Social media platforms have long been recognised as major disseminators of health misinformation. Many previous studies have found a negative association between health-protective behaviours and belief in the specific form of misinformation popularly known as ‘conspiracy theory’. Concerns have arisen regarding the spread of COVID-19 conspiracy theories on social media.

Three questionnaire surveys of social media use, conspiracy beliefs and health-protective behaviours with regard to COVID-19 among UK residents were carried out online, one using a self-selecting sample (N = 949) and two using stratified random samples from a recruited panel (N = 2250, N = 2254).

All three studies found a negative relationship between COVID-19 conspiracy beliefs and COVID-19 health-protective behaviours, and a positive relationship between COVID-19 conspiracy beliefs and use of social media as a source of information about COVID-19. Studies 2 and 3 also found a negative relationship between COVID-19 health-protective behaviours and use of social media as a source of information, and Study 3 found a positive relationship between health-protective behaviours and use of broadcast media as a source of information.

When used as an information source, unregulated social media may present a health risk that is partly but not wholly reducible to their role as disseminators of health-related conspiracy beliefs.

Psychotic symptoms occur more frequently in the general population than psychotic disorder and index risk for psychopathology. Multiple studies have reported on the prevalence of these symptoms using self-report questionnaires or clinical interviews but there is a lack of consensus about the prevalence of psychotic symptoms among children and adolescents.

We conducted a systematic review of all published literature on psychotic symptom prevalence in two age groups, children aged 9–12 years and adolescents aged 13–18 years, searching through electronic databases PubMed, Ovid Medline, PsycINFO and EMBASE up to June 2011, and extracted prevalence rates.

We identified 19 population studies that reported on psychotic symptom prevalence among children and adolescents. The median prevalence of psychotic symptoms was 17% among children aged 9–12 years and 7.5% among adolescents aged 13–18 years.

Psychotic symptoms are relatively common in young people, especially in childhood. Prevalence is higher in younger (9–12 years) compared to older (13–18 years) children.

Recent open-label trials show that psychedelics, such as ayahuasca, hold promise as fast-onset antidepressants in treatment-resistant depression.

To test the antidepressant effects of ayahuasca, we conducted a parallel-arm, double-blind randomized placebo-controlled trial in 29 patients with treatment-resistant depression. Patients received a single dose of either ayahuasca or placebo. We assessed changes in depression severity with the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Hamilton Depression Rating scale at baseline, and at 1 (D1), 2 (D2), and 7 (D7) days after dosing.

We observed significant antidepressant effects of ayahuasca when compared with placebo at all-time points. MADRS scores were significantly lower in the ayahuasca group compared with placebo at D1 and D2 (p = 0.04), and at D7 (p < 0.0001). Between-group effect sizes increased from D1 to D7 (D1: Cohen's d = 0.84; D2: Cohen's d = 0.84; D7: Cohen's d = 1.49). Response rates were high for both groups at D1 and D2, and significantly higher in the ayahuasca group at D7 (64% v. 27%; p = 0.04). Remission rate showed a trend toward significance at D7 (36% v. 7%, p = 0.054).

To our knowledge, this is the first controlled trial to test a psychedelic substance in treatment-resistant depression. Overall, this study brings new evidence supporting the safety and therapeutic value of ayahuasca, dosed within an appropriate setting, to help treat depression. This study is registered at http://clinicaltrials.gov (NCT02914769).

Mindfulness meditation (MM) practices constitute an important group of meditative practices that have received growing attention. The aim of the present paper was to systematically review current evidence on the neurobiological changes and clinical benefits related to MM practice in psychiatric disorders, in physical illnesses and in healthy subjects.

A literature search was undertaken using Medline, ISI Web of Knowledge, the Cochrane collaboration database and references of retrieved articles. Controlled and cross-sectional studies with controls published in English up to November 2008 were included.

Electroencephalographic (EEG) studies have revealed a significant increase in alpha and theta activity during meditation. Neuroimaging studies showed that MM practice activates the prefrontal cortex (PFC) and the anterior cingulate cortex (ACC) and that long-term meditation practice is associated with an enhancement of cerebral areas related to attention. From a clinical viewpoint, Mindfulness-Based Stress Reduction (MBSR) has shown efficacy for many psychiatric and physical conditions and also for healthy subjects, Mindfulness-Based Cognitive Therapy (MBCT) is mainly efficacious in reducing relapses of depression in patients with three or more episodes, Zen meditation significantly reduces blood pressure and Vipassana meditation shows efficacy in reducing alcohol and substance abuse in prisoners. However, given the low-quality designs of current studies it is difficult to establish whether clinical outcomes are due to specific or non-specific effects of MM.

Despite encouraging findings, several limitations affect current studies. Suggestions are given for future research based on better designed methodology and for future directions of investigation.

A lack of longitudinal studies has made it difficult to establish the direction of associations between circulating concentrations of low-grade chronic inflammatory markers, such as C-reactive protein and interleukin-6, and cognitive symptoms of depression. The present study sought to assess whether C-reactive protein and interleukin-6 predict cognitive symptoms of depression or whether these symptoms predict inflammatory markers.

In a prospective occupational cohort study of British white-collar civil servants (the Whitehall II study), serum C-reactive protein, interleukin-6 and cognitive symptoms of depression were measured at baseline in 1991–1993 and at follow-up in 2002–2004, an average follow-up of 11.8 years. Symptoms of depression were measured with four items describing cognitive symptoms of depression from the General Health Questionnaire. The number of participants varied between 3339 and 3070 (mean age 50 years, 30% women) depending on the analysis.

Baseline C-reactive protein (β=0.046, p=0.004) and interleukin-6 (β=0.046, p=0.005) predicted cognitive symptoms of depression at follow-up, while baseline symptoms of depression did not predict inflammatory markers at follow-up. After full adjustment for sociodemographic, behavioural and biological risk factors, health conditions, medication use and baseline cognitive systems of depression, baseline C-reactive protein (β=0.038, p=0.036) and interleukin-6 (β=0.041, p=0.018) remained predictive of cognitive symptoms of depression at follow-up.

These findings suggest that inflammation precedes depression at least with regard to the cognitive symptoms of depression.

Non-suicidal self-injury (NSSI) has received increased attention in the mental health literature and has been proposed as a diagnostic entity for DSM-5. However, data on NSSI in the United States adult population are lacking.

The prevalence and nature of NSSI were examined in a random-digit dialing sample of 439 adults in the United States. Participants were recruited during July and August of 2008.

Lifetime prevalence of NSSI was 5.9%, including 2.7% who had self-injured five or more times. The 12-month prevalence was 0.9%. Methods of NSSI reported included cutting/carving, burning, biting, scraping/scratching skin, hitting, interfering with wound healing and skin picking. Half of self-injurers reported multiple methods. The average age of onset was 16 years (median 14 years). Instances of NSSI infrequently co-occurred with suicidal thoughts and with use of alcohol or drugs and rarely required medical treatment. Most injurers reported that NSSI functioned to alleviate negative emotions. Fewer reported that they self-injured to punish themselves, to communicate with others/get attention or to escape a situation or responsibility. NSSI was associated with younger age, being unmarried and a history of mental health treatment, but not with gender, ethnicity, educational history or household income.

Results are largely consistent with previous research in adolescent and young adult samples. Study limitations notwithstanding, this study provides the most definitive and detailed information to date regarding the prevalence and characteristics of NSSI in US adults. In the future, it will be important for large-scale epidemiological studies of psychopathology to include questions about NSSI.

Literature supports a strong relationship between childhood maltreatment and mental illness but most studies reviewed are cross-sectional and/or use recall to assess maltreatment and are thus prone to temporality and recall bias. Research on the potential prospective impact of maltreatment reduction on the incidence of psychiatric disorders is scarce.

Electronic databases and grey literature from 1990 to 2014 were searched for English-language cohort studies with criteria for depression and/or anxiety and non-recall measurement of childhood maltreatment. Systematic review with meta-analysis synthesized the results. Study quality, heterogeneity, and publication bias were examined. Initial screening of titles and abstracts resulted in 199 papers being reviewed. Eight high-quality articles met eligibility criteria. Population attributable fractions (PAFs) estimated potential preventive impact.

The pooled odds ratio (OR) between any type of maltreatment and depression was 2.03 [95% confidence interval (CI) 1.37–3.01] and 2.70 (95% CI 2.10–3.47) for anxiety. For specific types of maltreatment and depression or anxiety disorders, the ORs were: physical abuse (OR 2.00, 95% CI 1.25–3.19), sexual abuse (OR 2.66, 95% CI 1.88–3.75), and neglect (OR 1.74, 95% CI 1.35–2.23). PAFs suggest that over one-half of global depression and anxiety cases are potentially attributable to self-reported childhood maltreatment. A 10–25% reduction in maltreatment could potentially prevent 31.4–80.3 million depression and anxiety cases worldwide.

This review provides robust evidence of childhood maltreatment increasing the risk for depression and anxiety, and reinforces the need for effective programs and policies to reduce its occurrence.

This paper aims to synthesise the literature on machine learning (ML) and big data applications for mental health, highlighting current research and applications in practice.

We employed a scoping review methodology to rapidly map the field of ML in mental health. Eight health and information technology research databases were searched for papers covering this domain. Articles were assessed by two reviewers, and data were extracted on the article's mental health application, ML technique, data type, and study results. Articles were then synthesised via narrative review.

Three hundred papers focusing on the application of ML to mental health were identified. Four main application domains emerged in the literature, including: (i) detection and diagnosis; (ii) prognosis, treatment and support; (iii) public health, and; (iv) research and clinical administration. The most common mental health conditions addressed included depression, schizophrenia, and Alzheimer's disease. ML techniques used included support vector machines, decision trees, neural networks, latent Dirichlet allocation, and clustering.

Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. With the majority of studies identified focusing on the detection and diagnosis of mental health conditions, it is evident that there is significant room for the application of ML to other areas of psychology and mental health. The challenges of using ML techniques are discussed, as well as opportunities to improve and advance the field.

The coronavirus disease 2019 (COVID-19) pandemic and associated lockdown could be considered a ‘perfect storm’ for increases in emotional distress. Such increases can only be identified by studies that use data collected before and during the pandemic. Longitudinal data are also needed to examine (1) the roles of previous distress and stressors in emotional distress during the pandemic and (2) how COVID-19-related stressors and coping strategies are associated with emotional distress when pre-pandemic distress is accounted for.

Data came from a cohort study (N = 768). Emotional distress (perceived stress, internalizing symptoms, and anger), COVID-19-related stressors, and coping strategies were measured during the pandemic/lockdown when participants were aged 22. Previous distress and stressors were measured before COVID-19 (at age 20).

On average, participants showed increased levels of perceived stress and anger (but not internalizing symptoms) during the pandemic compared to before. Pre-COVID-19 emotional distress was the strongest predictor of during-pandemic emotional distress, followed by during-pandemic economic and psychosocial stressors (e.g. lifestyle and economic disruptions) and hopelessness, and pre-pandemic social stressors (e.g. bullying victimization and stressful life events). Most health risks to self or loved ones due to COVID-19 were not uniquely associated with emotional distress in final models. Coping strategies associated with reduced distress included keeping a daily routine, physical activity, and positive reappraisal/reframing.

In our community sample, pre-pandemic distress, secondary consequences of the pandemic (e.g. lifestyle and economic disruptions), and pre-pandemic social stressors were more consistently associated with young adults' emotional distress than COVID-19-related health risk exposures.