Patients’ and Clinicians’ Visions of a Future Internet-of-Things System to Support Asthma Self-Management: Mixed Methods Study
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Abstract
Background: Supported self-management for asthma reduces acute attacks and improves control. The internet of things could connect patients to health care providers, community services, and their living environments to provide overarching support for self-management. Objective: We aimed to identify patients’ and clinicians’ preferences for a future internet-of-things system and explore their visions of its potential to support holistic self-management. Methods: In an exploratory sequential mixed methods study, we recruited patients from volunteer databases and charities’ social media. We purposively sampled participants to interview them about their vision of the design and utility of the internet of things as a future strategy for supporting self-management. Respondents who were not invited to participate in the interviews were invited to complete a web-based questionnaire to prioritize the features suggested by the interviewees. Clinicians were recruited from professional networks. Interviews were transcribed and analyzed thematically using PRISMS self-management taxonomy. Results: We interviewed 12 patients and 12 clinicians in the United Kingdom, and 140 patients completed the web-based questionnaires. Patients expressed mostly wanting a system to log their asthma control status automatically; provide real-time advice to help them learn about their asthma, identify and avoid triggers, and adjust their treatment. Peak flow (33/140, 23.6%), environmental (pollen, humidity, air temperature) (33/140, 23.6%), and asthma symptoms (25/140, 17.9%) were the specific data types that patient most wanted. Information about asthma and text or email access to clinical advice provided a feeling of safety for patients. Clinicians wanted automated objective data about the patients’ condition that they could access during consultations. The potential reduction in face-to-face consultations was appreciated by clinicians which they perceived could potentially save patients’ travel time and health service resources. Lifestyle logs of fitness regimes or weight control were valued by some patients but were of less interest to clinicians. Conclusions: An automated internet-of-things system that requires minimal input from the user and provides timely advice in line with an asthma action plan agreed by the patient with their clinician was preferred by most respondents. Links to asthma information and the ability to connect with clinicians by text or email were perceived by patients as features that would provide a sense of safety. Further studies are needed to evaluate the usability and effectiveness of internet-of-things systems in routine clinical practice.
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Of the 4 mixed-method studies, 1 demonstrated high quality.
“Of the 4 mixed-method studies, 1 demonstrated high quality [63]”
From Effectiveness and Acceptability of Asynchronous Digital Health in Asthma Care: Mixed Methods Systematic Review (2024) · cites this paper as [63]
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Self-citation
- Authors
- Hui, C. Y., McKinstry, B., Fulton, O., Buchner, M., & Pinnock, H.
- Affiliations
- Asthma UK Centre for Applied Research (GB)
- Corresponding author
- Pinnock, Hilary
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2021-04-13
- Volume
- 23
- Issue
- 4
- Pages
- e22432
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC8080146
- OpenAlex
- W3133310476
- Cited by
- 17
- References
- 35
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 2 · 2023: 4 · 2022: 7 · 2021: 1
- FWCI
- 3.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- National Institute for Health and Care Research (RP-PG-1016-20008)
- Asthma and Lung UK
- Asthma UK Centre for Applied Research
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Asthma and respiratory diseases
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- asthma, self-management, Internet of Things, patient preferences, clinician preferences, asthma action plan, peak flow monitoring, environmental triggers, remote patient monitoring, patient-clinician communication
- MeSH terms
- Self-Management, Asthma, Humans, Internet, Electronic Mail, Text Messaging, Social Media
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