Depression is an independent risk factor for cardiovascular disease (CVD), but it is unknown if successful depression treatment reduces CVD risk.

Using eIMPACT trial data, we examined the effect of modernized collaborative care for depression on indicators of CVD risk. A total of 216 primary care patients with depression and elevated CVD risk were randomized to 12 months of the eIMPACT intervention (internet cognitive-behavioral therapy [CBT], telephonic CBT, and select antidepressant medications) or usual primary care. CVD-relevant health behaviors (self-reported CVD prevention medication adherence, sedentary behavior, and sleep quality) and traditional CVD risk factors (blood pressure and lipid fractions) were assessed over 12 months. Incident CVD events were tracked over four years using a statewide health information exchange.

The intervention group exhibited greater improvement in depressive symptoms (p < 0.01) and sleep quality (p < 0.01) than the usual care group, but there was no intervention effect on systolic blood pressure (p = 0.36), low-density lipoprotein cholesterol (p = 0.38), high-density lipoprotein cholesterol (p = 0.79), triglycerides (p = 0.76), CVD prevention medication adherence (p = 0.64), or sedentary behavior (p = 0.57). There was an intervention effect on diastolic blood pressure that favored the usual care group (p = 0.02). The likelihood of an incident CVD event did not differ between the intervention (13/107, 12.1%) and usual care (9/109, 8.3%) groups (p = 0.39).

Successful depression treatment alone is not sufficient to lower the heightened CVD risk of people with depression. Alternative approaches are needed.

ClinicalTrials.gov Identifier: NCT02458690

To synthesize evidence and identify gaps in the literature on environmental cleaning and disinfection in the operating room based on a human factors and systems engineering approach guided by the Systems Engineering Initiative for Patient Safety (SEIPS) model.

A systematic scoping review.

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched 4 databases (ie, PubMed, EMBASE, OVID, CINAHL) for empirical studies on operating-room cleaning and disinfection. Studies were categorized based on their objectives and designs and were coded using the SEIPS model. The quality of randomized controlled trials and quasi-experimental studies with a nonequivalent groups design was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials.

In total, 40 studies were reviewed and categorized into 3 groups: observational studies examining the effectiveness of operating-room cleaning and disinfections (11 studies), observational study assessing compliance with operating-room cleaning and disinfection (1 study), and interventional studies to improve operating-room cleaning and disinfection (28 studies). The SEIPS-based analysis only identified 3 observational studies examining individual work-system components influencing the effectiveness of operating-room cleaning and disinfection. Furthermore, most interventional studies addressed single work-system components, including tools and technologies (20 studies), tasks (3 studies), and organization (3 studies). Only 2 studies implemented interventions targeting multiple work-system components.

The existing literature shows suboptimal compliance and inconsistent effectiveness of operating-room cleaning and disinfection. Improvement efforts have been largely focused on cleaning and disinfection tools and technologies and staff monitoring and training. Future research is needed (1) to systematically examine work-system factors influencing operating-room cleaning and disinfection and (2) to redesign the entire work system to optimize operating-room cleaning and disinfection.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

The COVID-19 pandemic has significantly impacted mental health services, with the literature reporting an increase in the incidence of psychiatric admissions.

The aim of this study was to assess the impact of the pandemic on clinical presentations, characteristics of admission and incidents occurring in three acute inpatient mental health facilities in the UK.

This was a retrospective study comparing data from the first and third UK lockdown to the five years prior to the pandemic. Data was acquired from electronic clinical records and addressed two acute psychiatric inpatient wards and one psychiatric intensive care unit. Key outcomes of comparison were clinical presentations, number of admissions, length of hospital stay, number of incidents and characteristics of incidents.

Compared to the previous 5 years, a higher number of incidents characterized by violence and aggression were reported during the first (56.8% vs 44.3%, x2=16.56, df=1, p<0.001) and third lockdown (100.0% vs 86.2%, x2=36.40, df=1, p<0.001). An increase in non-psychotic disorders was observed in the first lockdown (20.0% vs 13.1%, x2=4.76, df=1, p=0.029), whilst increased first episode psychosis (19.7% vs 11.3%, x2=8.1, df=1, p=0.004) and schizophrenia spectrum disorders (74.4% vs 57.2%, x2= 7.6, df=1, p=0.006) were diagnosed during the third lockdown. There were no significant changes in the diagnosis of mood disorders in both lockdowns compared to previously. The median length of inpatient stay significantly reduced during the first lockdown (28 days vs 36 days, x2= 7.66, df=1, p=0.006).

Increased inpatient incidents may be explained by the impact of the pandemic on staffing levels and resources, combined with increased emotional distress amongst patients in the face of uncertainty. The pandemic may have increased substance misuse potentially linked with the increased incidence of first episode psychosis.

S. Bonaccorso: None Declared, O. Ajnakina: None Declared, A. Ricciardi: None Declared, S. Ouabbou: None Declared, J. Wilson: None Declared, C. Theleritis: None Declared, M. Badhan: None Declared, A. Metastasio: None Declared, N. Stewart: None Declared, M. Barczyck: None Declared, F. Johansson: None Declared, T. Tharmaraja: None Declared, F. Schifano Speakers bureau of: Prof. Fabrizio Schifano is a member of the European Medical Agency

Dental healthcare personnel (DHCP) are at high risk of exposure to coronavirus disease 2019 (COVID-19). We sought to identify how DHCP changed their use of personal protective equipment (PPE) as a result of the COVID-19 pandemic, and to pilot an educational video designed to improve knowledge of proper PPE use.

The study comprised 2 sets of semistructured qualitative interviews.

The study was conducted in 8 dental clinics in a Midwestern metropolitan area.

In total, 70 DHCP participated in the first set of interviews; 63 DHCP participated in the second set of interviews.

In September–November 2020 and March–October 2021, we conducted 2 sets of semistructured interviews: (1) PPE use in the dental community during COVID-19, and (2) feedback on the utility of an educational donning and doffing video.

Overall, 86% of DHCP reported having prior training. DHCP increased the use of PPE during COVID-19, specifically N95 respirators and face shields. DHCP reported real-world challenges to applying infection control methods, often resulting in PPE modification and reuse. DHCP reported double masking and sterilization methods to extend N95 respirator use. Additional challenges to PPE included shortages, comfort or discomfort, and compatibility with specialty dental equipment. DHCP found the educational video helpful and relevant to clinical practice. Fewer than half of DHCP reported exposure to a similar video.

DHCP experienced significant challenges related to PPE access and routine use in dental clinics during the COVID-19 pandemic. An educational video improved awareness and uptake of appropriate PPE use among DHCP.

Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an exciting opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks.

To describe the amount of data collected during a multimodal longitudinal RMT study, in an MDD population.

RADAR-MDD is a multi-centre, prospective observational cohort study. People with a history of MDD were provided with a wrist-worn wearable, and several apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks and cognitive assessments and followed-up for a maximum of 2 years.

A total of 623 individuals with a history of MDD were enrolled in the study with 80% completion rates for primary outcome assessments across all timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. Data availability across all RMT data types varied depending on the source of data and the participant-burden for each data type. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. 110 participants had > 50% data available across all data types, and thus able to contribute to multiparametric analyses.

RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible.

No significant relationships.

A number of genomic conditions caused by copy number variants (CNVs) are associated with a high risk of neurodevelopmental and psychiatric disorders (ND-CNVs). Although these patients also tend to have cognitive impairments, few studies have investigated the range of emotion and behaviour problems in young people with ND-CNVs using measures that are suitable for those with learning difficulties.

A total of 322 young people with 13 ND-CNVs across eight loci (mean age: 9.79 years, range: 6.02–17.91, 66.5% male) took part in the study. Primary carers completed the Developmental Behaviour Checklist (DBC).

Of the total, 69% of individuals with an ND-CNV screened positive for clinically significant difficulties. Young people from families with higher incomes (OR = 0.71, CI = 0.55–0.91, p = .008) were less likely to screen positive. The rate of difficulties differed depending on ND-CNV genotype (χ2 = 39.99, p < 0.001), with the lowest rate in young people with 22q11.2 deletion (45.7%) and the highest in those with 1q21.1 deletion (93.8%). Specific patterns of strengths and weaknesses were found for different ND-CNV genotypes. However, ND-CNV genotype explained no more than 9–16% of the variance, depending on DBC subdomain.

Emotion and behaviour problems are common in young people with ND-CNVs. The ND-CNV specific patterns we find can provide a basis for more tailored support. More research is needed to better understand the variation in emotion and behaviour problems not accounted for by genotype.

The ‘sick-quitter’ hypothesis states that mental disorders associated with alcohol abstinence are accounted for by people who stop consuming alcohol because of poor health.

We investigated the association between alcohol abstinence and symptoms of common mental disorder and personality disorder, distinguishing between lifelong abstinence and abstinence following previous consumption.

Analyses were based on the British National Survey of Psychiatric Morbidity 2000, which sampled 8580 residents aged 16 to 74 years. Heavy consumers of alcohol were excluded, using the Alcohol Use Disorders Identification Test Questionnaire. Symptoms of common mental disorder (depression/anxiety) were identified by the Clinical Interview Schedule. The screening questionnaire of the Structured Clinical Interview for Axis II Personality Disorders was used to identify potential personality disorder. Self-reported alcohol abstinence was divided into lifelong abstinence and previous consumption. Previous consumers were asked why they had stopped. Covariates included socioeconomic status, social activity and general health status.

After adjustment, alcohol abstinence was associated with both common mental disorder symptoms and any personality disorder, but only for previous consumers (respective odds ratios 1.70 (1.23-2.34) and 1.45 (1.09-1.94)). Associations were non-specific, being apparent for most individual mental disorder symptoms and personality disorder categories. More detailed analysis indicated that associations were limited to previous consumers who reported ceasing alcohol consumption for health reasons.

The results were consistent with the ‘sick-quitter’ hypothesis and should be taken into account when interpreting associations between moderate alcohol consumption and beneficial health outcomes.