Evidence map›Paper›PMID 35511224›Full record

ArticleJMIR research protocols2022

Development of an Internet of Things Technology Platform (the NEX System) to Support Older Adults to Live Independently: Protocol for a Development and Usability Study.

Claire M Timon, Emma Heffernan, Sophia M Kilcullen, Hyowon Lee, Louise Hopper, Joe Quinn, David McDonald, Pamela Gallagher, Alan F Smeaton, Kieran Moran and 2 more

Abstract read
In one paragraph

Article in JMIR research protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Claire M TimonCentre for eIntegrated Care, School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0002-5778-6003
Emma HeffernanInsight Centre for Data Analytics, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0001-6638-0489
Sophia M KilcullenSchool of Psychology, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0001-6161-248X
Hyowon LeeSchool of Computing, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0003-4395-7702
Louise HopperSchool of Psychology, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0002-9382-5241
Joe QuinnDavra, Dublin, Ireland.ORCID https://orcid.org/0000-0001-9799-1717
David McDonaldDanalto Limited, Dublin, Ireland.ORCID https://orcid.org/0000-0001-8440-7366
Pamela GallagherSchool of Psychology, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0001-5558-1269
Alan F SmeatonInsight Centre for Data Analytics, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0003-1028-8389
Kieran MoranInsight Centre for Data Analytics, School of Health and Human Performance, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0003-2015-8967
Pamela HusseyCentre for eIntegrated Care, School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0003-2840-9361
Catriona MurphyCentre for eIntegrated Care, School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland.ORCID https://orcid.org/0000-0002-3262-1130

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn a rapidly aging population, new and efficient ways of providing health and social support to older adults are required that not only preserve independence but also maintain quality of life and safety.

objectiveThe NEX project aims to develop an integrated Internet of Things system coupled with artificial intelligence to offer unobtrusive health and wellness monitoring to support older adults living independently in their home environment. The primary objective of this study is to develop and evaluate the technical performance and user acceptability of the NEX system. The secondary objective is to apply machine learning algorithms to the data collected via the NEX system to identify and eventually predict changes in the routines of older adults in their own home environment.

methodsThe NEX project commenced in December 2019 and is expected to be completed by August 2022. Mixed methods research (web-based surveys and focus groups) was conducted with 426 participants, including older adults (aged ≥60 years), family caregivers, health care professionals, and home care workers, to inform the development of the NEX system (phase 1). The primary outcome will be evaluated in 2 successive trials (the Friendly trial [phase 2] and the Action Research Cycle trial [phase 3]). The secondary objective will be explored in the Action Research Cycle trial (phase 3). For the Friendly trial, 7 older adult participants aged ≥60 years and living alone in their own homes for a 10-week period were enrolled. A total of 30 older adult participants aged ≥60 years and living alone in their own homes will be recruited for a 10-week data collection period (phase 3).

resultsPhase 1 of the project (n=426) was completed in December 2020, and phase 2 (n=7 participants for a 10-week pilot study) was completed in September 2021. The expected completion date for the third project phase (30 participants for the 10-week usability study) is June 2022.

conclusionsThe NEX project has considered the specific everyday needs of older adults and other stakeholders, which have contributed to the design of the integrated system. The innovation of the NEX system lies in the use of Internet of Things technologies and artificial intelligence to identify and predict changes in the routines of older adults. The findings of this project will contribute to the eHealth research agenda, focusing on the improvement of health care provision and patient support in home and community environments. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35277.

Indexed as

activities of daily livingindependent livingInternet of Thingsmobile phoneolder adultswearable electronic devices

Identifiers

PMID35511224
PMCPMC9121220

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.