NIHR open research最新文献

Background: Asthma is a prevalent non-communicable disease in high-income countries, affecting more than 10% of their populations. While often symptomatically mild it accounts for 2-3% of primary care appointments, 60,000 hospital admissions, and 1,200 deaths annually in England. Importantly, a significant proportion of these events are the result of poor adherence to prescribed and effective treatments, with 60% of hospital admissions attributed to suboptimal compliance. This study aims to support the development and commissioning of interventions by establishing the value case for improving medication adherence.

Methods: A probabilistic cohort decision model was developed with the aim of estimating the long-term health impacts and resultant costs to the healthcare system of different levels of population medication adherence for those with difficult-to-control asthma. The model applies a Markov structure based on the Global Initiative for Asthma (GINA) guidelines to define the level of asthma control. Informative parameters are drawn from existing published literature supplemented by expert input where required.

Results: Improved adherence is associated with reduced asthma exacerbations and better overall health of the cohort, measured in life years and quality-adjusted life years (QALYs). For instance, an educational intervention that increased adherence from 50% to 70% reduced exacerbations by 1.75 over 20 years, while increasing QALYs by 0.20, and reducing the healthcare costs by £989.

Conclusions: Significant economic and health benefits can be achieved with effective interventions to improve treatment adherence in asthma. This study provides a value case for developing and commissioning such interventions.

Background: High quality shared decision-making (SDM) conversations involve people with or at risk of osteoporosis and clinicians working together to decide, where appropriate, which evidence-based medicines best fit the person's life, beliefs, and values. The improving uptake of Fracture Prevention drug treatments (iFraP) intervention comprises a computerised Decision Support Tool (DST), clinician training package and information resources, designed for use in UK Fracture Liaison Service (FLS) consultations. The iFraP intervention will be tested in a pragmatic, parallel-group, individual randomised controlled trial in patients referred to four FLSs in England. This mixed methods process evaluation aims to assess which components of iFraP were delivered and how (fidelity), whether iFraP results in a change in osteoporosis drug treatment initiation rates and how, and how context affects implementation of iFraP and outcomes.

Methods: We will collect quantitative data using (1) Case Report Forms completed by FLS clinicians; (2) self-reported questionnaires completed by patient participants; and (3) DST analytic data. We will collect qualitative data using (1) semi-structured interviews with patients who receive the iFraP intervention in their FLS appointment, FLS clinicians delivering iFraP appointments, and primary care clinicians that have consulted with a patient following their iFraP FLS appointment; and (2) FLS consultation recordings. A triangulation protocol will be used to integrate the quantitative and qualitative findings to generate novel insights about the intervention under evaluation.

Discussion: The process evaluation, alongside the trial, will help to understand what elements of the iFraP intervention were delivered and how, the mechanisms of impact and how context affected implementation and outcomes, and intervention acceptability. Mixed methods interpretation will lead to further insights about the implementation of SDM and DSTs in-practice.

Trial registration: ISRCTN: 10606407, 21/11/2022 https://doi.org/10.1186/ISRCTN10606407.

Introduction: Despite significant social and financial investment, evidence suggests that technology-enabled care services (TECS) for older adults with assisted living needs fail to meet their potential. Simultaneously, an increasingly diverse range of care and consumer technologies are entering the market with the potential to deliver innovative, effective, cost-effective, and scalable social care services. However, there is limited evidence illustrating how novel digital technologies are currently being deployed across social care. Before high-quality evidence can be generated, we need a clearer sense of delivery, what outcomes are being achieved, and the factors influencing their implementation and adoption at scale.

Methods: DIALOGUE identifies the novel digital care technologies being implemented for social care services for community-dwelling older adults with assisted living needs that have the greatest potential for future social care research. Working with two local authorities and an Integrated Care Board, DIALOGUE adopted a mixed methods approach, including a rapid review of academic and professional literature regarding technology implementation in social care, three co-production partnerships with older people with assisted living needs using digital technologies in social care services, a process evaluation of social care TEC delivery, and an e-Delphi survey of TECS staff.

Results: Older adults using social care services identified priorities in relation to signposting and information seeking, safety, security and trust, and costs and financing technologies as key priorities. Local authorities highlighted building awareness and training in person-centred approaches to TECS, building the evidence base for TECS, and ensuring that commissioning and implementation of TECS is aligned with service user priorities.

Conclusion: Project findings are being used to build a programme for future research regarding effective person-centred implementation of Social Care TECS. Initial work in building this agenda includes applications for NIHR research Health Technology Assessment and Research Programme for Social Care funding during 2024-2025.

Background: E-cigarettes, also known as vapes, are lower risk products compared to conventional cigarettes, that can aid smoking cessation. However, they have been developed to also appeal to people who do not smoke, and are not harm-free. The challenge is for vaping policy to support smokers to quit whilst also protecting non-smokers from starting. Simulation modelling can be used to synthesise existing evidence and make predictions about policy impacts. This research aims to identify (a) data sources that can inform modelling of vape policies in the United Kingdom (UK) and (b) gaps in data that are required to undertake appropriate modelling.

Methods: We held stakeholder workshops with academic experts, policy makers and public members to understand the requirements of a simulation model of vaping policy and existing data. Based on the findings of the first workshop and a review of existing modelling studies, we undertook a set of targeted rapid reviews to augment key existing reviews. We also developed a dataset dictionary. From these, we developed key recommendations about data collection and modelling.

Results: There is substantial UK evidence around many of the transitions between smoking and vaping behaviours, but these have not yet been estimated simultaneously. We also identified 25 UK studies assessing the socioeconomic, psychological and social network influences on vaping behaviours. However, there is limited evidence about the effectiveness of vaping policies in the UK, the impact of industry circumvention, the health harms of vaping for people who have never smoked, longer term evidence on the smoking harms of vaping and the use and impact of illegal vapes.

Conclusions: Addressing the identified gaps in the evidence will require targeted new research. By fostering collaboration across disciplines and ensuring transparency and consistency in modelling, the UK can build a credible, evidence-based foundation for shaping effective vape regulation.

Background/aims: This paper describes the development (content, theory, and construction) of a patient-centered, structured, individually tailored, multicomponent intervention (the iRehab intervention) to promote rehabilitation and recovery after critical illness.

Methods: The intervention was informed by the MRC framework for complex interventions and underpinned by existing literature and psychological theories. Key stakeholders included patients who had been in intensive care and multidisciplinary staff with experience in providing healthcare and undertaking research.

Results: The final intervention includes four core components: 1. weekly discussion and guidance regarding symptom management; 2. targeted exercise and physical activity; 3. support for psychological well-being; 4. peer support and information provision. These are packaged as a program to support rehabilitation and recovery after ICU discharge.Programme duration: Six weeks.Format: Weekly one-to-one remote needs assessment to identify individual participant symptoms and provide management plans, exercises, and strategies to best support recovery. Participants are encouraged to attend weekly group-based remote exercise sessions and group-based remote support sessions (iRehab Café).Mode of delivery: Remote delivery facilitated by online platforms such as Microsoft Teams or Zoom supported with video platform BEAM©, and delivery can also be supported by telephone. The preferred mode of remote delivery is agreed with the participant, and potential barriers to implementation are considered. Manuals are posted to all participants to support intervention delivery.

Discussion/conclusion: This paper reports the content, theory and construction of the iRehab intervention. The iRehab intervention is currently being tested in a multicenter RCT (iRehab ISRCTN11266403), and the details reported in this paper will help with understanding of the intervention, interpretation of the findings, and replication of the intervention. Detailed intervention manuals will be available upon the completion of the trial.

Background: International guidelines recommend structured diabetes education to empower individuals with type 2 diabetes (T2D). While DESMOND is an effective programme for T2D management, it is often inaccessible to people with intellectual disabilities (ID) due to their unique needs. There is limited evidence on the effectiveness of adapted T2D education for this group, despite the importance of tailored support in preventing complications and early mortality.We previously adapted the DESMOND programme for adults with ID, creating DESMOND-ID. A feasibility study showed it is possible to recruit and deliver the programme to adults with ID and their carers, who found it valuable. Initial findings suggest DESMOND-ID may improve blood glucose control, warranting further investigation through a large-scale randomised controlled trial (RCT).

Methods: The "My Diabetes & Me" study will be conducted in two stages: an internal pilot and a main RCT. The pilot will recruit 108 participants over 10 months to assess recruitment and retention, using glycated haemoglobin (HbA1c, mmol/mol) at six months as the primary outcome. This will inform the design of the main study.Across both stages, 450 participants will be randomly assigned to receive either the DESMOND-ID intervention or treatment as usual (TAU). The intervention group, with their carers, will attend weekly sessions for seven weeks, plus two booster sessions at one and three months post-programme.Primary outcome is HbA1c at six months. Secondary outcomes include HbA1c at 12 and 18 months (pilot only), anthropometric data, self-reported outcomes, and other risk factors. A process evaluation will explore barriers and facilitators to implementation using qualitative and quantitative methods.

Conclusion: DESMOND-ID is the first structured T2D education programme tailored for adults with ID, and this RCT is the first to evaluate its clinical and cost-effectiveness.

Trial registration: 09/11/2022ISRCTN83150600 ( https://doi.org/10.1186/ISRCTN83150600).

Background: The growing pressure faced by adult social care in England has fuelled interest in technology-enabled care (TEC). This includes the use of sensor-based technology to monitor activity patterns for 'proactive' interventions and care. However, evidence on its effectiveness and use is limited to feasibility pilots, as opposed to business-as-usual. Working with three local authorities using home sensors, we sought to define good practices and draw transferable lessons on implementing and embedding this technology in routine care practice.

Methods: Across all sites, we interviewed 51 staff and system stakeholders, 19 service users and family/informal caregivers. We also used secondary data to determine the feasibility of a full economic study. The analysis was guided by the NASSS (non-adoption, abandonment, and challenges to scale-up, spread and sustainability) framework to explore factors influencing implementation and sustained adoption of the technology in use.

Results: Home sensors were used across multiple care contexts (assessment, reablement, and long-term care monitoring). Perceived value and impact included an increase in service user independence and safety, family/informal caregiver reassurance, identifying healthcare needs, providing more holistic and objective assessments, and supporting dialogue regarding care needs. However, evidence of the impact across these areas was limited, and we were unable to obtain the data required to undertake an economic analysis. Key issues to consider for sustained adoption include the materiality and dependability of the technology, compatibility with service users and their care networks, workforce knowledge and confidence, inter-organizational routines and coordination work, and strategic alignment.

Conclusion: Our findings indicate the need to acknowledge the labor-intensive process of embedding and adapting the use of home sensors for proactive care. Decision makers need to focus on how to support and resource incremental and system wide-changes, with particular attention paid to ensuring technology dependability, 'wrap around' support, workforce knowledge and skills, co-adaptation of inter-organization routines, cross-stakeholder collaboration, and evaluation capabilities.

Introduction: The urgency to address climate change and reduce carbon emissions in healthcare, highlighted in the United Kingdom (UK) by the 'Delivering a 'Net Zero' National Health Service (NHS)' report, emphasises the need for healthcare organisations to adopt and integrate sustainability practices. General practice is recognised as a major source of greenhouse gas emissions, but evidence on achieving effective decarbonisation in general practice is limited, a knowledge gap that urgently needs further research. This study protocol sets out a subsequent study designed to examine the current approaches general practice uses for decarbonisation and to provide practical recommendations for facilitating, advancing, and sustaining these efforts, contributing to the goal of a net zero NHS.

Methods and analysis: A 30-month longitudinal case study will span three geographical sites in England and use a mixed methods study design. It will adopt a comprehensive approach, merging sociological (Normalisation Process Theory - NPT) and behavioural theories (Theoretical Domains Framework - TDF) to understand and address factors influencing decarbonisation efforts in general practice. NPT focuses on collective behaviours, emphasising relationships and interactions among professionals, patients, and stakeholders. TDF, with 14 domains simplifying behavioural change theories, concentrates on individual, social, and environmental factors. A systematic review will be conducted, and quantitative and qualitative data will be collected over a 12-month period from general practice, staff, patients, public, and key stakeholders' perspectives through surveys, interviews, and focus groups. Additionally, a non-clinical carbon calculator, alongside prescribing data, will be gathered to assess measurable changes in carbon emissions, informing a budget impact model for practice-specific and generic use.

Dissemination: A dynamic dissemination and impact strategy will be emplyed aimed at ensuring broad awareness, adoption, and accelerated uptake of decarbonisation measures. Outputs, including lay summaries, factsheets, policy briefs and academic presentations will be produced throughout the study and undergo regular review, targeting key audiences and ensuring alignment with regional and national goals.

Background: Young people from minoritised ethnic backgrounds experience greater mental health needs and face greater challenges when accessing mental health support. We evaluated implementation of a new mental wellbeing service for minoritised young people in an urban youth centre.

Methods: We evaluated the service during its first 12 months of implementation. We held twelve interviews with four service practitioners and three paired interviews with six young people. Fieldnotes were taken and used to contextualise interview data. Practitioners recorded young people's attendance. Qualitative data were analysed thematically. Attendance data were analysed descriptively.

Results: The service included Four components: a weekly two-hour session with mental health practitioners in the youth centre, opportunistic wellbeing conversations and activities, mentoring, and referrals to therapeutic support. It was developed iteratively to allow time for relationships between practitioners and with young people to develop and for intervention to be tailored to the setting.Implementation was facilitated by the setting's positive influence, practitioners' lived experience, iterative development of the service, and establishing trusting relationships. Barriers included the informal nature of activities, slow service implementation, and young people's inconsistent attendance and reluctance to engage with the service. 94 young people attended at least one session.

Conclusion: Successful implementation of wellbeing services in community settings for minoritised young people can be affected by the informal and relaxed nature of the setting and the activities delivered, and the extent to which young people are willing to engage. Additionally, it requires relationship building and flexibility in delivery and pace. Future development and evaluation of similar services should consider these requirements.

Background: Despite global efforts to improve on vaccine impact, many African countries have failed to achieve equitable vaccine benefits. Reduced vaccine impact may result from interplay between structural, social, and biological factors, that limit communities from fully benefiting from vaccination programs. However, the combined influence of these factors to reduced vaccine impact and the spatial distribution of vulnerable communities remains poorly understood. We developed a Community Vaccine Impact Vulnerability Index (CVIVI) that integrates data on multiple risk factors associated with reduced vaccine impact, to identify communities at risk, and key drivers of vulnerability.

Methods: The index was constructed using 17 indicators selected through literature review and categorised into structural, social, and biological domains. Secondary data was obtained from national Demographic and Health surveys from Uganda (2016) and Kenya (2022), covering 123 districts and 47 counties, respectively. Percentile rank methodology was used to construct domain-specific and overall vulnerability indices.. Geo-spatial techniques were used to classify and map districts/counties from least to most vulnerable.

Results: We observed distinct geographical patterns in vulnerability.. In Kenya, the most vulnerable counties were clustered in the northeast and eastern counties such as Turkana, Mandera, and West Polot. In Uganda, vulnerability was more dispersed, with the most vulnerable districts in the northeast (e.g. Amudat, Lamwo) and southwest e.g. Buliisa,Kyenjojo). Key drivers of vulnerability included long distance to health facilities, low maternal education, poverty, malnutrition, limited access to postnatal care, and limited access to mass media. Some areas with high vaccine coverage also showed high vulnerability, suggesting coverage data may not reliably reflect vaccine impact. Each community showed a unique vulnerability profile, shaped by different combinations of social, structural and biological factors, highlighting the need for context specific interventions.

Conclusions: The CVIVI is a useful tool for identifying vulnerable communities and underlying factors. It can guide the design of tailored strategies to improve vaccine impact in vulnerable settings.