Evidence map›Paper›PMID 31518283›Full record

ArticleJMIR aging2019

Mobile and Connected Health Technology Needs for Older Adults Aging in Place: Cross-Sectional Survey Study.

Jing Wang, Yan Du, Deidra Coleman, Michelle Peck, Sahiti Myneni, Hong Kang, Yang Gong

Abstract read
In one paragraph

Article in JMIR aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Trial
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  4. The need for clear medical data ownership laws.Journal of translational medicine · 2026
    Article
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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

7 authors.

Jing Wang *School of Nursing, The University of Texas Health Science Center at San Antonio, San Antonio, TX, United States.ORCID http://orcid.org/0000-0002-4012-0977
Yan DuSchool of Nursing, The University of Texas Health Science Center at San Antonio, San Antonio, TX, United States.ORCID http://orcid.org/0000-0003-0683-3989
Deidra ColemanCizik School of Nursing, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID http://orcid.org/0000-0003-1739-8804
Michelle PeckCizik School of Nursing, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID http://orcid.org/0000-0002-9669-3491
Sahiti MyneniSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID http://orcid.org/0000-0002-9211-1626
Hong KangSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID http://orcid.org/0000-0003-2526-6609
Yang GongSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID http://orcid.org/0000-0002-0864-8368

Funding

NRSA Training Core (TL1)TL1TR002647 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI CHUN, YONG-HEE PATRICIA, FREI, CHRISTOPHER R. · 2018 to 2022
$1.8M
6 · The paper itself

Abstract

backgroundAn increasing number of mobile and wearable devices are available in the market. However, the extent to which these devices can be used to assist older adults to age in place remains unclear.

objectiveThis study aimed to assess older adults' perceptions of using mobile and connected health technologies.

methodsUsing a cross-sectional design, a total of 51 participants were recruited from a senior community center. Demographics and usage of mobile or wearable devices and online health communities were collected using a survey questionnaire. Descriptive statistics assessed usage of devices and online health communities. The Fisher exact test was used to examine the relationship between technology usage and having access to a smartphone.

resultsThe sample was primarily comprised non-Hispanic white (35/51, 69%), educated (39/51, 76% any college), and female (36/51, 71%) participants, with an average age of 70 (SD 8) years. All participants were insured and nearly all lived at home (49/51, 94%). A total of 86% (44/51) of the participants had heard of wearable health devices, but only 18 out of 51 (35%) had ever used them. Over 80% (42/51) expressed interest in using such devices and were interested in tracking exercise and physical activity (46/51, 90%), sleep (38/51, 75%), blood pressure (34/51, 67%), diet (31/51, 61%), blood sugar (28/51, 55%), weight (26/51, 51%), and fall risk (23/51, 45%). The greatest concerns about using wearable devices were cost (31/51, 61%), safety (14/51, 28%), and privacy (13/51, 26%); one-fourth (12/51) reported having no concerns. They were mostly interested in sharing data from mobile and connected devices with their health care providers followed by family, online communities, friends, and no one. About 41% (21/51) of the older adults surveyed reported having ever heard of an online health community, and roughly 40% (20/51) of the participants reported being interested in joining such a community. Most participants reported having access to a smartphone (38/51, 74%), and those with such access were significantly more likely to show interest in using a wearable health device (P<.001) and joining an online health community (P=.05).

conclusionsOur findings suggest that, although few older adults are currently using mobile and wearable devices and connected health technologies for managing health, they are open to this idea and are mostly interested in sharing such data with their health care providers. Further studies are warranted to explore strategies to balance the data sharing preference of older adults and how to best integrate mobile and wearable device data with clinical workflow for health care providers to promote healthy aging in place.

Indexed as

aging in placeconnected healthindependent livingmobile healthremote monitoringwearable technology

Identifiers

PMID31518283
PMCPMC6715003

What OpenQuestion holds

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LicenceCC BY
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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.