Imperial College London

EUR ING Dr Edward A Meinert

Faculty of MedicineSchool of Public Health

Honorary Senior Lecturer
 
 
 
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Contact

 

e.meinert14

 
 
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Location

 

Reynolds BuildingCharing Cross Campus

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Summary

 

Publications

Publication Type
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125 results found

Milne-Ives M, Carroll C, Meinert E, 2022, Self-management Interventions for People With Parkinson Disease: Scoping Review., J Med Internet Res, Vol: 24

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

Journal article

Milne-Ives M, Fraser L, Khan A, Walker D, van Velthoven MH, May J, Wolfe I, Harding T, Meinert Eet 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

Journal article

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

Journal article

Khan A, Milne-Ives M, Meinert E, Iyawa GE, Jones RB, Josephraj ANet 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

Journal article

Maramba I, Jones R, Austin D, Edwards K, Meinert E, Chatterjee Aet 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%)

Journal article

Milne-Ives M, Homer S, Andrade J, Meinert E, Milne-Ives Met 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

Journal article

Milne-Ives M, Shankar R, Mclean B, Duun-Henriksen J, Blaabjerg L, Meinert Eet 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.

Journal article

Milne-Ives M, Leyden J, Maramba I, Chatterjee A, Meinert Eet 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

Journal article

Lam C, Meinert E, Yang A, Cui Zet 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

Journal article

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

Journal article

Chatterjee A, Strong G, Meinert E, Milne-Ives M, Halkes M, Wyatt-Haines Eet 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

Journal article

de Pennington N, Mole G, Lim E, Normando E, Xue K, Meinert Eet 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

Journal article

Milne-Ives M, Swancutt D, Burns L, Pinkney J, Tarrant M, Calitri R, Chatterjee A, Meinert Eet 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

Journal article

Milne-Ives M, Neill S, Bayes N, Blair M, Blewitt J, Bray L, Carrol ED, Carter B, Dawson R, Dimitri P, Lakhanpaul M, Roland D, Tavare A, Meinert E, and rest of the ASK SNIFF Consortiumet 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.

Journal article

Surodina S, Lam C, Grbich S, Milne-Ives M, van Velthoven M, Meinert Eet 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

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Journal article

Surodina S, Lam C, Grbich S, Milne-Ives M, van Velthoven M, Meinert Eet 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, Pages: e25560-e25560

<jats:sec> <jats:title>Background</jats:title> <jats:p>Researching people with herpes simplex virus (HSV) is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity.</jats:p> </jats:sec> <jats:sec> <jats:title>Objective</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>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.</jats:p>

Journal article

Milne-Ives M, Lam C, Rehman N, Sharif R, Meinert Eet 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.

Journal article

Lam C, Meinert E, Yang A, Cui Zet al., 2021, Comparison between centralized and decentralized supply chains of autologous chimeric antigen receptor T-cell therapies: a UK case study based on discrete event simulation., Cytotherapy, Vol: 23, Pages: 433-451

BACKGROUND AIMS: Decentralized, or distributed, manufacturing that takes place close to the point of care has been a manufacturing paradigm of heightened interest within the cell therapy domain because of the product's being living cell material as well as the need for a highly monitored and temperature-controlled supply chain that has the potential to benefit from close proximity between manufacturing and application. METHODS: To compare the operational feasibility and cost implications of manufacturing autologous chimeric antigen receptor T (CAR T)-cell products between centralized and decentralized schemes, a discrete event simulation model was built using ExtendSIM 9 for simulating the patient-to-patient supply chain, from the collection of patient cells to the final administration of CAR T therapy in hospitals. Simulations were carried out for hypothetical systems in the UK using three demand levels-low (100 patients per annum), anticipated (200 patients per annum) and high (500 patients per annum)-to assess resource allocation, cost per treatment and system resilience to demand changes and to quantify the risks of mix-ups within the supply chain for the delivery of CAR T treatments. RESULTS: The simulation results show that although centralized manufacturing offers better economies of scale, individual facilities in a decentralized system can spread facility costs across a greater number of treatments and better utilize resources at high demand levels (annual demand of 500 patients), allowing for an overall more comparable cost per treatment. In general, raw material and consumable costs have been shown to be one of the greatest cost drivers, and genetic modification-associated costs have been shown to account for over one third of raw material and consumable costs. Turnaround time per treatment for the decentralized scheme is shown to be consistently lower than its centralized counterpart, as there is no need for product freeze-thaw, packaging and transportat

Journal article

Milne-Ives M, Homer S, Andrade J, Meinert Eet al., 2021, Associations between Behaviour Change Techniques and engagement with mobile health apps: systematic review protocol, JMIR Research Protocols, Vol: 23, ISSN: 1929-0748

Background: The use of digitally-enabled care and the emphasis on self-management of health is growing. Mobile health apps provide a promising means of supporting health behaviour 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 behaviour change, it is essential to understand how engagement with mobile health apps and their target health behaviours can be better supported. Despite an increasing recognition of the importance of engagement in the literature, there is still a lack of understanding of how different components of engagement are associated with specific techniques that aim to change behaviours. Objective: The purpose of this systematic review protocol is to provide a synthesis of the associations between various Behaviour Change Techniques (BCTs) and the different components of engagement (and their outcome measures) with mobile health apps.Methods: The review protocol was structured using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) and the Population, Intervention, Comparator, and Outcome (PICO) frameworks. Seven databases will be systematically searched: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), APA PsycInfo, ScienceDirect, Cochrane Library and Web of Science. Title and abstract screening, full-text review, and data extraction will be conducted by two independent reviewers. Data will be extracted into a predetermined form, and any disagreements in screening or data extraction will be discussed, with a third reviewer consulted if consensus cannot be reached. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 and ROBINS-I tools and descriptive and thematic analyses will be used to summarise the relationships between BCTs and the different components of engagement.Results: The systematic review has not been started. It is expected to b

Journal article

Milne-Ives M, Meinert E, 2021, Digital technologies for monitoring and improving treatment adherence in children and adolescents with asthma: A scoping review of randomised controlled trials, Publisher: Cold Spring Harbor Laboratory

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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. One reviewer screened references, selected studies for inclusion based on the eligibility criteria, and extracted the data, which were synthesised in a descriptive analysis.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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; 6 of the 9 studies

Working paper

Meinert E, Eerens J, Banks C, Maloney S, Rivers G, Ilic D, Walsh K, Majeed A, Car Jet al., 2021, Exploring the cost of eLearning within the field of health professions education: Scoping review, JMIR Medical Education, Vol: 7, ISSN: 2369-3762

Background:Existing research on the costs associated with the design and deployment of eLearning in health professions education is limited. The relative costs of these learning platforms to those of face-to-face learning are also not well understood. The lack of predefined costing models used for eLearning cost data capture has made it difficult to complete cost evaluation.Objective:The key aim of this scoping review was to explore the state of evidence concerning cost capture within eLearning in health professions education. The review explores the available data to define cost calculations related to eLearning.Methods:The scoping review was performed using a search strategy with Medical Subject Heading terms and related keywords centered on eLearning and cost calculation with a population scope of health professionals in all countries. The search was limited to articles published in English. No restriction was placed on literature publication date.Results:In total, 7344 articles were returned from the original search of the literature. Of these, 232 were relevant to associated keywords or abstract references following screening. Full-text review resulted in 168 studies being excluded. Of these, 61 studies were excluded because they were unrelated to eLearning and focused on general education. In addition, 103 studies were excluded because of lack of detailed information regarding costs; these studies referred to cost in ways either indicating cost favorability or unfavorability, but without data to support findings. Finally, 4 studies were excluded because of limited cost data that were insufficient for analysis. In total, 42 studies provided data and analysis of the impact of cost and value in health professions education. The most common data source was total cost of training (n=29). Other sources included cost per learner, referring to the cost for individual students (n=13). The population most frequently cited was medical students (n=15), although 12 article

Journal article

Meinert E, Eerens J, Banks C, Maloney S, Rivers G, Ilic D, Walsh K, Majeed A, Car Jet al., 2021, Exploring the Cost of eLearning in Health Professions Education: Scoping Review, JMIR MEDICAL EDUCATION, Vol: 7, ISSN: 2369-3762

Journal article

Lam C, van Velthoven M, Meinert E, 2020, Developing a blockchain-based supply chain system for advanced therapies: study protocol, JMIR Research Protocols, Vol: 9, Pages: 1-6, ISSN: 1929-0748

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.

Journal article

Milne-Ives M, de Cock C, Lim E, Shehadeh M, de Pennington N, Mole G, Meinert Eet al., 2020, The effectiveness of artificial intelligence conversational agents in healthcare: a systematic review, Journal of Medical Internet Research, Vol: 22, ISSN: 1438-8871

Background: High demand on healthcare services and the growing capability of artificial intelligence has led to the development of conversational agents designed to support a variety of health-related activities - including behaviour change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase accessibility to healthcare services for the general public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in healthcare is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. Objective: This systematic review aimed to assess the effectiveness and usability of conversational agents in healthcare and identify the elements that users like and dislike, to inform future research and development of these agents. Methods: PubMed, Medline (Ovid), EMBASE, CINAHL, Web of Science, and ACM Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in healthcare. Endnote (version X9; Clarivate Analytics) reference management software was used for initial screening, then full-text screening was conducted by one reviewer. Data was extracted and risk of bias was assessed by one reviewer and validated by another. Results: A total of 31 studies were selected and included a variety of conversational agents - 14 chatbots (two of which were voice chatbots), 6 embodied conversational agents, 3 each of interactive voice response calls, virtual patients, and speech recognition screening systems, as well as one contextual question answering agent and one voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31) and positive or mixed effectiveness was found in three

Journal article

Milne-Ives M, Lam C, van Velthoven M, Meinert Eet al., 2020, The impact of Brexit on the UK pharmaceutical supply chain: a scoping review protocol, JMIR Research Protocols, Vol: 9, Pages: 1-6, ISSN: 1929-0748

The continuing uncertainty around Brexit has caused concern in the pharmaceutical industry and among healthcare professionals and patients. The exact consequences of Brexit on the UK pharmaceutical supply chain will depend on whether a deal is reached and what it entails, but it is likely to be affected by the withdrawal of the UK from the EU. Regulatory issues and delays in supply have the potential to seriously negatively affect the ability of UK residents to receive an adequate and timely supply of necessary medicines.

Journal article

Milne-Ives M, Lam C, Van Velthoven M, Meinert Eet al., 2020, Mobile fitness and weight management apps: an evaluation protocol, JMIR Research Protocols, Vol: 9, Pages: 1-5, ISSN: 1929-0748

Obesity is a large contributing factor for many non-communicable diseases and is a growing problem worldwide. Many mobile apps have been developed to help users improve their fitness and weight management behaviours. However, the speed at which apps are created and updated means that it is important to periodically assess their quality.

Journal article

Meinert E, Rahman E, Potter A, Lawrence W, Stenfors T, van Velthoven Met al., 2020, Usability of the mobile digital health ‘NoObesity’ app for families and healthcare professionals: a feasibility study, JMIR Research Protocols, Vol: 9, Pages: 1-10, ISSN: 1929-0748

Background: Almost a quarter or more than a fifth of children in the United Kingdom (UK) are overweight or obese by the time they start school. The UK Department of Health and Social Care has updated national policy for combating childhood obesity in 2018, with critical outcomes centred on sugar and caloric consumption reduction. Health Education England has developed two digital apps for families with children up to 15 and for their associated health care professionals (HCPs) to provide a digital learning resource and tool aimed at encouraging healthy lifestyles to prevent obesity.Objective: This feasibility study assesses Health Education England’s NoObesity app usability and acceptability to undertake activities to improve families’ diet and physical activity. The purpose of the study is to evaluate the app’s influence on self-efficacy and goal setting and to determine what can be learned to improve its design for future studies, should there be evidence of adoption and sustainability. Methods: The study population will include 20-40 families and their linked health care professionals. Recognising issues related to digital access associated with socioeconomic status (SES) and impact on information technology (IT) use, study recruitment will be regionally focused on a low SES area. The study will last nine-months; three months intervention period and six months follow up. The evaluation of feasibility, acceptability, and usability will be conducted using the following scales and theoretical frameworks: 1. The system usability scale; 2. The Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework; 3. Bandura’s model of health promotion; and 4. The Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Suitability (NASSS) framework. App use will be captured and quantitatively analysed for net use patterns (e.g. number of screens viewed, number of logins, cumulative minutes using the app, number of plans made

Journal article

Surodina S, Lam C, Grbich S, Milne-Ives M, Velthoven MV, Meinert Eet al., 2020, Requirements Engineering of a Herpes Simplex Virus Patient Registry: Alpha Phase

<jats:title>Abstract</jats:title> <jats:p><jats:bold>Background</jats:bold> Collecting data from people with herpes simplex virus is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity. 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 in order to determine the HSV infection risk group. <jats:bold>Methods</jats:bold>. The US National Health and Nutrition Examination Survey (NHANES, 2015-16) database has confirmed HSV1 and HSV2 status of American participants (14-49 years) as well as a wealth of demographic and health-related data. Two datasets – for HSV1 and HSV2 – were formed using this database, and an anonymous lifestyle-data based questionnaire with a Random Forest algorithm was devised using Python. The algorithm was optimised to reduce the number of questions and to identify risk groups for HSV. Data was split into subsets to train and test the model. <jats:bold>Results </jats:bold>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 HSV1 and HSV2 datasets, respectively. The number of questions was reduced from 150 to an average of 40, depending on age and gender, that together provides high predictability of the infection <jats:bold>Conclusions</jats:bold> This machine-learning algorithm for risk identification of people infected with HSV can be used in a real-world evidence registry to collect relevant lifestyle data. A current limitation is the absence of real user data and integration with electronic medical records that would enable model learning and improvement. Future work will explore model adjustments, anonymisation options, e

Journal article

de Cock C, van Velthoven M, Milne-Ives M, Mooney M, Meinert Eet al., 2020, Use of apps to promote childhood vaccination: a systematic review, JMIR mHealth and uHealth, Vol: 8, ISSN: 2291-5222

Vaccination is a critical step to reducing child mortality; however, vaccination rates have declined in many countries in recent years. This decrease has been associated with an increase in outbreaks of vaccine-preventable diseases. The potential for leveraging mobile platforms to promote vaccination coverage has been investigated in the development of numerous mobile apps. Whilst many are available for public use, there is little robust evaluation of these applications.

Journal article

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