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.

Primary surgical resection remains the mainstay of management in locally advanced differentiated thyroid cancer. Tyrosine kinase inhibitors have recently shown promising results in patients with recurrent locally advanced differentiated thyroid cancer. This study discussed four patients with locally advanced differentiated thyroid cancer managed with tyrosine kinase inhibitors used prior to surgery in the ‘neoadjuvant’ setting.

Prospective data collection through a local thyroid database from February 2016 identified four patients with locally advanced differentiated thyroid cancer unsuitable for primary surgical resection commenced on neoadjuvant tyrosine kinase inhibitor therapy.

All cases had T4a disease at presentation. Three cases tolerated tyrosine kinase inhibitor therapy for more than 14 months while the last case failed to tolerate treatment at 1 month. All patients subsequently underwent total thyroidectomy to facilitate adjuvant radioactive iodine treatment. Disease-specific survival remains at 100 per cent currently (range, 29–75 months).

Neoadjuvant tyrosine kinase inhibitors in locally advanced differentiated thyroid cancer can be effective in reducing primary tumour extent to potentially facilitate a more limited surgical resection for local disease control.

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.

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.

Lipids appear to mediate depressive vulnerability in the elderly, however, sex differences and genetic vulnerability have not been taken into account in previous prospective studies.

Depression was assessed in a population of 1040 women and 752 men aged 65 years and over at baseline and after 7-year follow-up. Clinical level of depression (DEP) was defined as having either a score of 16 and above on the Centre for Epidemiology Studies Depression scale or a diagnosis of current major depression on the Mini International Neuropsychiatric Interview. Lipid levels, apolipoprotein E and serotonin transporter linked promoter region (5-HTTLPR) genotypes were evaluated at baseline.

Multivariate analyses adjusted by socio-demographic and behavioral variables, measures of physical health including ischemic pathologies, and genetic vulnerability indicated gender-specific associations between dyslipidemia and DEP, independent of the use of lipid lowering agents or apolipoprotein E status. Men with low LDL-cholesterol levels had twice the risk of prevalent and incident DEP whereas in women low HDL-cholesterol levels were found to be significantly associated with increased prevalent DEP (OR = 1.5) only. A significant interaction was observed between low LDL-cholesterol and 5-HTTLPR genotype, men with s/s or s/l genotype being at increased risk of DEP (OR = 6.0 and 2.7, respectively). No significant gene-environment interaction was observed for women.

DEP is associated with higher atherogenic risk in women (low HDL-cholesterol), whereas the reverse is observed in men (low LDL-cholesterol). Late-life depression may have a complex gender-specific etiology involving genetic vulnerability in men.

There are often substantial delays before diagnosis and initiation of treatment in people bipolar disorder. Increased delays are a source of considerable morbidity among affected individuals.

To investigate the factors associated with delays to diagnosis and treatment in people with bipolar disorder.

Retrospective cohort study using electronic health record data from the South London and Maudsley NHS Foundation Trust (SLaM) from 1364 adults diagnosed with bipolar disorder. The following predictor variables were analysed in a multivariable Cox regression analysis on diagnostic delay and treatment delay from first presentation to SLaM: age, gender, ethnicity, compulsory admission to hospital under the UK Mental Health Act, marital status and other diagnoses prior to bipolar disorder.

The median diagnostic delay was 62 days (interquartile range: 17–243) and median treatment delay was 31 days (4–122). Compulsory hospital admission was associated with a significant reduction in both diagnostic delay (hazard ratio 2.58, 95% CI 2.18–3.06) and treatment delay (4.40, 3.63–5.62). Prior diagnoses of other psychiatric disorders were associated with increased diagnostic delay, particularly alcohol (0.48, 0.33–0.41) and substance misuse disorders (0.44, 0.31–0.61). Prior diagnosis of schizophrenia and psychotic depression were associated with reduced treatment delay.

Some individuals experience a significant delay in diagnosis and treatment of bipolar disorder, particularly those with alcohol/substance misuse disorders. These findings highlight a need to better identify the symptoms of bipolar disorder and offer appropriate treatment sooner in order to facilitate improved clinical outcomes. This may include the development of specialist early intervention services.

The authors have not supplied their declaration of competing interest.

Many studies have identified changes in the brain associated with obsessive–compulsive disorder (OCD), but few have examined the relationship between genetic determinants of OCD and brain variation.

We present the first genome-wide investigation of overlapping genetic risk for OCD and genetic influences on subcortical brain structures.

Using single nucleotide polymorphism effect concordance analysis, we measured genetic overlap between the first genome-wide association study (GWAS) of OCD (1465 participants with OCD, 5557 controls) and recent GWASs of eight subcortical brain volumes (13 171 participants).

We found evidence of significant positive concordance between OCD risk variants and variants associated with greater nucleus accumbens and putamen volumes. When conditioning OCD risk variants on brain volume, variants influencing putamen, amygdala and thalamus volumes were associated with risk for OCD.

These results are consistent with current OCD neurocircuitry models. Further evidence will clarify the relationship between putamen volume and OCD risk, and the roles of the detected variants in this disorder.

The authors have declared that no competing interests exist.

The present study explored associations between food choice motives, attitudes towards and intention to adopt personalised nutrition, to inform communication strategies based on consumer priorities and concerns.

A survey was administered online which included the Food Choice Questionnaire (FCQ) and items assessing attitudes towards and intention to adopt personalised nutrition.

Nationally representative samples were recruited in nine EU countries (n 9381).

Structural equation modelling indicated that the food choice motives ‘weight control’, ‘mood’, ‘health’ and ‘ethical concern’ had a positive association and ‘price’ had a negative association with attitude towards, and intention to adopt, personalised nutrition. ‘Health’ was positively associated and ‘familiarity’ negatively associated with attitude towards personalised nutrition. The effects of ‘weight control’, ‘ethical concern’, ‘mood’ and ‘price’ on intention to adopt personalised nutrition were partially mediated by attitude. The effects of ‘health’ and ‘familiarity’ were fully mediated by attitude. ‘Sensory appeal’ was negatively and directly associated with intention to adopt personalised nutrition.

Personalised nutrition providers may benefit from taking into consideration the importance of underlying determinants of food choice in potential users, particularly weight control, mood and price, when promoting services and in tailoring communications that are motivationally relevant.

The study purpose was to provide evidence of validity for the Primary Health Care Engagement (PHCE) Scale, based on exploratory factor analysis and reliability findings from a large national survey of regulated nurses residing and working in rural and remote Canadian communities.

There are currently no published provider-level instruments to adequately assess delivery of community-based primary health care, relevant to ongoing primary health care (PHC) reform strategies across Canada and elsewhere. The PHCE Scale reflects a contemporary approach that emphasizes community-oriented and community-based elements of PHC delivery.

Data from the pan-Canadian Nursing Practice in Rural and Remote Canada II (RRNII) survey were used to conduct an exploratory factor analysis and evaluate the internal consistency reliability of the final PHCE Scale.

The RRNII survey sample included 1587 registered nurses, nurse practitioners, licensed practical nurses, and registered psychiatric nurses residing and working in rural and remote Canada. Exploratory factor analysis identified an eight-factor structure across 28 items overall, and good internal consistency reliability was indicated by an α estimate of 0.89 for the final scale. The final 28-item PHCE Scale includes three of four elements in a contemporary approach to PHC (accessibility/availability, community participation, and intersectoral team) and most community-oriented/based elements of PHC (interdisciplinary collaboration, person-centred, continuity, population orientation, and quality improvement). We recommend additional psychometric testing in a range of health care providers and settings, as the PHCE Scale shows promise as a tool for health care planners and researchers to test interventions and track progress in primary health care reform.