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Background In a randomised controlled trial, contamination is defined as the receipt of active intervention amongst participants in the control arm. This review assessed the processes leading to contamination, its typical quantity, methods used to mitigate it, and impact of use of cluster randomisation to prevent it on study findings in trials of complex interventions in mental health. Methods This is a scoping review of trial design approaches and methods of study conduct to address contamination. Studies included were randomised controlled trials of complex interventions in mental health that described the process leading to, amount of, or solution used to counter contamination. The Medline, Embase, and PsycInfo databases were searched for trials published between 2000 and 2015. Risk of bias was assessed using the Jadad score and domains recommended by Cochrane plus some relevant to cluster randomised trials. Results Two hundred and thirty-four articles were included in the review. The main processes that led to contamination were health professionals delivering both active and comparator treatments and communication among clinicians and participants from the different trial arms. Twenty-three trials (10%) measured binary treatment receipt in the control arm with median 13% of participants found to be contaminated (IQR 5–33%). The most common design approach for dealing with contamination was the use of cluster randomisation ( n  = 93). In addition, many researchers used simple trial conduct methods to minimise contamination due to suspected contamination processes, such as organising for each clinician to provide only one treatment and separating trial arms spatially or temporally. There was little evidence for a relationship between cluster randomisation to avoid contamination and size of treatment effect estimate. Conclusion There was some evidence of modest levels of treatment contamination with a large range, although a minority of studies reported the amount of contamination. A limitation was that many trials described the problem in little detail. Overall there is a need for greater measurement and reporting of treatment receipt in the control arm of trials. Researchers should be aware of trial conduct methods that can be used to minimise contamination without resorting to cluster randomisation.

Depression is associated with the onset of type 2 diabetes. A systematic review and meta-analysis of observational studies, controlled trials, and unpublished data was conducted to examine the association between depression and insulin resistance (IR). Medline, EMBASE, and PsycINFO were searched for studies published up to September 2011. Two independent reviewers assessed the eligibility of each report based on predefined inclusion criteria (study design and measure of depression and IR, excluding prevalent cases of diabetes). Individual effect sizes were standardized, and a meta-analysis was performed to calculate a pooled effect size using random effects. Subgroup analyses and meta-regression were conducted to explore any potential source of heterogeneity between studies. Of 967 abstracts reviewed, 21 studies met the inclusion criteria of which 18 studies had appropriate data for the meta-analysis (n = 25,847). The pooled effect size (95% CI) was 0.19 (0.11-0.27) with marked heterogeneity (I(2) = 82.2%) using the random-effects model. Heterogeneity between studies was not explained by age or sex, but could be partly explained by the methods of depression and IR assessments. A small but significant cross-sectional association was observed between depression and IR, despite heterogeneity between studies. The pathophysiology mechanisms and direction of this association need further study using a purposively designed prospective or intervention study in samples at high risk for diabetes.

Gestational diabetes mellitus (GDM) is an increasingly common condition of pregnancy. It is associated with adverse fetal, infant and maternal outcomes, as well as an increased risk of GDM in future pregnancies and type 2 diabetes for both mother and offspring. Previous studies have shown that GDM can result in an emotionally distressing pregnancy, but there is little research on the patient experience of GDM care, especially of a demographically diverse UK population. The aim of this research was to explore the experiences of GDM and GDM care for a group of women attending a large diabetes pregnancy unit in southeast London, UK, in order to improve care. Framework analysis was used to support an integrated analysis of data from six focus groups with 35 women and semi-structured interviews with 15 women, held in 2015. Participants were purposively sampled and were representative of the population being studied in terms of ethnicity, age, deprivation score and body mass index (BMI). We identified seven themes: the disrupted pregnancy, projected anxiety, reproductive asceticism, women as baby machines, perceived stigma, lack of shared understanding and postpartum abandonment. These themes highlight the often distressing experience of GDM. While most women were grateful for the intensive support they received during pregnancy, the costs to their personal autonomy were high. Women described feeling valued solely as a means to produce a healthy infant, and felt chastised if they failed to adhere to the behaviours required to achieve this. This sometimes had an enduring impact to the potential detriment of women's long-term psychological and physical health. This study reveals the experiences of a demographically diverse group of patients with GDM, reflecting findings from previous studies globally and extending analysis to the context of improving care. Healthcare delivery may need to be reoriented to improve the pregnancy experience and help ensure women are engaged and attentive to their own health, particularly after birth, without compromising clinical pregnancy outcomes. Areas for consideration in GDM healthcare include: improved management of emotional responses to GDM; a more motivational approach; rethinking the medicalisation of care; and improved postpartum care.

Depression has been shown to be associated with elevated leptin levels, low-grade inflammation and insulin resistance. These derangements are often measured in mixed gender cohorts despite the different body compositions and hormonal environments of men and women and gender-specific prevalence and responses to depression. A cross-sectional analysis was carried out on a cohort of 639 participants from the ADDITION-Leicester dataset to assess differences in markers of diabetes risk, cardiovascular risk and inflammation in depressed and non-depressed individuals. Depressive symptoms were determined using the WHO (Five) well-being index. Multivariate linear and logistic regression analyses were adjusted for age, sex, ethnicity, body mass index, smoking, social deprivation and activity levels for continuous and binary variables respectively. Further analysis included stratifying the data by gender as well as assessing the interaction between depression and gender by including an interaction term in the model. Women with depressive symptoms had a 5.3% larger waist circumference (p = 0.003), 28.7% higher HOMA IR levels (p = 0.026), 6.6% higher log-leptin levels (p = 0.01) and 22.37% higher TNF-α levels (p = 0.015) compared with women without. Conversely, depressive symptoms in men were associated with 7.8% lower body fat % (p = 0.015) but 48.7% higher CRP levels (p = 0.031) compared to men without. However, interaction analysis failed to show a significant difference between men and women. Depressive symptoms are associated with metabolic derangements. Whilst women tended to show elevations in biomarkers related to an increased risk of type 2 diabetes (HOMA IR, leptin and TNF-α), men showed a marked increase in the cardiovascular disease risk biomarker CRP. However, perhaps due to the cohort size, interaction analysis did not show a significant gender difference.

Aims and objectives To assess the effectiveness of educational and/or psychological diabetes self‐management education (DSME) intervention for people with type 2 diabetes (T2DM) in the Asian Western Pacific (AWP) region. Background Translational research indicates that DSME is effective; therefore, it is important to look at the AWP region to see what has been implemented and what the potential barriers are for the low integration of DSME. The need for DSME is present, and programmes are being developed. Therefore, focusing a systematic review of DSME research in the AWP region would give a better understanding of which intervention approaches are associated with better clinical outcomes and are culturally acceptable. Design A systematic review. Methods A review of randomized controlled trials (RCTs) and comparative studies to evaluate the effectiveness of face‐to‐face delivery reporting educational and/or psychological interventions for people with T2DM was implemented. We conducted searches using MEDLINE, EMBASE, CINAHL, PubMed and ASSIA databases between January 1990–June 2018. Studies published in English and non‐English were included. Two reviewers independently extracted data on participant and intervention characteristics. The quality of evidence was rated on predetermined criteria. Main outcomes included glycaemic control (reduction in HbA1c level). Results We included 21 DSME programmes (17 RCTs), while 15 were group‐based approaches. Twelve studies (60%) were categorized as high quality. Three studies (25%) had a moderate (good) effect. Eight trials were effective in improving glycaemic control and reported statistically significant improvements in HbA1c levels. 50% of these were high‐intensity group‐based programmes.

Gestational diabetes and the maternal mental disorders of anxiety and depression have been implicated in adverse offspring neuro-behavioural outcomes but these exposures have only been studied in isolation. 1051 children whose mothers were diagnosed with gestational diabetes in UK’s Born in Bradford cohort had linkage to maternal primary care records, providing diagnostic and treatment codes for depression and anxiety. Education record linkage provided results of the Early Years Foundation Stage Profile from the first year of school, aged five. Risk of not attaining a ‘Good level of development’ was analysed using multivariable Poisson regression within a generalised estimating equation framework. Multiple imputation was implemented for missing data. There was limited evidence of increased risk of failure to attain a ‘good level of development’ in those additionally exposed to maternal mental disorders (adjusted RR 1.21; 95% CI 0.94, 1.55). However, there was more evidence in children of Pakistani maternal ethnicity (adjusted RR 1.36; 95% CI 1.04, 1.77) than White British; this may have been driven by English not being the primary language spoken in the home. Therefore there may be groups with GDM in whom it is particularly important to optimise both maternal physical and mental health to improve child outcomes.

We review the validity of the evidence for an association between depression and the risk of insulin resistance (IR). We describe the potentially plausible biological and behavioral mechanisms that explain how depression increases the risk of IR and consequent overt diabetes. We have identified gaps in the literature to guide future research. Evidence for bidirectional associations between depression and IR is inconsistent. Results showing positive associations between depression and IR are derived from cross-sectional studies, whereas negative findings are typically reported in cohort studies. On the other hand, tentative trial evidence suggests that the effective treatment of depression can improve IR, and that lifestyle programs improve IR and reduce depressive symptoms. These emerging themes could lead to potential new multidisciplinary approaches to preventing diabetes.

Objectives To assess the feasibility of an ante- and post-natal lifestyle intervention for women with gestational diabetes mellitus (GDM) to reduce type 2 diabetes risk. Design A partially randomised patient preference feasibility trial. Setting Diabetes antenatal clinics in two inner-London hospitals, UK. Participants Pregnant women [greater than or equal to]18 years with a GDM diagnosis and pre-pregnancy body mass index of [greater than or equal to]25kg/m.sup.2. Intervention Participants in the intervention group were offered four motivational interview-based sessions (two antenatally and two postnatally, at 3 and 6 months postpartum), a WhatsApp support group, a FitBit and electronic self-help resources. Outcome measures Recruitment; retention; intervention dose received; data completion; adaptions; proportion achieving [greater than or equal to]5% weight loss; weight change, blood glucose; blood pressure; diet, physical activity, breastfeeding and depression. Clinical outcomes were measured at baseline and 6 months postpartum. Results 50 participants were recruited from 155 eligible women (32% recruitment rate). Thirty-four were recruited to the intervention group (23 following randomisation (RI-group) and 11 based on preference (PI-group)); and 16 to the control group (13 randomised (RC-group) and 3 preference (PC-group)). Attrition was 44% (n = 22/50). Forty-six percent (n = 6) of the intervention group (25% (n = 2) of the RI-group and 80% (n = 4) of the PI-group) achieved [greater than or equal to]5% weight loss compared to 8% (n = 1) in the control group (95% confidence interval (CI) -0.69 to 0.07). Mean weight change was -2.1kg±9.0 in the intervention group (0kg±5.4 in the RI-group and -5.4kg±13.0 in the PI-group) compared to +4.4kg±4.9 in the control group (RC +4.4kg ±5.3 and PC +4.7kg ±3.1, 95% CI -12.4 to 0.2). Conclusions Recruitment was feasible, but strategies to improve retention are needed. The findings suggest the intervention can support women with GDM to lose weight. The observed weight loss was primarily in women who preferred the intervention. Therefore, future trials may need to adopt a preference design and consider factors associated with preference. Trial registration Trial registration: ISRCTN52675820

The coronavirus disease 2019 (COVID-19) pandemic is likely to lead to a significant increase in mental health disorders among healthcare workers (HCW). We evaluated the rates of anxiety, depressive and post-traumatic stress disorder (PTSD) symptoms in a population of HCW in the UK. An electronic survey was conducted between the 5 June 2020 and 31 July 2020 of all hospital HCW in the West Midlands, UK using clinically validated questionnaires: the 4-item Patient Health Questionnaire(PHQ-4) and the Impact of Event Scale-Revised (IES-R). Univariate analyses and adjusted logistic regression analyses were performed to estimate the strengths in associations between 24 independent variables and anxiety, depressive or PTSD symptoms. There were 2638 eligible participants who completed the survey (female: 79.5%, median age: 42 years, interquartile range: 32-51). The rates of clinically significant symptoms of anxiety, depression and PTSD were 34.3%, 31.2% and 24.5%, respectively. In adjusted analysis a history of mental health conditions was associated with clinically significant symptoms of anxiety (odds ratio (OR) = 2.3, 95% CI 1.9-2.7, P < 0.001), depression (OR = 2.5, 95% CI 2.1-3.0, P < 0.001) and PTSD (OR = 2.1, 95% CI 1.7-2.5, P < 0.001). The availability of adequate personal protective equipment (PPE), well-being support and lower exposure to moral dilemmas at work demonstrated significant negative associations with these symptoms (P ≤ 0.001). We report higher rates of clinically significant mental health symptoms among hospital HCW following the initial COVID-19 pandemic peak in the UK. Those with a history of mental health conditions were most at risk. Adequate PPE availability, access to well-being support and reduced exposure to moral dilemmas may protect hospital HCW from mental health symptoms.

Accelerometers and other wearable devices are increasingly being used in clinical trials to provide an objective measure of the impact of an intervention on physical activity. Missing data are ubiquitous in this setting, typically for one of two reasons: patients may not wear the device as per protocol, and/or the device may fail to collect data (e.g. flat battery, water damage). However, it is not always possible to distinguish whether the participant stopped wearing the device, or if the participant is wearing the device but staying still. Further, a lack of consensus in the literature on how to aggregate the data before analysis (hourly, daily, weekly) leads to a lack of consensus in how to define a “missing” outcome. Different trials have adopted different definitions (ranging from having insufficient step counts in a day, through to missing a certain number of days in a week). We propose an analysis framework that uses wear time to define missingness on the epoch and day level, and propose a multiple imputation approach, at the day level, which treats partially observed daily step counts as right censored. This flexible approach allows the inclusion of auxiliary variables, and is consistent with almost all the primary analysis models described in the literature, and readily allows sensitivity analysis (to the missing at random assumption) to be performed. Having presented our framework, we illustrate its application to the analysis of the 2019 MOVE-IT trial of motivational interviewing to increase exercise.