British Journal of Psychiatry最新文献

Background: There are increasing calls for neurodivergent peoples' involvement in research into neurodevelopmental conditions. So far, however, this has tended to be achieved only through membership of external patient and public involvement (PPI) panels. The Regulating Emotions - Strengthening Adolescent Resilience (RE-STAR) programme is building a new participatory model of translational research that places young people with diagnoses of attention-deficit hyperactivity disorder (ADHD) and autism at the heart of the research team so that they can contribute to shaping and delivering its research plan.

Aims: To outline the principles on which the RE-STAR participatory model is based and describe its practical implementation and benefits, especially concerning the central role of members of the Youth Researcher Panel (Y-RPers).

Method: The model presented is a culmination of a 24-month process during which Y-RPers moved from advisors to co-researchers integrated within RE-STAR. It is shaped by the principles of co-intentionality. The account here was agreed following multiple iterative cycles of collaborative discussion between academic researchers, Y-RPers and other stakeholders.

Results: Based on our collective reflections we offer general guidance on how to effectively integrate young people with diagnoses of ADHD and/or autism into the core of the translational research process. We also describe the specific theoretical, methodological and analytical benefits of Y-RPer involvement in RE-STAR.

Conclusions: Although in its infancy, RE-STAR has demonstrated the model's potential to enrich translational science in a way that can change our understanding of the relationship between autism, ADHD and mental health. When appropriately adapted we believe the model can be applied to other types of neurodivergence and/or mental health conditions.

The enormous impact of mental illness on work and productivity is a global challenge, with immense costs to wider society. Now is the time for action, with new international guidelines and an emergent consensus on occupational mental healthcare. Alongside governments, organisations and employers, psychiatrists have a leading role to play.

Mental health services have changed beyond recognition in my 38-year career. In this editorial I reflect on those changes and highlight the issues that undermine patient care and damage staff morale. In particular, modern mental health services have undermined the therapeutic relationship, the bedrock underpinning all psychiatric treatment.

The non-reporting of negative studies results in a scientific record that is incomplete, one-sided and misleading. The consequences of this range from inappropriate initiation of further studies that might put participants at unnecessary risk to treatment guidelines that may be in error, thus compromising day-to-day clinical practice.

Background: Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment.

Aims: To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants.

Method: Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses.

Results: Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, β_pooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I² = 3.61%); this was also found for an IMD index combining these features (n = 372, β_pooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I²= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (β_pooled = 0.16) and the IMD index (β_pooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission.

Conclusions: Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Background: Although attention-deficit hyperactivity disorder (ADHD) is often comorbid with schizophrenia spectrum and other psychotic disorders (SZSPD), concerns about an increased risk of psychotic events have limited its treatment with either psychostimulants or atomoxetine.

Aims: To examine whether the risk of hospital admission for psychosis in people with SZSPD was increased during the year following the introduction of such medications compared with the year before.

Method: This was a retrospective cohort study using Quebec (Canada) administrative health registries, including all Quebec residents with a public prescription drug insurance plan and a diagnosis of psychotic disorder, defined by relevant ICD-9 or ICD-10 codes, who initiated either methylphenidate, amphetamines or atomoxetine, between January 2010 and December 2016, in combination with antipsychotic medication. The primary outcome was time to hospital admission for psychosis within 1 year of initiation. State sequence analysis was also used to visualise admission trajectories for psychosis in the year following initiation of these medications, compared with the previous year.

Results: Out of 2219 individuals, 1589 (71.6%) initiated methylphenidate, 339 (15.3%) amphetamines and 291 (13.1%) atomoxetine during the study period. After adjustment, the risk of hospital admission for psychosis was decreased during the 12 months following the introduction of these medications when used in combination with antipsychotics (adjusted HR = 0.36, 95% CI 0.24-0.54; P < 0.0001).

Conclusions: These findings suggest that, in a real-world setting, when used concurrently with antipsychotic medication, methylphenidate, amphetamines and atomoxetine may be safer than generally believed in individuals with psychotic disorders.

We argue that editorial independence, through robust practice of publication ethics and research integrity, promotes good science and prevents bad science. We elucidate the concept of research integrity, and then discuss the dimensions of editorial independence. Best practice guidelines exist, but compliance with these guidelines varies. Therefore, we make recommendations for protecting and strengthening editorial independence.

Background: Late-life depression has been associated with volume changes of the hippocampus. However, little is known about its association with specific hippocampal subfields over time.

Aims: We investigated whether hippocampal subfield volumes were associated with prevalence, course and incidence of depressive symptoms.

Method: We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T₁-weighted and fluid-attenuated inversion recovery 3T magnetic resonance images. Depressive symptoms were assessed at baseline and annually over 7 years of follow-up (9-item Patient Health Questionnaire). We used negative binominal, logistic, and Cox regression analyses, corrected for multiple comparisons, and adjusted for demographic, cardiovascular and lifestyle factors.

Results: A total of n = 4174 participants were included (mean age 60.0 years, s.d. = 8.6, 51.8% female). Larger right hippocampal fissure volume was associated with prevalent depressive symptoms (odds ratio (OR) = 1.26, 95% CI 1.08-1.48). Larger bilateral hippocampal fissure (OR = 1.37-1.40, 95% CI 1.14-1.71), larger right molecular layer (OR = 1.51, 95% CI 1.14-2.00) and smaller right cornu ammonis (CA)3 volumes (OR = 0.61, 95% CI 0.48-0.79) were associated with prevalent depressive symptoms with a chronic course. No associations of hippocampal subfield volumes with incident depressive symptoms were found. Yet, lower left hippocampal amygdala transition area (HATA) volume was associated with incident depressive symptoms with chronic course (hazard ratio = 0.70, 95% CI 0.55-0.89).

Conclusions: Differences in hippocampal fissure, molecular layer and CA volumes might co-occur or follow the onset of depressive symptoms, in particular with a chronic course. Smaller HATA was associated with an increased risk of incident (chronic) depression. Our results could capture a biological foundation for the development of chronic depressive symptoms, and stresses the need to discriminate subtypes of depression to unravel its biological underpinnings.

Background: Computational models offer promising potential for personalised treatment of psychiatric diseases. For their clinical deployment, fairness must be evaluated alongside accuracy. Fairness requires predictive models to not unfairly disadvantage specific demographic groups. Failure to assess model fairness prior to use risks perpetuating healthcare inequalities. Despite its importance, empirical investigation of fairness in predictive models for psychiatry remains scarce.

Aims: To evaluate fairness in prediction models for development of psychosis and functional outcome.

Method: Using data from the PRONIA study, we examined fairness in 13 published models for prediction of transition to psychosis (n = 11) and functional outcome (n = 2) in people at clinical high risk for psychosis or with recent-onset depression. Using accuracy equality, predictive parity, false-positive error rate balance and false-negative error rate balance, we evaluated relevant fairness aspects for the demographic attributes 'gender' and 'educational attainment' and compared them with the fairness of clinicians' judgements.

Results: Our findings indicate systematic bias towards assigning less favourable outcomes to individuals with lower educational attainment in both prediction models and clinicians' judgements, resulting in higher false-positive rates in 7 of 11 models for transition to psychosis. Interestingly, the bias patterns observed in algorithmic predictions were not significantly more pronounced than those in clinicians' predictions.

Conclusions: Educational bias was present in algorithmic and clinicians' predictions, assuming more favourable outcomes for individuals with higher educational level (years of education). This bias might lead to increased stigma and psychosocial burden in patients with lower educational attainment and suboptimal psychosis prevention in those with higher educational attainment.