ABSTRACT
BACKGROUND: Nonmotor symptoms of Parkinson disease are a major factor of disease burden but are often underreported in clinical appointments. A digital tool has been developed to support the monitoring and management of nonmotor symptoms. OBJECTIVE: The aim of this study is to establish evidence of the impact of the system on patient confidence, knowledge, and skills for self-management of nonmotor symptoms, symptom burden, and quality of life of people with Parkinson and their care partners. It will also evaluate the usability, acceptability, and potential for adoption of the system for people with Parkinson, care partners, and health care professionals. METHODS: A mixed methods implementation and feasibility study based on the nonadoption, abandonment, scale-up, spread, and sustainability framework will be conducted with 60 person with Parkinson-care partner dyads and their associated health care professionals. Participants will be recruited from outpatient clinics at the University Hospitals Plymouth NHS Trust Parkinson service. The primary outcome, patient activation, will be measured over the 12-month intervention period; secondary outcomes include the system's impact on health and well-being outcomes, safety, usability, acceptability, engagement, and costs. Semistructured interviews with a subset of participants will gather a more in-depth understanding of user perspectives and experiences with the system. Repeated measures analysis of variance will analyze change over time and thematic analysis will be conducted on qualitative data. The study was peer reviewed by the Parkinson's UK Non-Drug Approaches grant board and is pending ethical approval. RESULTS: The study won funding in August 2021; data collection is expected to begin in December 2022. CONCLUSIONS: The study's success criteria will be affirming evidence regarding the system's feasibility, usability and acceptability, no serious safety risks identified, and an observed positive impact on patient activation. Results will be disseminated in academic peer-reviewed journals and in platforms and formats that are accessible to the general public, guided by patient and public collaborators. TRIAL REGISTRATION: ClinicalTrials.gov NCT05414071; https://clinicaltrials.gov/ct2/show/NCT05414071. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/40317.
ABSTRACT
BACKGROUND: Health care is shifting toward a more person-centered model; however, people with intellectual and developmental disabilities can still experience difficulties in accessing equitable health care. Given these difficulties, it is important to consider how humanizing principles, such as empathy and respect, can be best incorporated into health and social care practices for people with intellectual and developmental disabilities to ensure that they are receiving equitable treatment and support. OBJECTIVE: The purpose of our scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the development and implementation of interventions based on humanizing principles that aim to improve health and social care practices for people with intellectual and developmental disabilities. METHODS: The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) and PICOS (Population, Intervention, Comparator, Outcome, and Study) frameworks will be used to structure the review. A total of 6 databases (PubMed, MEDLINE, Embase, CINAHL, PsycINFO, and Web of Science) will be searched for English articles published in the previous 10 years that describe or evaluate health and social care practice interventions underpinned by the humanizing principles of empathy, compassion, dignity, and respect. Two reviewers will screen and select references based on the eligibility criteria and extract the data into a predetermined form. A descriptive analysis will be conducted to summarize the results and provide an overview of interventions in the following three main care areas: health care, social care, and informal social support. RESULTS: The results will be included in the scoping review, which is expected to begin in October 2022 and be completed and submitted for publication by January 2023. CONCLUSIONS: Our scoping review will summarize the state of the field of interventions that are using humanizing principles to improve health and social care for adults with intellectual and developmental disabilities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/31720.
ABSTRACT
BACKGROUND: Multimorbidity, which is associated with significant negative outcomes for individuals and health care systems, is increasing in the United Kingdom. However, there is a lack of knowledge about the risk factors (including health, behavior, and environment) for multimorbidity over time. An interdisciplinary approach is essential, as data science, artificial intelligence, and engineering concepts (digital twins) can identify key risk factors throughout the life course, potentially enabling personalized simulation of life-course risk for the development of multimorbidity. Predicting the risk of developing clusters of health conditions before they occur would add clinical value by enabling targeted early preventive interventions, advancing personalized care to improve outcomes, and reducing the burden on health care systems. OBJECTIVE: This study aims to identify key risk factors that predict multimorbidity throughout the life course by developing an intelligent agent using digital twins so that early interventions can be delivered to improve health outcomes. The objectives of this study are to identify key predictors of lifetime risk of multimorbidity, create a series of simulated computational digital twins that predict risk levels for specific clusters of factors, and test the feasibility of the system. METHODS: This study will use machine learning to develop digital twins by identifying key risk factors throughout the life course that predict the risk of later multimorbidity. The first stage of the development will be the training of a base predictive model. Data from the National Child Development Study, the North West London Integrated Care Record, the Clinical Practice Research Datalink, and Cerner's Real World Data will be split into subsets for training and validation, which will be done following the k-fold cross-validation procedure and assessed with the Prediction Model Risk of Bias Assessment Tool (PROBAST). In addition, 2 data sets-the Early-Life Data Cross-linkage in Research study and the Children and Young People's Health Partnership randomized controlled trial-will be used to develop a series of digital twin personas that simulate clusters of factors to predict different risk levels of developing multimorbidity. RESULTS: The expected results are a validated model, a series of digital twin personas, and a proof-of-concept assessment. CONCLUSIONS: Digital twins could provide an individualized early warning system that predicts the risk of future health conditions and recommends the most effective intervention to minimize that risk. These insights could significantly improve an individual's quality of life and healthy life expectancy and reduce population-level health burdens. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/35738.
ABSTRACT
Childhood obesity is one of the most serious public health challenges of the 21st century, with consequences lasting into adulthood. Internet of Things (IoT)-enabled devices have been studied and deployed for monitoring and tracking diet and physical activity of children and adolescents as well as a means of providing remote, ongoing support to children and their families. This review aimed to identify and understand current advances in the feasibility, system designs, and effectiveness of IoT-enabled devices to support weight management in children. We searched Medline, PubMed, Web of Science, Scopus, ProQuest Central and the IEEE Xplore Digital Library for studies published after 2010 using a combination of keywords and subject headings related to health activity tracking, weight management, youth and Internet of Things. The screening process and risk of bias assessment were conducted in accordance with a previously published protocol. Quantitative analysis was conducted for IoT-architecture related findings and qualitative analysis was conducted for effectiveness-related measures. Twenty-three full studies are included in this systematic review. The most used devices were smartphone/mobile apps (78.3%) and physical activity data (65.2%) from accelerometers (56.5%) were the most commonly tracked data. Only one study embarked on machine learning and deep learning methods in the service layer. Adherence to IoT-based approaches was low but game-based IoT solutions have shown better effectiveness and could play a pivotal role in childhood obesity interventions. Researcher-reported effectiveness measures vary greatly amongst studies, highlighting the importance for improved development and use of standardised digital health evaluation frameworks.
ABSTRACT
AIMS AND OBJECTIVES: To investigate the links between the binge pattern of drinking and the development of cognitive impairment in young adults in the UK. To determine from the findings whether cognitive impairment is an additional public health concern manifesting from this form of alcohol misuse and its relevance to nursing practice. BACKGROUND: Young adults in the UK are participating in binge drinking; a 'harmful' form of alcohol misuse. Morbidity and mortality associated with alcohol misuse is already a public health concern. DESIGN: Literature review. METHOD: Multiple database searches were undertaken, which revealed three case-control studies. The studies all investigated the binge pattern of drinking as well as meeting the following inclusion criteria; primary research published from 2005 onwards, used a human sample, participants were aged 18 to 24 and cognitive function was tested. RESULTS: The quantitative data found cognitive impairment present in young adult binge drinkers, specifically in regions of the frontal lobe, temporal lobe and hippocampus. Individually the studies did not pose strong enough evidence to generalise findings. However, collectively the core findings along with previous studies can validate the link between binge drinking and cognitive impairment. CONCLUSION: Nurse-led alcohol misuse screening and brief intervention is the most effective public health prevention strategy. It is important for nurses to keep abreast of current evidence to better inform their practice and the information they provide to their service users. This review emphasises the need for nurses to routinely screen young adults and address the associated risk to cognitive function when participating in harmful drinking.
