Publications
130 results found
Milne-Ives M, Homer SR, Andrade J, et al., 2023, Potential associations between behavior change techniques and engagement with mobile health apps: a systematic review, Frontiers in Psychology, Vol: 14, ISSN: 1664-1078
Introduction: Lack of engagement is a common challenge for digital health interventions. To achieve their potential, it is necessary to understand how best to support users’ engagement with interventions and target health behaviors. The aim of this systematic review was to identify the behavioral theories and behavior change techniques being incorporated into mobile health apps and how they are associated with the different components of engagement.Methods: The review was structured using the PRISMA and PICOS frameworks and searched six databases in July 2022: PubMed, Embase, CINAHL, APA PsycArticles, ScienceDirect, and Web of Science. Risk of bias was evaluated using the Cochrane Collaboration Risk of Bias 2 and the Mixed Methods Appraisal Tools.Analysis: A descriptive analysis provided an overview of study and app characteristics and evidence for potential associations between Behavior Change Techniques (BCTs) and engagement was examined.Results: The final analysis included 28 studies. Six BCTs were repeatedly associated with user engagement: goal setting, self-monitoring of behavior, feedback on behavior, prompts/cues, rewards, and social support. There was insufficient data reported to examine associations with specific components of engagement, but the analysis indicated that the different components were being captured by various measures.Conclusion: This review provides further evidence supporting the use of common BCTs in mobile health apps. To enable developers to leverage BCTs and other app features to optimize engagement in specific contexts and individual characteristics, we need a better understanding of how BCTs are associated with different components of engagement.Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022312596.
Milne-Ives M, Duun-Henriksen J, Blaabjerg L, et al., 2023, At home EEG monitoring technologies for people with epilepsy and intellectual disabilities: A scoping review, SEIZURE-EUROPEAN JOURNAL OF EPILEPSY, Vol: 110, Pages: 11-20, ISSN: 1059-1311
Hall AM, Aroori S, Carroll CB, et al., 2023, Impact of digital technologies on self-efficacy in people with Parkinson's: a scoping review protocol, BMJ OPEN, Vol: 13, ISSN: 2044-6055
Bounsall K, Milne-Ives M, Hall A, et al., 2023, Artificial Intelligence Applications for Assessment, Monitoring, and Management of Parkinson Disease Symptoms: Protocol for a Systematic Review, JMIR RESEARCH PROTOCOLS, Vol: 12, ISSN: 1929-0748
Meinert E, Milne-Ives M, Chaudhuri KR, et al., 2022, 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., JMIR Res Protoc, Vol: 11, ISSN: 1929-0748
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 acti
Milne-Ives M, Carroll C, Meinert E, 2022, Self-management Interventions for People With Parkinson Disease: Scoping Review, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 24, ISSN: 1438-8871
- Author Web Link
- Cite
- Citations: 1
Meinert E, Milne-Ives M, Chaudhuri KR, et al., 2022, The impact of a digital artificial intelligence system on the monitoring and self-management of non-motor symptoms in People with Parkinson’s: Proposal for a Phase 1 implementation study (Preprint)
<sec> <title>BACKGROUND</title> <p>Non-motor symptoms of Parkinson’s 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 NMS.</p> </sec> <sec> <title>OBJECTIVE</title> <p>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 NMS, symptom burden, and quality of life of people with Parkinson’s (PwP) and their care partners (CPs). It will also evaluate the usability, acceptability, and potential for adoption of the system for PwP, CPs, and healthcare professionals (HCPs).</p> </sec> <sec> <title>METHODS</title> <p>A mixed-methods implementation and feasibility study based on the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability framework will be conducted with 60 PwP-CP dyads and their associated HCPs. Participants will be recruited from outpatient clinics at the University Hospitals Plymouth NHS Trust’s Parkinson’s 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. Semi-structured interviews with a subset of participants will gather a more in-depth understanding of users' perspectives and experiences with the system. Repeated measures ANOVA will analyse change over time and thematic analysis will be conducted on qualitative data. The was peer-reviewed by the Parkinson’s UK Non-Drug Approaches grant board, and i
Milne-Ives M, Carroll C, Meinert E, 2022, Self-management interventions for people with Parkinson’s Disease: A scoping review (Preprint)
<sec> <title>BACKGROUND</title> <p>Parkinson’s disease can impose significant distress and costs on patients, families and caregivers, and healthcare systems. To address these burdens for families and the healthcare system, there is a need to better support patient self-management. To achieve this, there is a need for an overview of the current state of the literature on self-management, to identify what is being done, how well it is working, and what might be missing.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The purpose of this scoping review is to provide an overview of the current body of research on self-management interventions for people with Parkinson’s disease and to identify any knowledge gaps.</p> </sec> <sec> <title>METHODS</title> <p>The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks were used to structure the methodology of the review. One reviewer systematically searched four databases (PubMed, Ovid, Scopus, and Web of Science) for evaluations of self-management interventions for Parkinson’s 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 was extracted into a pre-established form and synthesised in a descriptive analysis.</p> </sec> <sec> <title>RESULTS</title> <p>There was variation a
Milne-Ives M, Rahman E, Bradwell H, et al., 2022, Acceptability and usability of a mobile app for family obesity prevention and management: A mixed-methods study (Preprint)
<sec> <title>BACKGROUND</title> <p>Childhood obesity is a growing global public health concern. Digital tools could encourage behaviour change for healthy lifestyles, but a better understanding of their strategies, adoption, and impact is needed to ensure that available tools actually benefit users. Health Education England developed a digital app (‘NoObesity’) to facilitate and improve communication between families and healthcare providers and to support healthy lifestyle behaviour change.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aim of the study was to collect evidence about the adoption and implementation of a family-focused app for childhood obesity prevention to inform further development. Specific objectives included examining the app’s usability, acceptability, and perceived impact, identifying barriers to engaging with the app and to changing behaviour, and gathering suggestions for improvement.</p> </sec> <sec> <title>METHODS</title> <p>225 parents were enrolled to evaluate a family app for childhood obesity prevention. Users’ experiences with the app and its perceived impact on motivation, self-efficacy, and behaviours were analysed based on two conceptual frameworks: the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) and Non-adoption, Abandonment and Challenges to the Scale-up, Spread and Suitability (NASSS) frameworks. The study took place between March 2020 and April 2021.</p> </sec> <sec> <title>RESULTS</title> <p>Thematic analysis found that goal-setting, prompts, and sug
Milne-Ives M, Fraser L, Khan A, et al., 2022, Life.course digital T.wins – I.ntelligent M.onitoring for E.arly and continuous intervention and prevention (LifeTIME): Proposal for a proof-of-concept study, JMIR Research Protocols, Vol: 11, ISSN: 1929-0748
Introduction: Multimorbidity, which is associated with significant negative outcomes for individuals and healthcare systems, is increasing in the UK. However, there is a lack of knowledge about the risk factors (including health, behaviour, and environment) for multimorbidity over time. An interdisciplinary approach is essential, as data science, artificial intelligence, and concepts from engineering (digital twins), have the potential to enable personalised simulation of life-course risk for the development of multimorbidity by identifying key risk factors throughout the life course. Predicting the risk of developing clusters of health conditions before they occur would add clinical value by enabling targeted early preventive interventions, advancing personalised care to improve outcomes, and reducing the burden on the UK’s healthcare systems. This study aims to identify key risk factors that predict multimorbidity throughout the lifetime through the development of 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 levels of risk for specific clusters of factors, and test the feasibility of the system. Methods: This study will use machine learning to identify key risk factors throughout life that predict the risk of later multimorbidity to develop digital twins. The first stage of the development will be the training of a base predictive model. Data from the National Child Development Study (NCDS), the North West London Integrated Care Record (NWL ICR), the Clinical Practice Research Datalink (CPRD), 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 PROBAST risk of bias tool. Two additional datasets - from the e
Meinert E, 2022, Humanising health and social care support for people with intellectual and developmental disabilities: Protocol for a scoping review, JMIR Research Protocols, Vol: 11, ISSN: 1929-0748
Background:Healthcare is shifting towards a more person-centred model, however, people with intellectual and developmental disabilities can still experience difficulties in accessing equitable healthcare. Given these difficulties, it is important to consider how 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 they are receiving humanising and equitable treatment and support.Objective:The purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the development and implementation of interventions based on humanising principles that aim to improve health and social care practices for people with intellectual and developmental disabilities.Methods:The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks will be used to structure the review. Six databases (PubMed, MEDLINE, Embase, CINAHL, PsycInfo, and Web of Science) will be searched for articles published in English in the previous 10 years that describe or evaluate health and social care practice interventions under-pinned by humanising principles of empathy, compassion, dignity, and respect. Two reviewers will collaboratively screen and select references based on the eligibility criteria and extract the data into a predetermined form. A descriptive analysis will be conducted to summarise the results and provide an overview of interventions in three main care areas: health care, social care, and informal social support.Results:Results will be included in the scoping review, which will be submitted for publication by June 2022.Conclusions:This scoping review will summarize the state of the field of interventions that are using humanising principles to improve health and social care for adults with in
Milne-Ives M, Carroll C, Meinert E, 2022, Self-management interventions for people with Parkinson’s Disease: A scoping review (Preprint)
<sec> <title>BACKGROUND</title> <p>Parkinson’s disease can impose significant distress and costs on patients, families and caregivers, and healthcare systems. To address these burdens for families and the healthcare system, there is a need to better support patient self-management. To achieve this, there is a need for an overview of the current state of the literature on self-management, to identify what is being done, how well it is working, and what might be missing.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The purpose of this scoping review is to provide an overview of the current body of research on self-management interventions for people with Parkinson’s disease and to identify any knowledge gaps.</p> </sec> <sec> <title>METHODS</title> <p>The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks were used to structure the methodology of the review. One reviewer systematically searched four databases (PubMed, Ovid, Scopus, and Web of Science) for evaluations of self-management interventions for Parkinson’s 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 was extracted into a pre-established form and synthesised in a descriptive analysis.</p> </sec> <sec> <title>RESULTS</title> <p>There was variation a
Khan A, Milne-Ives M, Meinert E, et al., 2022, A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic, BIOMEDICAL ENGINEERING AND COMPUTATIONAL BIOLOGY, Vol: 13, ISSN: 1179-5972
- Author Web Link
- Cite
- Citations: 3
Maramba I, Jones R, Austin D, et al., 2022, The role of health kiosks: a scoping review, JMIR Medical Informatics, Vol: 10, ISSN: 2291-9694
Background: Health kiosks are publicly accessible computing devices that provide access to services including health information provision, clinical measurement collection, patient self-check-in, telemonitoring and teleconsultation. While the increase in internet access and ownership of smart personal devices could make kiosks redundant, recent reports have predicted that the market will continue to grow. Objectives: We sought to clarify the current and future roles of health kiosks by investigating: (a) the setting, role, and clinical domains in which kiosks are used; (b) whether usability evaluations of health kiosks are being reported and if so, what methods are being utilized; and (c) what the barriers and facilitators are for the deployment of kiosks.Methods: We conducted a scoping review by a bibliographic search of the Google Scholar, PubMed and Web of Science databases for studies and other publications between January 2009 and June 2020. Eligible papers describe the implementation, either as primary studies, systematic reviews, or news and feature articles. Additional reports were obtained by manual searching and through querying key informants. For each article we abstracted settings, purposes, health domains, whether the kiosk was opportunistic or integrated with a clinical pathway, and inclusion of usability testing. We then summarized the data in frequency tables. Results: A total of 141 articles were included, 134 primary studies and seven reviews. 47% of the primary studies described kiosks in secondary care settings, other settings included community (23.9%), primary care (17.9%), and pharmacies (6.0%). The most common roles of health kiosks were providing health information (35.1%), taking clinical measurements (20.9%), screening (12.7%), telehealth (8.2%), and patient registration (6.0%). The five most frequent health domains were multiple conditions (24.6%), Human Immunodeficiency Virus (HIV) (7.5%), hypertension (7.5%), pediatric injuries (5.2%)
Lam C, Meinert E, Yang A, et al., 2022, Impact of fast-track regulatory designations on strategic commercialization decisions for autologous cell therapies, REGENERATIVE MEDICINE, Vol: 17, Pages: 155-174, ISSN: 1746-0751
Milne-Ives M, Homer S, Andrade J, et al., 2022, Associations Between Behavior Change Techniques and Engagement With Mobile Health Apps: Protocol for a Systematic Review, JMIR RESEARCH PROTOCOLS, Vol: 11, ISSN: 1929-0748
- Author Web Link
- Cite
- Citations: 1
Milne-Ives M, Shankar R, Mclean B, et al., 2022, Remote EEG monitoring of epilepsy in adults: A scoping review protocol, JMIR Research Protocols, Vol: 11, Pages: 1-6, ISSN: 1929-0748
Background: Electroencephalography (EEG) monitoring is a key tool in diagnosing and determining treatment for people with epilepsy; however, obtaining sufficient high-quality data can be a time-consuming, costly, and inconvenient process for patients and healthcare providers. Remote EEG monitoring has the potential to improve patient experience, data quality, and accessibility for people with intellectual or developmental disabilities. Objective: The purpose of this scoping review is to provide an overview of the current research evidence and knowledge gaps regarding the use of remote EEG monitoring interventions for adults with epilepsy. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks will be used to structure the review. Searches will be conducted in six databases (PubMed, MEDLINE, Embase, CINAHL, Web of Science, and ClinicalTrials.gov) for articles published in English that evaluate at least one out-of-hospital EEG monitoring intervention or device for adults with epilepsy. A descriptive analysis will be conducted to summarise the results and key themes and gaps in the literature will be discussed. Results: Results will be included in the scoping review, which will be submitted for publication by March 2022. Conclusions: This scoping review will summarize the state of the field of remote EEG monitoring interventions for adults with epilepsy and provide an overview of the strengths, weaknesses, and gaps in the research.
Milne-Ives M, Leyden J, Maramba I, et al., 2022, The Potential Impacts of a Digital Preoperative Assessment Service on Appointments, Travel-Related Carbon Dioxide Emissions, and User Experience: Case Study., JMIR Perioper Med, Vol: 5
BACKGROUND: The National Health Service (NHS) cannot keep up with the demand for operations and procedures. Preoperative assessments can be conducted on the internet to improve efficiency and reduce wait times for operations. MyPreOp is a cloud-based platform where patients can complete preoperative questionnaires. These are reviewed by a nurse who determines whether they need a subsequent face-to-face appointment. OBJECTIVE: The primary objective of this study is to describe the potential impact of MyPreOp (Ultramed Ltd) on the number of face-to-face appointments. The secondary objectives are to examine the time spent on preoperative assessments completed using MyPreOp in NHS Trusts and user ratings of usability and acceptability. METHODS: The study design was a case study service evaluation. Data were collected using the MyPreOp system from 2 NHS Trusts (Guy's and St Thomas' and Royal United Hospitals Bath) and the private BMI Bath Clinic during the 4-month period from September to December 2020. Participants were adults of any age and health status at the participating hospitals who used MyPreOp to complete a preoperative assessment before a scheduled surgery. The primary outcome was the number of face-to-face appointments avoided by patients who used MyPreOp. The investigated secondary outcomes included the length of time spent by nurses completing preoperative assessments, associated travel-related carbon dioxide emissions compared with standard care, and quantitative user feedback. User feedback was assessed at all 3 sites; however, the other outcomes could only be examined in the Royal United Hospitals Bath sample because of data limitations. RESULTS: Data from 2500 participants were included. Half of the assessed patients did not need a further face-to-face appointment and required a median of only 5.3 minutes of nurses' time to review. The reduction in appointments was associated with a small saving of carbon dioxide equivalent emissions (9.05 tons). Patien
Milne-Ives M, Fraser LK, Khan A, et al., 2021, Life Course Digital Twins–Intelligent Monitoring for Early and Continuous Intervention and Prevention (LifeTIME): Proposal for a Retrospective Cohort Study (Preprint)
<sec> <title>BACKGROUND</title> <p>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.</p> </sec> <sec> <title>OBJECTIVE</title> <p>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.</p> </sec> <sec> <title>METHODS</title> <p>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.
Milne-Ives M, Homer S, Andrade J, et al., 2021, Associations Between Behavior Change Techniques and Engagement With Mobile Health Apps: Protocol for a Systematic Review (Preprint)
<sec> <title>BACKGROUND</title> <p>Digitally enabled care along with an emphasis on self-management of health is steadily growing. Mobile health apps provide a promising means of supporting health behavior change; however, engagement with them is often poor and evidence of their impact on health outcomes is lacking. As engagement is a key prerequisite to health behavior change, it is essential to understand how engagement with mobile health apps and their target health behaviors can be better supported. Although the importance of engagement is emphasized strongly in the literature, the understanding of how different components of engagement are associated with specific techniques that aim to change behaviors is lacking.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The purpose of this systematic review protocol is to provide a synthesis of the associations between various behavior change techniques (BCTs) and the different components and measures of engagement with mobile health apps.</p> </sec> <sec> <title>METHODS</title> <p>The review protocol was structured using the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) and the PICOS (Population, Intervention, Comparator, Outcome, and Study type) frameworks. The following seven databases will be systematically searched: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, APA PsycInfo, ScienceDirect, Cochrane Library, and Web of Science. 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, any disagreements in screening or data extraction wil
Milne-Ives M, Shankar R, McLean B, et al., 2021, Remote Electroencephalography Monitoring of Epilepsy in Adults: Protocol for a Scoping Review (Preprint)
<sec> <title>BACKGROUND</title> <p>Electroencephalography (EEG) monitoring is a key tool in diagnosing and determining treatment for people with epilepsy; however, obtaining sufficient high-quality data can be a time-consuming, costly, and inconvenient process for patients and health care providers. Remote EEG monitoring has the potential to improve patient experience, data quality, and accessibility for people with intellectual or developmental disabilities.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The purpose of this scoping review is to provide an overview of the current research evidence and knowledge gaps regarding the use of remote EEG monitoring interventions for adults with epilepsy.</p> </sec> <sec> <title>METHODS</title> <p>The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks will be used to structure the review. Searches will be conducted in 6 databases (PubMed, MEDLINE, Embase, CINAHL, Web of Science, and ClinicalTrials.gov) for articles published in English that evaluate at least one out-of-hospital EEG monitoring intervention or device for adults with epilepsy. A descriptive analysis will be conducted to summarize the results; key themes and gaps in the literature will be discussed.</p> </sec> <sec> <title>RESULTS</title> <p>Results will be included in the scoping review, which will be submitted for publication by April 2022.</p> </sec>
Milne-Ives M, Lam C, Meinert E, 2021, Digital technologies for monitoring and improving treatment adherence in children and adolescents with asthma: A scoping review of randomised controlled trials, JMIR Public Health and Surveillance, Vol: 4, Pages: 1-12, ISSN: 2369-2960
Background: Inadequate paediatric asthma care has resulted in potentially avoidable unplanned hospital admissions and morbidity. A wide variety of digital technologies have been developed to help monitor and support treatment adherence for children and adolescents with asthma. However, existing reviews need to be updated and expanded to provide an overview of the current state of research around these technologies and how they are being integrated into existing healthcare services and care pathways. Objective: The purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the use of digital technologies to support the care of children and adolescents with asthma. Methods: The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. Five databases (PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, EMBASE, and PsycINFO) were systematically searched for studies published in English from 2014 on. Two reviewers independently screened the references and selected studies for inclusion based on the eligibility criteria. Data was systematically extracted per research questions, which were synthesised in a descriptive analysis.Results: A wide variety in study characteristics - including the number and age of participants, study duration, and type of digital intervention - was identified. There was mixed evidence for the effectiveness of the interventions; 7 of the 10 studies that evaluated treatment adherence found improvements, but the evidence was inconsistent for asthma control (6/9 reported improvement or maintenance, but only one was significantly different between groups) and health outcome variables (5/9 found no evidence of effectiveness). The 6 studies that examined patient perceptions and assessment
Chatterjee A, Strong G, Meinert E, et al., 2021, The use of video for patient information and education: A scoping review of the variability and effectiveness of interventions, PATIENT EDUCATION AND COUNSELING, Vol: 104, Pages: 2189-2199, ISSN: 0738-3991
- Author Web Link
- Cite
- Citations: 4
de Pennington N, Mole G, Lim E, et al., 2021, Safety and acceptability of a natural language artificial intelligence assistant to deliver clinical follow-up to cataract surgery patients: proposal, JMIR Research Protocols, Vol: 10, ISSN: 1929-0748
Background:Due to an aging population, the demand for many services is exceeding the capacity of the clinical workforce. As a result, staff are facing a crisis of burnout from being pressured to deliver high-volume workloads, driving increasing costs for providers. Artificial intelligence (AI), in the form of conversational agents, presents a possible opportunity to enable efficiency in the delivery of care.Objective:This study aims to evaluate the effectiveness, usability, and acceptability of Dora agent: Ufonia’s autonomous voice conversational agent, an AI-enabled autonomous telemedicine call for the detection of postoperative cataract surgery patients who require further assessment. The objectives of this study are to establish Dora’s efficacy in comparison with an expert clinician, determine baseline sensitivity and specificity for the detection of true complications, evaluate patient acceptability, collect evidence for cost-effectiveness, and capture data to support further development and evaluation.Methods:Using an implementation science construct, the interdisciplinary study will be a mixed methods phase 1 pilot establishing interobserver reliability of the system, usability, and acceptability. This will be done using the following scales and frameworks: the system usability scale; assessment of Health Information Technology Interventions in Evidence-Based Medicine Evaluation Framework; the telehealth usability questionnaire; and the Non-Adoption, Abandonment, and Challenges to the Scale-up, Spread and Suitability framework.Results:The evaluation is expected to show that conversational technology can be used to conduct an accurate assessment and that it is acceptable to different populations with different backgrounds. In addition, the results will demonstrate how successfully the system can be delivered in organizations with different clinical pathways and how it can be integrated with their existing platforms.Conclusions:The project’s ke
Milne-Ives M, Shankar R, Goodley D, et al., 2021, Humanizing Health and Social Care Support for People With Intellectual and Developmental Disabilities: Protocol for a Scoping Review (Preprint)
<sec> <title>BACKGROUND</title> <p>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.</p> </sec> <sec> <title>OBJECTIVE</title> <p>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.</p> </sec> <sec> <title>METHODS</title> <p>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
Milne-Ives M, Swancutt D, Burns L, et al., 2021, The effectiveness and usability of online, group-based interventions for people with severe obesity: Systematic review protocol, JMIR Research Protocols, Vol: 10, Pages: 1-7, ISSN: 1929-0748
Background: Globally, obesity is a growing crisis. Despite obesity being preventable, over a quarter of the United Kingdom adult population is currently considered clinically obese (typically Body Mass Index ≥35kg/m2). Access to treatment for people with severe obesity is limited by long wait times and local availability. Online and group-based interventions provide means of increasing the accessibility of obesity prevention and treatment services. However, there has been no prior review of the effectiveness of group-based interventions delivered online for people with severe obesity. Objective: The purpose of this systematic review protocol is to provide an evaluation of the effectiveness and usability of different types of online, group-based interventions for people with severe obesity. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols and the Population, Intervention, Comparator, and Outcome frameworks were used to structure this review. The review will systematically search seven databases: Medline, Embase, the Cumulative Index of Nursing and Allied Health Literature, American Psychological Association PsycNet, Web of Science, the Cochrane Library, and the ProQuest Dissertations and Theses databases. Two authors will independently screen the titles and abstracts of identified articles, select studies for inclusion based on the eligibility criteria, and extract data into a standardized form. Any disagreements will be discussed and resolved by a third reviewer if necessary. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias tool and a descriptive analysis will be used to evaluate effectiveness and usability.Results: The systematic review has not yet been started. It is expected to be completed and submitted for publication by May 2021. Conclusions: This systematic review will summarize the effectiveness and usability of online, group-based interventions for people with obesity. It will identify
Milne-Ives M, Neill S, Bayes N, et al., 2021, The impact of digital educational interventions to support parents caring for acutely ill children at home and factors that affect their use: systematic review protocol, JMIR Research Protocols, Vol: 10, ISSN: 1929-0748
Emergency and urgent care healthcare services are overburdened and the use of these services by acutely ill infants and children is increasing. A large proportion of these visits could be sufficiently addressed by other healthcare professionals. Uncertainty about the severity of a child’s symptoms is one of many factors that play a role in parents’ decisions to take their children to emergency services, demonstrating the need for improved support for health literacy. Digital interventions are a potential tool to improve parents’ knowledge, confidence, and self-efficacy at managing acute childhood illness. However, existing systematic reviews related to this topic need to be updated and expanded to provide a contemporary review of the impact, usability, and limitations of these solutions.
Surodina S, Lam C, Grbich S, et al., 2021, Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study., JMIRx Med, Vol: 2
BACKGROUND: Researching people with herpes simplex virus (HSV) is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity. OBJECTIVE: This project aimed to improve data collection for a real-world HSV registry by identifying predictors of HSV infection and selecting a limited number of relevant questions to ask new registry users to determine their level of HSV infection risk. METHODS: The US National Health and Nutrition Examination Survey (NHANES, 2015-2016) database includes the confirmed HSV type 1 and type 2 (HSV-1 and HSV-2, respectively) status of American participants (14-49 years) and a wealth of demographic and health-related data. The questionnaires and data sets from this survey were used to form two data sets: one for HSV-1 and one for HSV-2. These data sets were used to train and test a model that used a random forest algorithm (devised using Python) to minimize the number of anonymous lifestyle-based questions needed to identify risk groups for HSV. RESULTS: The model selected a reduced number of questions from the NHANES questionnaire that predicted HSV infection risk with high accuracy scores of 0.91 and 0.96 and high recall scores of 0.88 and 0.98 for the HSV-1 and HSV-2 data sets, respectively. The number of questions was reduced from 150 to an average of 40, depending on age and gender. The model, therefore, provided high predictability of risk of infection with minimal required input. CONCLUSIONS: This machine learning algorithm can be used in a real-world evidence registry to collect relevant lifestyle data and identify individuals' levels of risk of HSV infection. A limitation is the absence of real user data and integration with electronic medical records, which would enable model learning and improvement. Future work will explore model adjustments, anonymization options, explicit permissions, and a standardized data schema that meet the General Data Protection Regulation, Health Insurance Porta
Surodina S, Lam C, Grbich S, et al., 2021, Authors’ Response to Peer Reviews of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study”, JMIRx Med, Vol: 2, Pages: e28917-e28917
<jats:p />
Milne-Ives M, Lam C, Rehman N, et al., 2021, Distributed ledger infrastructure to verify adverse event reporting (DeLIVER): proposal for a proof-of-concept study, JMIR Research Protocols, Vol: 10, ISSN: 1929-0748
Background: Adverse drug event reporting is critical for ensuring patient safety; however, numbers of reports have been declining. There is a need for a more user-friendly reporting system and for a means of verifying reports that have been filed. Objectives: This project has two main objectives: 1) to identify the perceived benefits and barriers in the current reporting of adverse events by patients and healthcare providers and 2) to develop a distributed ledger infrastructure and user interface to collect and collate adverse event reports to create a comprehensive and interoperable database.Methods: A review of the literature will be conducted to identify the strengths and limitations of the current UK adverse event reporting system (the Yellow Card System). If insufficient information is found in this review, a survey will be created to collect data from system users. The results of these investigations will be incorporated into the development of a mobile and web app for adverse event reporting. A digital infrastructure will be built using distributed ledger technology to provide a means of linking reports with existing pharmaceutical tracking systems. Results: The key outputs of this project will be the development of a digital infrastructure including the backend distributed ledger system and the app-based user interface.Conclusions: This infrastructure is expected to improve the accuracy and efficiency of adverse event reporting systems by enabling the monitoring of specific medicines or medical devices over their life course while protecting patients’ personal health data.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.