Many people suffering from psychotic disorders report persistent auditory verbal hallucinations (‘voices’) despite pharmacological and psychological therapy. Interest is growing in approaches that emphasise the personal relationship between the patient and their voice(s). AVATAR therapy is one such approach that uses a digital representation (avatar) of a selected voice to facilitate a three-way discussion between patient, therapist and voice, the therapist speaking either as him/herself or in the digitally transformed voice of the avatar. Objectives: To describe AVATAR therapy and an ongoing multi-centre clinical trial. Methods: Encouraging findings from an earlier controlled trial (AVATAR1) comparing AVATAR therapy and supportive counselling informed our current multi-site cost-effectiveness trial of brief and extended versions of the therapy compared to treatment as usual (AVATAR2). Results: AVATAR1 delivered in 7 weekly sessions resulted in a reduction in the frequency, distress and power of voices that was significantly superior to supportive counselling. Clinical experience suggested that some participants improved in response to the early focus on anxiety while others seemed more responsive to later more formulation-driven approach. These findings led us to the current ongoing three arm clinical trial comprising a brief (6 session) focus on anxiety/assertiveness, an extended (12 session) formulation-driven approach both approaches compared to treatment as usual. Conclusion: Previous AVATAR studies suggest this is a therapy with considerable promise. It can be delivered through widely available laptop computers, usually in clinic but also remotely via existing commercial platforms. The current trial will address questions about dissemination, training and cost-effectiveness in NHS settings.

The digital technology employed in AVATAR therapy is provided by licence for the trial from Avatar Therapy Ltd

The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors.

Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change.

Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status.

We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

People displaying persistent, full-blown psychotic experiences without a need-for-care in the general population are an ideal group to investigate to differentiate those factors that are linked to distress and dysfunction from those that are merely associated with benign anomalous experiences. The UNIQUE study investigated the cognitive and social processes predicted by cognitive models of psychosis to differentiate between benign and pathological outcomes of psychotic experiences (PEs).

Two hundred and fifty-nine individuals were recruited (84 clinical participants with PEs; 92 non-clinical participants with PEs; 83 controls without PEs) from urban (South-East London) and rural (North Wales) UK sites. The three groups were compared on clinical and psychological measures, on reasoning tasks, and on their appraisals of experimental tasks inducing anomalous experiences (of thought interference symptoms and auditory hallucinations).

The clinical picture demonstrated a distinctive pattern of similarities and differences on PEs between the clinical and non-clinical groups, while their demographic and psychological profiles were markedly different. As predicted, the clinical group showed a ‘jump-to-conclusions’ reasoning style, and endorsed more threatening appraisals ratings of the experimentally-induced anomalous experiences than the non-clinical group, who did not differ from the controls.

The results of this study identified a number of specific factors that may be protective against transition to psychosis in individuals with persistent PEs. They also provide robust experimental evidence for the key role of appraisals in determining outcome, as postulated by cognitive models of psychosis.

Medical research Council, UK.

The authors have not supplied their declaration of competing interest.

Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.

To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.

Clinical isolates of Staphylococcus aureus, Enterococcus faecium, Pseudomonas aeruginosa, and Klebsiella pneumoniae were obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.

Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.

Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.

To characterize meal patterns across ten European countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study.

Cross-sectional study utilizing dietary data collected through a standardized 24 h diet recall during 1995–2000. Eleven predefined intake occasions across a 24 h period were assessed during the interview. In the present descriptive report, meal patterns were analysed in terms of daily number of intake occasions, the proportion reporting each intake occasion and the energy contributions from each intake occasion.

Twenty-seven centres across ten European countries.

Women (64 %) and men (36 %) aged 35–74 years (n 36 020).

Pronounced differences in meal patterns emerged both across centres within the same country and across different countries, with a trend for fewer intake occasions per day in Mediterranean countries compared with central and northern Europe. Differences were also found for daily energy intake provided by lunch, with 38–43 % for women and 41–45 % for men within Mediterranean countries compared with 16–27 % for women and 20–26 % for men in central and northern European countries. Likewise, a south–north gradient was found for daily energy intake from snacks, with 13–20 % (women) and 10–17 % (men) in Mediterranean countries compared with 24–34 % (women) and 23–35 % (men) in central/northern Europe.

We found distinct differences in meal patterns with marked diversity for intake frequency and lunch and snack consumption between Mediterranean and central/northern European countries. Monitoring of meal patterns across various cultures and populations could provide critical context to the research efforts to characterize relationships between dietary intake and health.