Self-management Interventions for People With Parkinson Disease: Scoping Review

\ua9 2022 Journal of Medical Internet Research. All rights reserved. Background: Parkinson disease can impose substantial distress and costs on patients, their families and caregivers, and health care systems. To address these burdens for families and health care systems, there is a need to better support patient self-management. To achieve this, an overview of the current state of the literature on self-management is needed to identify what is being done, how well it is working, and what might be missing. Objective: The aim of this scoping review was to provide an overview of the current body of research on self-management interventions for people with Parkinson disease and identify any knowledge gaps. Methods: The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) and Population, Intervention, Comparator, Outcome, and Study type frameworks were used to structure the methodology of the review. Due to time and resource constraints, 1 reviewer systematically searched 4 databases (PubMed, Ovid, Scopus, and Web of Science) for the evaluations of self-management interventions for Parkinson disease published in English. The references were screened using the EndNote X9 citation management software, titles and abstracts were manually reviewed, and studies were selected for inclusion based on the eligibility criteria. Data were extracted into a pre-established form and synthesized in a descriptive analysis. Results: There was variation among the studies on study design, sample size, intervention type, and outcomes measured. The randomized controlled trials had the strongest evidence of effectiveness: 5 out of 8 randomized controlled trials found a significant difference between groups favoring the intervention on their primary outcome, and the remaining 3 had significant effects on at least some of the secondary outcomes. The 2 interventions included in the review that targeted mental health outcomes both found significant changes over time, and the 3 algorithms evaluated performed well. The remaining studies examined patient perceptions, acceptability, and cost-effectiveness and found generally positive results. Conclusions: This scoping review identified a wide variety of interventions designed to support various aspects of self-management for people with Parkinson disease. The studies all generally reported positive results, and although the strength of the evidence varied, it suggests that self-management interventions are promising for improving the care and outcomes of people with Parkinson disease. However, the research tended to focus on the motor aspects of Parkinson disease, with few nonmotor or holistic interventions, and there was a lack of evaluation of cost-effectiveness. This research will be important to providing self-management interventions that meet the varied and diverse needs of people with Parkinson disease and determining which interventions are worth promoting for widespread adoption

Developing a blockchain-based supply chain system for advanced therapies: study protocol

Advanced therapies, including cell and gene therapies, have shown therapeutic promise in curing life-threatening diseases such as leukaemia and lymphoma. However, they can be complicated and expensive to deliver due to their sensitivity to environment, troublesome tissue, cell, or genetic material sourcing and complicated regulatory requirements

Mobile apps for health behaviour change in physical activity, diet, drug and alcohol use, and mental health: a systematic review

Background: With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioural health interventions. The large variation in these mobile health apps - their target patient group, health behaviour, and behavioural change strategies - has resulted in a large but incohesive body of literature. Objective: The purpose of this systematic review was to assess the effectiveness of mobile apps at improving health behaviours and outcomes, and to examine the inclusion and effectiveness of Behaviour Change Techniques in mobile health apps. Methods: Medline, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behaviour change. Two authors independently screened and selected studies according to the eligibility criteria. Data was extracted and risk of bias assessed by one reviewer and validated by a second reviewer. Results: 52 randomized controlled trials met the inclusion criteria and were included in analysis - 37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive - only one app was rated as less helpful and satisfactory than the control - and the studies that measured engagement and usability found relatively high study completion rates (mean = 83.3%, n = 18) and ease of use ratings (3 significantly better than control, 9/15 rated >70%) . However, there was little evidence of changed behaviour or health outcomes. Conclusions: There was not strong evidence found to support the effectiveness of mobile apps at improving health behaviours or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the behaviour change techniques that are most effective at promoting behaviour change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias

Artificial Intelligence Applications for Assessment, Monitoring, and Management of Parkinson Disease Symptoms: Protocol for a Systematic Review

\ua9 2023 The authors.Background: Parkinson disease (PD) is the second most prevalent neurodegenerative disease, with around 10 million people with PD worldwide. Current assessments of PD symptoms are conducted by questionnaires and clinician assessments and have many limitations, including unreliable reporting of symptoms, little autonomy for patients over their disease management, and standard clinical review intervals regardless of disease status or clinical need. To address these limitations, digital technologies including wearable sensors, smartphone apps, and artificial intelligence (AI) methods have been implemented for this population. Many reviews have explored the use of AI in the diagnosis of PD and management of specific symptoms; however, there is limited research on the application of AI to the monitoring and management of the range of PD symptoms. A comprehensive review of the application of AI methods is necessary to address the gap of high-quality reviews and highlight the developments of the use of AI within PD care. Objective: The purpose of this protocol is to guide a systematic review to identify and summarize the current applications of AI applied to the assessment, monitoring, and management of PD symptoms. Methods: This review protocol was structured using the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) and the Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. The following 5 databases will be systematically searched: PubMed, IEEE Xplore, Institute for Scientific Information’s Web of Science, Scopus, and the Cochrane Library. Title and abstract screening, full-text review, and data extraction will be conducted by 2 independent reviewers. Data will be extracted into a predetermined form, and any disagreements in screening or extraction will be discussed. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 tool for randomized trials and the Mixed Methods Appraisal Tool for nonrandomized trials. Results: As of April 2023, this systematic review has not yet been started. It is expected to begin in May 2023, with the aim to complete by September 2023. Conclusions: The systematic review subsequently conducted as a product of this protocol will provide an overview of the AI methods being used for the assessment, monitoring, and management of PD symptoms. This will identify areas for further research in which AI methods can be applied to the assessment or management of PD symptoms and could support the future implementation of AI-based tools for the effective management of PD

Engineering requirements of a Herpes simplex virus patient registry: discovery phase of a real-world evidence platform to advance pharmacogenomics and personalized medicine

Comprehensive pharmacogenomic understanding requires both robust genomic and demographic data. Patient registries present an opportunity to collect large amounts of robust, patient-level data. Pharmacogenomic advancement in the treatment of infectious diseases is yet to be fully realised. Herpes simplex virus (HSV) is one disease for which pharmacogenomic understanding is wanting. This paper aims to understand the key factors that impact data collection quality for medical registries and suggest potential design features of an HSV medical registry to overcome current constraints and allow for this data to be used as a complement to genomic and clinical data to further the treatment of HSV. This paper outlines the discovery phase for the development of an HSV registry with the aim of learning about the users and their contexts, the technological constraints and the potential improvements that can be made. The design requirements and user stories for the HSV registry have been identified for further alpha phase development. The current landscape of HSV research and patient registry development were discussed. Through the analysis of the current state of the art and thematic user analysis, potential design features were elucidated to facilitate the collection of high-quality, robust patient-level data which could contribute to advances in pharmacogenomic understanding and personalised medicine in HSV. The user requirements specification for the development of an HSV registry has been summarised and implementation strategies for the alpha phase discussed

Ferrimagnetism and disorder in epitaxial Mn(2-x)Co(x)VAl thin films

The quaternary full Heusler compound Mn(2-x)Co(x)VAl with x = 1 is predicted to be a half-metallic antiferromagnet. Thin films of the quaternary compounds with x = 0...2 were prepared by DC and RF magnetron co-sputtering on heated MgO (001) substrates. The magnetic structure was examined by x-ray magnetic circular dichroism and the chemical disorder was characterized by x-ray diffraction. Ferrimagnetic coupling of V to Mn was observed for Mn2VAl (x = 0). For x = 0.5, we also found ferrimagnetic order with V and Co antiparallel to Mn. The observed reduced magnetic moments are interpreted with the help of band structure calculations in the coherent potential approximation. Mn2VAl is very sensitive to disorder involving Mn, because nearest-neighbor Mn atoms couple anti-ferromagnetically. Co2VAl has B2 order and has reduced magnetization. In the cases with x >= 0.9 conventional ferromagnetism was observed, closely related to the atomic disorder in these compounds.Comment: 10 pages, 4 figure

The Impact of a Digital Artificial Intelligence System on the Monitoring and Self-management of Nonmotor Symptoms in People With Parkinson Disease: Proposal for a Phase 1 Implementation Study

Copyright 2022 The Authors. 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\u27s 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\u27s 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\u27s success criteria will be affirming evidence regarding the system\u27s 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

Combining theory and experiment to characterize the voltammetric behavior of nickel anodes in the Simons process

The Simons process, otherwise known as the electrochemical fluorination (ECF) method, is widely used in industry to electrolytically synthesize chemicals for various purposes. Even to this day, the exact mechanism of the ECF reaction remains unknown, but is believed to involve the formation of an anodic nickel fluoride film with highly oxidized nickel centers. In this study, experiments and density functional theory calculations are combined to characterize the initial anodic peak occurring at potentials typically required in an ECF cell. NiF2 is believed to form a passivating layer at low potentials. The calculations show that a potential of +3.1 V is required to oxidize surface Ni2+ centers to Ni3+. This is in good agreement with the measured anodic peak at +3.57 V