Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Evidence shows that research-active trusts have better clinical patient outcomes. Psychiatric trainees are required to develop knowledge and skills in research techniques and critical appraisal to enable them to practice evidence-based medicine and be research-active clinicians. This project aimed to evaluate and improve the support for developing research competencies available to general adult psychiatry higher trainees (HT) in the North-West of England.

General Adult HT in the North–West of England completed a baseline survey in November 2019 to ascertain trainee's experience of research training provision. The following interventions were implemented to address this feedback:

A trainee research handbook was produced, containing exemplar activies for developing research competencies and available training opportunities, supervisors and active research studies.

The trainee research representative circulated research and training opportunities between November 2019 – August 2020.

Research representatives held a trainee Question and Answer session in September 2020.

All General Adult HT were asked to complete an electronic survey in November 2020 to evaluate the effect of these interventions.

18 General Adult HT completed the baseline survey in November 2019. 29.4% of trainees thought they received enough information on research competencies and 88.9% wanted more written guidance. 38.9% of trainees knew who to contact about research within their NHS Trust and 33.3% were aware of current research studies. Identified challenges for meeting research competencies included lack of time, difficulty identifying a mentor and topic and accessibility of projects.

20 General Adult HT completed the repeat survey in November 2020. 50% of trainees wanted to be actively involved in research and 35% wanted to develop evidence-based medicine skills. A minority of trainees aimed to complete only the minimum ARCP requirements. All trainees thought the handbook was a useful resource for meeting research competencies and would recommend it to other trainees. In trainees who received the handbook, 94.7% thought they had received adequate support on meeting research competencies and 94.7% knew who to contact about research in their trust. 68.4% of trainees would like further written guidance on meeting research competencies. Trainees highlighted ongoing practical difficulties with engaging with research and concern about lacking required skills for research.

Trainees are motivated to engage with research on various different levels, not purely for ARCP purposes. Simple interventions can help trainees feel adequately supported with meeting research competencies. Further work to support trainee involvement in research and improve trainee confidence in engaging with research is required.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in shortages of personal protective equipment (PPE), underscoring the urgent need for simple, efficient, and inexpensive methods to decontaminate masks and respirators exposed to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). We hypothesized that methylene blue (MB) photochemical treatment, which has various clinical applications, could decontaminate PPE contaminated with coronavirus.

The 2 arms of the study included (1) PPE inoculation with coronaviruses followed by MB with light (MBL) decontamination treatment and (2) PPE treatment with MBL for 5 cycles of decontamination to determine maintenance of PPE performance.

MBL treatment was used to inactivate coronaviruses on 3 N95 filtering facepiece respirator (FFR) and 2 medical mask models. We inoculated FFR and medical mask materials with 3 coronaviruses, including SARS-CoV-2, and we treated them with 10 µM MB and exposed them to 50,000 lux of white light or 12,500 lux of red light for 30 minutes. In parallel, integrity was assessed after 5 cycles of decontamination using multiple US and international test methods, and the process was compared with the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method.

Overall, MBL robustly and consistently inactivated all 3 coronaviruses with 99.8% to >99.9% virus inactivation across all FFRs and medical masks tested. FFR and medical mask integrity was maintained after 5 cycles of MBL treatment, whereas 1 FFR model failed after 5 cycles of VHP+O3.

MBL treatment decontaminated respirators and masks by inactivating 3 tested coronaviruses without compromising integrity through 5 cycles of decontamination. MBL decontamination is effective, is low cost, and does not require specialized equipment, making it applicable in low- to high-resource settings.

Structural models of psychopathology consistently identify internalizing (INT) and externalizing (EXT) specific factors as well as a superordinate factor that captures their shared variance, the p factor. Questions remain, however, about the meaning of these data-driven dimensions and the interpretability and distinguishability of the larger nomological networks in which they are embedded.

The sample consisted of 10 645 youth aged 9–10 years participating in the multisite Adolescent Brain and Cognitive Development (ABCD) Study. p, INT, and EXT were modeled using the parent-rated Child Behavior Checklist (CBCL). Patterns of associations were examined with variables drawn from diverse domains including demographics, psychopathology, temperament, family history of substance use and psychopathology, school and family environment, and cognitive ability, using instruments based on youth-, parent-, and teacher-report, and behavioral task performance.

p exhibited a broad pattern of statistically significant associations with risk variables across all domains assessed, including temperament, neurocognition, and social adversity. The specific factors exhibited more domain-specific patterns of associations, with INT exhibiting greater fear/distress and EXT exhibiting greater impulsivity.

In this largest study of hierarchical models of psychopathology to date, we found that p, INT, and EXT exhibit well-differentiated nomological networks that are interpretable in terms of neurocognition, impulsivity, fear/distress, and social adversity. These networks were, in contrast, obscured when relying on the a priori Internalizing and Externalizing dimensions of the CBCL scales. Our findings add to the evidence for the validity of p, INT, and EXT as theoretically and empirically meaningful broad psychopathology liabilities.

Evidence-based treatment for panic disorder consists of disorder-specific cognitive behavioural therapy (CBT) protocols. However, most measures of CBT competence are generic and there is a clear need for disorder-specific assessment measures.

To fill this gap, we evaluated the psychometric properties of the Cognitive Therapy Competence Scale (CTCP) for panic disorder.

CBT trainees (n = 60) submitted audio recordings of CBT for panic disorder that were scored on a generic competence measure, the Cognitive Therapy Scale – Revised (CTS-R), and the CTCP by markers with experience in CBT practice and evaluation. Trainees also provided pre- to post-treatment clinical outcomes on disorder-specific patient report measures for cases corresponding to their therapy recordings.

The CTCP exhibited strong internal consistency (α = .79–.91) and inter-rater reliability (ICC = .70–.88). The measure demonstrated convergent validity with the CTS-R (r = .40–.54), although investigation into competence classification indicated that the CTCP may be more sensitive at detecting competence for panic disorder-specific CBT skills. Notably, the CTCP demonstrated the first indication of a relationship between therapist competence and clinical outcome for panic disorder (r = .29–.35); no relationship was found for the CTS-R.

These findings provide initial support for the reliability and validity of the CTCP for assessing therapist competence in CBT for panic disorder and support the use of anxiety disorder-specific competence measures. Further investigation into the psychometric properties of the measure in other therapist cohorts and its relationship with clinical outcomes is recommended.