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The coronavirus disease (COVID-19) pandemic has presented unique challenges for people with diabetes, in addition to their high-risk stratification for infection. Supporting people with diabetes to self-care has been critical to reduce their risk of severe infection. This global pandemic has presented an opportunity to digitalize diabetes care and rapidly implement virtual diabetes clinics, with the aim of optimizing diabetes management and well-being, while keeping patients safe. We performed a rapid review of the literature to evaluate the feasibility and effectiveness of virtual clinics in diabetes care before and during the COVID-19 pandemic and have combined these findings with our own reflections in practice. We identified examples demonstrating safety and feasibility of virtual diabetes clinics, which aligns with our own clinical experience during the pandemic. The advantages of virtual clinics include reduced treatment burden, improved therapeutic alliances, societal and psychological benefits, and in our experience, innovative solutions to overcome the challenges presented by the transition from in-person to virtual care. We have provided three infographics to illustrate lessons learned and key recommendations, including steps to establish a virtual diabetes clinic, a checklist guide for health care professionals conducting virtual clinics, and a patient guide for making the most out of the virtual clinic. It is important to continue adapting to this pandemic and to make technology a sustainable option for the future of diabetes care.

Digital health interventions (DHIs) are increasingly becoming integrated into diabetes self-management to improve behavior. Despite DHIs becoming available to people with chronic conditions, the development strategies and processes undertaken are often not well described. With theoretical frameworks available in current literature, it is vital that DHIs follow a shared language and communicate a robust development process in a comprehensive way. This paper aims to bring a unique perspective to digital development, as it describes the systematic process of developing a digital self-management program for people with type 2 diabetes, MyDESMOND. We provide a step-by-step guide, based on the intervention mapping (IM) framework to illustrate the process of adapting an existing face-to-face self-management program (diabetes education and self- management for ongoing and newly diagnosed, DESMOND) and translating it to a digital platform (MyDESMOND). Overall, this paper describes the 4 IM steps that were followed to develop MyDESMOND—step 1 to establish a planning group and a patient and public involvement group to describe the context of the intervention and program goals, step 2 to identify objectives and determinants at early design stages to maintain a focus on the strategies adopted, step 3 to generate the program components underpinned by appropriate psychological theories and models, and step 4 to develop the program content and describe the iterative process of refining the content and format of the digital program for implementation. This paper concludes with a number of key learnings collated throughout our development process, which we hope other researchers may find useful when developing DHIs for chronic conditions.

Background Office workers spend 70–85% of their time at work sitting. High levels of sitting have been linked to poor physiological and psychological health. Evidence shows the need for fully powered randomised controlled trials, with long-term follow-up, to test the effectiveness of interventions to reduce sitting time. Objective Our objective was to test the clinical effectiveness and cost-effectiveness of the SMART Work & Life intervention, delivered with and without a height-adjustable workstation, compared with usual practice at 12-month follow-up. Design A three-arm cluster randomised controlled trial. Setting Councils in England. Participants Office workers. Intervention SMART Work & Life is a multicomponent intervention that includes behaviour change strategies, delivered by workplace champions. Clusters were randomised to (1) the SMART Work & Life intervention, (2) the SMART Work & Life intervention with a height-adjustable workstation (i.e. SMART Work & Life plus desk) or (3) a control group (i.e. usual practice). Outcome measures were assessed at baseline and at 3 and 12 months. Main outcome measures The primary outcome was device-assessed daily sitting time compared with usual practice at 12 months. Secondary outcomes included sitting, standing, stepping time, physical activity, adiposity, blood pressure, biochemical measures, musculoskeletal issues, psychosocial variables, work-related health, diet and sleep. Cost-effectiveness and process evaluation data were collected. Results A total of 78 clusters (756 participants) were randomised [control, 26 clusters (n = 267); SMART Work & Life only, 27 clusters (n = 249); SMART Work & Life plus desk, 25 clusters (n = 240)]. At 12 months, significant differences between groups were found in daily sitting time, with participants in the SMART Work & Life-only and SMART Work & Life plus desk arms sitting 22.2 minutes per day (97.5% confidence interval –38.8 to –5.7 minutes/day; p = 0.003) and 63.7 minutes per day (97.5% confidence interval –80.0 to –47.4 minutes/day; p < 0.001), respectively, less than the control group. Participants in the SMART Work & Life plus desk arm sat 41.7 minutes per day (95% confidence interval –56.3 to –27.0 minutes/day; p < 0.001) less than participants in the SMART Work & Life-only arm. Sitting time was largely replaced by standing time, and changes in daily behaviour were driven by changes during work hours on workdays. Behaviour changes observed at 12 months were similar to 3 months. At 12 months, small improvements were seen for stress, well-being and vigour in both intervention groups, and for pain in the lower extremity and social norms in the SMART Work & Life plus desk group. Results from the process evaluation supported these findings, with participants reporting feeling more energised, alert, focused and productive. The process evaluation also showed that participants viewed the intervention positively; however, the extent of engagement varied across clusters. The average cost of SMART Work & Life only and SMART Work & Life plus desk was £80.59 and £228.31 per participant, respectively. Within trial, SMART Work & Life only had an incremental cost-effectiveness ratio of £12,091 per quality-adjusted life-year, with SMART Work & Life plus desk being dominated. Over a lifetime, SMART Work & Life only and SMART Work & Life plus desk had incremental cost-effectiveness ratios of £4985 and £13,378 per quality-adjusted life-year, respectively. Limitations The study was carried out in one sector, limiting generalisability. Conclusions The SMART Work & Life intervention, provided with and without a height-adjustable workstation, was successful in changing sitting time. Future work There is a need for longer-term follow-up, as well as follow-up within different organisations. Trial registration Current Controlled Trials ISRCTN11618007. Plain language summary Office workers spend a large proportion of their day sitting. High levels of sitting have been linked to diseases, such as type 2 diabetes, heart disease and some cancers. The SMART Work & Life intervention is designed to reduce office workers’ sitting time inside and outside work. The SMART Work & Life intervention involves organisational, environmental, group and individual strategies to encourage a reduction in sitting time and was designed to be delivered with and without a height-adjustable workstation (which allows the user to switch between sitting and standing while working). To test whether or not the SMART Work & Life intervention worked, we recruited 756 office workers from councils in Leicester/Leicestershire, Greater Manchester and Liverpool, UK. Participants were from 78 office groups. One-third of the participants received the intervention, one-third received the intervention with a height-adjustable workstation and one-third were a control group (and carried on as usual). Workplace champions in each office group were given training and resources to deliver the intervention. Data were collected at the start of the study, with follow-up measurements at 3 and 12 months. We measured sitting time using a small device worn on the thigh and collected data on weight, body fat, blood pressure, blood sugar and cholesterol levels. We asked participants about their health and work and spoke to participants to find out what they thought of the intervention. Our results showed that participants who received the intervention without workstation sat for 22 minutes less per day, and participants who received the intervention with workstation sat for 64 minutes less per day, than participants in the control group. Levels of stress, well-being, vigour (i.e. personal and emotional energy and cognitive liveliness) and pain in the lower extremity appeared to improve in the intervention groups. Participants viewed the intervention positively and reported several benefits, such as feeling more energised, alert, focused and productive; however, the extent to which participants engaged with the intervention varied across groups. Scientific summary Background High levels of sedentary behaviour (e.g. sitting, reclining or lying, and expending ≤ 1.5 metabolic equivalents) have been linked to poor health outcomes, including type 2 diabetes, cardiovascular disease, some cancers and premature mortality. In addition to physiological health outcomes, high levels of sitting are detrimentally associated with cognitive function, mental health and a lower quality of life. Working-age adults spend around 60–70% of their workday sitting, with workdays being more sedentary than non-workdays; however, this can vary by occupation. Office workers spend 70–85% of their time at work sitting and accumulate a large proportion (40–50%) of this time in prolonged sitting bouts. Office workers also typically spend a large proportion of their leisure time sitting, compared with other occupations. In the workplace, lower levels of sitting have been linked to higher work vigour, higher job performance and lower presenteeism. Workplaces are, therefore, an ideal setting for implementing interventions to reduce daily sitting. Current evidence shows a need for fully powered randomised controlled trials (RCTs) with long-term follow-up to test the effectiveness of interventions to reduce sitting. Previous work from our group, evaluating multicomponent interventions to address high levels of sitting in office workers, found that significant reductions in sitting time across the day were mainly driven by changes to workplace sitting and to not daily sitting, indicating that a whole-day approach to encourage reductions in daily sitting was needed to maximise the potential health benefits. Objectives The main aim of the study was to evaluate the clinical effectiveness and cost-effectiveness of the SMART Work & Life (SWAL) intervention (provided with and without a height-adjustable workstation) in a sample of desk-based office workers. If both interventions were shown to be effective in comparison with the control group, then a secondary aim would be to determine if one intervention was more clinically effective and cost-effective than the other. Primary objective To investigate the impact of the SWAL intervention, delivered with and without a height-adjustable workstation, on device-assessed daily sitting time compared with usual practice at 12 months’ follow-up. Secondary objectives To investigate the impact of the SWAL intervention, delivered with and without a height-adjustable workstation, over the short term (assessed at 3 months) and longer term (assessed at 12 months) on: daily sitting time on any valid day (3 months) and on workdays and non-workdays sitting time during work hours daily time spent standing and in light and moderate or vigorous physical activity (MVPA) across any valid day, during work hours and on workdays and non-workdays daily time spent stepping and number of steps across any valid day, during work hours and on workdays and non-workdays markers of adiposity [i.e. body mass index (BMI), per cent body fat, waist circumference] blood pressure blood biomarkers [i.e. fasting glucose, cholesterol, triglycerides, glycated haemoglobin (HbA1c)] musculoskeletal health psychosocial health (i.e. fatigue, stress, anxiety and depression, well-being and quality of life) work-related health and performance (i.e. work engagement, job performance and satisfaction, occupational fatigue, presenteeism, sickness absence) sleep duration and quality. To undertake a full economic analysis of the SWAL intervention. To conduct a mixed-methods process evaluation throughout the intervention implementation period (using qualitative and quantitative measures) with participants and workplace champions. Methods Design A three-arm cluster RCT with a cost-effectiveness and process evaluation analysis. Follow-up measures were taken at 3 and 12 months. Setting Local councils in Leicester, Leicestershire, Greater Manchester and Liverpool, UK. Participants Participants were recruited from across participating councils (i.e. Leicester City Council, Leicestershire County Council, Salford City Council, Bolton Council, Trafford Council and Liverpool City Council). Participants were office-based employees (aged ≥ 18 years) who spent the majority (≥ 50%) of their day sitting, were at least 60% full-time equivalent and were able to walk without assistance. Employees who were pregnant, who already used a height-adjustable workstation or were unable to communicate in English were not eligible. Participants were grouped into clusters either by a shared office space (although could be made up of different teams/departments) or if they were members of the same team but split into different office spaces. To be eligible, each cluster was required to have at least one participant willing to undertake the role of workplace champion and at least four participants in the cluster. Informed consent was obtained from participants before the baseline measurement session and verbal consent was confirmed at each follow-up. Sample size To detect a 60-minute difference in average daily sitting time between the intervention groups and the control group [assuming a sitting time standard deviation (SD) of 90 minutes, 90% power, a two-tailed significance level of 5%, an average cluster size of 10 (range 4–38), an intraclass correlation coefficient of 0.05, the number of clusters being inflated by a factor of 1.23, allowing for one cluster drop out per arm and a 40% loss to follow-up/non-compliance with the activPAL (PAL Technologies Ltd, Glasgow, UK)], the required sample size was 690 participants from 72 clusters. Testing two intervention arms independently with the control arm was also taken account of as part of the sample size calculation. Interventions The SWAL intervention is a multicomponent intervention grounded in several behaviour change theories, which aims to reduce daily sitting in office workers. The SWAL intervention includes organisational-level behaviour change strategies (e.g. management buy-in), environmental-level behaviour change strategies (e.g. relocating waster bins, printers) and group-/individual-level behaviour change strategies (e.g. education, action-planning, goal-setting, addressing barriers, group coaching, challenges, self-monitoring) that are delivered by workplace champions. After all baseline measures were carried out, clusters were randomised to one of the following three conditions: (1) SWAL only, (2) the SWAL intervention with the addition of a height-adjustable workstation (i.e. SWAL plus desk) or (3) the control group. Randomisation was stratified by area (i.e. Leicester, Salford or Liverpool) and cluster size [i.e. small (

In recent years, multiple countries worldwide have implemented behavioural interventions within national healthcare systems. Describing the content of these interventions is critical to improve their implementation, replication, and effectiveness, as well as to advance behavioural science. Tools, such as the Behaviour Change Technique Taxonomy, can enhance the quality of intervention description and reporting. As interventions are frequently developed without the use of such tools, retrospective coding of existing interventions to accurately characterise their content is becoming more common. However, the use of these tools for retrospective coding poses various challenges, the discussion of which has been neglected to date. This commentary discusses the challenges encountered when retrospectively describing the content of five nationally implemented programmes for type 2 diabetes in the United Kingdom and the Republic of Ireland and suggests recommendations to tackle these challenges. We present important methodological, practical, and ethical considerations for researchers to reflect on, relevant to the retrospective description of existing interventions. Specifically, we discuss (i) the importance of positive relationships and collaboration with intervention stakeholders, (ii) the practical and ethical considerations when analysing the content of implemented interventions, (iii) the independence of research teams and the potential for misclassification of intervention content, and (iv) the challenges associated with the analysis of intervention content using behavioural science tools. There is a growing demand for more robust approaches to address the methodological, practical, and ethical challenges associated with such studies. The present commentary describes key issues to be considered by research teams, as well as concrete recommendations to improve the retrospective characterisation of intervention content. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions Health education is integral to cardiometabolic disease (CMD) management. This study aimed to assess whether and how education preferences have changed over time, and whether trends differ by sociodemographic characteristics (education status, age, ethnicity, and sex).A cross‐sectional questionnaire was deployed across five counties in the East Midlands, UK between 2017 and 2022 to adults with CMD (type 2 diabetes, cardiovascular disease or cerebrovascular disease). Respondent demographic data were collected alongside health education preferences. Statistical analyses ascertained whether demographic characteristics influenced preferences. The distribution of preferences over time was charted to identify trends.A total of 4301 eligible responses were collected. Face‐to‐face one‐to‐one education was preferred (first choice for 75.1% of participants) but popularity waned over the five‐year period. Trends were similar amongst demographic groups. Online education showed a U‐shaped trend: In 2017, 44% of respondents ranked it as acceptable, peaking at 53% in 2019, but declining again, to below base line, 43%, by 2022. This modality was more popular with participants aged younger than 65 years, but popularity in people older than 65 years increased over the study period. The popularity of printed information also declined over time across all demographic groups except those of South Asian ethnicity, for whom it remained static.The overwhelming preference for face‐to‐face one‐to‐one health education from a doctor or nurse highlights the importance of preserving access to this modality, even in the face of current NHS pressures and trends towards digitalisation. Trends are changing, and should continue to be monitored, including between different sociodemographic groups. [ABSTRACT FROM AUTHOR]

Aims: Attendance at diabetes self‐management education and support (DSMES) programmes for type 2 diabetes is associated with positive outcomes, but the impact on some outcomes is inconsistent and tends to decline over time. Understanding the active ingredients of effective programmes is essential to optimise their effectiveness. This study aimed to (1) retrospectively identify behaviour change techniques (BCTs), mechanisms of action (MoAs) and intervention functions in two DSMES programmes, the Community‐Oriented Diabetes Education and the Diabetes Education and Self‐Management for Ongoing and Newly Diagnosed and (2) examine variation in content between programmes. Methods: A multiple case study approach, including a documentary analysis of the programme materials, was conducted. Materials were coded using the BCT Taxonomy v1, the Mode of Delivery Ontology v1 and the Intervention Source Ontology v1. The Behaviour Change Wheel guidance and the Theory and Techniques tool were used to identify intervention functions and MoAs. Programme stakeholders provided feedback on the findings. Results: Thirty‐four BCTs were identified across the programmes, with 22 common to both. The identified BCTs were frequently related to 'goals and planning', 'feedback and monitoring' and 'natural consequences'. BCTs were linked with 15 MoAs, predominantly related to reflective motivation ('beliefs about capabilities' and 'beliefs about consequences') and psychological capability ('knowledge'). BCTs served six intervention functions, most frequently 'education', 'enablement' and 'persuasion'. Conclusions: Although both programmes included several BCTs, some BCTs were rarely or never used. Additional BCTs could be considered to potentially enhance effectiveness by addressing a wider range of barriers. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To investigate the association between age at diagnosis of type 2 diabetes and depressive symptoms, diabetes-specific distress, and self-compassion among adults with type 2 diabetes. RESEARCH DESIGN AND METHODS: This analysis used data from the Chronotype of Patients with Type 2 Diabetes and Effect on Glycemic Control (CODEC) cross-sectional study. Information was collected on depressive symptoms, diabetes-specific distress, and self-compassion, measured using validated self-report questionnaires, in addition to sociodemographic and clinical data. Multivariable regression models, adjusted for diabetes duration, sex, ethnicity, deprivation status, prescription of antidepressants (selective serotonin reuptake inhibitors), and BMI were used to investigate the association between age at diagnosis of type 2 diabetes and each of the three psychological outcomes. RESULTS: A total of 706 participants were included; 64 (9.1%) were diagnosed with type 2 diabetes at <40 years, 422 (59.8%) between 40 and 59 years, and 220 (31.2%) at ≥60 years of age. After adjustment for key confounders, including diabetes duration, younger age at diagnosis was significantly associated with higher levels of depressive symptoms (βadj: −0.18 [95% CI −0.25 to −0.10]; P < 0.01) and diabetes-specific distress (βadj: −0.03 [95% CI −0.04 to −0.02]; P < 0.01) and lower levels of self-compassion (βadj: 0.01 [95% CI 0.00 to 0.02]; P < 0.01). CONCLUSIONS: Diagnosis of type 2 diabetes at a younger age is associated with lower psychological well-being, suggesting the need for clinical vigilance and the availability of age-appropriate psychosocial support. [ABSTRACT FROM AUTHOR]

Long-term needs of stroke survivors (especially psychosocial needs and stroke prevention) are not adequately addressed. Self-management programmes exist but the optimal content and delivery approach is unclear. We aim to describe the process undertook to develop a structured self-management programme to address these unmet needs. Based on the Medical Research Council framework for complex interventions, the development involved three phases: "Exploring the idea": Evidence synthesis and patient and public involvement (PPI) with stroke survivors, carers and healthcare professionals. "The iterative phase": Development and iterative refinement of the format, content, underpinning theories and philosophy of the self-management programme My Life After Stroke (MLAS), with PPI. MLAS consists of two individual appointments and four group sessions over nine weeks, delivered interactively by two trained facilitators. It aims to build independence, confidence and hope and focusses on stroke prevention, maximising physical potential, social support and managing emotional responses. MLAS is grounded in the narrative approach and social learning theory. "Ready for research": The refinement of a facilitator curriculum and participant resources to support programme delivery. Through a systematic process, we developed an evidence- and theory-based self-management programme for stroke survivors MLAS warrants evaluation in a feasibility study. My Life After Stroke(MLAS) has been developed using a systematic process, to address the unmet needs of stroke survivors. This systematic process, involved utilising evidence, theories, patient and public involvement, expertise and guidelines from other long-term conditions. This may further help the development of similar self-management programme within the field of stroke. MLAS warrants further evaluation within a feasibility study. [ABSTRACT FROM AUTHOR]

Abstract The process of obtaining ethical permission for medical research is particularly complex in multicentre studies. This article explores the experience of seeking approval for a mixed-method study of children's [...]