ArticleBMC geriatrics2022
How to create value with unobtrusive monitoring technology in home-based dementia care: a multimethod study among key stakeholders.
Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Misalignments of values and preferences: Finding an ideal elder care arrangement.Journal of medical ethics · 2026Article
- Compatibility of the CEN-ISO/TS 82304-2 Health App Assessment Framework With Catalan and Italian Health Authorities' Needs: Qualitative Interview Study.JMIR formative research · 2025Article
- How can patients shape digital medicine? A rapid review of patient and public involvement and engagement in the development of digital health technologies for neurological conditions.Expert review of pharmacoeconomics & outcomes research · 2025Review
- Patient and public involvement in the co-design and assessment of unobtrusive sensing technologies for care at home: a user-centric design approach.BMC geriatrics · 2025Article
- Article
- Defining the value proposition in diagnostic technology: challenges and opportunities for its understanding and development - a review with a multiperspective reflective analysis.Frontiers in medicine · 2025Review
- Reliable Contactless Monitoring of Heart Rate, Breathing Rate, and Breathing Disturbance During Sleep in Aging: Digital Health Technology Evaluation Study.JMIR mHealth and uHealth · 2024Article
- Using an Empathetic Approach to Explore Technology Readiness and Needs for Digital Services to Assist People with Dementia.International journal of environmental research and public health · 2024Article
- Low-Fidelity Prototype of a Sensor-Dependent Interaction Platform: Formative Evaluation With Informal Caregivers of Older Adults With Cognitive Impairment.JMIR formative research · 2024Article
- Article
- Personalized Technological Support for Informal Caregivers of Older People with Dementia: A Co-Design Approach Involving Potential End Users and Healthcare Professionals in Three Focus Groups in Italy.Healthcare (Basel, Switzerland) · 2023Article
- Understanding acceptance of contactless monitoring technology in home-based dementia care: a cross-sectional survey study among informal caregivers.Frontiers in digital health · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a growing interest to support extended independent living of people with dementia (PwD) via unobtrusive monitoring (UM) technologies which allow caregivers to remotely monitor lifestyle, health, and safety of PwD. However, these solutions will only be viable if developers obtain a clear picture of how to create value for all relevant stakeholders involved and achieve successful implementation. The aim of this study was therefore to explore the value proposition of UM technology in home-based dementia care and preconditions for successful implementation from a multi-stakeholder perspective.
methodsWe conducted an expert-informed survey among potential stakeholders (n = 25) to identify key stakeholders for UM technology in home-based dementia care. Subsequently, focus groups and semi-structured interviews were conducted among 5 key stakeholder groups (n = 24) including informal caregivers (n = 5), home care professionals (n = 5), PwD (n = 4), directors and managers within home care (n = 4), and policy advisors within the aged care and health insurance sector (n = 6). The sessions addressed the value proposition- and business model canvas and were analyzed using thematic analysis.
resultsStakeholders agreed that UM technology should provide gains such as objective surveillance, timely interventions, and prevention of unnecessary control visits, whereas pains mainly included information overload, unplannable care due to real-time monitoring, and less human interaction. The overall design-oriented need referred to clear situation classifications including urgent care (fall- and wandering detection), non-urgent care (deviations in eating, drinking, sleeping), and future care (risk predictions). Most important preconditions for successful implementation of UM technology included inter-organizational collaboration, a shared vision on re-shaping existing care processes, integrated care ICT infrastructures, clear eligibility criteria for end-users, and flexible care reimbursement systems.
conclusionsOur findings can guide the value-driven development and implementation of UM technology for home-based dementia care. Stakeholder values were mostly aligned, although stakeholders all had their own perspective on what UM technology should accomplish. Besides, our study highlights the complexity of implementing novel UM technology in home-based dementia care. To achieve successful implementation, organizational and financial preconditions, as well as digital data exchange between home care organizations, will be important.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.