To assess the prevalence of elevated risk of serious mental illness and probable ICD-11 adjustment disorder in the UK population at two time points during COVID-19, and their association with COVID-19-related stressful events.

To check the dose–response model for stress between the number of COVID-19-related stressful events and mental health indices.

We conducted two cross-sectional studies, using internet survey samples across the UK (N = 1293 for study 1; N = 1073 for study 2). Samples used internet panel surveys during March–April 2020 and 3 months later (June 2020), and used random stratified samples. Studies assessed prevalence of serious risk of mental illness and probable ICD-11 adjustment disorder.

Elevated risk of serious mental illness was found among those with COVID-19-related social life or occupationally stressful events (study 1). Elevated risk of serious mental illness and probable ICD-11 adjustment disorder was evident among those reporting COVID-19-related stressful events (personal health problems and caregiving; study 2). Cumulative COVID-19-related stressful events were associated with elevated risk of serious mental illness in study 1 (odds ratio 1.65; 95% CI 1.03–2.64; P = 0.037), and with both elevated risk of serious mental illness (odds ratio 2.19; 95% CI 1.15–4.15; P = 0.017) and probable ICD-11 adjustment disorder (odds ratio 2.45; 95% CI 1.27–4.72; P = 0.007) in study 2.

Psychiatrists should be aware that COVID-19-related stressful events can lead to serious psychological problems. Mental health professionals need to pay particular attention to patients who report cumulative COVID-19-related stressful events, and consider them for mental health assessment and treatment.

Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction.

Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction.

Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback.

All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction.

The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.

Chronic psychotic disorders (CPDs) occur worldwide and cause significant burden. Poor medication adherence is pervasive, but has not been well studied in sub-Saharan Africa.

This cross-sectional survey of 100 poorly adherent Tanzanian patients with CPD characterised clinical features associated with poor adherence.

Descriptive statistics characterised demographic and clinical variables, including barriers to adherence, adherence behaviours and attitudes, and psychiatric symptoms. Measures included the Tablets Routine Questionnaire, Drug Attitudes Inventory, the Brief Psychiatric Rating Scale, the Clinical Global Impressions scale, the Alcohol Use Disorders Identification Test and Alcohol, Smoking and Substance Involvement Screening Test. The relationship between adherence and other clinical variables was evaluated.

Mean age was 35.7 years (s.d. 8.8), 61% were male and 80% had schizophrenia, with a mean age at onset of 22.4 (s.d. 7.6) years. Mean proportion of missed CPD medication was 64%. One in ten had alcohol dependence. Most individuals had multiple adherence barriers. Most clinical variables were not significantly associated with the Tablets Routine Questionnaire; however, in-patients with CPD were more likely to have worse adherence (P ≤ 0.01), as were individuals with worse medication attitudes (Drug Attitudes Inventory, P < 0.01), higher CPD symptom severity levels (Brief Psychiatric Rating Scale, P < 0.001) and higher-risk use of alcohol (Alcohol Use Disorders Identification Test, P < 0.001).

Poorly adherent patients had multiple barriers to adherence, including poor attitudes toward medication and treatment, high illness acuity and substance use comorbidity. Treatments need to address adherence barriers, and consider family supports and challenges from an intergenerational perspective.

The coronavirus disease 2019 (COVID-19) pandemic is likely to lead to a significant increase in mental health disorders among healthcare workers (HCW).

We evaluated the rates of anxiety, depressive and post-traumatic stress disorder (PTSD) symptoms in a population of HCW in the UK.

An electronic survey was conducted between the 5 June 2020 and 31 July 2020 of all hospital HCW in the West Midlands, UK using clinically validated questionnaires: the 4-item Patient Health Questionnaire(PHQ-4) and the Impact of Event Scale-Revised (IES-R). Univariate analyses and adjusted logistic regression analyses were performed to estimate the strengths in associations between 24 independent variables and anxiety, depressive or PTSD symptoms.

There were 2638 eligible participants who completed the survey (female: 79.5%, median age: 42 years, interquartile range: 32–51). The rates of clinically significant symptoms of anxiety, depression and PTSD were 34.3%, 31.2% and 24.5%, respectively. In adjusted analysis a history of mental health conditions was associated with clinically significant symptoms of anxiety (odds ratio (OR) = 2.3, 95% CI 1.9–2.7, P < 0.001), depression (OR = 2.5, 95% CI 2.1–3.0, P < 0.001) and PTSD (OR = 2.1, 95% CI 1.7–2.5, P < 0.001). The availability of adequate personal protective equipment (PPE), well-being support and lower exposure to moral dilemmas at work demonstrated significant negative associations with these symptoms (P ≤ 0.001).

We report higher rates of clinically significant mental health symptoms among hospital HCW following the initial COVID-19 pandemic peak in the UK. Those with a history of mental health conditions were most at risk. Adequate PPE availability, access to well-being support and reduced exposure to moral dilemmas may protect hospital HCW from mental health symptoms.

No co-productive narrative synthesis of system-level facilitators and barriers to personal recovery in mental illness has been undertaken.

To clarify system-level facilitators and barriers to personal recovery of people with mental illness.

Qualitative study guided by thematic analysis. Data were collected through one focus group, which involved seven service users and three professionals. This group had 11 meetings, each lasting 2 h at a local research institute, between July 2016 to January 2018.

The analysis yielded three themes: barriers inhibiting positive interaction within personal relationship networks, roots of barriers from mental health systems and the social cultural context, and possible solutions to address the roots. Barriers were acknowledged as those related to sense of safety, locus of control within oneself and reunion with self. The roots of barriers were recognised within mental health services, including system without trauma sensitivity, lack of advocacy support and limited access to psychosocial approaches. Roots from social cultural context were also found. There were no narratives relating to facilitators. A possible solution was to address the roots from systems. Social cultural change was called for that makes personalised goals most valued, with an inclusive design that overcomes stigma, to achieve an open and accepting community.

The analysis yielded system-level barriers specific to each recovery process. Roots of barriers that need transformation to facilitate personal recovery were identified within mental health services. Social interventions should be further explored to translate the suggested social cultural changes into action.

Suicide prediction models have been formulated in a variety of ways and are heterogeneous in the strength of their predictions. Machine learning has been a proposed as a way of improving suicide predictions by incorporating more suicide risk factors.

To determine whether machine learning and the number of suicide risk factors included in suicide prediction models are associated with the strength of the resulting predictions.

Random-effect meta-analysis of exploratory suicide prediction models constructed by combining two or more suicide risk factors or using clinical judgement (Prospero Registration CRD42017059665). Studies were located by searching for papers indexed in PubMed before 15 August 2020 with the term suicid* in the title.

In total, 86 papers reported 102 suicide prediction models and included 20 210 411 people and 106 902 suicides. The pooled odds ratio was 7.7 (95% CI 6.7–8.8) with high between-study heterogeneity (I2 = 99.5). Machine learning was associated with a non-significantly higher odds ratio of 11.6 (95% CI 6.0–22.3) and clinical judgement with a non-significantly lower odds ratio of 4.7 (95% CI 2.1–10.9). Models including a larger number of suicide risk factors had a higher odds ratio when machine-learning studies were included (P = 0.02). Among non-machine-learning studies, suicide prediction models including fewer risk factors performed just as well as those including more risk factors.

Machine learning might have the potential to improve the performance of suicide prediction models by increasing the number of included suicide risk factors but its superiority over other methods is unproven.

The COVID-19 pandemic caused drastic changes in healthcare and severe social restrictions. Healthcare workers (HCWs) are on the front line against the virus and have been highly exposed to pandemic-related stressors, but there are limited data on their psychological involvement for a large sample in Italy.

To investigate the prevalence of anxiety, distress and burnout in HCWs of North-West Italy during the COVID-19 pandemic, and to detect potential psychosocial factors associated with their emotional response.

This cross-sectional, survey-based study enrolled 797 HCWs. Participants completed the Impact of Event Scale – Revised, the State-Trait Anxiety Inventory – Form Y and the Maslach Burnout Inventory; demographic, family and work characteristics were also collected. Global psychological outcome, differences among professions and independent factors associated with worst psychological outcome were assessed.

Almost a third of the sample had severe state anxiety and distress, high emotional exhaustion and depersonalisation, and low personal accomplishment. Distress was higher in women and nurses, whereas depersonalisation was higher in men. Family division, increased workload, job changes and frequent contact with COVID-19 were associated with worst psychological outcome. Trait anxiety was associated with significantly higher risk for developing state anxiety, distress and burnout.

An elevated psychological burden related to the COVID-19 pandemic was observed in HCWs of North-West Italy. The identification of family and work characteristics and a psychological pre-existing condition as factors associated with worst psychological outcome may help provide a tailored, preventive, organisational and psychological approach in counteracting the psychological effects of future pandemics.

Maternal psychopathology during pregnancy is associated with negative outcomes in offspring. Increased placental transfer of maternal cortisol may contribute to mediate this association. Hair cortisol concentrations (HCCs) appear to be a good biomarker of long-term prenatal stress exposure. Little is known about the associations between severe maternal psychopathology and perinatal infant HCCs.

We assessed HCCs in the perinatal period in mother–infant dyads with and without severe psychiatric disorders.

We examined group differences in HCCs of mother–infant dyads (n = 18) subjected to severe maternal psychiatric disorders versus healthy control dyads (n = 27). We assessed the correlation of HCCs between mother and infant within both groups, and the association between current maternal symptoms and HCCs in patient dyads.

Median (interquartile range) and distribution of HCC differed in patients compared with control mothers (U = 468.5, P = 0.03). HCCs in infants of patients did not differ from control infants (U = 250.0, P = 0.67). Subsequently, we found that HCCs within healthy control dyads were correlated (n = 27, r 0.55 (0.14), P = 0.003), but were not within patient dyads (n = 18, r 0.082 (0.13), P = 0.746). HCCs in infants of patients showed a positive correlation with maternal symptoms (n = 16, r = 0.63 (0.06), P = 0.008).

These preliminary findings suggest that infant HCC reflect perinatal stress exposure. In infants, these early differences could influence lifetime hypothalamic–pituitary–adrenal axis functioning, which might be associated with increased susceptibility to later disease.

Predicting and preventing relapse presents a crucial opportunity and first step to improve outcomes and reduce the care gap for persons living with schizophrenia. Using commercially available smartphones and smartwatches, technology now affords opportunities to capture real-time and longitudinal profiles of patients’ symptoms, cognition, physiology and social patterns. This novel data makes it possible to explore relationships between behaviours, physiology and symptoms, which may yield personalised relapse signals.

Smartphone Health Assessment for Relapse Prevention (SHARP), an international mental health research study supported by the Wellcome Trust, will inform the development of a scalable and sharable digital health solution to monitor personal risk of relapse. The resulting technology will be studied toward predicting and preventing relapse among individuals diagnosed with serious mental illness.

SHARP is a two-phase study with research sites in Boston, Massachusetts, and Bangalore and Bhopal, India. During phase 1, focus groups will be conducted at each study site to collect feedback on the design and features available on mindLAMP, a digital health platform. Individuals with serious mental illness will use mindLAMP for the duration of a year during phase 2.

The results of the research outlined in this protocol will guide the development of technology and digital tools to help address pervasive challenges in global mental health.

The digital tools developed as a result of this study, and participants’ experiences using them, may offer insight into opportunities to expand digital mental health resources and optimize their utilisation around the world.

Secure forensic mental health services treat patients with high rates of treatment-resistant psychoses. High rates of obesity and medical comorbidities are common. Population-based studies have identified high-risk groups in the event of SARS-CoV-2 infection, including those with problems such as obesity, lung disease and immune-compromising conditions. Structured assessment tools exist to ascertain the risk of adverse outcome in the event of SARS-CoV-2 infection.

To assess risk of adverse outcome in the event of SARS-CoV-2 infection in a complete population of forensic psychiatry patients using structured assessment tools.

All patients of a national forensic mental health service (n = 141) were rated for risk of adverse outcome in the event of SARS-CoV-2 infection, using two structured tools, the COVID-Age tool and the COVID-Risk tool.

We found high rates of relevant physical comorbidities. Mean chronological age was 45.5 years (s.d. = 11.4, median 44.1), mean score on the COVID-Age tool was 59.1 years (s.d. = 19.4, median 58.0), mean difference was 13.6 years (s.d. = 15.6), paired t = 10.9, d.f. = 140, P < 0.001. Three patients (2.1%) were chronologically over 70 years of age, compared with 43 (30.5%) with a COVID-Age over 70 (χ2 = 6.99, d.f. = 1, P = 0.008, Fisher's exact test P = 0.027).

Patients in secure forensic psychiatric services represent a high-risk group for adverse outcomes in the event of SARS-COV-2 infection. Population-based guidance on self-isolation and other precautions based on chronological age may not be sufficient. There is an urgent need for better physical health research and treatment in this group.

Ketamine is a new and promising treatment for depression but comes with challenges to implement because of its potential for abuse.

We sought the views of patients to inform policy and practical decisions about the clinical use of ketamine before large-scale roll-out is considered.

This qualitative study used three focus groups and three validation sessions from 14 patients with prior diagnoses of depression but no experience of ketamine treatment. Focus groups explored their views about clinical use of ketamine and the best way for ketamine to be administered and monitored. The qualitative data were analysed by three service-user researchers using thematic analysis.

Five themes were generated: changing public perceptions, risks, monitoring, privacy and data protection, and practical aspects. Participants were conscious of the stigma attached to ketamine as a street drug and wanted better public education, and evidence on the safety of ketamine after long-term use. They felt that monitoring was required to provide evidence for ketamine's safe use and administration, but there were concerns about the misuse of this information. Practical aspects included discussions about treatment duration, administration and accessibility (for example who would receive it, under what criteria and how).

Patients are enthusiastic about ketamine treatment but need more information before national roll-out. The wider societal impact of ketamine treatment also needs to be considered and patients need to be part of any future roll-out to ensure its success.

The COVID-19 pandemic has caused unprecedented stress and fear throughout the world.

To evaluate the psychological effects of the COVID-19 pandemic on the Saudi public, and to examine the performance of the Arabic version of the Four-Dimensional Symptom Questionnaire (4DSQ) scale.

We conducted an online questionnaire-based cross-sectional survey of a sample of the Saudi public.

The study included 347 participants, who reported significantly higher levels of distress, depressive symptoms, anxiety symptoms and somatisation compared with a normative sample. Females scored higher in terms of somatisation, depression and anxiety symptoms, and distress. Obtaining COVID-19 information from friends and relatives was associated with higher levels of somatisation, depression and anxiety symptoms, and distress. Cronbach's alpha was 0.93 for the distress scale, 0.88 for the depression scale, 0.88 for the anxiety scale and 0.86 for the somatisation scale.

Levels of psychological distress were high among the Saudi public during the COVID-19 pandemic. We found high reliability for the Arabic version of the 4DSQ scale. However, three items did not conform to the four-factor structure, namely, item 1: ‘During the past week, did you suffer from dizziness or feeling light-headed?’, item 20: ‘During the past week, did you suffer from disturbed sleep?’ and item 46: ‘During the past week did you ever think I wish I was dead?’.

COVID-19 was declared a pandemic in March 2020, by the World Health Organization. The pandemic has had unprecedented worldwide implications, in particular on marginalized populations.

The aim of this study is to review the impact of the pandemic on patients with schizophrenia spectrum disorders.

A number of databases were searched for this review, including PubMed, EMBASE, PsycINFO and Google Scholar. Search terms included psychosis and COVID-19, schizophrenia and COVID-19, and severe mental illness and COVID-19. We included all English language papers and preprints. The final search was done on 15 July 2020.

Forty-seven relevant studies were identified and included in this review. Studies were summarised into five main subcategories: potential impact of the COVID-19 pandemic on physical health outcomes of patients with schizophrenia spectrum disorders, impact on mental health outcomes, review of case reports and case series to date, treatment recommendation guidelines and risk of increased prevalence of psychosis.

Patients with schizophrenia spectrum disorders may be vulnerable to the effects of the COVID-19 pandemic. This patient population has a number of risk factors, including psychosocial adversities and illness related factors. Continuous monitoring and long-term studies of the impact of the pandemic on this patient population are required.

Although the negative effects of the COVID-19 pandemic on mental health have attracted interest, little attention has focused on its positive effects and possible post-traumatic growth.

To assess anxiety, well-being and post-traumatic growth in carers of children aged 6–16 years in Portugal and the UK.

A cross-sectional online survey of volunteers conducted at the peak of the first wave of COVID-19 during lockdown (1 May to 27 June 2020).

A total of 385 caregivers (Portuguese, n = 185; UK, n = 200), predominantly mothers (n = 341, 88.6%), completed the survey. The majority were working exclusively from home (n = 271, 70.4%), almost half reported a reduction in income (n = 174, 45.2%), most children were home taught (n = 358, 93%), and 75 (19.5%) identified a family member with suspected or confirmed COVID-19 infection. In total, 341 caregivers (88.6%) identified positives arising from COVID-19, most commonly related to the post-traumatic growth domains of improved relationships, a greater appreciation of life, discovering and embracing new possibilities, and positive spiritual change. A comparison of those who did (n = 341) and did not (n = 34) report any positives found a significant difference in well-being scores (t373 = 2.24, P = 0.025) but not in anxiety scores (t373 = 0.75, P = 0.45).

Despite experiencing considerable adversity, examples of post-traumatic growth during the lockdown were common. Although the voluntary online nature of our survey is a limitation, our findings suggest that further research exploring post-traumatic growth following pandemics is warranted.

The COVID-19 pandemic has seen an increase in depression and anxiety among those with and without a history of mental illness. Commonly used forms of psychological therapy improve mental health by teaching psychotherapeutic strategies that assist people to better manage their symptoms and cope with life stressors. Minimal research to date has explored their application or value in managing mental health during significant broad-scale public health crises.

To determine which psychotherapeutic strategies people who have previously received therapy use to manage their distress during the COVID-19 pandemic, and whether the use and perceived helpfulness of these strategies has an effect on symptoms of depression and anxiety.

Data (N = 857) was drawn from multiple waves of a representative longitudinal study of the effects of COVID-19 on the mental health of Australian adults, which includes measures of anxiety, depression and experiences with psychotherapy and psychotherapeutic strategies.

Previous engagement in therapy with psychotherapeutic strategies had a protective effect on depressive but not anxiety symptoms. Common and helpful strategies used by respondents were exercise, mindfulness and breathing exercises. Using mindfulness and perceiving it to be helpful was associated with lower levels of depression and anxiety symptoms. No other strategies were associated with improved mental health.

Prior knowledge of psychotherapeutic strategies may play a role in managing mental health during unprecedented public health events such as a global pandemic. There may be value in promoting these techniques more widely in the community to manage general distress during such times.

The processes and planning involved in choosing and attempting to die by a particular method of suicide are not well understood. Accounts from those who have thought about or attempted suicide using a specific method might allow us to better understand the ways in which people come to think about, plan and enact a suicide attempt.

To understand from first-person accounts the processes and planning involved in a suicide attempt on the railway.

Thematic analysis was conducted of qualitative interviews (N = 34) undertaken with individuals who had contemplated or attempted suicide by train.

Participants explained how they decided upon a particular method, time and place for a suicide attempt. Plans were described as being contingent on a number of elements (including the likelihood of being seen or interrupted), rather than being fixed in advance. Participants mentally rehearsed and evaluated a particular method, which would sometimes involve imagining in detail what would happen before, during and after an attempt. The extent to which this involved others (train drivers, partners, friends) was striking.

By giving people free reign to describe in their own words the processes they went through in planning and undertaking a suicide attempt, and by not interpreting such accounts through a lens of deficit and pathology, we can arrive at important insights into how people come to think and feel about, plan and enact a suicide attempt. The findings have implications in terms of understanding suicide risk and prevention more broadly.