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Ernawati I, Yasin NM, Setyopranoto I, Ikawati Z. Effect of Mobile Health Applications on Improving Self-Management Knowledge and Seizure Control in Epilepsy Patients: A Scoping Review. Healthc Inform Res 2024; 30:127-139. [PMID: 38755103 PMCID: PMC11098771 DOI: 10.4258/hir.2024.30.2.127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 04/05/2024] [Accepted: 04/08/2024] [Indexed: 05/18/2024] Open
Abstract
OBJECTIVES Mobile health app-based interventions are increasingly being developed to support chronic disease management, particularly for epilepsy patients. These interventions focus on managing stress, monitoring drug side effects, providing education, and promoting adherence to medication regimens. Therefore, this scoping review aims to assess how mobile health applications improve epilepsy patients' knowledge and seizure control, and to identify the features of these apps that are frequently used and have proven to be beneficial. METHODS This scoping review was conducted using scientific databases such as ScienceDirect, PubMed, and Google Scholar, adhering to the Joanna Briggs Institute guidelines. The review framework consisted of five steps: identifying research questions, finding relevant articles, selecting articles, presenting data, and compiling the results. The literature search included all original articles published in English from 2013 to 2023. RESULTS Among six articles that discussed mobile applications for epilepsy patients, all featured similar functionalities, including education on epilepsy management and seizure monitoring. Four of the articles highlighted behavioral interventions, such as reminder systems, designed to improve medication adherence. The remaining two articles focused on a side-effect reporting system that enabled doctors or health workers to evaluate and regularly monitor adverse effects. CONCLUSIONS This scoping review reveals that mobile health applications employing a combination of educational and behavioral interventions for epilepsy patients significantly improve knowledge about patient self-management and medication adherence. These interventions can prevent seizures, increase awareness, enable better activity planning, improve safety, and reduce the frequency of seizures and side effects of antiepileptic drugs.
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Affiliation(s)
- Iin Ernawati
- Doctoral Program in Pharmacy, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta,
Indonesia
- Akademi Farmasi Surabaya, Surabaya,
Indonesia
| | - Nanang Munif Yasin
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta,
Indonesia
| | - Ismail Setyopranoto
- Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta,
Indonesia
| | - Zullies Ikawati
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta,
Indonesia
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Monfort E, Latour P. Fostering patient engagement through the co-design of seizure detection and monitoring technologies: A roadmap for collaboration between research and development. Rev Neurol (Paris) 2024; 180:211-215. [PMID: 38040546 DOI: 10.1016/j.neurol.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 10/02/2023] [Indexed: 12/03/2023]
Abstract
The large number of technological developments suggests that patients with epilepsy can be better supported in the management of their seizures, especially when their condition is drug resistant. Patients and their caregivers, who are generally supportive of seizure detection and monitoring technologies, can provide relevant information to improve their effectiveness. We propose a comprehensive co-design approach to support more efficient development of seizure detection and monitoring technologies. Such an approach should follow the steps of the research and development process, take into account the temporal requirements characteristic of seizure management, focus on the themes of autonomy and self-management, and be guided by disease experts. If co-design practices are to continue to contribute to their development, they must also meet the scientific requirements of validity and reproducibility.
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Affiliation(s)
- E Monfort
- University of Grenoble Alpes, CNRS, TIMC, UFR SHS, 1251, avenue Centrale, CS 40700, 38000 Grenoble cedex 9, France.
| | - P Latour
- Medical Center of La Teppe, 26600 Tain-l'Hermitage, France
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Biondi A, Simblett SK, Viana PF, Laiou P, Fiori AMG, Nurse E, Schreuder M, Pal DK, Richardson MP. Feasibility and acceptability of an ultra-long-term at-home EEG monitoring system (EEG@HOME) for people with epilepsy. Epilepsy Behav 2024; 151:109609. [PMID: 38160578 DOI: 10.1016/j.yebeh.2023.109609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Recent technological advancements offer new ways to monitor and manage epilepsy. The adoption of these devices in routine clinical practice will strongly depend on patient acceptability and usability, with their perspectives being crucial. Previous studies provided feedback from patients, but few explored the experience of them using independently multiple devices independently at home. PURPOSE The study, assessed through a mixed methods design, the direct experiences of people with epilepsy independently using a non-invasive monitoring system (EEG@HOME) for an extended duration of 6 months, at home. We aimed to investigate factors affecting engagement, gather qualitative insights, and provide recommendations for future home epilepsy monitoring systems. MATERIALS AND METHODS Adults with epilepsy independently were trained to use a wearable dry EEG system, a wrist-worn device, and a smartphone app for seizure tracking and behaviour monitoring for 6 months at home. Monthly acceptability questionnaires (PSSUQ, SUS) and semi-structured interviews were conducted to explore participant experience. Adherence with the procedure, acceptability scores and systematic thematic analysis of the interviews, focusing on the experience with the procedure, motivation and benefits and opinion about the procedure were assessed. RESULTS Twelve people with epilepsy took part into the study for an average of 193.8 days (range 61 to 312) with a likelihood of using the system at six months of 83 %. The e-diary and the smartwatch were highly acceptable and preferred to a wearable EEG system (PSSUQ score of 1.9, 1.9, 2.4). Participants showed an acceptable level of adherence with all solutions (Average usage of 63 %, 66 %, 92 %) reporting more difficulties using the EEG twice a day and remembering to complete the daily behavioural questionnaires. Clear information and training, continuous remote support, perceived direct and indirect benefits and the possibility to have a flexible, tailored to daily routine monitoring were defined as key factors to ensure compliance with long-term monitoring systems. CONCLUSIONS EEG@HOME study demonstrated people with epilepsy' interest and ability in active health monitoring using new technologies. Remote training and support enable independent home use of new non-invasive technologies, but to ensure long term acceptability and usability systems will require to be integrated into patients' routines, include healthcare providers, and offer continuous support and personalized feedback.
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Affiliation(s)
- Andrea Biondi
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom.
| | - Sara K Simblett
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom; Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom
| | - Pedro F Viana
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom; Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Petroula Laiou
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom
| | - Anna M G Fiori
- King's College Hospital NHS Foundation Trust, London, United Kingdom
| | - Ewan Nurse
- Seer Medical Inc, Melbourne, VIC, Australia; Department of Medicine, St. Vincent's Hospital Melbourne, The University of Melbourne, Melbourne, VIC, Australia
| | | | - Deb K Pal
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom
| | - Mark P Richardson
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom; NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom
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Wang B, Asan O, Zhang Y. Shaping the future of chronic disease management: Insights into patient needs for AI-based homecare systems. Int J Med Inform 2024; 181:105301. [PMID: 38029700 DOI: 10.1016/j.ijmedinf.2023.105301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 11/02/2023] [Accepted: 11/16/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND The rising demand for healthcare resources, especially in chronic disease management, has elevated the importance of Artificial Intelligence (AI) in healthcare. While AI-based homecare systems are being developed, the perspectives of chronic patients, who are one of the primary beneficiaries and risk bearers of these technologies, remain largely under-researched. While recent research has highlighted the importance of AI-based homecare systems, the current understanding of patients' desired designs and features is still limited. OBJECTIVE This paper explores chronic patients' perspectives regarding AI-based homecare systems, an area currently underrepresented in research. We aim to identify the factors influencing their decision to use such systems, elucidate the potential roles of government and other concerned authorities, and provide feedback to AI developers to enhance adoption, system design, and usability and improve the overall healthcare experiences of chronic patients. METHOD A web-based open-ended questionnaire was designed to gather the perspectives of chronic patients about AI-based homecare systems. In total, responses from 181 participants were collected. Using Krippendorff's clustering technique, an inductive thematic analysis was performed to identify the main themes and their respective subthemes. RESULT Through rigorous coding and thematic analysis of the collected responses, we identified four major themes further segmented into thirteen subthemes. These four primary themes were: 1) "Personalized Design", emphasizing the need for patients to manage their health condition better through personalized and educational resources and user-friendly interfaces; 2) "Emotional & Social Support", underscoring the desire for AI systems to facilitate social connectivity and provide emotional support to improve the well-being of chronic patients at home; 3) "System Integration & Proactive Care", addressing the importance of seamless communication, proactive patient monitoring and integration with existing healthcare platforms; and 4) "Ethics & Regulation", prioritizing ethical guidelines, regulatory compliance, and affordability in the design. CONCLUSION This study has offered significant insights into the needs and expectations of chronic patients regarding AI-based home care systems. 'The findings highlight the importance of personalized and accessible care, emotional and social support, seamless system integration, proactive care, and ethical considerations in designing and implementing such systems. By aligning the design and operation of these systems with the lived experiences and expectations of patients, we can better ensure their acceptance and effectiveness.
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Affiliation(s)
- Bijun Wang
- Department of Business Analytics and Data Science, Florida Polytechnic University, Lakeland, FL 33805, USA
| | - Onur Asan
- School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ 07047, USA.
| | - Yiqi Zhang
- Department of Industrial and Manufacturing Engineering, Penn State University, State College, PA 16801, USA
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Khoshkangin A, Agha Seyyed Esmaeil Amiri FS, Ghaddaripouri K, Noroozi N, Mazaheri Habibi MR. Investigating the role of mobile health in epilepsy management: A systematic review. J Educ Health Promot 2023; 12:304. [PMID: 38023071 PMCID: PMC10670869 DOI: 10.4103/jehp.jehp_1188_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/26/2022] [Indexed: 12/01/2023]
Abstract
Epilepsy is the most common chronic neurologic disease which is characterized by recurrent attacks of headache after seizure. Researches show that self-management is an important factor in improving the quality of life and quality of care of people affected by epilepsy. Mobile phone technologies play a potential role in patient care assistance and treatment of epilepsy. This systematic review was conducted with an aim to study the role of mobile health in the management of epilepsy. This study was conducted by searching databases such as PubMed, Scopus, Web of Science, and Google scholar search engines using the following keywords: "m-health," "mobile health," "Telemedicine," "Mobile Application," "Smartphone," "epilepsy," and "epilepsy management." Articles published from January 1, 1990 to September 1, 2021 were searched. Inclusion criteria included all articles published in English with a focus on the role of mHealth in the management of epilepsy. Review articles and studies that were not about patients were omitted. In this study, of a total of 4225 retrieved articles, 10 studies met the full-text inclusion criteria. Three types of researches (30%) were done in the USA, five studies (50%) were conducted as randomized controlled trials, and eight articles (80%) had the highest quality. Among the considered articles, three articles (30%) were engaged in training users in epilepsy management. Five articles (50%) reported improvement in seizure control in patients with epilepsy and two articles (20%) did not report any significant improvement. Mobile technologies have a promising role in providing health assessment, education, and other services for patients, and they also help in controlling seizures attack and improvement of epilepsy management. These technologies enjoy great attractiveness, and utilizing them will lead to patient satisfaction.
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Affiliation(s)
- Atefeh Khoshkangin
- Department of Health Information Technology, Varastegan Institute for Medical Sciences, Mashhad, Iran
- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | - Kosar Ghaddaripouri
- Department of Health Information Technology, Varastegan Institute for Medical Sciences, Mashhad, Iran
| | - Navid Noroozi
- Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran
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Simblett SK, Pennington M, Quaife M, Siddi S, Lombardini F, Haro JM, Peñarrubia-Maria MT, Bruce S, Nica R, Zorbas S, Polhemus A, Novak J, Dawe-Lane E, Morris D, Mutepua M, Odoi C, Wilson E, Matcham F, White KM, Hotopf M, Wykes T; RADAR-CNS consortium. Patient preferences for key drivers and facilitators of adoption of mHealth technology to manage depression: A discrete choice experiment. J Affect Disord 2023:S0165-0327(23)00364-6. [PMID: 36934854 DOI: 10.1016/j.jad.2023.03.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 03/10/2023] [Accepted: 03/12/2023] [Indexed: 03/21/2023]
Abstract
BACKGROUND In time, we may be able to detect the early onset of symptoms of depression and even predict relapse using behavioural data gathered through mobile technologies. However, barriers to adoption exist and understanding the importance of these factors to users is vital to ensure maximum adoption. METHOD In a discrete choice experiment, people with a history of depression (N = 171) were asked to select their preferred technology from a series of vignettes containing four characteristics: privacy, clinical support, established benefit and device accuracy (i.e., ability to detect symptoms), with different levels. Mixed logit models were used to establish what was most likely to affect adoption. Sub-group analyses explored effects of age, gender, education, technology acceptance and familiarity, and nationality. RESULTS Higher level of privacy, greater clinical support, increased perceived benefit and better device accuracy were important. Accuracy was the most important, with only modest compromises willing to be made to increase other factors such as privacy. Established benefit was the least valued of the attributes with participants happy with technology that had possible but unknown benefits. Preferences were moderated by technology acceptance, age, nationality, and educational background. CONCLUSION For people with a history of depression, adoption of technology may be driven by the desire for accurate detection of symptoms. However, people with lower technology acceptance and educational attainment, those who were younger, and specific nationalities may be willing to compromise on some accuracy for more privacy and clinical support. These preferences should help shape design of mHealth tools.
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Torres-Castaño A, Abt-Sacks A, Toledo-Chávarri A, Suarez-Herrera JC, Delgado-Rodríguez J, León-Salas B, González-Hernández Y, Carmona-Rodríguez M, Serrano-Aguilar P. Ethical, Legal, Organisational and Social Issues of Teleneurology: A Scoping Review. Int J Environ Res Public Health 2023; 20:3694. [PMID: 36834388 PMCID: PMC9962592 DOI: 10.3390/ijerph20043694] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/13/2023] [Accepted: 02/15/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Neurological disorders are the leading cause of disability and the second leading cause of death worldwide. Teleneurology (TN) allows neurology to be applied when the doctor and patient are not present in the same place, and sometimes not at the same time. In February 2021, the Spanish Ministry of Health requested a health technology assessment report on the implementation of TN as a complement to face-to-face neurological care. METHODS A scoping review was conducted to answer the question on the ethical, legal, social, organisational, patient (ELSI) and environmental impact of TN. The assessment of these aspects was carried out by adapting the EUnetHTA Core Model 3.0 framework, the criteria established by the Spanish Network of Health Technology Assessment Agencies and the analysis criteria of the European Validate (VALues In Doing Assessments of healthcare TEchnologies) project. Key stakeholders were invited to discuss their concerns about TN in an online meeting. Subsequently, the following electronic databases were consulted from 2016 to 10 June 2021: MEDLINE and EMBASE. RESULTS 79 studies met the inclusion criteria. This scoping review includes 37 studies related to acceptability and equity, 15 studies developed during COVID and 1 study on environmental aspects. Overall, the reported results reaffirm the necessary complementarity of TN with the usual face-to-face care. CONCLUSIONS This need for complementarity relates to factors such as acceptability, feasibility, risk of dehumanisation and aspects related to privacy and the confidentiality of sensitive data.
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Affiliation(s)
- Alezandra Torres-Castaño
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- Evaluation Unit of the Canary Islands Health Service (SESCS), 38109 Tenerife, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 28029 Madrid, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
| | - Analía Abt-Sacks
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- Evaluation Unit of the Canary Islands Health Service (SESCS), 38109 Tenerife, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 28029 Madrid, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
| | - Ana Toledo-Chávarri
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- Evaluation Unit of the Canary Islands Health Service (SESCS), 38109 Tenerife, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 28029 Madrid, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
| | - José Carlos Suarez-Herrera
- Evaluation Unit of the Canary Islands Health Service (SESCS), 38109 Tenerife, Spain
- UNITWIN/UNESCO Chair, Research, Planning and Development of Local Health Systems, Department of Clinical Sciences, University of Las Palmas de Gran Canaria, 35001 Las Palmas de Gran Canaria, Spain
| | - Janet Delgado-Rodríguez
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
- Department of Philosophy I, University of Granada, 18071 Granada, Spain
| | - Beatriz León-Salas
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- Evaluation Unit of the Canary Islands Health Service (SESCS), 38109 Tenerife, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 28029 Madrid, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
| | - Yadira González-Hernández
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- Evaluation Unit of the Canary Islands Health Service (SESCS), 38109 Tenerife, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 28029 Madrid, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
| | - Montserrat Carmona-Rodríguez
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 28029 Madrid, Spain
- The Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS), 28071 Madrid, Spain
- Health Technology Assessment Agency, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Pedro Serrano-Aguilar
- Canary Islands Health Research Institute Foundation (FIISC), 38320 Tenerife, Spain
- Institute of Biomedical Technologies, University of La Laguna, 38200 Tenerife, Spain
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Harvey PD, Depp CA, Rizzo AA, Strauss GP, Spelber D, Carpenter LL, Kalin NH, Krystal JH, McDonald WM, Nemeroff CB, Rodriguez CI, Widge AS, Torous J. Technology and Mental Health: State of the Art for Assessment and Treatment. Am J Psychiatry 2022; 179:897-914. [PMID: 36200275 DOI: 10.1176/appi.ajp.21121254] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Technology is ubiquitous in society and is now being extensively used in mental health applications. Both assessment and treatment strategies are being developed and deployed at a rapid pace. The authors review the current domains of technology utilization, describe standards for quality evaluation, and forecast future developments. This review examines technology-based assessments of cognition, emotion, functional capacity and everyday functioning, virtual reality approaches to assessment and treatment, ecological momentary assessment, passive measurement strategies including geolocation, movement, and physiological parameters, and technology-based cognitive and functional skills training. There are many technology-based approaches that are evidence based and are supported through the results of systematic reviews and meta-analyses. Other strategies are less well supported by high-quality evidence at present, but there are evaluation standards that are well articulated at this time. There are some clear challenges in selection of applications for specific conditions, but in several areas, including cognitive training, randomized clinical trials are available to support these interventions. Some of these technology-based interventions have been approved by the U.S. Food and Drug administration, which has clear standards for which types of applications, and which claims about them, need to be reviewed by the agency and which are exempt.
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Affiliation(s)
- Philip D Harvey
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Colin A Depp
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Albert A Rizzo
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Gregory P Strauss
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - David Spelber
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Linda L Carpenter
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Ned H Kalin
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - John H Krystal
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - William M McDonald
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Charles B Nemeroff
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Carolyn I Rodriguez
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - Alik S Widge
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
| | - John Torous
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, and Miami VA Medical Center (Harvey); Department of Psychiatry, UC San Diego Medical Center, La Jolla (Depp); USC Institute for Creative Technologies, University of Southern California, Los Angeles (Rizzo); Department of Psychology, University of Georgia, Athens (Strauss); Department of Psychiatry, Dell Medical Center, University of Texas at Austin (Spelber, Nemeroff); Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I. (Carpenter); Department of Psychiatry, University of Wisconsin Medical School, Madison (Kalin); Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Krystal); Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto (Rodriguez); Department of Psychiatry and Behavioral Sciences and Medical Discovery Team-Addictions, University of Minnesota, Minneapolis (Widge); Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston (Torous)
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9
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Spreadbury JH, Young A, Kipps CM. A Comprehensive Literature Search of Digital Health Technology Use in Neurological Conditions: Review of Digital Tools to Promote Self-management and Support. J Med Internet Res 2022; 24:e31929. [PMID: 35900822 PMCID: PMC9377435 DOI: 10.2196/31929] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 03/13/2022] [Accepted: 05/19/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The use of digital health technology to promote and deliver postdiagnostic care in neurological conditions is becoming increasingly common. However, the range of digital tools available across different neurological conditions and how they facilitate self-management are unclear. OBJECTIVE This review aims to identify digital tools that promote self-management in neurological conditions and to investigate their underlying functionality and salient clinical outcomes. METHODS We conducted a search of 6 databases (ie, CINAHL, EMBASE, MEDLINE, PsycINFO, Web of Science, and the Cochrane Review) using free text and equivalent database-controlled vocabulary terms. RESULTS We identified 27 published articles reporting 17 self-management digital tools. Multiple sclerosis (MS) had the highest number of digital tools followed by epilepsy, stroke, and headache and migraine with a similar number, and then pain. The majority were aimed at patients with a minority for carers. There were 5 broad categories of functionality promoting self-management: (1) knowledge and understanding; (2) behavior modification; (3) self-management support; (4) facilitating communication; and (5) recording condition characteristics. Salient clinical outcomes included improvements in self-management, self-efficacy, coping, depression, and fatigue. CONCLUSIONS There now exist numerous digital tools to support user self-management, yet relatively few are described in the literature. More research is needed to investigate their use, effectiveness, and sustainability, as well as how this interacts with increasing disability, and their integration within formal neurological care environments.
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Affiliation(s)
- John Henry Spreadbury
- Faculty of Medicine, University of Southampton, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom.,Clinical Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Alex Young
- Clinical Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Christopher Myles Kipps
- Clinical Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.,Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
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10
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White KM, Williamson C, Bergou N, Oetzmann C, de Angel V, Matcham F, Henderson C, Hotopf M. A systematic review of engagement reporting in remote measurement studies for health symptom tracking. NPJ Digit Med 2022; 5:82. [PMID: 35768544 DOI: 10.1038/s41746-022-00624-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 06/01/2022] [Indexed: 01/25/2023] Open
Abstract
Remote Measurement Technologies (RMTs) could revolutionise management of chronic health conditions by providing real-time symptom tracking. However, the promise of RMTs relies on user engagement, which at present is variably reported in the field. This review aimed to synthesise the RMT literature to identify how and to what extent engagement is defined, measured, and reported, and to present recommendations for the standardisation of future work. Seven databases (Embase, MEDLINE and PsycINFO (via Ovid), PubMed, IEEE Xplore, Web of Science, and Cochrane Central Register of Controlled Trials) were searched in July 2020 for papers using RMT apps for symptom monitoring in adults with a health condition, prompting users to track at least three times during the study period. Data were synthesised using critical interpretive synthesis. A total of 76 papers met the inclusion criteria. Sixty five percent of papers did not include a definition of engagement. Thirty five percent included both a definition and measurement of engagement. Four synthetic constructs were developed for measuring engagement: (i) engagement with the research protocol, (ii) objective RMT engagement, (iii) subjective RMT engagement, and (iv) interactions between objective and subjective RMT engagement. The field is currently impeded by incoherent measures and a lack of consideration for engagement definitions. A process for implementing the reporting of engagement in study design is presented, alongside a framework for definition and measurement options available. Future work should consider engagement with RMTs as distinct from the wider eHealth literature, and measure objective versus subjective RMT engagement.Registration: This review has been registered on PROSPERO [CRD42020192652].
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11
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Sivathamboo S, Nhu D, Piccenna L, Yang A, Antonic-Baker A, Vishwanath S, Todaro M, Yap LW, Kuhlmann L, Cheng W, O'Brien TJ, Lannin NA, Kwan P. Preferences and User Experiences of Wearable Devices in Epilepsy: A Systematic Review and Mixed-Methods Synthesis. Neurology 2022; 99:e1380-e1392. [PMID: 35705497 DOI: 10.1212/wnl.0000000000200794] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 04/12/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To examine the preferences and user experiences of people with epilepsy and caregivers regarding automated wearable seizure detection devices. METHODS We performed a mixed-methods systematic review. We searched electronic databases for original peer-reviewed publications between January 1, 2000, and May 26, 2021. Key search terms included "epilepsy", "seizure", "wearable", and "non-invasive". We performed a descriptive and a qualitative thematic analysis of the studies included according to the technology acceptance model. Full texts of the discussion sections were further analyzed to identify word frequency and word mapping. RESULTS Twenty-two observational studies were identified. Collectively, they comprised responses from 3299 participants including patients with epilepsy, caregivers and healthcare workers. Sixteen studies examined user preferences, five examined user experiences, and one examined both experiences and preferences. Important preferences for wearables included improving care, cost, accuracy, and design. Patients desired real-time detection with a latency of ≤15 minutes from seizure occurrence, along with high sensitivity (≥90%) and low false-alarm rates. Device related costs were a major factor for device acceptance, where device costs of <$300 USD and a monthly subscription fee of <$20 USD were preferred. Despite being a major driver of wearable-based technologies, sudden unexpected death in epilepsy (SUDEP) was rarely discussed. Among studies evaluating user experiences, there was a greater acceptance towards wristwatches. Thematic coding analysis showed that attitudes towards device use, and perceived usefulness were reported consistently. Word mapping identified 'specificity', 'cost', and 'battery' as key single terms, and 'battery life', 'insurance coverage', 'prediction/detection quality', and the effect of devices on 'daily life' as key bigrams. DISCUSSION User acceptance of wearable technology for seizure detection was strongly influenced by accuracy, design, comfort, and cost. Our findings emphasise the need for standardised and validated tools to comprehensively examine preferences and user experiences of wearable devices in this population, using the themes identified in this study. Greater efforts to incorporate perspectives and user experiences in developing wearables for seizure detection, particularly in community-based settings are needed. PROSPERO REGISTRATION CRD42020193565.
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Affiliation(s)
- Shobi Sivathamboo
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia.,Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia.,Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, 3000, Victoria, Australi
| | - Duong Nhu
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Clayton, 3800, Victoria, Australia
| | - Loretta Piccenna
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia.,Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia.,Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia
| | - Anthony Yang
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia.,Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia.,Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia
| | - Ana Antonic-Baker
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia
| | - Swarna Vishwanath
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia
| | - Marian Todaro
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia.,Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia.,Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, 3000, Victoria, Australi
| | - Lim Wei Yap
- Department of Chemical and Biological Engineering, Monash University, Clayton, 3800, Victoria, Australi
| | - Levin Kuhlmann
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Clayton, 3800, Victoria, Australia
| | - Wenlong Cheng
- Department of Chemical and Biological Engineering, Monash University, Clayton, 3800, Victoria, Australi
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia.,Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia.,Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, 3000, Victoria, Australi
| | - Natasha A Lannin
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia.,Alfred Health (Allied Health Directorate), Melbourne, 3004, Victoria, Australia
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, 3004, Victoria, Australia .,Department of Neurology, Alfred Health, Melbourne, 3004, Victoria, Australia.,Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, 3000, Victoria, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, 3000, Victoria, Australi
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12
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Simblett S, Pennington M, Quaife M, Theochari E, Burke P, Brichetto G, Devonshire J, Lees S, Little A, Pullen A, Stoneman A, Thorpe S, Weyer J, Polhemus A, Novak J, Dawe-Lane E, Morris D, Mutepua M, Odoi C, Wilson E, Wykes T. Key Drivers and Facilitators of the Choice to Use mHealth Technology in People With Neurological Conditions: Observational Study. JMIR Form Res 2022; 6:e29509. [PMID: 35604761 PMCID: PMC9171601 DOI: 10.2196/29509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/21/2021] [Accepted: 01/04/2022] [Indexed: 11/16/2022] Open
Abstract
Background There is increasing interest in the potential uses of mobile health (mHealth) technologies, such as wearable biosensors, as supplements for the care of people with neurological conditions. However, adherence is low, especially over long periods. If people are to benefit from these resources, we need a better long-term understanding of what influences patient engagement. Previous research suggests that engagement is moderated by several barriers and facilitators, but their relative importance is unknown. Objective To determine preferences and the relative importance of user-generated factors influencing engagement with mHealth technologies for 2 common neurological conditions with a relapsing-remitting course: multiple sclerosis (MS) and epilepsy. Methods In a discrete choice experiment, people with a diagnosis of MS (n=141) or epilepsy (n=175) were asked to select their preferred technology from a series of 8 vignettes with 4 characteristics: privacy, clinical support, established benefit, and device accuracy; each of these characteristics was greater or lower in each vignette. These characteristics had previously been emphasized by people with MS and or epilepsy as influencing engagement with technology. Mixed multinomial logistic regression models were used to establish which characteristics were most likely to affect engagement. Subgroup analyses explored the effects of demographic factors (such as age, gender, and education), acceptance of and familiarity with mobile technology, neurological diagnosis (MS or epilepsy), and symptoms that could influence motivation (such as depression). Results Analysis of the responses to the discrete choice experiment validated previous qualitative findings that a higher level of privacy, greater clinical support, increased perceived benefit, and better device accuracy are important to people with a neurological condition. Accuracy was perceived as the most important factor, followed by privacy. Clinical support was the least valued of the attributes. People were prepared to trade a modest amount of accuracy to achieve an improvement in privacy, but less likely to make this compromise for other factors. The type of neurological condition (epilepsy or MS) did not influence these preferences, nor did the age, gender, or mental health status of the participants. Those who were less accepting of technology were the most concerned about privacy and those with a lower level of education were prepared to trade accuracy for more clinical support. Conclusions For people with neurological conditions such as epilepsy and MS, accuracy (ie, the ability to detect symptoms) is of the greatest interest. However, there are individual differences, and people who are less accepting of technology may need far greater reassurance about data privacy. People with lower levels of education value greater clinician involvement. These patient preferences should be considered when designing mHealth technologies.
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Affiliation(s)
- Sara Simblett
- Psychology Department, King's College London, London, United Kingdom
| | - Mark Pennington
- Psychology Department, King's College London, London, United Kingdom
| | - Matthew Quaife
- Health Economics Department, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | | | - Patrick Burke
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
| | - Giampaolo Brichetto
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
- Italian Multiple Sclerosis Society and Foundation, Rome, Italy
| | - Julie Devonshire
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
| | - Simon Lees
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
| | - Ann Little
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
- International Bureau for Epilepsy, Dublin, Ireland
| | - Angie Pullen
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
- Epilepsy Action, Leeds, United Kingdom
| | - Amanda Stoneman
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
- Epilepsy Action, Leeds, United Kingdom
| | - Sarah Thorpe
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
| | - Janice Weyer
- Remote Assessment of Disease and Relapse in Central Nervous System Disorders Patient Advisory Board, King's College London, London, United Kingdom
| | - Ashley Polhemus
- Merck Sharp & Dohme Information Technology, Prague, Czech Republic
| | - Jan Novak
- Psychology Department, King's College London, London, United Kingdom
- Merck Sharp & Dohme Information Technology, Prague, Czech Republic
- Faculty of Science, Charles University, Prague, Czech Republic
| | - Erin Dawe-Lane
- Psychology Department, King's College London, London, United Kingdom
| | - Daniel Morris
- Psychology Department, King's College London, London, United Kingdom
| | - Magano Mutepua
- Psychology Department, King's College London, London, United Kingdom
| | - Clarissa Odoi
- Psychology Department, King's College London, London, United Kingdom
- South London and Maudsley Biomedical Research Centre, London, United Kingdom
| | - Emma Wilson
- Psychology Department, King's College London, London, United Kingdom
| | - Til Wykes
- Psychology Department, King's College London, London, United Kingdom
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13
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Andrews JA, Craven MP, Lang AR, Guo B, Morriss R, Hollis C. Making remote measurement technology work in multiple sclerosis, epilepsy and depression: survey of healthcare professionals. BMC Med Inform Decis Mak 2022; 22:125. [PMID: 35525933 PMCID: PMC9077644 DOI: 10.1186/s12911-022-01856-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 04/15/2022] [Indexed: 11/21/2022] Open
Abstract
Background Epilepsy, multiple sclerosis (MS) and depression are long term, central nervous system disorders which have a significant impact on everyday life. Evaluating symptoms of these conditions is problematic and typically involves repeated visits to a clinic. Remote measurement technology (RMT), consisting of smartphone apps and wearables, may offer a way to improve upon existing methods of managing these conditions. The present study aimed to establish the practical requirements that would enable clinical integration of data from patients’ RMT, according to healthcare professionals. Methods This paper reports findings from an online survey of 1006 healthcare professionals currently working in the care of people with epilepsy, MS or depression. The survey included questions on types of data considered useful, how often data should be collected, the value of RMT data, preferred methods of accessing the data, benefits and challenges to RMT implementation, impact of RMT data on clinical practice, and requirement for technical support. The survey was presented on the JISC online surveys platform. Results Among this sample of 1006 healthcare professionals, respondents were positive about the benefits of RMT, with 73.2% indicating their service would be likely or highly likely to benefit from the implementation of RMT in patient care plans. The data from patients’ RMT devices should be made available to all nursing and medical team members and could be reviewed between consultations where flagged by the system. However, results suggest it is also likely that RMT data would be reviewed in preparation for and during a consultation with a patient. Time to review information is likely to be one of the greatest barriers to successful implementation of RMT in clinical practice. Conclusions While further work would be required to quantify the benefits of RMT in clinical practice, the findings from this survey suggest that a wide array of clinical team members treating epilepsy, MS and depression would find benefit from RMT data in the care of their patients. Findings presented could inform the implementation of RMT and other digital interventions in the clinical management of a range of neurological and mental health conditions. Supplementary Information The online version contains supplementary material available at 10.1186/s12911-022-01856-z.
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Affiliation(s)
- J A Andrews
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK. .,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.
| | - M P Craven
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.,Human Factors Research Group, Faculty of Engineering, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - A R Lang
- Human Factors Research Group, Faculty of Engineering, University of Nottingham, Nottingham, UK
| | - B Guo
- ARC-EM, School of Medicine, University of Nottingham, Nottingham, UK
| | - R Morriss
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK.,ARC-EM, School of Medicine, University of Nottingham, Nottingham, UK
| | - C Hollis
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
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14
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Biondi A, Santoro V, Viana PF, Laiou P, Pal DK, Bruno E, Richardson MP. Noninvasive mobile EEG as a tool for seizure monitoring and management: A systematic review. Epilepsia 2022; 63:1041-1063. [PMID: 35271736 PMCID: PMC9311406 DOI: 10.1111/epi.17220] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/07/2022] [Accepted: 03/07/2022] [Indexed: 11/30/2022]
Abstract
In the last two decades new noninvasive mobile electroencephalography (EEG) solutions have been developed to overcome limitations of conventional clinical EEG and to improve monitoring of patients with long-term conditions. Despite the availability of mobile innovations, their adoption is still very limited. The aim of this study is to review the current state-of-the-art and highlight the main advantages of adopting noninvasive mobile EEG solutions in clinical trials and research studies of people with epilepsy or suspected seizures. Device characteristics are described, and their evaluation is presented. Two authors independently performed a literature review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A combination of different digital libraries was used (Embase, MEDLINE, Global Health, PsycINFO and https://clinicaltrials.gov/). Twenty-three full-text, six conference abstracts, and eight webpages were included, where a total of 14 noninvasive mobile solutions were identified. Published studies demonstrated at different levels how EEG recorded via mobile EEG can be used for visual detection of EEG abnormalities and for the application of automatic-detection algorithms with acceptable specificity and sensitivity. When the quality of the signal was compared with scalp EEG, many similarities were found in the background activities and power spectrum. Several studies indicated that the experience of patients and health care providers using mobile EEG was positive in different settings. Ongoing trials are focused mostly on improving seizure-detection accuracy and also on testing and assessing feasibility and acceptability of noninvasive devices in the hospital and at home. This review supports the potential clinical value of noninvasive mobile EEG systems and their advantages in terms of time, technical support, cost, usability, and reliability when applied to seizure detection and management. On the other hand, the limitations of the studies confirmed that future research is needed to provide more evidence regarding feasibility and acceptability in different settings, as well as the data quality and detection accuracy of new noninvasive mobile EEG solutions.
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Affiliation(s)
- Andrea Biondi
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Viviana Santoro
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Pedro F. Viana
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK,Faculty of MedicineUniversity of LisbonLisbonPortugal
| | - Petroula Laiou
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Deb K. Pal
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Elisa Bruno
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Mark P. Richardson
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
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15
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Goonesekera Y, Donkin L. A Cognitive Behavior Therapy Chatbot (Otis) for Health Anxiety Management: A Mixed-Methods Pilot Study (Preprint). JMIR Form Res 2022; 6:e37877. [PMID: 36150049 PMCID: PMC9586257 DOI: 10.2196/37877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 09/01/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background An increase in health anxiety was observed during the COVID-19 pandemic. However, due to physical distancing restrictions and a strained mental health system, people were unable to access support to manage health anxiety. Chatbots are emerging as an interactive means to deliver psychological interventions in a scalable manner and provide an opportunity for novel therapy delivery to large groups of people including those who might struggle to access traditional therapies. Objective The aim of this mixed methods pilot study was to investigate the feasibility, acceptability, engagement, and effectiveness of a cognitive behavioral therapy (CBT)–based chatbot (Otis) as an early health anxiety management intervention for adults in New Zealand during the COVID-19 pandemic. Methods Users were asked to complete a 14-day program run by Otis, a primarily decision tree–based chatbot on Facebook Messenger. Health anxiety, general anxiety, intolerance of uncertainty, personal well-being, and quality of life were measured pre-intervention, postintervention, and at a 12-week follow-up. Paired samples t tests and 1-way ANOVAs were conducted to investigate the associated changes in the outcomes over time. Semistructured interviews and written responses in the self-report questionnaires and Facebook Messenger were thematically analyzed. Results The trial was completed by 29 participants who provided outcome measures at both postintervention and follow-up. Although an average decrease in health anxiety did not reach significance at postintervention (P=.55) or follow-up (P=.08), qualitative analysis demonstrated that participants perceived benefiting from the intervention. Significant improvement in general anxiety, personal well-being, and quality of life was associated with the use of Otis at postintervention and follow-up. Anthropomorphism, Otis’ appearance, and delivery of content facilitated the use of Otis. Technical difficulties and high performance and effort expectancy were, in contrast, barriers to acceptance and engagement of Otis. Conclusions Otis may be a feasible, acceptable, and engaging means of delivering CBT to improve anxiety management, quality of life, and personal well-being but might not significantly reduce health anxiety.
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Affiliation(s)
- Yenushka Goonesekera
- Department of Psychological Medicine, The University of Auckland, Auckland, New Zealand
| | - Liesje Donkin
- Department of Psychological Medicine, The University of Auckland, Auckland, New Zealand
- Department of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand
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16
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Onorati F, Regalia G, Caborni C, LaFrance WC, Blum AS, Bidwell J, De Liso P, El Atrache R, Loddenkemper T, Mohammadpour-Touserkani F, Sarkis RA, Friedman D, Jeschke J, Picard R. Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit. Front Neurol 2021; 12:724904. [PMID: 34489858 PMCID: PMC8418082 DOI: 10.3389/fneur.2021.724904] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 07/27/2021] [Indexed: 12/03/2022] Open
Abstract
Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (EDA) has been shown effective to detect primarily and secondarily generalized tonic-clonic seizures, here termed as convulsive seizures (CS). A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm. Here we present its performance on pediatric and adult patients in epilepsy monitoring units (EMUs). Methods: Patients diagnosed with epilepsy participated in a prospective multi-center clinical study. Three board-certified neurologists independently labeled CS from video-EEG. The Detection Algorithm was evaluated in terms of Sensitivity and false alarm rate per 24 h-worn (FAR) on all the data and on only periods of rest. Performance were analyzed also applying the Detection Algorithm offline, with a less sensitive but more specific parameters configuration (“Active mode”). Results: Data from 152 patients (429 days) were used for performance evaluation (85 pediatric aged 6–20 years, and 67 adult aged 21–63 years). Thirty-six patients (18 pediatric) experienced a total of 66 CS (35 pediatric). The Sensitivity (corrected for clustered data) was 0.92, with a 95% confidence interval (CI) of [0.85-1.00] for the pediatric population, not significantly different (p > 0.05) from the adult population's Sensitivity (0.94, CI: [0.89–1.00]). The FAR on the pediatric population was 1.26 (CI: [0.87–1.73]), higher (p < 0.001) than in the adult population (0.57, CI: [0.36–0.81]). Using the Active mode, the FAR decreased by 68% while reducing Sensitivity to 0.95 across the population. During rest periods, the FAR's were 0 for all patients, lower than during activity periods (p < 0.001). Conclusions: Performance complies with FDA's requirements of a lower bound of CI for Sensitivity higher than 0.7 and of a FAR lower than 2, for both age groups. The pediatric FAR was higher than the adult FAR, likely due to higher pediatric activity. The high Sensitivity and precision (having no false alarms) during sleep might help mitigate SUDEP risk by summoning caregiver intervention. The Active mode may be advantageous for some patients, reducing the impact of the FAR on daily life. Future work will examine the performance and usability outside of EMUs.
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Affiliation(s)
| | | | | | - W Curt LaFrance
- Division of Neuropsychiatry and Behavioral Neurology, Rhode Island Hospital, Brown University, Providence, RI, United States
| | - Andrew S Blum
- Department of Neurology, Rhode Island Hospital, Brown University, Providence, RI, United States
| | | | - Paola De Liso
- Department of Neuroscience, Bambino Gesù Children's Hospital, Istituto di Ricovero e Cura a Carattere Scientifico, Rome, Italy
| | - Rima El Atrache
- Department of Neurology, Boston Children's Hospital, Boston, MA, United States
| | - Tobias Loddenkemper
- Department of Neurology, Boston Children's Hospital, Boston, MA, United States
| | | | - Rani A Sarkis
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, United States
| | - Daniel Friedman
- Department of Neurology, New York University Langone Medical Center, New York, NY, United States
| | - Jay Jeschke
- Department of Neurology, New York University Langone Medical Center, New York, NY, United States
| | - Rosalind Picard
- Empatica, Inc., Boston, MA, United States.,MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
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17
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Adanijo A, McWilliams C, Wykes T, Jilka S. Investigating Mental Health Service User Opinions on Clinical Data Sharing: Qualitative Focus Group Study. JMIR Ment Health 2021; 8:e30596. [PMID: 34477558 PMCID: PMC8449295 DOI: 10.2196/30596] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 06/22/2021] [Accepted: 06/22/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Sharing patient data can help drive scientific advances and improve patient care, but service users are concerned about how their data are used. When the National Health Service proposes to scrape general practitioner records, it is very important that we understand these concerns in some depth. OBJECTIVE This study aims to investigate views of mental health service users on acceptable data sharing to provide clear recommendations for future data sharing systems. METHODS A total of 4 focus groups with 4 member-checking groups were conducted via the internet between October 2020 and March 2021, with a total of 22 service users in the United Kingdom. Thematic analysis was used to identify the themes. RESULTS Six main themes, with several subthemes were identified, such as the purpose of data sharing-for profit, public good, and continuation of care; discrimination through the misattribution of physical symptoms to mental health conditions (ie, diagnostic overshadowing) alongside the discrimination of individuals or groups within society (ie, institutional discrimination); safeguarding data by preserving anonymity and confidentiality, strengthening security measures, and holding organizations accountable; data accuracy and informed consent-increasing transparency about data use and choice; and incorporating service user involvement in system governance to provide insight and increase security. CONCLUSIONS This study extends the limited research on the views and concerns of mental health service users regarding acceptable data sharing. If adopted, the recommendations should improve the confidence of service users in sharing their data. The five recommendations include screening to ensure that data sharing benefits the public, providing service users with information about how their data are shared and what for, highlighting the existing safeguarding procedures, incorporating service user involvement, and developing tailored training for health care professionals to address issues of diagnostic overshadowing and inaccurate health records. Adopting such systems would aid in data sharing for legitimate interests that will benefit patients and the National Health Service.
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Affiliation(s)
- Abimbola Adanijo
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Caoimhe McWilliams
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Til Wykes
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Sagar Jilka
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley NHS Foundation Trust, London, United Kingdom.,Division of Mental Health & Wellbeing, Warwick Medical School, University of Warwick, Coventry, United Kingdom
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18
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Bruno E, Böttcher S, Viana PF, Amengual-Gual M, Joseph B, Epitashvili N, Dümpelmann M, Glasstetter M, Biondi A, Van Laerhoven K, Loddenkemper T, Richardson MP, Schulze-Bonhage A, Brinkmann BH. Wearable devices for seizure detection: Practical experiences and recommendations from the Wearables for Epilepsy And Research (WEAR) International Study Group. Epilepsia 2021; 62:2307-2321. [PMID: 34420211 DOI: 10.1111/epi.17044] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 07/20/2021] [Accepted: 08/05/2021] [Indexed: 02/06/2023]
Abstract
The Wearables for Epilepsy And Research (WEAR) International Study Group identified a set of methodology standards to guide research on wearable devices for seizure detection. We formed an international consortium of experts from clinical research, engineering, computer science, and data analytics at the beginning of 2020. The study protocols and practical experience acquired during the development of wearable research studies were discussed and analyzed during bi-weekly virtual meetings to highlight commonalities, strengths, and weaknesses, and to formulate recommendations. Seven major essential components of the experimental design were identified, and recommendations were formulated about: (1) description of study aims, (2) policies and agreements, (3) study population, (4) data collection and technical infrastructure, (5) devices, (6) reporting results, and (7) data sharing. Introducing a framework of methodology standards promotes optimal, accurate, and consistent data collection. It also guarantees that studies are generalizable and comparable, and that results can be replicated, validated, and shared.
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Affiliation(s)
- Elisa Bruno
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sebastian Böttcher
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany.,Ubiquitous Computing, Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany
| | - Pedro F Viana
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Faculty of Medicine, University of Lisbon, Lisboa, Portugal
| | - Marta Amengual-Gual
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Boney Joseph
- Department of Neurology and Biomedical Engineering, Mayo Foundation, Rochester, Minnesota, USA
| | - Nino Epitashvili
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Matthias Dümpelmann
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Martin Glasstetter
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Andrea Biondi
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Kristof Van Laerhoven
- Ubiquitous Computing, Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Mark P Richardson
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Benjamin H Brinkmann
- Department of Neurology and Biomedical Engineering, Mayo Foundation, Rochester, Minnesota, USA
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19
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Abstract
Acceptability is a core concept in digital health. Available frameworks have not clearly articulated why and how researchers, practitioners and policy makers may wish to study the concept of acceptability. Here, we aim to discuss (i) the ways in which acceptability might differ from closely related concepts, including user engagement; (ii) the utility of the concept of acceptability in digital health research and practice; (iii) social and cultural norms that influence acceptability; and (iv) pragmatic means of measuring acceptability, within and beyond the research process. Our intention is not to offer solutions to these open questions but to initiate a debate within the digital health community. We conducted a narrative review of theoretical and empirical examples from the literature. First, we argue that acceptability may usefully be considered an emergent property of a complex, adaptive system of interacting components (e.g., affective attitude, beliefs), which in turn influences (and is influenced by) user engagement. Second, acceptability is important due to its ability to predict and explain key outcomes of interest, including user engagement and intervention effectiveness. Third, precisely what people find acceptable is deeply contextualized and interlinked with prevailing social and cultural norms. Understanding and designing for such norms (e.g., through drawing on principles of user centered design) is therefore key. Finally, there is a lack of standard acceptability measures and thresholds. Star ratings coupled with free-text responses may provide a pragmatic means of capturing acceptability. Acceptability is a multifaceted concept, which may usefully be studied with a complexity science lens.
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Affiliation(s)
- Olga Perski
- Department of Behavioural Science and Health, University College London, London, UK
| | - Camille E Short
- Melbourne Centre for Behaviour Change, Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia.,Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
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20
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Côté J, Beaudet L, Auger P, Rouleau G, Chicoine G, Léger V, Keezer M, Reid MA, Nguyen DK. Evaluation of a web-based virtual nursing intervention to support self-management among adults with epilepsy: A mixed-methods study. Epilepsy Behav 2021; 114:107581. [PMID: 33246896 DOI: 10.1016/j.yebeh.2020.107581] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 10/21/2020] [Accepted: 10/21/2020] [Indexed: 11/30/2022]
Abstract
OBJECTIVE A web-based intervention was developed to support epilepsy self-management. A mixed methods study was undertaken to evaluate the intervention's extent of utilization, acceptability and preliminary effects, and to assess user perception of it. METHODS First, a pilot parallel-group randomized controlled trial was conducted with a convenience sample of 75 adult with epilepsy who had Internet access allocated on a 1:1 ratio into an experimental group that received the intervention (experimental group (EG), n = 37) and a control group invited to consult epilepsy-related websites (control group (CG), n = 38). Self-management, knowledge, and quality of life (QoL) outcomes were measured at baseline and one and three months later. Descriptive statistics of extent of utilization and acceptability were computed. Linear mixed models were conducted to assess change in outcomes over time and between groups. Subsequently, an exploratory qualitative study was carried out with 15 EG participants. Qualitative data were subjected to thematic analysis. RESULTS Participants had a mean age of 40 years (range: 18-73), 45% were female, and mean time since diagnosis was 18 years (range: less than a year to 60 years). In the EG, 70% of the participants completed the intervention. Regarding acceptability, participants (n = 25) were satisfied overall (88%) and found content clear (92%) and the information reliable (100%). EG participants experienced greater improvement in QoL compared with CG participants, least-squares means (95% CI): 0.41 (0.06, 0.76). Three major themes emerged from the interviews (n = 15): intervention provides certain personal benefits; clinical content is of general interest but should be tailored; and intervention should target "new" patients early in the care trajectory. DISCUSSION The web-based intervention shows promise in terms of usefulness in enhancing QoL, and user experience showed that it is acceptable and helpful. It could constitute a complementary service in support of existing services for people with epilepsy and their families.
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Affiliation(s)
- José Côté
- Research Chair in Innovative Nursing Practices, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Research Centre of the Centre Hospitalier de l'Université de Montréal, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Faculty of Nursing of the Université de Montréal, 2375 Chemin de la Côte-Sainte-Catherine, Montreal, Quebec H3T 1A8, Canada.
| | - Line Beaudet
- Research Centre of the Centre Hospitalier de l'Université de Montréal, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Faculty of Nursing of the Université de Montréal, 2375 Chemin de la Côte-Sainte-Catherine, Montreal, Quebec H3T 1A8, Canada; Centre Hospitalier de l'Université de Montréal, 900 rue St-Denis, Montreal, Quebec H2X 0A9, Canada.
| | - Patricia Auger
- Research Chair in Innovative Nursing Practices, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Research Centre of the Centre Hospitalier de l'Université de Montréal, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada.
| | - Geneviève Rouleau
- Research Chair in Innovative Nursing Practices, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Research Centre of the Centre Hospitalier de l'Université de Montréal, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada.
| | - Gabrielle Chicoine
- Research Chair in Innovative Nursing Practices, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Faculty of Nursing of the Université de Montréal, 2375 Chemin de la Côte-Sainte-Catherine, Montreal, Quebec H3T 1A8, Canada.
| | - Vanessa Léger
- Centre Hospitalier de l'Université de Montréal, 900 rue St-Denis, Montreal, Quebec H2X 0A9, Canada.
| | - Mark Keezer
- Research Centre of the Centre Hospitalier de l'Université de Montréal, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Centre Hospitalier de l'Université de Montréal, 900 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Faculty of Medicine of the Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, Quebec H3T 1J4, Canada.
| | - Marc-André Reid
- Research Chair in Innovative Nursing Practices, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Faculty of Nursing of the Université de Montréal, 2375 Chemin de la Côte-Sainte-Catherine, Montreal, Quebec H3T 1A8, Canada.
| | - Dang Khoa Nguyen
- Research Centre of the Centre Hospitalier de l'Université de Montréal, 850 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Centre Hospitalier de l'Université de Montréal, 900 rue St-Denis, Montreal, Quebec H2X 0A9, Canada; Faculty of Medicine of the Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, Quebec H3T 1J4, Canada.
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21
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Bruno E, Biondi A, Böttcher S, Vértes G, Dobson R, Folarin A, Ranjan Y, Rashid Z, Manyakov N, Rintala A, Myin-Germeys I, Simblett S, Wykes T, Stoneman A, Little A, Thorpe S, Lees S, Schulze-Bonhage A, Richardson M. Remote Assessment of Disease and Relapse in Epilepsy: Protocol for a Multicenter Prospective Cohort Study. JMIR Res Protoc 2020; 9:e21840. [PMID: 33325373 PMCID: PMC7773514 DOI: 10.2196/21840] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 10/06/2020] [Accepted: 10/20/2020] [Indexed: 01/20/2023] Open
Abstract
Background In recent years, a growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. In clinical practice, seizure assessment typically relies on self-report, which is known to be highly unreliable. Moreover, most people with epilepsy self-identify factors that lead to increased seizure likelihood, including mood, behavior, sleep pattern, and cognitive alterations, all of which are amenable to measurement via multiparametric RMT. Objective The primary aim of this multicenter prospective cohort study is to assess the usability, feasibility, and acceptability of RMT in the community setting. In addition, this study aims to determine whether multiparametric RMT collected in populations with epilepsy can prospectively estimate variations in seizure occurrence and other outcomes, including seizure frequency, quality of life, and comorbidities. Methods People with a diagnosis of pharmacoresistant epilepsy will be recruited in London, United Kingdom, and Freiburg, Germany. Participants will be asked to wear a wrist-worn device and download ad hoc apps developed on their smartphones. The apps will be used to collect data related to sleep, physical activity, stress, mood, social interaction, speech patterns, and cognitive function, both passively from existing smartphone sensors (passive remote measurement technology [pRMT]) and actively via questionnaires, tasks, and assessments (active remote measurement technology [aRMT]). Data will be collected continuously for 6 months and streamed to the Remote Assessment of Disease and Relapse-base (RADAR-base) server. Results The RADAR Central Nervous System project received funding in 2015 from the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No. 115902. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and European Federation of Pharmaceutical Industries and Associations. Ethical approval was obtained in London from the Bromley Research Ethics Committee (research ethics committee reference: 19/LO/1884) in January 2020. The first participant was enrolled on September 30, 2020. Data will be collected until September 30, 2021. The results are expected to be published at the beginning of 2022. Conclusions RADAR Epilepsy aims at developing a framework of continuous data collection intended to identify ictal and preictal states through the use of aRMT and pRMT in the real-life environment. The study was specifically designed to evaluate the clinical usefulness of the data collected via new technologies and compliance, technology acceptability, and usability for patients. These are key aspects to successful adoption and implementation of RMT as a new way to measure and manage long-term disorders. International Registered Report Identifier (IRRID) PRR1-10.2196/21840
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Affiliation(s)
- Elisa Bruno
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Andrea Biondi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Sebastian Böttcher
- Epilepsy Center, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Gergely Vértes
- Epilepsy Seizure Detection - Neurology UCB Pharma, Brussels, Belgium
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Amos Folarin
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Yatharth Ranjan
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Zulqarnain Rashid
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Nikolay Manyakov
- Feasibility Advanced Analytics, Clinical Insights and Experience, Janssen Research and Development, Beerse, Belgium
| | - Aki Rintala
- Department of Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium.,Faculty of Social Services and Health Care, LAB University of Applied Sciences, Lahti, Finland
| | - Inez Myin-Germeys
- Department of Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium
| | - Sara Simblett
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Til Wykes
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Amanda Stoneman
- The RADAR-CNS patient advisory board, King's College London, UK, London, United Kingdom
| | - Ann Little
- The RADAR-CNS patient advisory board, King's College London, UK, London, United Kingdom
| | - Sarah Thorpe
- The RADAR-CNS patient advisory board, King's College London, UK, London, United Kingdom
| | - Simon Lees
- The RADAR-CNS patient advisory board, King's College London, UK, London, United Kingdom
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Mark Richardson
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
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22
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Craven MP, Andrews JA, Lang AR, Simblett SK, Bruce S, Thorpe S, Wykes T, Morriss R, Hollis C. Informing the Development of a Digital Health Platform Through Universal Points of Care: Qualitative Survey Study. JMIR Form Res 2020; 4:e22756. [PMID: 33242009 PMCID: PMC7728533 DOI: 10.2196/22756] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 09/17/2020] [Accepted: 09/30/2020] [Indexed: 01/14/2023] Open
Abstract
Background Epilepsy, multiple sclerosis (MS), and depression are chronic conditions where technology holds potential in clinical monitoring and self-management. Over 5 years, the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) consortium has explored the application of remote measurement technology (RMT) to the management and self-management of patients in these clinical areas. The consortium is large and includes clinical and nonclinical researchers as well as a patient advisory board. Objective This formative development study aimed to understand how consortium members viewed the potential of RMT in epilepsy, MS, and depression. Methods In this qualitative survey study, we developed a methodological tool, universal points of care (UPOC), to gather views on the potential use, acceptance, and value of a novel RMT platform across 3 chronic conditions (MS, epilepsy, and depression). UPOC builds upon use case scenario methodology, using expert elicitation and analysis of care pathways to develop scenarios applicable across multiple conditions. After developing scenarios, we elicited views on the potential of RMT in these different scenarios through a survey administered to 28 subject matter experts, consisting of 16 health care practitioners; 5 health care services researchers; and 7 people with lived experience of MS, epilepsy, or depression. Survey results were analyzed thematically and using an existing framework of factors describing links between design and context. Results The survey elicited potential beneficial applications of the RADAR-CNS RMT system as well as patient, clinical, and nonclinical requirements of RMT across the 3 conditions of interest. Potential applications included recognition of early warning signs of relapse from subclinical signals for MS, seizure precipitant signals for epilepsy, and behavior change in depression. RMT was also thought to have the potential to overcome the problem of underreporting, which is especially problematic in epilepsy, and to allow the capture of secondary symptoms that are not generally collected in MS, such as mood. Conclusions Respondents suggested novel and unanticipated uses of RMT, including the use of RMT to detect emerging side effects of treatment, enable behavior change for sleep regulation and activity, and offer a way to include family and other carers in a care network, which could assist with goal setting. These suggestions, together with others from this and related work, will inform the development of the system for its eventual application in research and clinical practice. The UPOC methodology was effective in directing respondents to consider the value of health care technologies in condition-specific experiences of everyday life and working practice.
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Affiliation(s)
- Michael P Craven
- NIHR Mindtech Medtech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom.,Bioengineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom
| | - Jacob A Andrews
- NIHR Mindtech Medtech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom.,Division of Psychiatry and Applied Psychology, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Alexandra R Lang
- Human Factors Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
| | - Sara K Simblett
- Institute of Psychology, Psychiatry and Neuroscience, King's College London, London, United Kingdom
| | - Stuart Bruce
- Patient Advisory Board, RADAR-CNS, London, United Kingdom
| | - Sarah Thorpe
- Patient Advisory Board, RADAR-CNS, London, United Kingdom
| | - Til Wykes
- Institute of Psychology, Psychiatry and Neuroscience, King's College London, London, United Kingdom.,NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Richard Morriss
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.,Division of Psychiatry and Applied Psychology, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Chris Hollis
- NIHR Mindtech Medtech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom.,Division of Psychiatry and Applied Psychology, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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23
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Bruno E, Biondi A, Böttcher S, Lees S, Schulze-Bonhage A, Richardson MP. Day and night comfort and stability on the body of four wearable devices for seizure detection: A direct user-experience. Epilepsy Behav 2020; 112:107478. [PMID: 33181896 DOI: 10.1016/j.yebeh.2020.107478] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 08/24/2020] [Accepted: 09/06/2020] [Indexed: 12/25/2022]
Abstract
PURPOSE Wearable devices are progressively becoming an available tool for continuous seizure detection. Motivation to use wearables is not only driven by the accuracy and reliability of the performance but also by the form factor, comfort, and stability on the body. We collected direct feedback and device placement-related issues experienced by a cohort of people with epilepsy (PWE) to investigate to what extent available devices are nonintrusive, comfortable, and stable on the body. METHODS Four models of wearable devices (E4 wrist band, Everion upper arm band, IMEC upper arm band, and Epilog scalp patch electrodes) were worn by PWE who were admitted to two epilepsy monitoring units (EMUs) in London and Freiburg. Participants were periodically reviewed, and accidental displacements of the devices were annotated. Participants' experience was assessed using the Technology Acceptance Model Fast Form (TAM-FF) plus two additional questions on comfort. A thematic analysis was also performed on the free text of the questionnaire. RESULTS One hundred and fifteen participants were enrolled. The devices had a good stability on the body including during seizures. Overall, all the devices were considered comfortable to be worn, including during sleep. However, devices containing wires and patches demonstrated a lesser degree of stability on the body and were judged less positively. Participants age was correlated with TAM-FF mean scores, and older participants judged the devices less favorably compared with younger participants. DISCUSSION Removable but securely fitted, wireless, and comfortable designs were considered more appropriate for a continuous monitoring aimed at seizure detection. Some caution may be required when patch electrodes and electrodes glued to the skin or to the scalp are used, as those evaluated in the present study demonstrated a lower level of acceptability and a lower degree of stability to the body, especially at night. These factors could limit a continuous monitoring decreasing the device performance for nocturnal, unsupervised seizures which are at higher risk of lethality.
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Affiliation(s)
- Elisa Bruno
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.
| | - Andrea Biondi
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Sebastian Böttcher
- Epilepsy Center, Department of Neurosurgery, Medical Center, University of Freiburg, Germany
| | - Simon Lees
- The RADAR-CNS patient advisory board, King's College London, UK
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Department of Neurosurgery, Medical Center, University of Freiburg, Germany
| | - Mark P Richardson
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
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24
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Bruno E, Biondi A, Thorpe S, Richardson M. Patients self-mastery of wearable devices for seizure detection: A direct user-experience. Seizure 2020; 81:236-40. [DOI: 10.1016/j.seizure.2020.08.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/05/2020] [Accepted: 08/19/2020] [Indexed: 11/22/2022] Open
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25
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Simblett S, Matcham F, Curtis H, Greer B, Polhemus A, Novák J, Ferrao J, Gamble P, Hotopf M, Narayan V, Wykes T. Patients' Measurement Priorities for Remote Measurement Technologies to Aid Chronic Health Conditions: Qualitative Analysis. JMIR Mhealth Uhealth 2020; 8:e15086. [PMID: 32519975 PMCID: PMC7315360 DOI: 10.2196/15086] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 10/31/2019] [Accepted: 12/15/2019] [Indexed: 01/19/2023] Open
Abstract
Background Remote measurement technology (RMT), including the use of mobile phone apps and wearable devices, may provide the opportunity for real-world assessment and intervention that will streamline clinical input for years to come. In order to establish the benefits of this approach, we need to operationalize what is expected in terms of a successful measurement. We focused on three clinical long-term conditions where a novel case has been made for the benefits of RMT: major depressive disorder (MDD), multiple sclerosis (MS), and epilepsy. Objective The aim of this study was to conduct a consultation exercise on the clinical end point or outcome measurement priorities for RMT studies, drawing on the experiences of people with chronic health conditions. Methods A total of 24 participants (16/24 women, 67%), ranging from 28 to 65 years of age, with a diagnosis of one of three chronic health conditions―MDD, MS, or epilepsy―took part in six focus groups. A systematic thematic analysis was used to extract themes and subthemes of clinical end point or measurement priorities. Results The views of people with MDD, epilepsy, and MS differed. Each group highlighted unique measurements of importance, relevant to their specific needs. Although there was agreement that remote measurement could be useful for tracking symptoms of illness, some symptoms were specific to the individual groups. Measuring signs of wellness was discussed more by people with MDD than by people with MS and epilepsy. However, overlap did emerge when considering contextual factors, such as life events and availability of support (MDD and epilepsy) as well as ways of coping (epilepsy and MS). Conclusions This is a unique study that puts patients’ views at the forefront of the design of a clinical study employing novel digital resources. In all cases, measuring symptom severity is key; people want to know when their health is getting worse. Second, symptom severity needs to be placed into context. A holistic approach that, in some cases, considers signs of wellness as well as illness, should be the aim of studies employing RMT to understand the health of people with chronic conditions.
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Affiliation(s)
- Sara Simblett
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Faith Matcham
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Hannah Curtis
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Ben Greer
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Ashley Polhemus
- Merck Research Labs IT, Merck Sharpe & Dohme, Prague, Czech Republic
| | - Jan Novák
- Merck Research Labs IT, Merck Sharpe & Dohme, Prague, Czech Republic
| | - Jose Ferrao
- Merck Research Labs IT, Merck Sharpe & Dohme, Prague, Czech Republic
| | - Peter Gamble
- Merck Research Labs IT, Merck Sharpe & Dohme, Prague, Czech Republic
| | - Matthew Hotopf
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | | | - Til Wykes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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- RADAR-CNS, London, United Kingdom
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26
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Nasseri M, Nurse E, Glasstetter M, Böttcher S, Gregg NM, Laks Nandakumar A, Joseph B, Pal Attia T, Viana PF, Bruno E, Biondi A, Cook M, Worrell GA, Schulze-Bonhage A, Dümpelmann M, Freestone DR, Richardson MP, Brinkmann BH. Signal quality and patient experience with wearable devices for epilepsy management. Epilepsia 2020; 61 Suppl 1:S25-S35. [PMID: 32497269 DOI: 10.1111/epi.16527] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 04/14/2020] [Accepted: 04/14/2020] [Indexed: 01/24/2023]
Abstract
Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject poor-quality or corrupt data segments. In this study, commercially available wearable sensors were placed on patients with epilepsy undergoing in-hospital or in-home electroencephalographic (EEG) monitoring, and healthy volunteers. Empatica E4 and Biovotion Everion were used to record accelerometry (ACC), photoplethysmography (PPG), and electrodermal activity (EDA). Byteflies Sensor Dots were used to record ACC and PPG, the Activinsights GENEActiv watch to record ACC, and Epitel Epilog to record EEG data. PPG and EDA signals were recorded for multiple days, then epochs of high-quality, marginal-quality, or poor-quality data were visually identified by reviewers, and reviewer annotations were compared to automated signal quality measures. For ACC, the ratio of spectral power from 0.8 to 5 Hz to broadband power was used to separate good-quality signals from noise. For EDA, the rate of amplitude change and prevalence of sharp peaks significantly differentiated between good-quality data and noise. Spectral entropy was used to assess PPG and showed significant differences between good-, marginal-, and poor-quality signals. EEG data were evaluated using methods to identify a spectral noise cutoff frequency. Patients were asked to rate the usability and comfort of each device in several categories. Patients showed a significant preference for the wrist-worn devices, and the Empatica E4 device was preferred most often. Current wearable devices can provide high-quality data and are acceptable for routine use, but continued development is needed to improve data quality, consistency, and management, as well as acceptability to patients.
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Affiliation(s)
- Mona Nasseri
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ewan Nurse
- Seer Medical, Melbourne, Victoria, Australia.,Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Martin Glasstetter
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Sebastian Böttcher
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Nicholas M Gregg
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Boney Joseph
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Tal Pal Attia
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Pedro F Viana
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.,Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Elisa Bruno
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Andrea Biondi
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Mark Cook
- Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Gregory A Worrell
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andreas Schulze-Bonhage
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Matthias Dümpelmann
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | | | - Mark P Richardson
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Benjamin H Brinkmann
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
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27
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Bruno E, Viana PF, Sperling MR, Richardson MP. Seizure detection at home: Do devices on the market match the needs of people living with epilepsy and their caregivers? Epilepsia 2020; 61 Suppl 1:S11-S24. [DOI: 10.1111/epi.16521] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 04/08/2020] [Accepted: 04/09/2020] [Indexed: 01/22/2023]
Affiliation(s)
- Elisa Bruno
- Division of Neuroscience Institute of Psychiatry, Psychology & Neuroscience King's College London UK
| | - Pedro F. Viana
- Division of Neuroscience Institute of Psychiatry, Psychology & Neuroscience King's College London UK
- Faculdade de Medicina Universidade de Lisboa Lisboa Portugal
- Department of Neurosciences and Mental Health (Neurology) Centro Hospitalar Lisboa Norte Lisboa Portugal
| | - Michael R. Sperling
- Department of Neurology Jefferson Comprehensive Epilepsy Center Thomas Jefferson University Philadelphia PA USA
| | - Mark P. Richardson
- Division of Neuroscience Institute of Psychiatry, Psychology & Neuroscience King's College London UK
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28
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Lewinski AA, Shapiro A, Gierisch JM, Goldstein KM, Blalock DV, Luedke MW, Gordon AM, Bosworth HB, Drake C, Lewis JD, Sinha SR, Husain AM, Tran TT, Van Noord MG, Williams JW. Barriers and facilitators to implementation of epilepsy self-management programs: a systematic review using qualitative evidence synthesis methods. Syst Rev 2020; 9:92. [PMID: 32334641 PMCID: PMC7183113 DOI: 10.1186/s13643-020-01322-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 03/06/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Epilepsy affects nearly 50 million people worldwide. Self-management is critical for individuals with epilepsy in order to maintain optimal physical, cognitive, and emotional health. Implementing and adopting a self-management program requires considering many factors at the person, program, and systems levels. We conducted a systematic review of qualitative and mixed-methods studies to identify facilitators and barriers that impact implementation and adoption of self-management programs for adults with epilepsy. METHODS We used established systematic review methodologies for qualitative and mixed-methods studies. We included studies addressing facilitators (i.e., factors that aided) or barriers (i.e., factors that impeded) to implementation and adoption of self-management interventions for adults with epilepsy. We conducted a narrative thematic synthesis to identify facilitators and barriers. RESULTS The literature search identified 2700 citations; 13 studies met eligibility criteria. Our synthesis identified five themes that categorize facilitators and barriers to successful implementation epilepsy self-management: (1) relevance, intervention content that facilitates acquisition of self-management skills; (2) personalization, intervention components that account for the individual's social, physical, and environmental characteristics; (3) intervention components, components and dosing of the intervention; (4) technology considerations, considerations that account for individual's use, familiarity with, and ownership of technology; and (5) clinician interventionist, role and preparation of the individual who leads intervention. We identified facilitators in 11 of the 13 studies and barriers in 11 of the 13 studies and classified these by social-ecological level (i.e., patient/caregiver, program, site/system). CONCLUSION Identification of facilitators and barriers at multiple levels provides insight into disease-specific factors that influence implementation and adoption of self-management programs for individuals with epilepsy. Our findings indicate that involving individuals with epilepsy and their caregivers in intervention development, and then tailoring intervention content during the intervention, can help ensure the content is relevant to intervention participants. Our findings also indicate the role of the clinician (i.e., the individual who provides self-management education) is important to intervention implementation, and key issues with clinicians were identified as barriers and opportunities for improvement. Overall, our findings have practical value for those seeking to implement and adopt self-management interventions for epilepsy and other chronic illnesses. SYSTEMATIC REVIEW REGISTRATION PROSPERO registration number is CRD42018098604.
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Affiliation(s)
- Allison A Lewinski
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.
| | - Abigail Shapiro
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Cooperative Studies Program Epidemiology Center-Durham, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Jennifer M Gierisch
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.,Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Karen M Goldstein
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Dan V Blalock
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Matthew W Luedke
- Department of Neurology, Duke University Medical Center, Durham, NC, USA.,Neurodiagonostic Center, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Adelaide M Gordon
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Hayden B Bosworth
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.,Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA.,School of Nursing, Duke University, Durham, NC, USA.,Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Connor Drake
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Center for Personalized Health Care, Duke University School of Medicine, Durham, NC, USA
| | - Jeffrey D Lewis
- Department of Neurology, Uniformed Services University School of Medicine, Bethesda, MD, USA
| | - Saurabh R Sinha
- Department of Neurology, Duke University Medical Center, Durham, NC, USA.,Neurodiagonostic Center, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Aatif M Husain
- Department of Neurology, Duke University Medical Center, Durham, NC, USA.,Neurodiagonostic Center, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Neuroscience Medicine, Duke Clinical Research Institute, Duke University, Durham, NC, USA
| | - Tung T Tran
- Department of Neurology, Duke University Medical Center, Durham, NC, USA.,Neurodiagonostic Center, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | | | - John W Williams
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA.,Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
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29
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Simblett SK, Biondi A, Bruno E, Ballard D, Stoneman A, Lees S, Richardson MP, Wykes T. Patients' experience of wearing multimodal sensor devices intended to detect epileptic seizures: A qualitative analysis. Epilepsy Behav 2020; 102:106717. [PMID: 31785481 DOI: 10.1016/j.yebeh.2019.106717] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 11/13/2019] [Accepted: 11/13/2019] [Indexed: 01/10/2023]
Abstract
BACKGROUND The health management of patients with epilepsy could be improved by wearing devices that reliably detect when epileptic seizures happen. For the devices to be widely adopted, they must be acceptable and easy to use for patients, and their views are very important. Previous studies have collected feedback from patients on hypothetical devices, but very few have examined experience of wearing actual devices. PURPOSE This study assessed the first-hand experiences of people with epilepsy using wearable devices, continuously over a period of time. The aim was to understand how acceptable and easy they were to use, and whether it is reasonable to expect that people will use them. MATERIALS AND METHODS Adults with a diagnosis of epilepsy admitted routinely to a hospital epilepsy monitoring unit were asked to wear one, or more, wearable biosensor devices, tested for seizure detection. The devices are designed to continuously monitor and record signals from the body (biosignals). Participants completed semistructured interviews about their experiences of wearing the device(s). A systematic thematic analysis extracted themes from the interviews, focusing on acceptability and usability. Feedback was organized into (1) participants' experiences of the devices, any support they required and reasons for stopping wearing them; (2) their thoughts about using this technology outside a hospital setting. RESULTS Twenty-one people with epilepsy wore one, or more, wearable devices for an average of 112.81 (SD = 71.83) hours. Participants found the devices convenient, and had no problem wearing them in hospital or sharing the data collected from them with the researchers and medical professionals. However, the presence of wires, bulky size, discomfort, and need for support, moderated experience. Participants' thoughts about wearing them in everyday life were strongly influenced by how visible and perceived accuracy. Willingness to use a smartphone app to complete questionnaires depended on the frequency, number of questions, and support. CONCLUSIONS Overall, this work provides evidence about the feasibility and acceptability of using wearable devices to monitor seizure activity in people with epilepsy. Key barriers and facilitators to use while in hospital and hypothetical use in everyday life were identified and will be helpful for guiding future implementation.
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Affiliation(s)
- Sara Katherine Simblett
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom.
| | - Andrea Biondi
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, United Kingdom
| | - Elisa Bruno
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, United Kingdom
| | - Dominic Ballard
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, United Kingdom
| | - Amanda Stoneman
- Epilepsy Action (British Epilepsy Association), New Anstey House, Leeds, United Kingdom; RADAR-CNS Patient Advisory Board, King's College London, London, United Kingdom
| | - Simon Lees
- RADAR-CNS Patient Advisory Board, King's College London, London, United Kingdom
| | - Mark P Richardson
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, United Kingdom; NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, United Kingdom
| | - Til Wykes
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, United Kingdom
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