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Ferreira J, Peixoto R, Lopes L, Beniczky S, Ryvlin P, Conde C, Claro J. User involvement in the design and development of medical devices in epilepsy: A systematic review. Epilepsia Open 2024. [PMID: 39324505 DOI: 10.1002/epi4.13038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 07/27/2024] [Accepted: 08/13/2024] [Indexed: 09/27/2024] Open
Abstract
OBJECTIVE This systematic review aims to describe the involvement of persons with epilepsy (PWE), healthcare professionals (HP) and caregivers (CG) in the design and development of medical devices is epilepsy. METHODS A systematic review was conducted, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligibility criteria included peer-reviewed research focusing on medical devices for epilepsy management, involving users (PWE, CG, and HP) during the MDD process. Searches were performed on PubMed, Web of Science, and Scopus, and a total of 55 relevant articles were identified and reviewed. RESULTS From 1999 to 2023, there was a gradual increase in the number of publications related to user involvement in epilepsy medical device development (MDD), highlighting the growing interest in this field. The medical devices involved in these studies encompassed a range of seizure detection tools, healthcare information systems, vagus nerve stimulation (VNS) and electroencephalogram (EEG) technologies reflecting the emphasis on seizure detection, prediction, and prevention. PWE and CG were the primary users involved, underscoring the importance of their perspectives. Surveys, usability testing, interviews, and focus groups were the methods used for capturing user perspectives. User involvement occurs in four out of the five stages of MDD, with production being the exception. SIGNIFICANCE User involvement in the MDD process for epilepsy management is an emerging area of interest holding a significant promise for improving device quality and patient outcomes. This review highlights the need for broader and more effective user involvement, as it currently lags in the development of commercially available medical devices for epilepsy management. Future research should explore the benefits and barriers of user involvement to enhance medical device technologies for epilepsy. PLAIN LANGUAGE SUMMARY This review covers studies that have involved users in the development process of medical devices for epilepsy. The studies reported here have focused on getting input from people with epilepsy, their caregivers, and healthcare providers. These devices include tools for detecting seizures, stimulating nerves, and tracking brain activity. Most user feedback was gathered through surveys, usability tests, interviews, and focus groups. Users were involved in nearly every stage of device development except production. The review highlights that involving users can improve device quality and patient outcomes, but more effective involvement is needed in commercial device development. Future research should focus on the benefits and challenges of user involvement.
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Affiliation(s)
- João Ferreira
- Faculty of Engineering, University of Porto, Porto, Portugal
- Biostrike Unipessoal Lda, Porto, Portugal
| | - Ricardo Peixoto
- Faculty of Engineering, University of Porto, Porto, Portugal
- Biostrike Unipessoal Lda, Porto, Portugal
| | - Lígia Lopes
- Faculty of Engineering, University of Porto, Porto, Portugal
- FBAUP-Faculty of Fine Arts, University of Porto, Porto, Portugal
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
| | - Carlos Conde
- i3S, Instituto de Investigação e Inovação Em Saúde, University of Porto, Porto, Portugal
- School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal
- Institute for Molecular and Cell Biology, University of Porto, Porto, Portugal
| | - João Claro
- Faculty of Engineering, University of Porto, Porto, Portugal
- INESC TEC, Porto, Portugal
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Moorthy P, Weinert L, Schüttler C, Svensson L, Sedlmayr B, Müller J, Nagel T. Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review. JMIR Mhealth Uhealth 2024; 12:e52179. [PMID: 38578671 PMCID: PMC11031706 DOI: 10.2196/52179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 12/15/2023] [Accepted: 02/01/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential. OBJECTIVE This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations. METHODS We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords "wearable devices," "mobile apps," "mHealth apps," "physiological data," "usability," "user experience," and "user evaluation" were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. RESULTS A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation. CONCLUSIONS Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.
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Affiliation(s)
- Preetha Moorthy
- Department of Biomedical Informatics, Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lina Weinert
- Institute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany
- Section for Oral Health, Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg, Germany
| | - Christina Schüttler
- Medical Center for Information and Communication Technology, University Hospital Erlangen, Erlangen, Germany
| | - Laura Svensson
- Institute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany
| | - Brita Sedlmayr
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Julia Müller
- Institute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany
| | - Till Nagel
- Human Data Interaction Lab, Mannheim University of Applied Sciences, Mannheim, Germany
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Komal K, Cleary F, Wells JSG, Bennett L. A systematic review of the literature reporting on remote monitoring epileptic seizure detection devices. Epilepsy Res 2024; 201:107334. [PMID: 38442551 DOI: 10.1016/j.eplepsyres.2024.107334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/19/2024] [Accepted: 02/26/2024] [Indexed: 03/07/2024]
Abstract
BACKGROUND Early detection and alert notification of an impending seizure for people with epilepsy have the potential to reduce Sudden Unexpected Death in Epilepsy (SUDEP). Current remote monitoring seizure detection devices for people with epilepsy are designed to support real-time monitoring of their vital health parameters linked to seizure alert notification. An understanding of the rapidly growing literature on remote seizure detection devices is essential to address the needs of people with epilepsy and their carers. AIM This review aims to examine the technical characteristics, device performance, user preference, and effectiveness of remote monitoring seizure detection devices. METHODOLOGY A systematic review referenced to PRISMA guidelines was used. RESULTS A total of 1095 papers were identified from the initial search with 30 papers included in the review. Sixteen non-invasive remote monitoring seizure detection devices are currently available. Such seizure detection devices were found to have inbuilt intelligent sensor functionality to monitor electroencephalography, muscle movement, and accelerometer-based motion movement for detecting seizures remotely. Current challenges of these devices for people with epilepsy include skin irritation due to the type of patch electrode used and false alarm notifications, particularly during physical activity. The tight-fitted accelerometer-type devices are reported as uncomfortable from a wearability perspective for long-term monitoring. Also, continuous recording of physiological signals and triggering alert notifications significantly reduce the battery life of the devices. The literature highlights that 3.2 out of 5 people with epilepsy are not using seizure detection devices because of the cost and appearance of the device. CONCLUSION Seizure detection devices can potentially reduce morbidity and mortality for people with epilepsy. Therefore, further collaboration of clinicians, technical experts, and researchers is needed for the future development of these devices. Finally, it is important to always take into consideration the expectations and requirements of people with epilepsy and their carers to facilitate the next generation of remote monitoring seizure detection devices.
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Affiliation(s)
- K Komal
- School of Health Sciences, South East Technological University, Cork Road, Waterford, Ireland; Walton Institute, South East Technological University, Cork Road, Waterford, Ireland.
| | - F Cleary
- Walton Institute, South East Technological University, Cork Road, Waterford, Ireland
| | - J S G Wells
- School of Health Sciences, South East Technological University, Cork Road, Waterford, Ireland
| | - L Bennett
- School of Health Sciences, South East Technological University, Cork Road, Waterford, Ireland
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Donner E, Devinsky O, Friedman D. Wearable Digital Health Technology for Epilepsy. N Engl J Med 2024; 390:736-745. [PMID: 38381676 DOI: 10.1056/nejmra2301913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Affiliation(s)
- Elizabeth Donner
- From the Division of Neurology, Hospital for Sick Children, and the Department of Paediatrics, University of Toronto - both in Toronto (E.D.); and the Epilepsy Center, Department of Neurology, New York University Grossman School of Medicine, New York (O.D., D.F.)
| | - Orrin Devinsky
- From the Division of Neurology, Hospital for Sick Children, and the Department of Paediatrics, University of Toronto - both in Toronto (E.D.); and the Epilepsy Center, Department of Neurology, New York University Grossman School of Medicine, New York (O.D., D.F.)
| | - Daniel Friedman
- From the Division of Neurology, Hospital for Sick Children, and the Department of Paediatrics, University of Toronto - both in Toronto (E.D.); and the Epilepsy Center, Department of Neurology, New York University Grossman School of Medicine, New York (O.D., D.F.)
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5
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Jeppesen J, Christensen J, Mølgaard H, Beniczky S. Automated detection of focal seizures using subcutaneously implanted electrocardiographic device: A proof-of-concept study. Epilepsia 2023; 64 Suppl 4:S59-S64. [PMID: 37029748 DOI: 10.1111/epi.17612] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/06/2023] [Accepted: 04/06/2023] [Indexed: 04/09/2023]
Abstract
Phase 2 studies showed that focal seizures could be detected by algorithms using heart rate variability (HRV) in patients with marked autonomic ictal changes. However, wearable surface electrocardiographic (ECG) devices use electrode patches that need to be changed often and may cause skin irritation. We report the first study of automated seizure detection using a subcutaneously implantable cardiac monitor (ICM; Confirm Rx, Abbott). For this proof-of-concept (phase 1) study, we recruited six patients admitted to long-term video-electroencephalographic monitoring. Fifteen-minute epochs of ECG signals were saved for each seizure and for control (nonseizure) epochs in the epilepsy monitoring unit (EMU) and in the patients' home environment (1-8 months). We analyzed the ICM signals offline, using a previously developed HRV algorithm. Thirteen seizures were recorded in the EMU, and 41 seizures were recorded in the home-monitoring period. The algorithm accurately identified 50 of 54 focal seizures (sensitivity = 92.6%, 95% confidence interval [CI] = 85.6%-99.6%). Twelve of the 13 seizures in the EMU were detected (sensitivity = 92.3%, 95% CI = 77.2%-100%), and 38 of the 41 seizures in the out-of-hospital setting were detected (sensitivity = 92.7%, 95% CI = 84.7%-100%). Four false detections were found in the 141 control (nonseizure) epochs (false alarm rate = 2.7/24 h). Our results suggest that automated seizure detection using a long-term, subcutaneous ICM device is feasible and accurate in patients with focal seizures and autonomic ictal changes.
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Affiliation(s)
- Jesper Jeppesen
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Jakob Christensen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | - Henning Mølgaard
- Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark
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Hadady L, Klivényi P, Fabó D, Beniczky S. Real-world user experience with seizure detection wearable devices in the home environment. Epilepsia 2023; 64 Suppl 4:S72-S77. [PMID: 35195898 DOI: 10.1111/epi.17189] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/29/2022] [Accepted: 01/31/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To evaluate direct user experience with wearable seizure detection devices in the home environment. METHODS A structured online questionnaire was completed by 242 users (175 caregivers and 67 persons with epilepsy), most of the patients (87.19%) having tonic-clonic seizures. RESULTS The vast majority of the users were overall satisfied with the wearable device, considered that using the device was easy, and agreed that the use of the device improved their quality of life (median = 6 on 7-point Likert scale). A high retention rate (84.58%) and a long median usage time (14 months) were reported. In the home environment, most users (75.85%) experienced seizure detection sensitivity similar (≥95%) to what was previously reported in validation studies in epilepsy monitoring units. The experienced false alarm rate was relatively low (0-0.43 per day). Due to the alarms, almost one third of persons with epilepsy (PWEs; 30.00%) experienced decrease in the number of seizure-related injuries, and almost two thirds of PWEs (65.41%) experienced improvement in the accuracy of seizure diaries. Nonvalidated devices had significantly lower retention rate, overall satisfaction, perceived sensitivity, and improvement in quality of life, as compared with validated devices. SIGNIFICANCE Our results demonstrate the feasibility and usefulness of automated seizure detection in the home environment.
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Affiliation(s)
- Levente Hadady
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
| | - Péter Klivényi
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
| | - Dániel Fabó
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Sándor Beniczky
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Danish Epilepsy Center, Dianalund, Denmark
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Böttcher S, Vieluf S, Bruno E, Joseph B, Epitashvili N, Biondi A, Zabler N, Glasstetter M, Dümpelmann M, Van Laerhoven K, Nasseri M, Brinkman BH, Richardson MP, Schulze-Bonhage A, Loddenkemper T. Data quality evaluation in wearable monitoring. Sci Rep 2022; 12:21412. [PMID: 36496546 PMCID: PMC9741649 DOI: 10.1038/s41598-022-25949-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Wearable recordings of neurophysiological signals captured from the wrist offer enormous potential for seizure monitoring. Yet, data quality remains one of the most challenging factors that impact data reliability. We suggest a combined data quality assessment tool for the evaluation of multimodal wearable data. We analyzed data from patients with epilepsy from four epilepsy centers. Patients wore wristbands recording accelerometry, electrodermal activity, blood volume pulse, and skin temperature. We calculated data completeness and assessed the time the device was worn (on-body), and modality-specific signal quality scores. We included 37,166 h from 632 patients in the inpatient and 90,776 h from 39 patients in the outpatient setting. All modalities were affected by artifacts. Data loss was higher when using data streaming (up to 49% among inpatient cohorts, averaged across respective recordings) as compared to onboard device recording and storage (up to 9%). On-body scores, estimating the percentage of time a device was worn on the body, were consistently high across cohorts (more than 80%). Signal quality of some modalities, based on established indices, was higher at night than during the day. A uniformly reported data quality and multimodal signal quality index is feasible, makes study results more comparable, and contributes to the development of devices and evaluation routines necessary for seizure monitoring.
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Affiliation(s)
- Sebastian Böttcher
- grid.7708.80000 0000 9428 7911Department of Neurosurgery, Epilepsy Center, Medical Center – University of Freiburg, Freiburg, Germany ,grid.5836.80000 0001 2242 8751Ubiquitous Computing, Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany
| | - Solveig Vieluf
- grid.38142.3c000000041936754XDivision of Epilepsy and Clinical Neurophysiology, Boston Children’s Hospital, Harvard Medical School, Boston, MS USA
| | - Elisa Bruno
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK
| | - Boney Joseph
- grid.66875.3a0000 0004 0459 167XBioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN USA
| | - Nino Epitashvili
- grid.7708.80000 0000 9428 7911Department of Neurosurgery, Epilepsy Center, Medical Center – University of Freiburg, Freiburg, Germany
| | - Andrea Biondi
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK
| | - Nicolas Zabler
- grid.7708.80000 0000 9428 7911Department of Neurosurgery, Epilepsy Center, Medical Center – University of Freiburg, Freiburg, Germany
| | - Martin Glasstetter
- grid.7708.80000 0000 9428 7911Department of Neurosurgery, Epilepsy Center, Medical Center – University of Freiburg, Freiburg, Germany
| | - Matthias Dümpelmann
- grid.7708.80000 0000 9428 7911Department of Neurosurgery, Epilepsy Center, Medical Center – University of Freiburg, Freiburg, Germany ,grid.5963.9Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany
| | - Kristof Van Laerhoven
- grid.5836.80000 0001 2242 8751Ubiquitous Computing, Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany
| | - Mona Nasseri
- grid.66875.3a0000 0004 0459 167XBioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN USA ,grid.266865.90000 0001 2109 4358School of Engineering, University of North Florida, Jacksonville, FL USA
| | - Benjamin H. Brinkman
- grid.66875.3a0000 0004 0459 167XBioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN USA
| | - Mark P. Richardson
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK
| | - Andreas Schulze-Bonhage
- grid.7708.80000 0000 9428 7911Department of Neurosurgery, Epilepsy Center, Medical Center – University of Freiburg, Freiburg, Germany
| | - Tobias Loddenkemper
- grid.38142.3c000000041936754XDivision of Epilepsy and Clinical Neurophysiology, Boston Children’s Hospital, Harvard Medical School, Boston, MS USA
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Ding Y, Liu C, Xu H, Wang M, Zhang J, Gu J, Cui Y, Wei L, Zhang Y. Effect of social support on illness perception in patients with atrial fibrillation during "Blanking Period": Mediating role of sense of mastery. Nurs Open 2022; 10:115-122. [PMID: 35855521 PMCID: PMC9748061 DOI: 10.1002/nop2.1284] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 04/12/2022] [Accepted: 06/05/2022] [Indexed: 01/04/2023] Open
Abstract
AIM To explore whether sense of mastery can mediate the relationship between social support and illness perception in patients with atrial fibrillation (AF) who were at the "Blanking Period." DESIGN A cross-sectional design. METHODS 405 patients with AF who were at the "Blanking Period" in the Affiliated Hospital of Qingdao University were recruited; they completed a set of questionnaires, including the Perceived Social Support Scale, the Personal Mastery Scale and the Brief Illness Perception Questionnaire. RESULTS Social support and sense of mastery were both adversely connected to illness perception. The indirect effect of social support on illness perception through sense of mastery was negative, accounting for 86.04% of the total effect. CONCLUSION During the "Blanking Period," better social support and sense of mastery contribute to a positive illness perception of AF patients. Social support also can influence patients' illness perception indirectly via the mediator of sense of mastery.
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Affiliation(s)
- Yun‐Mei Ding
- School of NursingQingdao UniversityQingdaoChina,Affiliated Hospital of Qingdao UniversityQingdaoChina
| | | | - Hong‐Xuan Xu
- Department of Health SciencesLund UniversityLundSweden
| | - Mao‐Jing Wang
- Affiliated Hospital of Qingdao UniversityQingdaoChina
| | | | - Jia‐Yun Gu
- School of NursingQingdao UniversityQingdaoChina
| | - Yan Cui
- Affiliated Hospital of Qingdao UniversityQingdaoChina
| | - Lili Wei
- Department of NursingAffiliated Hospital of Qingdao UniversityQingdaoChina
| | - Yan Zhang
- Department of NursingAffiliated Hospital of Qingdao UniversityQingdaoChina
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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: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [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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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: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [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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11
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Qureshi HN, Manalastas M, Ijaz A, Imran A, Liu Y, Al Kalaa MO. Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations. Healthcare (Basel) 2022; 10:293. [PMID: 35206907 PMCID: PMC8872156 DOI: 10.3390/healthcare10020293] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/13/2022] [Accepted: 01/14/2022] [Indexed: 11/24/2022] Open
Abstract
Fifth generation (5G) mobile communication technology can enable novel healthcare applications and augment existing ones. However, 5G-enabled healthcare applications demand diverse technical requirements for radio communication. Knowledge of these requirements is important for developers, network providers, and regulatory authorities in the healthcare sector to facilitate safe and effective healthcare. In this paper, we review, identify, describe, and compare the requirements for communication key performance indicators in relevant healthcare use cases, including remote robotic-assisted surgery, connected ambulance, wearable and implantable devices, and service robotics for assisted living, with a focus on quantitative requirements. We also compare 5G-healthcare requirements with the current state of 5G capabilities. Finally, we identify gaps in the existing literature and highlight considerations for this space.
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Affiliation(s)
- Haneya Naeem Qureshi
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA; (M.M.); (Y.L.); (M.O.A.K.)
- AI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, Tulsa, OK 74135, USA; (A.I.); (A.I.)
| | - Marvin Manalastas
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA; (M.M.); (Y.L.); (M.O.A.K.)
- AI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, Tulsa, OK 74135, USA; (A.I.); (A.I.)
| | - Aneeqa Ijaz
- AI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, Tulsa, OK 74135, USA; (A.I.); (A.I.)
| | - Ali Imran
- AI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, Tulsa, OK 74135, USA; (A.I.); (A.I.)
| | - Yongkang Liu
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA; (M.M.); (Y.L.); (M.O.A.K.)
| | - Mohamad Omar Al Kalaa
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA; (M.M.); (Y.L.); (M.O.A.K.)
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12
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Hubbard I, Beniczky S, Ryvlin P. The Challenging Path to Developing a Mobile Health Device for Epilepsy: The Current Landscape and Where We Go From Here. Front Neurol 2021; 12:740743. [PMID: 34659099 PMCID: PMC8517120 DOI: 10.3389/fneur.2021.740743] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 09/03/2021] [Indexed: 11/13/2022] Open
Abstract
Seizure detection, and more recently seizure forecasting, represent important avenues of clinical development in epilepsy, promoted by progress in wearable devices and mobile health (mHealth), which might help optimizing seizure control and prevention of seizure-related mortality and morbidity in persons with epilepsy. Yet, very long-term continuous monitoring of seizure-sensitive biosignals in the ambulatory setting presents a number of challenges. We herein provide an overview of these challenges and current technological landscape of mHealth devices for seizure detection. Specifically, we display, which types of sensor modalities and analytical methods are available, and give insight into current clinical practice guidelines, main outcomes of clinical validation studies, and discuss how to evaluate device performance at point-of-care facilities. We then address pitfalls which may arise in patient compliance and the need to design solutions adapted to user experience.
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Affiliation(s)
- Ilona Hubbard
- Department of Clinical Neurosciences, Vaud University Hospital, Lausanne, Switzerland
| | - Sandor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark.,Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Vaud University Hospital, Lausanne, Switzerland
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13
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Monfort E, Poulet C, Nahas C, Bakridan S, Clair L, Latour P. Clustering patients and caregivers for technology design: A step prior to the design of an innovative technological device for the detection of epileptic seizures. Epilepsy Behav 2021; 122:108233. [PMID: 34352671 DOI: 10.1016/j.yebeh.2021.108233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 07/19/2021] [Accepted: 07/19/2021] [Indexed: 10/20/2022]
Abstract
AIMS Seizure detection using heart rate variability, from a detailed analysis by deep learning analysis system, may help patients with epilepsy to manage their symptoms. This exploratory study aims to identify patient and caregiver groups, according to acceptability factors. METHODS Two versions of the same questionnaire were designed to survey quality of life, self-efficacy, and patients with epilepsy and caregivers on seizure detection acceptability using a patch, after watching a video that described a patch connected to a companion application. Participation was voluntary and anonymous. RESULTS Responses from 68 patients with epilepsy and 33 caregivers were collected. Patients with epilepsy were grouped into three clusters: supportive, indeterminate, and reluctant to use the technology. Caregivers were also grouped into three clusters: supportive, reluctant to use the technology, either with sensitivity to their environment, or with hedonic motivation. The clusters enable the distinction between participants in self-efficacy. CONCLUSIONS Clustering of patients with epilepsy and caregivers should be a prerequisite to the design of a technological device intended to promote self-management of seizure detection. These groupings distinguish those who are favorable, reluctant or undecided to use the technology. These can be based on an assessment of self-efficacy.
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Affiliation(s)
| | | | | | | | - Laetitia Clair
- Medical Center of La Teppe, 26600 Tain-l'Hermitage, France
| | - Patrick Latour
- Medical Center of La Teppe, 26600 Tain-l'Hermitage, France
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14
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Affiliation(s)
- Mark Manford
- Neurology, Cambridge University, Cambridge CB2 1TN, UK
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15
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van Westrhenen A, Souhoka T, Ballieux ME, Thijs RD. Seizure detection devices: Exploring caregivers' needs and wishes. Epilepsy Behav 2021; 116:107723. [PMID: 33485167 DOI: 10.1016/j.yebeh.2020.107723] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 12/16/2020] [Accepted: 12/16/2020] [Indexed: 11/26/2022]
Abstract
INTRODUCTION User preferences for seizure detection devices (SDDs) have been previously assessed using surveys and interviews, but these have not addressed the latent needs and wishes. Context mapping is an approach in which designers explore users' dreams and fears to anticipate potential future experiences and optimize the product design. METHODS A generative group session was held using the context mapping approach. Two types of nocturnal SDD users were included: three professional caregivers at a residential care facility and two informal caregivers of children with refractory epilepsy and learning disabilities. Participants were invited to share their personal SDD experiences and briefed to make their needs and wishes explicit. The audiotaped session was transcribed and analyzed together with the collected material using inductive content analysis. The qualitative data was classified by coding the content, grouping codes into categories and themes, and combining those into general statements (abstraction). RESULTS "Trust" emerged as the most important theme, entangling various emotional and practical factors that influence caregiver's trust in a device. Caregivers expressed several factors that could help to gain their trust in an SDD, including integration of different modalities, insight on all parameters overnight, personal adjustment of the algorithm, recommendation by a neurologist, and a set-up period. Needs regarding alerting seemed to differ between the two types of caregivers in our study: professional caregivers preferred to be alerted only for potentially dangerous seizures, whereas informal caregivers emphasized the urge to be alerted for every event, thus indicating the need for personal adjustment of SDD settings. CONCLUSION In this explorative study, we identified several key elements for nocturnal SDD implementation including the importance of gaining trust and the possibility to adjust SDD settings for different types of caregivers.
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Affiliation(s)
- Anouk van Westrhenen
- Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede, PO Box 540, 2130 AM Hoofddorp, The Netherlands; Department of Neurology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA Leiden, The Netherlands.
| | - Tessa Souhoka
- Productzaken, Haringkade 137, 2584 ED Den Haag, The Netherlands.
| | - Maaike E Ballieux
- Stichting ZorgIntensief & Epilepsie (ZIE), Hoofddorp, The Netherlands.
| | - Roland D Thijs
- Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede, PO Box 540, 2130 AM Hoofddorp, The Netherlands; Department of Neurology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA Leiden, The Netherlands.
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16
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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] [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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