A Digital Program to Prevent Falls and Improve Well-Being in People Living with Dementia in the Community: the KOKU-LITE Feasibility Randomised Controlled Trial Protocol

medrxiv(2024)

引用 0|浏览3
摘要
Introduction: Around 885,000 people live with dementia in the UK of which around 50% experience a fall each year. Keep On Keep Up (KOKU) is an NHS approved gamified, digital health program designed to maintain function and reduce falls through strength & balance exercises (FaME/OTAGO), and health literacy games. KOKU has been adapted to the needs of people living with Dementia (PLwD) in the community, known as KOKU-LITE. This trial aims to test the feasibility and acceptability of trial processes and usability of KOKU-LITE. Methods and analysis: A two-arm, mixed methods, feasibility randomised controlled trial will be conducted. Participants aged 55 years and over meeting the eligibility criteria will be recruited from patient organisations across Greater Manchester, UK. Participants randomised into the intervention arm will receive 6 weeks KOKU-LITE and participants randomised into the control arm will continue with usual care. Outcome measures include: recruitment rate, adherence, quality of life, participants' Activities of Daily Living, physical activity levels, functional ability, lower limb strength, fear of falling, falls risk, mood, and users experience of the technology. Post-intervention interviews or focus groups with participants and health and social care professionals will explore feasibility of trial processes & technology and evaluate the usability and acceptability of the intervention respectively. Analyses will be descriptive. Ethics and dissemination: This feasibility trial has been reviewed and received favourable ethical approval from Yorkshire & The Humber - Bradford Leeds Research Ethics Committee, Newcastle upon Tyne (REC reference 23/YH/0262). The findings of the study will be disseminated through peer-reviewed scientific journals, at conferences, publication on University of Manchester, Applied Research Collaboration Greater Manchester (ARC-GM) and KOKU websites. Trial registration number: [NCT06149702][1] ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial NCT06149702 ### Funding Statement This work is supported by the National Institute of Health Research (NIHR) and Alzheimers Society (award number NIHR200174). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This feasibility trial has been reviewed and received favourable ethical approval from Yorkshire & The Humber - Bradford Leeds Research Ethics Committee, Newcastle upon Tyne (REC reference 23/YH/0262). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes At the end of the project, we will deposit a fully anonymised dataset in an open data repository - Figshare at the University of Manchester Library, as well as by request from the primary and corresponding author on reasonable request. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT06149702&atom=%2Fmedrxiv%2Fearly%2F2024%2F07%2F18%2F2024.07.17.24310446.atom
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
0
您的评分 :

暂无评分

数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn