Patients with neurological disorders frequently present with co-occurring psychiatric symptoms, often requiring assessment within specialist neuropsychiatric services. This study aimed to describe the spectrum of psychiatric presentations seen in a specialist neuropsychiatry outpatient population and evaluate the prevalence and severity of anxiety and depressive symptoms among patients attending a tertiary neuropsychiatry clinic.

A descriptive cross-sectional study was conducted in a tertiary regional neuropsychiatry outpatient clinic in London. Consecutive patients attending the service were invited to participate. Participants completed a standardised questionnaire collecting demographic data and standardised measures of mood and anxiety were administered using the Patient Health Questionnaire-9 (PHQ-9) and the Generalised Anxiety Disorder-7 (GAD-7). Of those invited, 79 participants were included in the final analysis.

High levels of psychiatric comorbidity were observed across the neuropsychiatric cohort, with substantial variability between diagnostic groups. Patients diagnosed with functional neurological disorder (FND) demonstrated the greatest affective symptom burden: 92% reported at least mild depressive symptoms and 83% met criteria for clinically significant anxiety. Other neuropsychiatric subgroups similarly exhibited notable levels of anxiety and depression although to a lesser extent than the FND group.

This study demonstrates a substantial and heterogeneous psychiatric symptom burden among patients attending a specialist neuropsychiatry outpatient service. The particularly high prevalence of affective symptoms in individuals with FND highlights the need for comprehensive, integrated, and multidisciplinary approaches to assessment and treatment. Improved recognition and management of psychiatric comorbidities may have important implications for clinical outcomes, patient experience, and long-term prognosis within neuropsychiatric populations.

Functional Neurological Disorder (FND) presents with diverse and often overlappingneurological symptoms, reflecting marked clinical heterogeneity. Research has largely focused on psychological and psychosocial contributors, while biological and developmental health factors earlier in life remain comparatively underexplored. This study examined the prevalence and clinical relevance of early biological factors, neurodevelopmental features, and childhood or adolescent physical health conditions in a cohort of patients with FND.

We conducted a retrospective analysis of medical records from 282 individuals diagnosed with FND within a tertiary neuropsychiatry service. Extracted data included biological complications occurring around birth, documented neurodevelopmental delays or diagnoses, neurodivergent conditions, and significant medical illnesses during childhood or adolescence. Functional neurological symptoms were grouped into seizure-related, motor, sensory, and cognitive presentations to explore potential associations.

Indicators of early biological and developmental vulnerability were frequently observed. Nearly one-third of patients had recorded perinatal problems, while neurodevelopmental delays and neurodivergent conditions were identified in approximately one-fifth of the cohort. Childhood or adolescent physical illness was common, affecting almost half of the sample.

Early biological, developmental, and physical health factors are commonly documented in individuals with FND and may form part of the broader clinical context in which functional symptoms emerge. Rather than suggesting causation, these findings highlight the importance of considering neurodevelopmental and early-life health vulnerability when conceptualising FND and its varied presentations. Incorporating this perspective may aid in understanding clinical complexity and supporting more individualisedassessment approaches.

To evaluate the effectiveness of case management for children and young people (CYP) with mental disorders, substance use, or neurodevelopmental conditions, and to identify components and contextual factors associated with improved outcomes.

This was a systematic review and multi-level meta-analysis of randomised controlled trials (RCTs). Databases were searched from inception to June 2025. Reference lists and prior reviews were hand-searched for additional studies. Eligibility criteria: RCTs involving participants aged 5–18 years with mental health, substance use, or neurodevelopmental conditions, comparing case management (or equivalent) to treatment as usual, waiting list, or a less intensive model in community/outpatient settings. Outcomes extracted were clinical and social outcomes (which included any outcomes related to symptoms and functioning), service use (which included any outcomes related to the numberof service contacts or treatments given, excluding differences in treatments offered due to the experimental conditions), satisfaction, and cost-effectiveness. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Cochrane RoB 2 tool. Effect sizes (Hedges’ g) were pooled and meta-analyses were conducted for clinical and social outcomes and service use, applying a multilevel model to account for effect-size clustering within and between studies. Narrative review was conducted for satisfaction and cost-effectiveness. The certainty of evidence was rated using GRADE.

Fourteen studies were included, comprising 16 comparisons, most of which were conducted in the United States. Case management was associated with a small improvement in clinical and social outcomes (Hedges’ g=0.15; 95% CI 0.02 to 0.28) and a moderate increase in service use (g=0.68; 95% CI 0.20 to 1.17). Heterogeneity was high. Economic analyses suggested potential cost-effectiveness through reduced out-of-home placement and treatment dropout. Evidence for satisfaction was mixed. There were some concerns or high risk of bias in 10 out of 14 studies. The certainty of evidence using GRADE was very low for clinical and social outcomes and low for service use.

The review indicates that case management can improve engagement and service use among CYP with complex mental health needs, though clinical benefits are modest, and evidence quality is limited.

Body Dysmorphic Disorder (BDD) is overrepresented in aesthetic medicine (prevalence up to 18.6% in aesthetic cohorts versus ~1.7–2.9% in the general population). Professional bodies recommend psychological assessment before cosmetic intervention and referral to mental health services if BDD is suspected.

We aim to examine post-assessment care by:

• Quantifying the gap between recommended assessment/referral standards and real-world practice.

• Assessing how well the literature captures referral conversion (screening to specialist assessment).

• Identifying patient, clinician, and system barriers that prevent completion of specialist mental-health assessment.

A targeted review was conducted using evidence from aesthetic-surgery meta-analyses, dermatology and plastic surgery guidelines, aesthetic-practice safety documents, insurer psychological-risk frameworks, and psychiatric assessment resources. Sources were reviewed for prevalence data, referral expectations and realities, and documented barriers to mental-health engagement.

Although BDD prevalence in aesthetic settings is consistently studied and reported,published literature rarely captures how many screen-positive patients are referred for psychiatric assessment.

Despite the presence of several high-accuracy validated BDD screening tools, recent database evidence highlights ongoing missed detection: in a cohort of 226,374 cosmetic-surgery patients (from August 2002–August 2022), 52.1% of BDD diagnoses occurred only after procedures.

Literature shows that barriers span patient-level (denial, doctor-shopping), clinician-level (concerns about conflict, reputational or financial impact, limited training), and system-level (lack of structured referral pathways, limited multidisciplinary integration, absence of warm-handover mechanisms). However, there are minimal quantitative studies measuring these factors.

UK-based literature documents BDD prevalence and outcome risk in cosmetic seekers and provides validated screening tools and professional standards, but there is minimal evidence reporting UK metrics on referral-conversion or psychiatric follow-through.

Professional guidelines recommend that suspected BDD requires specialist evaluation, yet referral completion rates remain unmeasured and pathway implementation inconsistent across aesthetic practice settings. The absence of referral-conversion data and evidence of missed diagnoses, highlight a critical knowledge and safety gap. Priority actions include: auditing current screening and referral practices in regulated aesthetic settings, establishing clear referral triggers and destinations, implementing warm-handover mechanisms, and developing integrated pathways between aesthetic and mental health services to improve early detection and patient safety.

To map emerging evidence on how endogenous female sex hormones influence ADHD symptom trajectories and treatment response, and to prioritise a concise, pragmatic research agenda that can be taken forward by clinicians and researchers.

We carried out a targeted narrative review of recent reviews, cohort studies, mechanistic reports and pragmatic clinical series published in the last decade. Selection emphasised studies that reported cycle-linked symptom data, used within-subject comparisons, incorporated endocrine assays, or described medication-adjustment strategies. The goal was to identify consistent clinical signals, methodological weaknesses, and high-yield research priorities rather than to perform an exhaustive systematic search.

Across menstrual, peripartum and perimenopausal windows a consistent clinical signal emerges: many women with ADHD report predictable worsening of attention, executive function and affective regulation during low-oestradiol states (late luteal/menstrual phase, early postpartum, and perimenopause). Mechanistic work indicates that oestrogen modulates dopaminergic and noradrenergic circuits implicated in attention and cognitive control, providing biological plausibility for these observations. Small within-subject and pragmatic reports suggest stimulant efficacy and tolerability may vary by cycle phase and that some clinicians achieve symptomatic benefit with cycle-timed dose adjustments; however, these data are preliminary. The literature is dominated by observational designs, retrospective self-report, small samples, inconsistent outcome measures and sparse serial hormone sampling. These limitations constrain causal inference and generalisability. Perinatal evidence highlights postpartum vulnerability but lacks robust registries linking medication decisions to maternal and infant outcomes. Perimenopausal findings are emerging but heterogeneous.

There is sufficient signal to warrant routine clinical enquiry about symptom cyclicity and to adopt a cycle-aware, flexible management approach in practice. To move from signal to guidance we recommend three priority studies: (1) short prospective menstrual-cycle cohorts with daily symptom tracking and serial oestradiol/progesterone assays; (2) within-subject medication response trials comparing follicular and luteal phases with pharmacokinetic sampling; and (3) perinatal registries documenting medication choices and maternal-infant outcomes. Implementing this focused agenda will accelerate translation of hormonal mechanisms into practical, gender-sensitive ADHD care.

Schizophrenia is associated with abnormalities in mismatch negativity (MMN), an event-related potential linked to sensory memory and information-processing deficits. MMN has been widely studied as a biomarker for disease progression. This review and meta-analysis examines the magnitude of MMN abnormalities in schizophrenia and explores factors associated with these effects. In addition, this study evaluates a large language model approach for automated data extraction, with potential applications for future meta-analyses.

MEDLINE, Embase and PsycINFO databases were searched from inception to 14 November 2025. A total number of 2493 articles investigating auditory MMN in patients with an established diagnosis of schizophrenia, first-episode psychosis, high-risk groups, and first-degree relatives was identified. Manual data extraction was compared to an automated data extraction using OpenAI’s GPT5 model. The mean effect size of auditory MMN in patients compared to controls was calculated. Subgroup analyses for deviant type and auditory paradigm were conducted. The effects of age, sex, illness duration, symptom severity and antipsychotic dose were analysed.

A total of 140 studies were included in the analysis. Compared to the controls, patients with schizophrenia showed reduced auditory MMN amplitudes (g=0.72, 95% CI [0.63–0.82]). MMN impairment increased significantly (p<0.0001) across illness stages from high-risk individuals (g=0.37) to first-episode psychosis (g=0.50) and chronic schizophrenia (g=0.85). Subgroup analyses by deviant type and auditory paradigm showed no statistically significant differences in effect sizes. Auditory MMN amplitude was not significantlyreduced among first-degree relatives. Meta-regression analyses found that both antipsychotic dose (p<0.0001) and illness duration (p<0.0001) significantly moderated MMN effect sizes, while sex, symptom scales’ scores and patient age were not significant modulators. OpenAI’s GPT5 model accurately extracted data across 95% of fields.

This large meta-analysis confirms that auditory MMN amplitude is reduced in schizophrenia and modulated by both duration of illness and antipsychotic dose. This is present in high-risk groups, intensifying with progression to first-episode psychosis and chronic schizophrenia. These findings reinforce MMN as a potential biomarker of neurophysiological dysfunction in schizophrenia across stages of illness. Additionally, automated data extraction provided promising feasibility for accelerating future large-scale meta-analytic workflows.

Clinical depression is one of the most prevalent psychiatric illnesses, yet patient understanding of the condition is often lacking. Effectively educating patients on their diagnosis is a key communication skill for clinicians and future doctors.

This qualitative study aimed to compare how consultants and medical students, two ends of the medical hierarchy, differ when explaining depression to patients, whilst examining the potential clinical and educational implications.

Semi-structured online interviews were conducted with 12 final-year students and four consultants (two psychiatrists and two general practitioners). Participants were asked to role-play how they would discuss a suspected depression diagnosis to a lay patient, and explain the condition.

Linguistic and thematic analysis was conducted using Nvivo.

Consultants tended to avoid heavy neurobiological discussion, using simplifications and generalisations to explain things with brevity and relating back to a patient’s individual experience. One psychiatrist explained that this simplified description aimed to prioritise patient comprehension and acceptance to treatment, where ‘bogg[ing] them down with…scientific facts’ was feared to cause confusion or take emphasis from what the clinician deemed important.

In contrast, despite avoiding medical jargon, students gave more verbose biochemical explanations. All students referred to the neurobiological theory behind depression within their answers.‘Serotonin’ specifically was mentioned by three students, but not by any consultants. Students also showed difference in language style, often asserting a more declarative tone by informing a patient of their diagnosis, clearly separating themselves as the expert. Consultants framed explanations as a collaboration and promoted patient self-reflection, inviting the patient to follow their diagnostic conclusion, reducing doctor–patient asymmetry in the hypothetical consultation.

Students medicalised depression to properly inform patients and validate their experiences. Comparatively, consultants were succinct and practical for clarity, comprehension and mutual understanding. There is research to support this latter approach, which suggests that an overemphasis on the neurobiological basis of depression can cause a lack of focus on the social and emotional dimensions of the illness. This may even cause a favouring of pharmacological over cognitive therapies.

Communication skills training for these students has effectively taught them to avoid unexplained medical jargon, but may need greater emphasis on delivering practical, patient-centred information when educating patients on their psychiatric conditions. However, due to the limited scope of this study, further research would be needed with larger cohorts in a more clinically realistic setting.

Current antipsychotic treatments in schizophrenia inadequately address negative and cognitive symptoms and are associated with significant metabolic side effects, contributing to poor adherence and relapse. This review evaluates and synthesises current evidence on the ketogenic diet in schizophrenia and identifies methodological limitations to inform future research.

A systematic search was conducted across PubMed, MEDLINE, Embase, PsycINFO, and Scopus using terms related to “ketogenic diet” and “schizophrenia”. Primary studies involving participants with schizophrenia receiving a ketogenic diet were included; animal studies, secondary analyses, non-ketogenic or exogenous ketone interventions, and non-English publications were excluded. Of 1177 records identified, 11 studies met the inclusion criteria and were appraised using Joanna Briggs Institute tools.

Across 11 studies involving 38 participants, with follow-up ranging from 2 weeks to 12 years, ketogenic diet interventions were associated with improvements in psychotic and mood symptoms, often observed within weeks. Several studies also reported improvements in metabolic markers and physical well-being and reduced antipsychotic use, including complete withdrawal in some participants. Greater adherence was reported when participants received structured support. Symptom relapse was reported following diet discontinuation, suggesting possible diet-dependence. Reported adverse effects were generally mild and transient.

Preliminary evidence suggests potential mental and metabolic benefits of the ketogenic diet in schizophrenia; however, current findings are limited by small sample sizes, reliance on case reports and pilot designs, and inconsistent adherence. Future large-scale, controlled trials should use standardised symptom measures and systematic reporting of psychiatric and metabolic outcomes to establish efficacy, safety, and comparability.

The authors have not received any financial sponsorship.

To synthesise qualitative evidence on the lived experiences transitioning from child to adult health and social care services for young people with Attention Deficit/Hyperactivity Disorder (ADHD) in the UK.

A systematic search of MEDLINE, PsycINFO, Embase, Scopus, ASSIA, and grey literature sources was conducted on 3 June 2025. Eligible studies were qualitative or mixed-method, published from 2014 onwards and examined the transition experiences of young people with ADHD in the UK. Studies were excluded if they were purely quantitative, non-UK, or pre-2014. Methodological quality was appraised using the Critical Appraisal Skills Programme checklist. The data was synthesised using thematic analysis and narrative synthesis.

Nine studies were included: seven peer-reviewed papers and two grey literature reports. Across 224 participants (90 young people, 82 family members, 52 clinicians), three overarching themes were identified: (1) communication as a determinant of transition experience, (2) negotiating discontinuity and change and (3) interdependence of individual and systemic factors.

Transition to adult services for young people with ADHD is commonly experienced as fragmented, poorly coordinated and psychologically distressing. The findings highlight the need for developmentally informed, person-centred transition protocols that recognise transition as an active process rather than a discrete administrative event. Future research should prioritise disengaged young people and investigate long-term trajectories to inform evidence-based policy and service development.

Social media use is nearly universal among adolescents, yet its relationship with mental health remains contested. Much public and policy debate focuses on total time spent on social media, despite emerging evidence that qualitative aspects of use may be more relevant. Clarifying which dimensions of social media use are most strongly associated with mental health outcomes is essential for informing school, clinical, and policy interventions.

This review aimed to synthesise evidence on the association between social media use and mental health outcomes in secondary school students (approximately ages 11–18). We hypothesised that (1) problematic social media use would show stronger and more consistent associations with adverse mental health outcomes than time-based measures, and (2) contextual and experiential patterns of use would be more informative than frequency or duration alone.

A rapid systematic review was conducted using a structured web-based search strategy to identify peer-reviewed systematic reviews, meta-analyses, and high-quality longitudinal or quasi-experimental studies examining social media use and mental health outcomes in adolescents attending secondary school. Eligible outcomes included depressive symptoms, anxiety symptoms, psychological distress, wellbeing, sleep disturbance, and self-harm-related outcomes. Social media exposure measures were categorised as time/frequency of use, problematic social media use (defined as compulsive or impairment-associated use), and patterns or experiences of use (e.g. active versus passive engagement, social comparison, feedback sensitivity). Findings were synthesised narratively by exposure category and outcome domain.

Across included evidence syntheses and longitudinal studies, associations between time spent on social media and mental health outcomes were generally small and inconsistent, with substantial susceptibility to confounding and reverse causality. In contrast, problematic social media use demonstrated more robust and consistent associations with depressive symptoms, anxiety symptoms, and psychological distress. Evidence examining patterns and experiences of use suggested that mechanisms such as social comparison, sleepdisruption, and emotional reactivity to online feedback may partially explain observed associations. Evidence evaluating school-based restriction policies alone showed limited and mixed effects on mental health outcomes.

Findings support the hypothesis that problematic and impairment-related social media use, rather than total time spent, is most consistently associated with poorer mental health in secondary school students. Interventions and assessments should prioritise loss of control, sleep disruption, and emotional impact of use rather than focusing solely on duration. Stronger causal inference will require future studies using objective exposure measures and experimental designs.

In seeking treatment for children presenting with psychiatric symptoms, many families ask about use of complementary and alternative medicine (CAM), including herbal preparations, to help their child cope with mental health distress in addition or alongsideconventional care. This includes remedies to support their child through anxiety, sleep disturbance, low mood and attention difficulties. In UK paediatric populations, CAM use is widespread (41% in one tertiary survey), and 44.6% of families managing childhood ADHD report non-mainstream treatments. However, clinical evidence of their efficacy and tolerability is weak and rarely synthesised.

In today’s multidisciplinary healthcare system, an understanding of CAMs, including their psychiatric outcomes and safety sensitivity, will improve shared family decision-making in child and adolescentpsychiatry. Our aim is to map paediatric interventional and published trial evidence for 19 culturally used botanicals shortlisted for reputed psychiatric/behavioural benefits in children to be included in a systematic review.

We hypothesised the clinical literature would be sparse, heterogeneous, and majorly consisting of smaller studies.

Nineteen botanicals were shortlisted from commonly used traditional preparations with plausible tolerability in children and reputed benefits for psychiatric/behavioural symptoms. We conducted an evidence map of these herbs using two sources: (1) ClinicalTrials.gov (“Find Studies”) filtered to interventional studies, age group “child”, and status “completed”; and (2) PubMed searches using herb name/botanical name terms combined with child/adolescent terms and publication types “clinical trial” or “randomized controlled trial”. For each herb, we recorded trail counts and manually screened each record’s primary outcome/condition to retain only those with psychiatric/behavioural relevance. This includes anxiety, depression, ADHD (Attention-Deficit/Hyperactivity Disorder), sleep, mood, and cognition.

ClinicalTrials.gov identified 52 completed paediatric interventional records across11/19 herbs (median 1 per herb; range 0–19). Counts were highly skewed: lavender (19) and chamomile (8) accounted for over half of registry records; eight herbs had no completed paediatric interventional record. PubMed trial-type searches retrieved 36 publications across 11/19 herbs (median 1; range 0–9), similarly concentrated: lavender (9), moringa (8) and chamomile (7) comprise two-thirds of trial-type publications. Across both registries, studies had variable measurements of psychiatric/behavioural outcomes, and inconsistent reporting of adverse effects.

Paediatric interventional and published trial evidence for culturallyused botanicals with reputed psychiatric benefits is limited and unevenly distributed. Many candidates are supported by zero or single trials and heterogeneous outcomes. This evidence map will be used to inform a focused systematic review investigating mental health outcomes and tolerability and identify best candidates for further research.

Graves disease (GD) is an autoimmune thyroid disease and is the most common cause of hyperthyroidism in developed countries. Research suggests that patients with GD experience high levels of anxiety and depression. Until recently, this increased prevalence hasbeen attributed largely to Graves-induced hyperthyroidism, however even after achieving euthyroidism, many patients continue to suffer from neuropsychiatric symptoms. This suggests that the mood symptoms present in these individuals may be associated with the autoimmune inflammatory processes underlying GD. This relationship has yet to be fully understood, highlighting the need for an evaluation of the current literature. This systematic review aimed to assess the prevalence of anxiety and depression in GD patients and to identify associated risk factors.

The review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered on the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42024611942). EMBASE, MEDLINE, PsycINFO and the Cochrane Library were searched up to 31 October 2024. Papers were included providing the participants were diagnosed with GD and satisfied the diagnostic criteria for anxiety, depression or both; or provided symptomatology measures. Studies were quality assessed using Hawker’s tool. 29 studies were included and underwent data extraction. Studies using a case-control design were summarised separately.

Symptoms of anxiety and depression were consistently higher in the GD group versus healthy controls. GD patients displayed a higher baseline degree of anxiety and depression, compared with patients with other causes of hyperthyroidism. Depression and anxiety were more prevalent in relapsed hyperthyroid GD patients, compared with remitted euthyroid GD patients. Risk factors included body mass index (BMI), physical activity, gender, stress and smoking. A limitation of the review was the high study heterogeneity resulting from the variety of study designs included.

These findings highlight a population that may benefit from early psychiatric assessment. The higher prevalence of anxiety and depression observed in GD patients, including those who are euthyroid, reflects the complex interplay between autoimmune, endocrine and psychological processes underpinning the relationship between GD and mental health conditions. This pattern emphasises the need for a multidisciplinary, integrated and holistic approach when managing and treating GD patients. Future research establishing the mechanisms responsible for this increased prevalence could facilitate the development of targeted interventions and preventative treatments.

Funding: None.

The prevalence of Autism Spectrum Disorder (ASD) varies across populations. Research shows that ethnicity and migration status may influence when and how ASD is diagnosed. Understanding ethnic differences in the prevalence of ASD and any associated drivers is important to ensure fair access to assessment and support. This review explores how ethnicity and migration background may influence ASD identification by examining theprevalence and incidence of ASD among ethnic minority groups in the UK, Sweden and the Netherlands. These countries have sizeable immigrant and minority populations. The review also compares patterns of ASD classification and diagnostic subtypes across these countries.

We conducted a systematic review of epidemiological studies that reported ASD prevalence or incidence by ethnicity, parental country of birth, or migration status in these countries. We searched MEDLINE, Embase, PsycINFO, CINAHL and PubMed, along with grey literature including Google Scholar. Reference lists of included studies were also screened for relevant studies.

Eight studies published between 1987 and 2025 met inclusion criteria. They drew on large population datasets such as education records, health and psychiatric registers, child health services and clinical service data. We summarised the findings with attention to study design, diagnostic criteria and methods used to identify ASD cases and patterns of ethnic differences.

Findings differed across countries and diagnostic subtypes. In the UK, most studies reported higher recorded ASD prevalence or incidence among some ethnic minority groups, particularly Black and South Asian children. These patterns were often linked to socioeconomic disadvantage and differences in how families accessed or were referred to services.

Swedish studies consistently found higher ASD prevalence among children of immigrant parents especially those from non-Northern European regions. These groups were more likely diagnosed as ASD with intellectual disability or more severe forms of autism.

Conversely, the Dutch study reported a lower overall incidence of ASD among children of immigrant origin. This was mainly due to fewer diagnoses of Asperger syndrome and PDD-NOS.

Across several studies, children whose families were immigrants from low and middle income countries showed lower recorded rates of high-functioning ASD but relatively higher rates of more severe ASD presentations.

Ethnicity and migration-related differences in ASD prevalence varied across countries and diagnostic subtypes. These patterns appear to reflect differences in diagnostic practices, service access and sociocultural factors. Thus, ethnicity data and cross-national comparisons of ASD prevalence should be interpreted cautiously, considering contextual and methodological factors.

Psychotic disorders display marked ethnic disparities in incidence in the UK, with Black African and Black Caribbean populations consistently shown to have elevated risk.Leicester City is one of the UK’s most ethnically diverse cities and hosts a large and long-standing Somali community. Clinicians within the Psychosis Intervention and Early Recovery (PIER) service have perceived disproportionate Somali representation. This study quantitatively examines whether Somali patients are over-represented in PIER relative to population size and compares this pattern with African and Caribbean groups.

• • To determine whether Somali patients are over-represented in the Psychosis Intervention and Early Recovery (PIER) service relative to their proportion in Leicester City’s population.

• • To compare Somali over-representation to that of combined Black African/Caribbean groups.

• • To quantify crude prevalence, odds ratios (ORs), confidence intervals (CIs), and statistical significance of observed over-representation.

A retrospective analysis was conducted using a Leicester-City-only EIP caseload dataset (n=310). Ethnicity categories were collapsed into Somali, African/Caribbean (African + Caribbean + Other Black), and Other groups. Population denominators were taken from ONS Census data, including 2150 Somali write-in responses in Leicester City and African/Caribbean proportions based on Black African (~4%) and Black Caribbean (~1.36%) census data. Statistical methods included crude proportions, ORs, 95% CIs, and χ² tests.

Somali patients accounted for 7.7% of the EIP case load but only 0.58% of the Leicester population. OR for Somali over-representation was 13.45, p <0.001. African/Caribbean patients accounted for 10.3% of cases vs 5.36% of the population, OR 1.93, p <0.001. Somali patients were markedly more over-represented than the broader African/Caribbean group.

Somali individuals are substantially over-represented in early psychosis service usage in Leicester. This pattern exceeds the known elevated risk observed in African and Caribbean groups. Findings highlight urgent public health, cultural, and service-access implications requiring further investigation.

Adult ADHD remains largely defined by behavioural criteria developed for childhood presentations. In adult psychiatric practice, however, many individuals present with burnout, anxiety, or emotional exhaustion rather than overt attentional complaints. These patients often describe functioning well in some contexts but struggling disproportionately with routine, low-urgency, or poorly defined tasks. This work aims to explore whether adult ADHD is better conceptualised as a disorder of salience and arousal regulation rather than a simple deficit of attention or impulse control, and whether such a formulation better accounts for late diagnosis and masked presentations.

This work draws on repeated clinical observations from general adult psychiatricpractice, including experience in adult ADHD assessment services, synthesised into anonymised composite vignettes to identify recurring patterns of cognition, behaviour, and emotional experience. These observations were considered alongside established executive, motivational, and salience-based models of ADHD, and contemporary neurobiological accounts of dopamine and noradrenaline modulation, sensory gating, and time perception, to develop a clinically coherent formulation. An exploratory evolutionary perspective was used cautiously to illustrate environmental mismatch rather than ancestral advantage.

Consistent features extended beyond standard diagnostic criteria and included reliance on urgency or interest to initiate tasks, development of highly personalised systems of working, rapid associative thinking alongside episodes of task paralysis, conversational working-memory bottlenecks, and difficulties maintaining awareness of objects or people once out of view. Many individuals also described strong internal value systems and high personal standards, with particular sensitivity to inefficiency or perceived unfairness. Hyperfocus and distractibility could be understood within a single salience-arousal framework rather than as opposing phenomena. Functional decline commonly occurred at points of developmental or occupational transition and following additional stressors, consistent with cumulative compensatory fatigue rather than late onset.

Conceptualising adult ADHD as a regulation phenotype provides a clinically useful account of context-dependent functioning, burnout, and late diagnosis. This framework supports improved recognition of masked ADHD across adult services and encourages formulations that integrate pharmacological treatment with psychoeducation and environmental adaptation. Moving beyond checklist-driven assessment towards pattern-based clinical understanding may reduce secondary morbidity and improve long-term functional outcomes in adults with ADHD.

Suicide is a significant cause of death worldwide and is prevalent among homeless individuals. However, aspects of suicide in homeless mental health patients remain under-researched. This study aims to analyse socioeconomic, clinical, and service-related characteristics of homeless mental health patients who died by suicide in England between 2012 and 2022, with a focus on age group and ethnic background.

This retrospective cohort cross-correlational study uses data from the National Confidential Inquiry into Suicide and Safety in Mental Health (NCISH). Homelessness was classified as having ‘no fixed abode’. Comparative analyses, including multivariable logistic regression, were conducted between homeless (n=324) and non-homeless patients (n=12,605). Subgroup analyses were performed within the homeless group based on age group (under 45 years and over 45 years) and ethnic background (Ethnic Minority background and White-British).

Homeless patients were more likely to be male, younger and socioeconomically disadvantaged, to have dual diagnoses of substance dependence, adjustment disorders and histories of substance misuse, self-harm and service disengagement. They were more likely to die within 24 hours of last service contact. Younger homeless patients displayed higher prevalence of substance misuse and self-harm, and for self-harm leading to service contact. Older homeless patients more often faced recent financial difficulties. Homeless patients from ethnic minority backgrounds had a higher prevalence of affective disorders, immigration-related vulnerability and a concerningly lower median age of death.

Suicide in homeless mental health patients is associated with complex socioeconomic and clinical vulnerabilities. Our findings emphasise the need for integrated, culturally sensitive and targeted suicide prevention strategies.

Muslims in the United Kingdom face significant barriers to accessing mental health care. Cultural and religious practices influence how Muslims access mental health care and interpret causes of mental illnesses. However, current literature does not clearly separate cultural and religious influences on help-seeking, making it difficult to determine how each factor independently influences help-seeking behaviours.

The overarching aim of this study was to explore how Islamic beliefs influence mental health help-seeking for Muslim university students.

Participants were recruited through convenience, purposive and snowball sampling. Semi-structured interviews discussing mental health and Islam were conducted with participants who identified as Muslims living in the UK. Reflexive inductive thematic analysis was used to analyse interview transcripts.

Nine Muslim university students, eight of whom studied medicine, were recruited. Five major themes were identified:

• • Generational differences in understanding mental illness.

• • Relationship between culture and religion.

• • Mental health and the supernatural.

• • Choosing a mental health service.

• • Gender differences.

A key finding was the existence of a ‘dual lens’; participants demonstrated high mental health literacy whilst simultaneously holding beliefs in supernatural causes of mental illness. Thisresulted in a circumstantial preference for mental health care. Whilst National Health Service (NHS) services were the first resort for mental illnesses deemed purely biomedical, they were avoided if participants believed supernatural factors were causing the illness. This was due to a fear of scepticism from clinicians and perceptions of a lack of NHS cultural competency. Instead, participants preferred to seek help from Muslim mental health organisations (MMHOs). But access to MMHOs was hindered by a lack of awareness of these services.

Islamic beliefs can act as a strong motivator for help-seeking for the participants, though this is often overshadowed by cultural stigma. To address patients’ ‘dual lens’ framework, clinicians must adopt a ‘biopsychosocial-spiritual’ model that validates religious beliefs as part of holistic care. Increased collaboration between the NHS and MMHOs is crucial to bridge the current service gap and increase awareness in the Muslim community of the mental health support available.

Dysregulation of cortisol and folate–two biomarkers central to stress physiology and one-carbon metabolism–has been consistently reported in schizophrenia. However, the extent to which clinical and lifestyle variables shape these biomarkers remains insufficiently understood. Factors such as smoking, thyroid dysfunction, and prior psychiatric history are biologically relevant confounders: nicotine alters folate turnover and methylation pathways; hypothyroidism disrupts one-carbon metabolism and HPA-axis regulation; and long-standing psychiatric illness is associated with chronic stress-system alterations. These mechanisms may generate atypical biochemical signatures that complicate interpretation of peripheral biomarkers in schizophrenia. This study therefore investigated whether these variables contribute to unexpected cortisol and folate variations beyond the anticipated case–control differences.

A case–control design was implemented involving 33 patients with schizophrenia (DSM–5 diagnosis confirmed by two consultant psychiatrists) and 33 age-and sex-matched healthy controls without personal or familial psychiatric history. To minimize circadian effects, fasting venous blood samples were collected between 07:00–08:00am. Serum cortisol and folate were measured using standardized AccuBind ELISA kits, with all assays performed in duplicate. Samples were processed under uniform laboratory conditions and stored at −20°C. Symptom severity and extrapyramidal side effects were assessed by a blinded psychiatrist using the PANSS and SAS scales. Demographic and clinical variables–including smoking status, thyroid disease, and psychiatric history–were systematically documented. Normality was assessed using the Shapiro–Wilk test; group comparisons employed t-tests or Mann–Whitney U tests; and associations were examined using Spearman correlations (p<0.05). Ethical approval was obtained from Golestan University of Medical Sciences.

Compared with healthy controls, patients with schizophrenia exhibited significantly lower serum cortisol (54.98 ± 26.90 vs. 96.10 ± 57.15 µg/dL; p<0.0001) and folate levels (2.21 ± 2.20 vs. 14.69 ± 11.68 ng/mL; p<0.0001). Beyond these expected findings, several distinct patterns emerged:

• Participants with a psychiatric history showed markedly reduced cortisol (12.16 ± 10.27 vs. 57.77 ± 26.45; p=0.017).

• Individuals with hypothyroidism demonstrated significantly lower folate (1.94 ± 1.89 vs. 5.30 ± 2.78; p=0.020).

• Smokers unexpectedly exhibited higher folate levels (4.70 ± 2.73 vs. 1.94 ± 1.86; p=0.036).

No significant correlations were found between biomarkers and PANSS or SAS scores.

In addition to global reductions in cortisol and folate in schizophrenia, this study identifies distinct biomarker signatures linked to smoking, thyroid dysfunction, and psychiatric history. These findings underscore the importance of accounting for metabolic and lifestyle factors when interpreting peripheral biomarkers in psychiatric research and clinical practice.

Depression represents a leading cause of disability in England, with NHS Talking Therapies providing evidence-based psychological treatments to over 1.8 million people annually. Despite overall effectiveness, persistent disparities in recovery and engagement exist across demographic groups, particularly by age and ethnicity. Predictive modelling offers an opportunity to identify patients at risk of dropout or non-recovery, but few studies have evaluated such models for fairness.

This study aimed to develop and evaluate fairness-aware machine learning models to predict recovery and dropout in NHS Talking Therapies using early-treatment clinical data. In addition to assessing predictive performance, the study quantified algorithmic fairness across demographic groups, focusing on disparities in true positive rates by age and ethnicity. We hypothesised that integrating fairness constraints into model training would reduce demographic disparities while preserving predictive performance, thereby supporting more equitable and targeted service delivery.

This study analysed routinely collected clinical data from 33,341 patients discharged from an NHS Foundation Trust in North-West England between January 2024 andJuly 2025. Outcomes included dropout after assessment, dropout before session four, and recovery following at least one therapy session. Predictor variables comprised demographic characteristics, referral pathway, and item-level Patient Health Questionnaire-9 (PHQ-9) responses, including early symptom change. Baseline models included L2-regularised logistic regression and Extreme Gradient Boosting (XGBoost). Performance was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUROC), accuracy, and Equal Opportunity (parity in true positive rate (TPR)) across age, gender, and ethnicity. A custom fairness-aware XGBoost model was developed using a dynamic dual-ascent regularisation controller to reduce subgroup disparities during training.

Baseline models showed moderate discrimination (AUROC 0.65 for dropout after assessment; 0.75 for recovery), with logistic regression performing similarly to XGBoost. However, substantial disparities were observed, with TPR gaps exceeding 0.40 across age groups and 0.30 across ethnic groups. The fairness-aware XGBoost model maintained discrimination (AUROC 0.64–0.74) while markedly reducing subgroup disparities, achieving up to an 84% reduction in age-related gaps, approximately 50% in gender, and 40% in ethnicity, with only a minimal reduction in overall accuracy.

These findings demonstrate that fairness-aware optimisation can mitigate demographic disparities in predictive modelling for mental health services while preserving predictive performance. To our knowledge, this represents the first application of fairness-constrained machine learning in NHS Talking Therapies. Such approaches could support more equitable, data-driven care pathways when implemented as clinician decision-support tools with ongoing fairness monitoring.

To discuss the potential role of artificial intelligence (AI) in different diagnostic interventions in dementia.

A literature search was conducted in PubMed on 6 February 2026 using the terms “artificial intelligence” AND “dementia”. The search identified 5257 records, which were limited to publications from 2021–2026, yielding 3598 records. Filters for free full-text availability and study type (clinical trials, randomized controlled trials, systematic reviews, meta-analyses, and reviews) were applied, resulting in 303 articles.

Inclusion criteria were: (1) studies focused on the application of artificial intelligence in dementia; (2) human studies; (3) peer-reviewed articles; (4) publication within the last five years; and (5) availability of full text in English. Exclusion criteria included: (1) non-dementia populations; (2) non-AI-based methodologies; (3) conference abstracts, editorials, letters, and commentaries; and (4) animal or simulation-only studies.

Titles of the 303 eligible articles were screened for relevance, resulting in 50 studies included for further analysis.

Dementia is a clinical outcome of complex neurological disorders with a multitude of aetiologies and risk factors. Conventional methods in early diagnosis and management of dementia pose several risks and costs. Integrating AI with a sophisticated learning model can provide a comprehensive assessment in the diagnosis of dementia. Early diagnostic efforts can be achieved through a combination of AI-based neuroimaging such as MRI, PET, and CT scans, genetic and metabolic biomarkers supported by a robust pattern recognition algorithm. Incorporation of AI in dementia diagnosis can enable early recognition, leading to a 40% risk modification.

However, a number of methodological constraints should be noted when using AI for diagnosis like lack of algorithm development and standard definitions. Other challenges include difficulties in integrating healthcare systems, as well as data privacy and ethical concerns.

Artificial intelligence has significant potential to enhance the diagnosis and prognosis of dementia by improving early detection and reducing costs. Despite methodological, ethical, and integration challenges, effective collaboration between AI and medical professionals and the development of standardized approaches are essential for successful implementation in clinical practice.