Meta-analyses of functional magnetic resonance imaging (fMRI) studies have been used to elucidate the most reliable neural features associated with various psychiatric disorders. However, it has not been well-established whether each of these neural features is linked to a specific disorder or is transdiagnostic across multiple disorders and disorder categories, including mood, anxiety, and anxiety-related disorders.

This project aims to advance our understanding of the disorder-specific and transdiagnostic neural features associated with mood, anxiety, and anxiety-related disorders as well as to refine the methodology used to compare multiple disorders.

We conducted an exhaustive PubMed literature search followed by double-screening, double-extraction, and cross-checking to identify all whole-brain, case-control fMRI activation studies of mood, anxiety, and anxiety-related disorders in order to construct a large-scale meta-analytic database of primary studies of these disorders. We then employed multilevel kernel density analysis (MKDA) with Monte-Carlo simulations to correct for multiple comparisons as well as ensemble thresholding to reduce cluster size bias to analyze primary fMRI studies of mood, anxiety, and anxiety-related disorders followed by application of triple subtraction techniques and a second-order analysis to elucidate the disorder-specificity of the previously identified neural features.

We found that participants diagnosed with mood, anxiety, and anxiety-related disorders exhibited statistically significant (p < .05 – 0.0001; FWE-corrected) differences in neural activation relative to healthy controls throughout the cerebral cortex, limbic system, and basal ganglia. In addition, each of these psychiatric disorders exhibited a particular profile of neural features that ranged from disorder-specific, to category-specific, to transdiagnostic.

These findings indicate that psychiatric disorders exhibit a complex profile of neural features that vary in their disorder-specificity and can be detected with large-scale fMRI meta-analytic techniques. This approach has potential to fundamentally transform neuroimaging investigations of clinical disorders by providing a novel procedure for establishing disorder-specificity of observed results, which can be then used to advance our understanding of individual disorders as well as broader nosological issues related to diagnosis and classification of psychiatric disorders.

None Declared

Generalized anxiety disorder (GAD) is a highly prevalent mental illness that is associated with clinically significant distress, functional impairment, and poor emotional regulation. Primary functional magnetic resonance imaging (fMRI) studies of GAD report neural abnormalities in comparison to healthy controls. However, many of these findings in the primary literature are inconsistent, and it is unclear whether they are specific to GAD or shared transdiagnostically across related disorders.

This meta-analysis seeks to establish the most reliable neural abnormalities observed in individuals with GAD, as reported in the primary fMRI activation literature.

We conducted an exhaustive literature search in PubMed to identify primary studies that met our pre-specified inclusion criteria and then extracted relevant data from primary, whole-brain fMRI activation studies of GAD that reported coordinates in Talairach or MNI space. We then used multilevel kernel density analysis (MKDA) with ensemble thresholding to examine the differences between adults with GAD and healthy controls in order to identify brain regions that reached statistical significance across primary studies.

Patients with GAD showed statistically significant (α=0.05–0.0001; family-wise-error-rate corrected) neural activation in various regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.

These results inform our understanding of the neural basis of GAD and are interpreted using a frontolimbic model of anxiety as well as specific clinical symptoms of this disorder and its relation to other mood and anxiety disorders. These results also suggest possible novel targets for emerging neurostimulation therapies (e.g., transcranial magnetic stimulation) and may be used to advance our understanding of the effects of current pharmaceutical treatments and ways to improve treatment selection and symptom-targeting for patients diagnosed with GAD.

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Functional magnetic resonance imaging (fMRI) has been used to identify the neural activity of both youth and adults diagnosed with major depressive disorder (MDD) in comparison to healthy age-matched controls. Previously reported abnormalities in depressed youth appear to mostly align with those found in depressed adults; however, some of the reported aberrant brain activity in youth has not been consistent with what is observed in adults, and to our knowledge there has not yet been a formal, quantitative comparison of these two groups. In addition, it is not known whether these observed differences between youth and adults with depression are attributable to developmental age or length-of-illness.

The aim of this study is to elucidate the similarities and differences in patterns of abnormal neural activity between adults and youth diagnosed with MDD and to then determine whether these observed differences are due to either developmental age or length-of-illness.

We used multilevel kernel density analysis (MKDA) with ensemble thresholding and triple subtraction to separately determine neural abnormalities throughout the whole brain in primary studies of depressed youth and depressed adults and then directly compare the observed abnormalities between each of those age groups. We then conducted further comparisons between multiple subgroups to control for age and length-of-illness and thereby determine the source of the observed differences between youth and adults with depression.

Adults and youth diagnosed with MDD demonstrated reliable, differential patterns of abnormal activation in various brain regions throughout the cerebral cortex that are statistically significant (p < .05; FWE-corrected). In addition, several of these brain regions that exhibited differential patterns of neural activation between the two age groups can be reliably attributed to either developmental age or length-of-illness.

These findings indicate that there are common and disparate patterns of brain activity between youth and adults with MDD, several of which can be reliably attributed to developmental age or length-of-illness. These results expand our understanding of the neural basis of depression across development and course of illness and may be used to inform the development of new, age-specific clinical treatments as well as prevention strategies for this disorder.

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Major depressive disorder (MDD) is a highly prevalent mental illness that frequently originates in early development and is pervasive during adolescence. Despite its high prevalence and early age of onset, our understanding of the potentially unique neural basis of MDD in this age group is still not well understood, and the existing primary literature on the topic includes many new and divergent results. This limited understanding of MDD in youth presents a critical need to further investigate its neural basis in youth and presents an opportunity to also improve clinical treatments that target its neural abnormalities.

The present study aims to advance our understanding of the neural basis of MDD in youth by identifying abnormal functional activation in various brain regions compared with healthy controls.

We conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies of MDD by using a well-established method, multilevel kernel density analysis (MKDA) with ensemble thresholding, to quantitatively combine all existing whole-brain fMRI studies of MDD in youth compared with healthy controls. This method involves a voxel-wise, whole-brain approach, that compares neural activation of patients with MDD to age-matched healthy controls across variations of task-based conditions, which we subcategorize into affective processing, executive functioning, positive valence, negative valence, and symptom provocation tasks.

Youth with MDD exhibited statistically significant (p<0.05; FWE-corrected) hyperactivation and hypoactivation in multiple brain regions compared with age-matched healthy controls. These results include significant effects that are stable across various tasks as well as some that appear to depend on task conditions.

This study strengthens our understanding of the neural basis of MDD in youth and may also be used to help identify possible similarities and differences between youth and adults with depression. It may also help inform the development of new treatment interventions and tools for predicting unique treatment responses in youth with depression.

None Declared

Curiosity toward the effects of psychedelic drugs on neural activation has increased due to their potential therapeutic benefits, particularly serotonergic psychedelics that act as 5-HT2A receptor agonists such as LSD, psilocybin, and MDMA. However, the pattern of their effects on neural activity in various brain regions in both clinical and healthy populations is still not well understood, and primary studies addressing this issue have sometimes generated inconsistent results.

The present meta-analysis aims to advance our understanding of the most widely used serotonergic psychedelics – LSD, psilocybin, and MDMA – by examining their effects on the functional activation throughout the whole brain among both clinical and healthy participants.

We conducted this meta-analysis by applying multilevel kernel density analysis (MKDA) with ensemble thresholding to quantitatively combine existing functional magnetic resonance imaging (fMRI) studies that examined whole-brain functional activation of clinical or healthy participants who were administered a serotonergic psychedelic.

Serotonergic psychedelics, including LSD, psilocybin, and MDMA, exhibited significant effects (α=0.05) on neural activation in several regions throughout the cerebral cortex and basal ganglia, including effects that may be common across and unique within each drug.

These observed effects of serotonergic psychedelics on neural activity advance our understanding of the functional neuroanatomy associated with their administration and may inform future studies of both their adverse and therapeutic effects, including emerging clinical applications for the treatment of several psychiatric disorders.

None Declared

Major depressive disorder (MDD) is a highly prevalent mental illness that often first occurs or persists into adulthood and is considered the leading cause of disability and disease burden worldwide. Unfortunately, individuals diagnosed with MDD who seek treatment often experience limited symptom relief and may not achieve long-term remission, which is due in part to our limited understanding of its underlying pathophysiology. Many studies that use task-based functional magnetic resonance imaging (fMRI) have found abnormal activation in brain regions in adults diagnosed with MDD, but those findings are often inconsistent; in addition, previous meta-analyses that quantitatively integrate this large body literature have found conflicting results.

This meta-analysis aims to advance our understanding of the neural basis of MDD in adults, as measured by fMRI activation studies, and address inconsistencies and discrepancies in the empirical literature.

We employed multilevel kernel density analysis (MKDA) with ensemble thresholding, a well-established method for voxel-wise, whole-brain meta-analyses, to conduct a quantitative comparison of all relevant primary fMRI activation studies of adult patients with MDD compared to age-matched healthy controls.

We found that adults with MDD exhibited a reliable pattern of statistically significant (p<0.05; FWE-corrected) hyperactivation and hypoactivation in several brain regions compared to age-matched healthy controls across a variety of experimental tasks.

This study supports previous findings that there is reliable neural basis of MDD that can be detected across heterogenous fMRI studies. These results can be used to inform development of promising treatments for MDD, including protocols for personalized interventions. They also provide the opportunity for additional studies to examine the specificity of these effects among various populations-of-interest, including youth vs. adults with depression as well as other related mood and anxiety disorders.

None Declared

Public responses to a future novel disease might be influenced by a subset of individuals who are either sensitized or desensitized to concern-generating processes through their lived experiences during the coronavirus disease 2019 (COVID-19) pandemic. Such influences may be critical for shaping public health messaging during the next emerging threat.

This study explored the potential outcomes of the influence of lived experiences by using a dynamic multiplex network model to simulate a COVID-19 outbreak in a population of 2000 individuals, connected by means of disease and communication layers. Then a new disease was introduced, and a subset of individuals (50% or 100% of hospitalized during the COVID-19 outbreak) was assumed to be either sensitized or desensitized to concern-generating processes relative to the general population, which alters their adoption of non-pharmaceutical interventions (social distancing).

Altered perceptions and behaviors from lived experiences with COVID-19 did not necessarily result in a strong mitigating effect for the novel outbreak. When public disease response is already strong or sensitization is assumed to be a robust effect, then a sensitized subset may enhance public mitigation of an outbreak through social distancing.

In preparing for future outbreaks, assuming an experienced and disease-aware public may compromise effective design of effective public health messaging and mitigative action.

There is emerging evidence of heterogeneity within treatment-resistance schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and a smaller group becoming treatment-resistant after an initial response period. It has been suggested that these groups have different aetiologies. Few studies have investigated socio-demographic and clinical differences between early and late onset of TRS.

This study aims to investigate socio-demographic and clinical correlates of late-onset of TRS.

Using data from the electronic health records of the South London and Maudsley, we identified a cohort of people with TRS. Regression analyses were conducted to identify correlates of the length of treatment to TRS. Analysed predictors include gender, age, ethnicity, positive symptoms severity, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics.

We observed a continuum of the length of treatment until TRS presentation. Having severe hallucinations and delusions at treatment start was associated shorter duration of treatment until the presentation of TRS.

Our findings do not support a clear cut categorisation between early and late TRS, based on length of treatment until treatment resistance onset. More severe positive symptoms predict earlier onset of treatment resistance.

DFdF, GKS, EF and IR have received research funding from Janssen and H. Lundbeck A/S. RDH and HS have received research funding from Roche, Pfizer, Janssen and Lundbeck. SES is employed on a grant held by Cardiff University from Takeda Pharmaceutical Comp

Ethnic disparities in treatment with clozapine, the antipsychotic recommended for treatment-resistant schizophrenia (TRS), have been reported. However, these investigations frequently suffer from potential residual confounding. For example, few studies have restricted the analyses to TRS samples and none has controlled for benign ethnic neutropenia.

This study investigated if service-users’ ethnicity influenced clozapine prescription in a cohort of people with TRS.

Information from the clinical records of South London and Maudsley NHS Trust was used to identify a cohort of service-users with TRS between 2007 and 2017. In this cohort, we used logistic regression to investigate any association between ethnicity and clozapine prescription while adjusting for potential confounding variables, including sociodemographic factors, psychiatric multimorbidity, substance use, benign ethnic neutropenia, and inpatient and outpatient care received.

We identified 2239 cases that met the criteria for TRS. Results show that after adjusting for confounding variables, people with Black African ethnicity had half the odds of being treated with clozapine and people with Black Caribbean or Other Black background had about two-thirds the odds of being treated with clozapine compared White British service-users. No disparities were observed regarding other ethnic groups, namely Other White background, South Asian, Other Asian, or any other ethnicity.

There was evidence of inequities in care among Black ethnic groups with TRS. Interventions targeting barriers in access to healthcare are recommended.

During the conduction of the study, DFdF, GKS, and RH received funds from the NIHR Maudsley Biomedical Research Centre. For other activities outside the submitted work, DFdF received research funding from the UK Department of Health and Social Care, Janss

Research shows persistent ethnic inequities in mental health experiences and outcomes, with a higher incidence of illnesses among minoritised ethnic groups. People with psychosis have an increased risk of multiple long-term conditions (MLTC; multimorbidity). However, there is limited research regarding ethnic inequities in multimorbidity in people with psychosis. This study investigates ethnic inequities in physical health multimorbidity in a cohort of people with psychosis.

In this retrospective cohort study, using the Clinical Records Interactive Search (CRIS) system, we identified service-users of the South London and Maudsley NHS Trust with a schizophrenia spectrum disorder, and then additional diagnoses of diabetes, hypertension, low blood pressure, overweight or obesity and rheumatoid arthritis. Logistic and multinomial logistic regressions were used to investigate ethnic inequities in odds of multimorbidity (psychosis plus one physical health condition), and multimorbidity severity (having one or two physical health conditions, or three or more conditions), compared with no additional health conditions (no multimorbidity), respectively. The regression models adjusted for age and duration of care and investigated the influence of gender and area-level deprivation.

On a sample of 20 800 service-users with psychosis, aged 13–65, ethnic differences were observed in the odds for multimorbidity. Controlling for sociodemographic factors and duration of care, compared to White British people, higher odds of multimorbidity were found for people of Black African [adjusted Odds Ratio = 1.41, 95% Confidence Intervals (1.23–1.56)], Black Caribbean [aOR = 1.79, 95% CI (1.58–2.03)] and Black British [aOR = 1.64, 95% CI (1.49–1.81)] ethnicity. Reduced odds were observed among people of Chinese [aOR = 0.61, 95% CI (0.43–0.88)] and Other ethnic [aOR = 0.67, 95% CI (0.59–0.76)] backgrounds. Increased odds of severe multimorbidity (three or more physical health conditions) were also observed for people of any Black background.

Ethnic inequities are observed for multimorbidity among people with psychosis. Further research is needed to understand the aetiology and impact of these inequities. These findings support the provision of integrated health care interventions and public health preventive policies and actions.

Remote consultation technology has been rapidly adopted due to the COVID-19 pandemic. However, some healthcare settings have faced barriers in implementation. We present a study to investigate changes in rates of remote consultation during the pandemic using a large electronic health record (EHR) dataset.

The Clinical Record Interactive Search tool (CRIS) was used to examine de-identified EHR data of people receiving mental healthcare in South London, UK. Data from around 37,500 patients were analysed for each week from 7th January 2019 and 20th September 2020 using linear regression and locally estimated scatterplot smoothing (LOESS) to investigate changes in the number of clinical contacts (in-person, remote or non-attended) with mental healthcare professionals and prescribing of antipsychotics and mood stabilisers. The data are presented in an interactive dashboard: http://rpatel.co.uk/TelepsychiatryDashboard.

The frequency of in-person contacts was substantially reduced following the onset of the pandemic (β coefficient: -5829.6 contacts, 95% CI -6919.5 to -4739.6, p<0.001), while the frequency of remote contacts increased significantly (β coefficient: 3338.5 contacts, 95% CI 3074.4 to 3602.7, p<0.001). Rates of remote consultation were lower in older adults than in working age adults, children and adolescents. Despite the increase in remote contact, antipsychotic and mood stabiliser prescribing remained at similar levels.

The COVID-19 pandemic has been associated with a marked increase in remote consultation, particularly among younger patients. However, there was no evidence that this has led to changes in prescribing. Further work is needed to support older patients in accessing remote mental healthcare.

All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: RS has received funding from Janssen, GSK and Takeda outside the submitted work. RP has received funding from Janssen, Induction Healthcare and H

Food security status is a continuum ranging from high to very low food security. While marginal food security falls next to high food security on the spectrum, new quantitative research indicates marginal food security status is associated with negative health outcomes and poor academic performance among college students. Qualitative research focusing on college students experiencing marginal food security has not been conducted. The current study aims to qualitatively explore experiences of college students with marginal food security and to identify themes to better understand and provide context regarding how marginal food security impacts students.

Students were recruited for semi-structured interviews with questions designed to study the challenges associated with students’ food situations. All interviews were recorded and transcribed with themes identified via an inductive approach.

A large public university on the US west coast.

Thirty college students.

Key themes that emerged: purchasing cheap unhealthy foods, insufficient time to prepare and eat meals on a regular basis, stress and anxiety around the inability to eat healthy food and future health issues, self-perception of health when eating poorly along with physical symptoms and low academic motivation by not fully participating in their courses due to few healthy food options or missing meals.

Marginal food security can potentially diminish students’ health and their capacity to learn and succeed in their coursework. The results emphasise that students experiencing marginal food security should not be grouped with students experiencing high food security.