The British Journal of Psychiatry最新文献

An increase in mental disorders has been suggested, but the interpretation of such trends remains unclear. This study examines changes in the 12-month prevalence of anxiety and mood disorders over 12 years and evaluates whether clinical characteristics or sociodemographic, vulnerability and health-lifestyle risk factors contributed to these trends.

To assess trends in the 12-month prevalence of anxiety disorders (i.e. panic disorder, agoraphobia, social anxiety disorder or generalised anxiety disorder) and mood disorders (major depressive disorder, dysthymia or bipolar disorder) and explore whether changes in clinical profiles or risk factors influenced these trends.

Data from 11 615 respondents (mean age 43.5 years, 53.5% female) in the Netherlands Mental Health Survey and Incidence Studies (NEMESIS) were analysed, covering 2007–2009 (NEMESIS-2, n = 6646) and 2019–2022 (NEMESIS-3, n = 4969). Diagnoses were determined using the Composite International Diagnostic Interview 3.0.

The 12-month prevalence of all anxiety and mood disorders was significantly higher in 2019–2022 compared to 2007–2009, with relative increases across disorders ranging from approximately a half to more than double their previous rates. Any anxiety or mood disorder increased from 10.2 to 16.7%. Clinical profiles were equally severe in 2019–2022; rather, there was increased mental health care use, a higher number of comorbid disorders and earlier onset. Examination of 14 risk factors showed no consistent evidence of greater prevalence or increased relative impact over time.

There was a consistent rise in the 12-month prevalence of anxiety and mood disorders over 12 years. This increase was not explained by changes in risk factors or less severe disorder reporting. Instead, these findings suggest a concerning decline in public mental health, highlighting the need for effective prevention strategies, timely interventions and better mental health resource allocation to address growing clinical demands.

An increasing number of women of childbearing age are treated for attention-deficit hyperactivity disorder (ADHD). Limited evidence exists on risk of pregnancy loss associated with ADHD medication use in early pregnancy.

To assess whether ADHD medication use during pregnancy is associated with increased risk of miscarriage.

We conducted a nationwide, register-based, case–control study, using linked Norwegian data from Medical Birth Registry of Norway, Norwegian Patient Registry, Norwegian Control and Payment of Health Reimbursements Database and Norwegian Prescription Database. Among pregnant women with ADHD, those with miscarriage (n = 2993 cases) were matched with up to four live births (n = 10 305 controls) by maternal age and year of conception. ADHD medication exposure during pregnancy was defined as any use (one or more filled prescriptions) and categorised into tertiles of total defined daily doses (DDDs) as a proxy for dose. The main outcome was miscarriage (pregnancy loss before 20 weeks). Conditional logistic regression was used to estimate adjusted odds ratios (aORs) with 95% confidence intervals, adjusting for psychiatric comorbidities, psychotropic and teratogenic medications, and maternal age at conception.

Of 13 298 pregnancies, 1389 (10.5%) were exposed to ADHD medications. Any ADHD medication use was associated with increased miscarriage risk (aOR 1.60, 95% CI 1.41–1.83). Methylphenidate (aOR 1.55, 95% CI 1.35–1.79), lisdexamfetamine (aOR 1.81, 95% CI 1.06–3.10) and atomoxetine (aOR 2.34, 95% CI 1.41–3.89) were associated with increased risks. Higher levels of medication exposure, categorised by DDD tertiles, were associated with increased odds of miscarriage, increasing from 1.14 (95% CI 0.91–1.42) for the lowest tertile to 2.11 (95% CI 1.71–2.60) for the highest.

ADHD medication use during pregnancy is associated with increased miscarriage risk. However, filled prescriptions may not reflect actual use. Further research is needed to clarify these associations and refine risk estimates.

There is an urgent need for better evidence-based interventions in mental health. High-quality randomised controlled trials in humans are often lacking, especially when dealing with complex situations or novel therapeutic targets. Other potentially useful data may be available, such as from early-phase trials, observational or mechanistic studies or animal experiments. Triangulation offers an opportunity to consider a wider variety of evidence together to prioritise future research directions, and ultimately to inform clinical decisions. Here we describe GATE (the GALENOS Approach to Triangulating Evidence). This is the methodology of triangulation, co-produced with people with lived experience, and applied as an integral part of the GALENOS project (Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis; https://www.galenos.org.uk/). We outline the considerations of triangulation in psychiatry and our experience to date in assessing animal and human data together, using triangulation to prioritise future research directions. With GATE at its core, GALENOS not only enables novel insights to emerge, but points us towards a future of collaborative research better equipped to examine the most pressing questions in mental health.

Research exploring delusions among individuals with psychosis often focuses on form, rather than content, and on prevalence, rather than change in a cohort over time. While delusional forms are mostly consistent across cultures and historical periods, the content of delusions is shaped by sociopolitical factors.

We explored the form and content of delusions in a modern sample of individuals with psychosis, examining the extent to which the internet and new technologies become incorporated into delusional frameworks. We investigated whether there was a change in the prevalence of technology delusions over time and how gender, age and education level impacted the probability that a subject would experience technology delusions.

We reviewed the medical records of 228 adults with psychosis who were seeking treatment at a large academic medical centre between 2016 and 2024 and extracted any description of delusional thought content. We characterised delusions into subtypes and explored the ways these delusions feature the internet and new technologies. To examine temporal trends in the content of delusions, we conducted a binary logistic regression analysis with year as the predictor variable and the presence of technology-related content in delusions as the outcome variable.

Most subjects (88.2%) reported delusional thought content, with over half (51.7%) describing technology delusions. Logistic regression between the year and technology-related delusion outcome revealed statistically significant (β = 0.139, p = 0.038, 95% CI (0.008, 0.270)) correlation. For each 1-year increase, the odds of a subject presenting with technology delusions increased by approximately 15% (odds ratio 1.15).

Among individuals with psychotic disorders, the internet and new technologies are increasingly salient in delusional frameworks. Clinicians should be aware of these themes while eliciting symptoms from patients and also while educating trainees.

Diagnosis of cancer can be a stressful and life-threatening event that is associated with suicide risk.

To investigate how suicide risk changes over time after cancer diagnosis, and, specifically, when it becomes similar to that of matched controls.

Using a nationwide population-based database, we identified a total of 171 474 individuals aged ≥20 years newly diagnosed with cancer between 2009 and 2017 and 1:5 age- and sex-matched controls. We calculated adjusted hazard ratios (aHRs) with 95% confidence intervals of suicide in cancer patients for the full period and with a 1- to 5-year lag period.

During a mean follow-up of 6.7 years, 0.3% of cancer patients (491 of 171 474) died by suicide, with incidence rates of 0.4 per 1000 person-years. Cancer patients had higher risk of suicide (aHR 1.64, 95% CI 1.48–1.81) compared with matched controls. Suicide risk remained higher than that of matched controls with a 1- or 2-year lag period (aHR 1.38, 95% CI 1.23–1.55 and aHR 1.32, 95% CI 1.16–1.50, respectively), but there was no significant difference with a 5-year lag period (aHR 1.13, 95% CI 0.93–1.38). However, those with haematologic cancers were at higher suicide risk than matched controls even 5 years after diagnosis (e.g. aHR 9.26, 95% CI 1.30–65.87 for Hodgkin lymphoma).

In cancer patients, suicide risk remained elevated for several years after diagnosis, but decreased over time and became similar to that of matched controls after 5 years. However, the temporal pattern varied by cancer type, and suicide risk remained high for patients with haematological cancers. Suicide risk screening is necessary from the time of cancer diagnosis, even in long-term survivors.