This study reports preliminary findings on the prevalence of, and factors associated with, mental health and well-being outcomes of healthcare workers during the early months (April-June) of the ...COVID-19 pandemic in the UK.
Preliminary cross-sectional data were analysed from a cohort study (n=4378). Clinical and non-clinical staff of three London-based NHS Trusts, including acute and mental health Trusts, took part in an online baseline survey. The primary outcome measure used is the presence of probable common mental disorders (CMDs), measured by the General Health Questionnaire. Secondary outcomes are probable anxiety (seven-item Generalised Anxiety Disorder), depression (nine-item Patient Health Questionnaire), post-traumatic stress disorder (PTSD) (six-item Post-Traumatic Stress Disorder checklist), suicidal ideation (Clinical Interview Schedule) and alcohol use (Alcohol Use Disorder Identification Test). Moral injury is measured using the Moray Injury Event Scale.
Analyses showed substantial levels of probable CMDs (58.9%, 95% CI 58.1 to 60.8) and of PTSD (30.2%, 95% CI 28.1 to 32.5) with lower levels of depression (27.3%, 95% CI 25.3 to 29.4), anxiety (23.2%, 95% CI 21.3 to 25.3) and alcohol misuse (10.5%, 95% CI 9.2 to 11.9). Women, younger staff and nurses tended to have poorer outcomes than other staff, except for alcohol misuse. Higher reported exposure to moral injury (distress resulting from violation of one's moral code) was strongly associated with increased levels of probable CMDs, anxiety, depression, PTSD symptoms and alcohol misuse.
Our findings suggest that mental health support for healthcare workers should consider those demographics and occupations at highest risk. Rigorous longitudinal data are needed in order to respond to the potential long-term mental health impacts of the pandemic.
This paper exploits recent developments in topological data analysis to present a pipeline for clustering based on Mapper, an algorithm that reduces complex data into a one-dimensional graph.
We ...present a pipeline to identify and summarise clusters based on statistically significant topological features from a point cloud using Mapper.
Key strengths of this pipeline include the integration of prior knowledge to inform the clustering process and the selection of optimal clusters; the use of the bootstrap to restrict the search to robust topological features; the use of machine learning to inspect clusters; and the ability to incorporate mixed data types. Our pipeline can be downloaded under the GNU GPLv3 license at https://github.com/kcl-bhi/mapper-pipeline .
The Social media, Smartphone use and Self-Harm (3S-YP) study is a prospective observational cohort study to investigate the mechanisms underpinning associations between social media and smartphone ...use and self-harm in a clinical youth sample. We present here a comprehensive description of the cohort from baseline data and an overview of data available from baseline and follow-up assessments.
Young people aged 13-25 years were recruited from a mental health trust in England and followed up for 6 months. Self-report data was collected at baseline and monthly during follow-up and linked with electronic health records (EHR) and user-generated data.
A total of 362 young people enrolled and provided baseline questionnaire data. Most participants had a history of self-harm according to clinical (n = 295, 81.5%) and broader definitions (n = 296, 81.8%). At baseline, there were high levels of current moderate/severe anxiety (n = 244; 67.4%), depression (n = 255; 70.4%) and sleep disturbance (n = 171; 47.2%). Over half used social media and smartphones after midnight on weekdays (n = 197, 54.4%; n = 215, 59.4%) and weekends (n = 241, 66.6%; n = 263, 72.7%), and half met the cut-off for problematic smartphone use (n = 177; 48.9%). Of the cohort, we have questionnaire data at month 6 from 230 (63.5%), EHR data from 345 (95.3%), social media data from 110 (30.4%) and smartphone data from 48 (13.3%).
The 3S-YP study is the first prospective study with a clinical youth sample, for whom to investigate the impact of digital technology on youth mental health using novel data linkages. Baseline findings indicate self-harm, anxiety, depression, sleep disturbance and digital technology overuse are prevalent among clinical youth. Future analyses will explore associations between outcomes and exposures over time and compare self-report with user-generated data in this cohort.
Polypharmacy is commonly defined based on the number of medications taken concurrently using standard cut-offs, but several studies have highlighted the need for a multidimensional assessment. We ...developed a multidimensional measure of polypharmacy and compared with standard cut-offs. Data were extracted for 2141 respondents of the 2007 Prescription Drug Survey, a sub-study of the Health Retirement Study. Latent classes were identified based on multiple indicators of polypharmacy, including quantity, temporality and risk profile. A four-class model was selected based on fit statistics and clinical interpretability: 'High risk, long-term' (Class 1), 'Low risk, long-term' (Class 2), 'High risk, short-term' (Class 3), and 'High risk for drug interactions, medium-term, regular' (Class 4). Classes differed regarding sex, cohabitation, disability and multimorbidity. Participants in the 'low risk' class tended to be male, cohabitating, and reported fewer health conditions, compared to 'high risk' classes. Polypharmacy classes were compared to standard cut-offs (5+ or 9+ medications) in terms of overlap and mortality risk. The three 'high risk' classes overlapped with the groups concurrently taking 5+ and 9+ medications per month. However, the multidimensional measure further differentiated individuals in terms of risk profile and temporality of medication taking, thus offering a richer assessment of polypharmacy.
To examine whether psychosocial work characteristics at age 45 years predict exit from the labour market by the age of 50 years in data from the 1958 British Birth Cohort.
Psychosocial work ...characteristics (decision latitude, job demands, job strain and work social support at 45 years and job insecurity at 42 years) measured by questionnaire were linked to employment outcomes (unemployment, retirement, permanent sickness, homemaking) at 50 years in 6510 male and female participants.
Low decision latitude (RR = 2.01, 95%CI 1.06,3.79), low work social support (RR = 1.96, 95%CI 1.12,3.44), and high job insecurity (RR = 2.27, 95%CI 1.41, 3.67) predicted unemployment at 50, adjusting for sex, housing tenure, socioeconomic status, marital status, and education. High demands were associated with lower risk of unemployment (RR = 0.50, 95%CI 0.29,0.88) but higher risk of permanent sickness (RR = 2.14, 95%CI 1.09,4.21).
Keeping people in the workforce beyond 50 years may contribute to both personal and national prosperity. Employers may wish to improve working conditions for older workers, in particular, increase control over work, increase support and reduce demands to retain older employees in the workforce.
ObjectivesTo develop and probe the first computerised decision-support tool to provide antidepressant treatment guidance to general practitioners (GPs) in UK primary care.DesignA parallel group, ...cluster-randomised controlled feasibility trial, where individual participants were blind to treatment allocation.SettingSouth London NHS GP practices.ParticipantsTen practices and eighteen patients with treatment-resistant current major depressive disorder.InterventionsPractices were randomised to two treatment arms: (a) treatment-as-usual, (b) computerised decision support tool.ResultsTen GP practices participated in the trial, which was within our target range (8–20). However, practice and patient recruitment were slower than anticipated and only 18 of 86 intended patients were recruited. This was due to fewer than expected patients being eligible for the study, as well as disruption resulting from the COVID-19 pandemic. Only one patient was lost to follow-up. There were no serious or medically important adverse events during the trial. GPs in the decision tool arm indicated moderate support for the tool. A minority of patients fully engaged with the mobile app-based tracking of symptoms, medication adherence and side effects.ConclusionsOverall, feasibility was not shown in the current study and the following modifications would be needed to attempt to overcome the limitations found: (a) inclusion of patients who have only tried one Selective Serotonin Reuptake Inhibitor, rather than two, to improve recruitment and pragmatic relevance of the study; (b) approaching community pharmacists to implement tool recommendations rather than GPs; (c) further funding to directly interface between the decision support tool and self-reported symptom app; (d) increasing the geographic reach by not requiring detailed diagnostic assessments and replacing this with supported remote self-report.Trial registration numberNCT03628027.
Objective Policy in many industrialized countries increasingly emphasizes extended working life. We examined associations between physical and cognitive capability in mid-adulthood and work in late ...adulthood. Methods Using self-reported physical limitations and performance-based physical and cognitive capability at age 53, assessed by trained nurses from the Medical Research Council (MRC) National Survey of Health and Development, we examined prospective associations with extended working (captured by age at and reason for retirement from main occupation, bridge employment in paid work after retirement from the main occupation, and voluntary work participation) up to age 68 among ＞2000 men and women. Results Number of reported physical limitations at age 53 was associated with higher likelihood of retiring for negative reasons and lower likelihood of participating in bridge employment, adjusted for occupational class, education, partner's employment, work disability at age 53, and gender. Better performance on physical and cognitive tests was associated with greater likelihood of participating in bridge or voluntary work. Cognitive capability in the top 10% compared with the middle 80% of the distribution was associated with an odds ratio of bridge employment of 1.71 95% confidence interval (95% CI) 1.21-2.42. Conclusions The possibility for an extending working life is less likely to be realized by those with poorer midlife physical or cognitive capability, independently of education, and social class. Interventions to promote capability, starting in mid-adulthood or earlier, could have long-term consequences for extending working.
Prediction models should be externally validated to assess their performance before implementation. Several prediction models for coronavirus disease-19 (COVID-19) have been published. This ...observational cohort study aimed to validate published models of severity for hospitalized patients with COVID-19 using clinical and laboratory predictors.
Prediction models fitting relevant inclusion criteria were chosen for validation. The outcome was either mortality or a composite outcome of mortality and ICU admission (severe disease). 1295 patients admitted with symptoms of COVID-19 at Kings Cross Hospital (KCH) in London, United Kingdom, and 307 patients at Oslo University Hospital (OUH) in Oslo, Norway were included. The performance of the models was assessed in terms of discrimination and calibration.
We identified two models for prediction of mortality (referred to as Xie and Zhang1) and two models for prediction of severe disease (Allenbach and Zhang2). The performance of the models was variable. For prediction of mortality Xie had good discrimination at OUH with an area under the receiver-operating characteristic (AUROC) 0.87 95% confidence interval (CI) 0.79-0.95 and acceptable discrimination at KCH, AUROC 0.79 0.76-0.82. In prediction of severe disease, Allenbach had acceptable discrimination (OUH AUROC 0.81 0.74-0.88 and KCH AUROC 0.72 0.68-0.75). The Zhang models had moderate to poor discrimination. Initial calibration was poor for all models but improved with recalibration.
The performance of the four prediction models was variable. The Xie model had the best discrimination for mortality, while the Allenbach model had acceptable results for prediction of severe disease.
IntroductionThe Antidepressant Advisor Study is a feasibility trial of a computerised decision-support tool which uses an algorithm to provide antidepressant treatment guidance for general ...practitioners (GPs) in the UK primary care service. The tool is the first in the UK to implement national guidelines on antidepressant treatment guidance into a computerised decision-support tool.Methods and analysisThe study is a parallel group, cluster-randomised controlled feasibility trial where participants are blind to treatment allocation. GPs were assigned to two treatment arms: (1) treatment-as-usual (TAU) and (2) computerised decision-support tool to assist with antidepressant choices. The study will assess recruitment and lost to follow-up rates, GP satisfaction with the tool and impact on health service use. A meaningful long-term roll-out unit cost will be calculated for the tool, and service use data will be collected at baseline and follow-up to inform a full economic evaluation of a future trial.Ethics and disseminationThe study has received National Health Service ethical approval from the London—Camberwell St Giles Research Ethics Committee (ref: 17/LO/2074). The trial was pre-registered in the Clinical Trials.gov registry. The results of the study will be published in a pre-publication archive within 1 year of completion of the last follow-up assessment.Trial registration numberNCT03628027.
ObjectivesSickness absence is strongly associated with poor mental health, and mental disorders often go untreated. In this population-based cohort study, we identified people receiving fit notes ...from their general practitioner (GP) and determined access to mental health treatment stratified by health complaint and demographic variables.DesignLongitudinal study of health records.SettingPrimary care and secondary mental health care in the borough of Lambeth, South London. Forty-five GP practices in Lambeth and the local secondary mental healthcare trust.ParticipantsThe analytical sample included 293 933 working age adults (16–60 years) registered at a Lambeth GP practice between 1 January 2014 and 30 April 2016.Primary and secondary outcome measuresThree indicators of mental healthcare in the year after first fit note were antidepressant prescription, contact with Improving Access to Psychological Therapy (IAPT) services and contact with secondary mental health services.Results75% of people with an identified mental health condition at first fit note had an indicator of mental healthcare in the following year. Black Caribbean and Black African groups presenting with mental disorders were less likely to have a mental healthcare indicator compared with White British groups.ConclusionsThe majority of those with an identified mental health need receive some treatment in the year following a fit note; however, our results suggest Black African and Black Caribbean groups with an identified mental healthcare need have less complete access compared to the White British group.
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