Evidence map›Paper›PMID 31262674›Full record

ArticlePatient education and counseling2019

SMS-facilitated home blood pressure monitoring: A qualitative analysis of resultant health behavior change.

Matthew E Allen, Taya Irizarry, Julian Einhorn, Thomas W Kamarck, Brian P Suffoletto, Lora E Burke, Bruce L Rollman, Matthew F Muldoon

Open access · greenAbstract read
In one paragraph

Article in Patient education and counseling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 14% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Trial
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  6. Review
  7. Article
  8. Delineating and clarifying the concept of self-care monitoring: a concept analysis.International journal of qualitative studies on health and well-being · 2023
    Review
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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

8 authors at 3 institutions in 1 country.

Matthew E AllenUniversity of Virginia School of Medicine, Charlottesville, VA, USA. Electronic address: mea97@pitt.edu.
Taya IrizarryDepartment of Health & Community Systems, University of Pittsburgh School of Nursing, Pittsburgh, PA, USA. Electronic address: TAI19@pitt.edu.
Julian EinhornDepartment of Psychology, University of Pittsburgh School of Arts and Sciences, Pittsburgh, PA, USA. Electronic address: JZE8@pitt.edu.
Thomas W KamarckDepartment of Psychology, University of Pittsburgh School of Arts and Sciences, Pittsburgh, PA, USA. Electronic address: tkam@pitt.edu.
Brian P SuffolettoDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address: suffbp@upmc.edu.
Lora E BurkeDepartment of Health & Community Systems, University of Pittsburgh School of Nursing, Pittsburgh, PA, USA; Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA. Electronic address: lbu100@pitt.edu.
Bruce L RollmanDivision of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Behavioral Health and Smart Technology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address: RollmanBL@upmc.edu.
Matthew F MuldoonDivision of Cardiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Heart and Vascular Institute Hypertension Center, UPMC Health System, Pittsburgh, PA, USA. Electronic address: mfm10@pitt.edu.
University of Pittsburgh · USUniversity of Virginia · USUPMC Health System · US

Funding

CARDIOVASCULAR BEHAVIORAL MEDICINE RESEARCH TRAININGT32HL007560 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Peter J Gianaros, REBECCA C THURSTON · 1985 to 2026
$11.3M
NHLBI NIH HHS T32 HL007560
6 · The paper itself

Abstract

objectiveHypertension is largely asymptomatic and, as a result, patients often fail to sufficiently engage in medication adherence and other health behaviors to control their blood pressure (BP). This study explores the mechanisms by which MyBP, an automated SMS-facilitated home blood pressure monitoring (HBPM) program, helps facilitate healthy behavior changes.

methodsA thematic analysis of transcribed audio-recordings from semi-structured post-intervention interviews (n = 40) was conducted.

resultsThree primary themes were identified as contributing most to patients' decision to initiate a behavior change: 1) increased hypertension literacy attributed to educational videos presented at enrollment, 2) increased day-to-day salience of blood pressure levels as a result of consistent HBPM, and 3) use of BP readings as feedback, with high readings triggering motivations to make behavior changes. These themes and most accompanying sub-themes correspond to constructs in the Health Belief Model and Social Cognitive Theory.

conclusionPatient-centered HBPM interventions such asMyBP appear to promote improvements in hypertension self-management via several mechanisms consistent with recognized models of behavior change. PRACTICE IMPLICATIONS: SMS-supported HBPM, paired with video-based education, may provide a simple and scalable way of encouraging health behavior adherence in hypertensive patients.

Indexed as

Health BehaviorText MessagingAdultAgedAttitude to HealthBlood PressureBlood Pressure DeterminationBlood Pressure Monitoring, AmbulatoryFemaleHumansHypertensionInterviews as TopicMaleMedication AdherenceMiddle AgedQualitative ResearchBehavior changeHome blood pressure monitoringHypertensionQualitativeText-messaging

Identifiers

PMID31262674
PMCPMC6851464
OpenAlexW2953323500

What OpenQuestion holds

Textmetadata
LicenceTDM
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.