Cited by 21Mobile Health and mHealth ApplicationsTelemedicine and Telehealth ImplementationTechnology Use by Older Adults

Investigating user identification in remote patient monitoring devices

Open access
Ondiege, Brian, Clarke, Malcolm·2017·Bioengineering

Abstract

With the increase in the number of people having a chronic disease, there is an increase in households having more than a single person suffering from the same chronic illness. One problem of monitoring such patients in their own home is that current devices have a limitation in the number of people who can use a single device. This study investigates the use of Near Field Communication (NFC) for identification in a multi-user environment. METHODS: A mixed-method qualitative and quantitative approach was adopted, including focus groups, observations and a field trial. Data were collected in three phases. In Phase 1, five focus groups were conducted with patients to determine their beliefs, concerns and issues with using identification in remote patient monitoring devices. In Phase 2, participants were given a blood pressure monitor modified to include an NFC reader to enable identification. The modified device was given to patients living as a couple in the same household and both suffering from hypertension. Both patients used the device for a period of two weeks to observe their acceptance of the technology and determine their experience of usage. A total of 40 (20 couples) patients participated in the trial. Non-adherence to the full monitoring regimen was low and was mainly due to usability issues or commitments taking them away from the home and thus unable to take readings. After the trial period participants were invited to discuss their experiences with the technology in a focus group discussion (Phase 3), a total of five focus groups were conducted. Focus group discussions with the patients revealed that most participants liked using the system and were not apprehensive towards Healthcare Information Technology (HIT). The participants also had suggestions for improvements that could be made to the modified blood pressure monitor (such as, rechargeable in place batteries, integrate the components, easier to use cuff, and increased sensitivity of the NFC reader) that might improve the overall experience of the proposed technology and its acceptance. CONCLUSION: The study proposes a new framework, the Senior Patient Technology Acceptance Model (SPTAM) that offers an understanding of the needs of the elderly towards technology use and the factors that influence its acceptance. SPTAM emphasises that involving the patient in the early stages of development can lead to a more user-centred technology and help in identifying any underlying issues at an early stage, thus avoiding adding features which patients do not need. The findings from this empirical research can be used as recommendations to improve current RPM devices, save the NHS costs, inform standardization groups.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/bioengineering4030076

Cites

38 of 38 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Patients frequently struggle with digital health literacy gaps, technology-induced anxiety, and the logistical burden of integrating rigid measurement protocols into their daily routines.

    “patients frequently struggle with digital health literacy gaps, technology-induced anxiety, and the logistical burden of integrating rigid measurement protocols into their daily routines [9,10].”

    From Clinical Efficacy and Patient Adherence Hurdles of Remote Patient Monitoring (RPM) Frameworks in Managing Hypertension and Type 2 Diabetes: A Scoping Review (2026) · cites this paper as [9]

    The Results (section 3.2) describe concerns about complex technology and a need for training, while the Discussion (section 4.1) discusses technology-related anxiety. The Discussion (section 4.2) also links missed measurements to other commitments and bulky equipment. But the Results (section 3.3) report that 90% adhered to the monitoring regimen, and section 4.1 says most participants were willing to use the technology; these findings do not support the claim that patients frequently struggle with all three barriers. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. [2]Ondiege B. Clarke M. Healthcare Professionals Perception on Information Security Presented at the 5th International Conference on Internet Technologies & Society Taipei, Taiwan 10–12 December 2014
  2. [9]Ondiege B. Clarke M. Mapp G. Exploring Security of Remote Patient Monitoring Devices using NFC Technology for Identification of the Frail Elderly Proceedings of the 8th International Conference e-Health Funchal, Portugal 1–3 July 2016 1 3
  3. [23]Fazio R.H. How Do Attitudes Guide Behavior? The Handbook of Motivation and Cognition: Foundation of Social Behavior Sorrentino R.M. Higgins E.T. Guilford Press New York, NY, USA 1986 204 243

Cited by

Sorted by citations

Authors
Ondiege, B., & Clarke, M.
Affiliations
Brunel University of London (GB)
Corresponding author
Ondiege, Brian
Venue
Bioengineering
Publisher
MDPI AG
Published
2017-09-13
Volume
4
Issue
3
Pages
76
ISSN
2306-5354 (ISSN-L)
OpenAlex
W2754345373
Cited by
19
References
38
Citations by year
2026: 1 · 2025: 4 · 2024: 3 · 2023: 3 · 2022: 4 · 2021: 2 · 2020: 1 · 2018: 1
FWCI
0.89
Type
journal article
Language
en
Open access
Locations
  • Bioengineering (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Brunel University Research Archive (BURA) (Brunel University London) (submittedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
  • Social Sciences › Demography › Technology Use by Older Adults
Keywords
remote patient monitoring, user identification, near field communication, blood pressure monitors, hypertension, chronic disease, technology acceptance, elderly patients, usability, patient-centered design, home monitoring, user experience

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review