Evidence map›Paper›PMID 27347490›Full record

ArticlemHealth2016

Stroke patients and their attitudes toward mHealth monitoring to support blood pressure control and medication adherence.

Carolyn Jenkins, Nina-Sarena Burkett, Bruce Ovbiagele, Martina Mueller, Sachin Patel, Brenda Brunner-Jackson, Raelle Saulson, Frank Treiber

Erratum issuedAbstract read
In one paragraph

Article in mHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Carolyn JenkinsCollege of Nursing, Medical University of South Carolina, Charleston, SC, USA.
Nina-Sarena BurkettDepartment of Neurology, Medical University of South Carolina, Charleston, SC, USA.
Bruce OvbiageleDepartment of Neurology, Medical University of South Carolina, Charleston, SC, USA.
Martina MuellerCollege of Nursing, Medical University of South Carolina, Charleston, SC, USA.
Sachin PatelCollege of Nursing, Medical University of South Carolina, Charleston, SC, USA; Technology Applications Center for Healthful Lifestyles, Medical University of South Carolina, Charleston, SC, USA.
Brenda Brunner-JacksonCollege of Nursing, Medical University of South Carolina, Charleston, SC, USA; Technology Applications Center for Healthful Lifestyles, Medical University of South Carolina, Charleston, SC, USA.
Raelle SaulsonDepartment of Neurology, Medical University of South Carolina, Charleston, SC, USA.
Frank TreiberCollege of Nursing, Medical University of South Carolina, Charleston, SC, USA; Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Technology Applications Center for Healthful Lifestyles, Medical University of South Carolina, Charleston, SC, USA.

Funding

South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR000062 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T. · 2012 to 2014
$9.4M
Stroke Investigative Research & Educational Network (SIREN)U54HG007479 · NHGRI · COLLEGE OF MEDICINE, UNIVERSITY OF IBADAN · PI OVBIAGELE, BRUCE, OWOLABI, MAYOWA OJO · 2013 to 2017
$4.2M
Tailored Hospital-based Risk Reduction to Impede Vascular Events after Stroke (THU01NS079179 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI OVBIAGELE, BRUCE · 2012 to 2016
$2.1M
Phone-based Intervention Under Nurse Guidance after Stroke (PINGS)R21NS094033 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI OVBIAGELE, BRUCE · 2015 to 2016
$337k
NCATS NIH HHS UL1 TR000062NCATS NIH HHS UL1 TR001450NHGRI NIH HHS U54 HG007479NINDS NIH HHS R21 NS094033NINDS NIH HHS U01 NS079179
6 · The paper itself

Abstract

backgroundMobile health, or mHealth, has increasingly been signaled as an effective means to expedite communication and improve medical regimen adherence, especially for patients with chronic health conditions such as stroke. However, there is a lack of data on attitudes of stroke patients toward mHealth. Such information will aid in identifying key indicators for feasibility and optimal implementation of mHealth to prevent and/or decrease rates of secondary stroke. Our objective was to ascertain stroke patients' attitudes toward using mobile phone enabled blood pressure (BP) monitoring and medication adherence and identify factors that modulate these attitudes.

methodsSixty stroke patients received a brief demonstration of mHealth devices to assist with BP control and medication adherence and a survey to evaluate willingness to use this technology.

resultsThe 60 participants had a mean age of 57 years, were 43.3% male, and 53.3% were White. With respect to telecommunication prevalence, 93.3% owned a cellular device and 25% owned a smartphone. About 70% owned a working computer. Regarding attitudes, 85% felt comfortable with a doctor or nurse using mHealth technologies to monitor personal health information, 78.3% believed mHealth would help remind them to follow doctor's directions, and 83.3% were confident that technology could effectively be used to communicate with health care providers for medical needs.

conclusionsMobile device use is high in stroke patients and they are amenable to mHealth for communication and assistance in adhering to their medical regimens. More research is needed to explore usefulness of this technology in larger stroke populations.

Indexed as

attitudes of stroke patientsMobile phone based health or mHealthsurvey research

Identifiers

PMID27347490
PMCPMC4916920

What OpenQuestion holds

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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.