment of PLEs among adolescents, emphasizing early intervention and tailored treatment strategies.

The last two decades have seen considerable development in our understanding of delusions, with medical perspectives broadening into more holistic bio-psychosocial models. Of particular relevance to services is the increasing evidence base for cognitive behavioural models and treatments. A number of national initiatives have aimed to ensure these developments are reflected in services. Primarily these have targeted adult services, yet delusions are no less common in older adults. Across two older adult services this study searched over 10,000 clinical notes to assess the number of individuals experiencing delusions, explored the perspectives of 27 staff members regarding their clinical approaches to working with delusions, and delivered a brief training on cognitive behavioural models and treatments of delusions. Three service users contributed to the training content. Endorsement of theoretical perspectives regarding delusions were measured pre- and post-training. Results showed over 20% of patients in the service may be experiencing paranoia or delusions, but only a handful were referred for CBT. Of 27 staff participants, less than half had received training on working with delusions, most of which was from as many as 20 years ago. Nearly all reported that a lack of knowledge prevented them from considering psychological perspectives. A quarter of staff across the two teams attended the training. No immediate changes in outcome measures were seen immediately post-training, with a striking diversity in approach reported by different members of staff. All staff qualitatively reported finding the training valuable, although engagement was dampened by high levels of stress and burnout.

1. (1) To understand the developing cognitive behavioural evidence base for understanding and treating delusions in older adults.

2. (2) To understand the need for this growing evidence base to be reflected in services, including older adult services, not only in structured interventions offered by psychological therapists, but also in patient interactions and care planning by all professions working in multi-disciplinary teams.

3. (3) To understand some of the key challenges in assessing and improving current understanding of cognitive behavioural approaches to delusions within services.

Psychosis prediction has been a key focus of psychiatry research for over 20 years. The two dominant approaches to identifying psychosis risk have been the clinical high-risk (CHR) and the familial high-risk (FHR) approaches. To date, the real-world sensitivity of these approaches – that is, the proportion of all future psychotic disorders in the population that they identify – has not been systematically reviewed.

We systematically reviewed and meta-analysed studies in MEDLINE, Embase, PsychINFO, and Web of Science (from inception until September 2024) that reported data on the sensitivity of CHR and FHR approaches – i.e., individuals with a psychosis diagnosis preceded by a CHR diagnosis or a history of parental psychosis (PROSPERO: CRD42024542268).

We identified four CHR studies and four FHR studies reporting relevant data. The pooled estimate of the sensitivity of the CHR approach was 6.7% (95% CI: 1.5–15.0%) and of the FHR approach was 6.5% (95% CI: 4.4–8.9%). There was a high level of heterogeneity between studies. Most FHR studies had a low risk of bias, but most CHR studies had a high risk of bias.

Pooled data suggest that CHR and FHR approaches, each, capture only about 6–7% of future psychotic disorders. These findings demonstrate the need for additional approaches to identify risk for psychosis.

Individuals with borderline intellectual functioning and intellectual disabilities (intellectual impairment) may be at increased risk of psychosis. However, studies have been limited by small and selected samples. Moreover, the role of early life trauma, a key risk factor for psychosis, in the associations is unknown.

Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort, we investigated the associations between intellectual impairment, psychotic disorders, and psychotic experiences, and assessed the mediating role of trauma in childhood. Individuals with intellectual impairment were identified using a multisource measure utilizing indicators from ALSPAC combined with health and administrative records. Psychotic disorder diagnoses were extracted through linkage to primary care records. Psychotic experiences were assessed at ages 18 and 24 using the semi-structured Psychosis-Like Symptoms interview (PLIKSi). Trauma between ages 5 and 11 was assessed with questionnaires and interviews administered to children and parents at multiple ages. Multiple imputation was performed to mitigate bias due to missing data.

The maximum sample after multiple imputation was 9,407. We found associations between intellectual impairment and psychotic disorders (OR = 4.57; 95%CI: 1.56–13.39). Evidence was weaker in the case of psychotic experiences (OR = 1.63; 95%CI: 0.93–2.84). There was some evidence suggesting a mediating role of trauma in the associations between intellectual impairment and psychotic experiences (OR = 1.09; 95%CI: 1.03–1.15). Complete records analyses yielded comparable estimates.

Intellectual impairment is associated with psychotic disorders and experiences in adulthood. Research into the contribution of trauma could shape intervention strategies for psychotic disorders in this population.

Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms.

Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort–cost computation.

k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores.

Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.

This study explored the association among dissociative experiences, recovery from psychosis and a range of factors relevant to psychosis and analysed whether dissociative experiences (compartmentalisation, detachment and absorption) could be used to predict specific stages of recovery. A cross-sectional design was used, and 75 individuals with psychosis were recruited from the recovery services of the Gloucestershire Health and Care NHS Foundation Trust. Five questionnaires were used – the Dissociative Experiences Scale – II (DES), Detachment and Compartmentalisation Inventory (DCI), Questionnaire about the Process of Recovery, Stages of Recovery Instrument (STORI), and Positive and Negative Syndrome Scale – and a proforma was used to collect demographic data.

Our findings indicated that compartmentalisation, detachment and absorption, as measured by DES and DCI, do not predict stages of recovery as measured by the STORI.

The results of this study suggest that there is no simple relationship between dissociative and psychotic symptoms. They also suggest a need to assess these symptoms separately in practice and indicate that special approaches to treatment of psychosis may be needed in cases where such symptoms have a significant role.