Understand perceptions of COVID-19 messages and information sources among rural wastewater treatment plant operators to inform context-specific communication strategies for implementing wastewater surveillance methodologies locally.

Eight employees from 7 Eastern Kentucky facilities involved in SARS-CoV-2 wastewater surveillance participated in semi-structured interviews. Respondents shared perceptions of traditional and social media COVID-19 information channels in their communities, as well as factors influencing trustworthiness of sources. Using the U.S. Centers for Disease Control and Prevention’s Crisis and Emergency Risk Communication (CERC) framework, 3 investigators conducted iterative, thematic coding of interview transcripts.

Respondents’ statements most frequently related to “Be Credible,” “Be Right,” and “Promote Action” CERC constructs, while mixed messages, high volumes of information, and numerous sources undermined trust in COVID-19 information.

Understanding the relative importance of CERC constructs and their distractors may improve future risk communication to advance infectious disease surveillance strategies in rural contexts.

Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Epidemiological data offer conflicting views of the natural course of binge-eating disorder (BED), with large retrospective studies suggesting a protracted course and small prospective studies suggesting a briefer duration. We thus examined changes in BED diagnostic status in a prospective, community-based study that was larger and more representative with respect to sex, age of onset, and body mass index (BMI) than prior multi-year prospective studies.

Probands and relatives with current DSM-IV BED (n = 156) from a family study of BED (‘baseline’) were selected for follow-up at 2.5 and 5 years. Probands were required to have BMI > 25 (women) or >27 (men). Diagnostic interviews and questionnaires were administered at all timepoints.

Of participants with follow-up data (n = 137), 78.1% were female, and 11.7% and 88.3% reported identifying as Black and White, respectively. At baseline, their mean age was 47.2 years, and mean BMI was 36.1. At 2.5 (and 5) years, 61.3% (45.7%), 23.4% (32.6%), and 15.3% (21.7%) of assessed participants exhibited full, sub-threshold, and no BED, respectively. No participants displayed anorexia or bulimia nervosa at follow-up timepoints. Median time to remission (i.e. no BED) exceeded 60 months, and median time to relapse (i.e. sub-threshold or full BED) after remission was 30 months. Two classes of machine learning methods did not consistently outperform random guessing at predicting time to remission from baseline demographic and clinical variables.

Among community-based adults with higher BMI, BED improves with time, but full remission often takes many years, and relapse is common.

To evaluate the impact of implementing clinical decision support (CDS) tools for outpatient antibiotic prescribing in the emergency department (ED) and clinic settings.

We performed a before-and-after, quasi-experimental study that employed an interrupted time-series analysis.

The study institution was a quaternary, academic referral center in Northern California.

We included prescriptions for patients in the ED and 21 primary-care clinics within the same health system.

We implemented a CDS tool for azithromycin on March 1, 2020, and a CDS tool for fluoroquinolones (FQs; ie, ciprofloxacin, levofloxacin, and moxifloxacin) on November 1, 2020. The CDS added friction to inappropriate ordering workflows while adding health information technology (HIT) features to easily perform recommended actions. The primary outcome was the number of monthly prescriptions for each antibiotic type, by implementation period (before vs after).

Immediately after azithromycin-CDS implementation, monthly rates of azithromycin prescribing decreased significantly in both the ED (−24%; 95% CI, −37% to −10%; P < .001) and outpatient clinics (−47%; 95% CI, −56% to −37%; P < .001). In the first month after FQ-CDS implementation in the clinics, there was no significant drop in ciprofloxacin prescriptions; however, there was a significant decrease in ciprofloxacin prescriptions over time (−5% per month; 95% CI, −6% to −3%; P < .001), suggesting a delayed effect of the CDS.

Implementing CDS tools was associated with an immediate decrease in azithromycin prescriptions, in both the ED and clinics. CDS may serve as a valuable adjunct to existing antimicrobial stewardship programs.

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.

Cannabis use has been associated with increased risk of psychiatric disorders. However, associations between adolescent cannabis use, depression and anxiety disorders are inconsistently reported in longitudinal samples.

To study associations of adolescent cannabis use with depression and anxiety disorders.

We used data from the Northern Finland Birth Cohort 1986, linked to nationwide registers, to study the association between adolescent cannabis use and depression and anxiety disorders until 33 years of age (until 2018).

We included 6325 participants (48.8% male) in the analyses; 352 (5.6%) participants reported cannabis use until 15–16 years of age. By the end of the follow-up, 583 (9.2%) participants were diagnosed with unipolar depression and 688 (10.9%) were diagnosed with anxiety disorder. Cannabis use in adolescence was associated with an increased risk of depression and anxiety disorders in crude models. After adjusting for parental psychiatric disorder, baseline emotional and behavioural problems, demographic factors and other substance use, using cannabis five or more times was associated with increased risk of anxiety disorders (hazard ratio 2.01, 95% CI 1.15–3.82), and using cannabis once (hazard ratio 1.93, 95% CI 1.30–2.87) or two to four times (hazard ratio 2.02, 95% CI 1.24–3.31) was associated with increased risk of depression.

Cannabis use in adolescence was associated with an increased risk of future depression and anxiety disorders. Further research is needed to clarify if this is a causal association, which could then inform public health messages about the use of cannabis in adolescence.

There is now a strong body of literature showing that bullying victimisation during childhood and adolescence precedes the later development of anxiety and depressive disorders. This study aimed to quantify the burden of anxiety and depressive disorders attributable to experiences of bullying victimisation for the Australian population.

This study updated a previous systematic review summarising the longitudinal association between bullying victimisation and anxiety and depressive disorders. Estimates from eligible studies published from inception until 18 August 2018 were included and meta-analyses were based on quality-effects models. Pooled relative risks were combined with a contemporary prevalence estimate for bullying victimisation for Australia in order to calculate population attributable fractions (PAFs) for the two mental disorder outcomes. PAFs were then applied to estimates of the burden of anxiety and depressive disorders in Australia expressed as disability-adjusted life years (DALYs).

The findings from this study suggest 7.8% of the burden of anxiety disorders and 10.8% of the burden of depressive disorders are attributable to bullying victimisation in Australia. An estimated 30 656 DALYs or 0.52% (95% uncertainty interval 0.33–0.72%) of all DALYs in both sexes and all ages in Australia were attributable to experiences of bullying victimisation in childhood or adolescence.

There is convincing evidence to demonstrate a causal relationship between bullying victimisation and mental disorders. This study showed that bullying victimisation contributes a significant proportion of the burden of anxiety and depressive disorders. The investment and implementation of evidence-based intervention programmes that reduce bullying victimisation in schools could reduce the burden of disease arising from common mental disorders and improve the health of Australians.

Antineuronal antibodies are associated with psychosis, although their clinical significance in first episode of psychosis (FEP) is undetermined.

To examine all patients admitted for treatment of FEP for antineuronal antibodies and describe clinical presentations and treatment outcomes in those who were antibody positive.

Individuals admitted for FEP to six mental health units in Queensland, Australia, were prospectively tested for serum antineuronal antibodies. Antibody-positive patients were referred for neurological and immunological assessment and therapy.

Of 113 consenting participants, six had antineuronal antibodies (anti-N-methyl-D-aspartate receptor antibodies [n = 4], voltage-gated potassium channel antibodies [n = 1] and antibodies against uncharacterised antigen [n = 1]). Five received immunotherapy, which prompted resolution of psychosis in four.

A small subgroup of patients admitted to hospital with FEP have antineuronal antibodies detectable in serum and are responsive to immunotherapy. Early diagnosis and treatment is critical to optimise recovery.

None.