Evidence map›Paper›PMID 37350699›Full record

ArticleNursing research

Interindividual Variability in Self-Monitoring of Blood Pressure Using Consumer-Purchased Wireless Devices.

Yaguang Zheng, Yanfu Zhang, Heng Huang, Geoffrey H Tison, Lora E Burke, Saul Blecker, Victoria Vaughan Dickson, Jeffrey E Olgin, Gregory M Marcus, Mark J Pletcher

Open access · greenAbstract read
In one paragraph

Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Trial
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

10 authors at 1 institution in 5 countries.

St. Gregory's University · US

Funding

The Health ePeople Resource for Mobilized ResearchU2CEB021881 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARCUS, GREGORY M, OLGIN, JEFFREY E · 2015 to 2020
$10.3M
Technology Research in Chronic & Critical IllnessT32NR008857 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Young Ji Lee · 2005 to 2026
$4.0M
NIBIB NIH HHS U2C EB021881NINR NIH HHS T32 NR008857
6 · The paper itself

Abstract

backgroundEngagement with self-monitoring of blood pressure (BP) declines, on average, over time but may vary substantially by individual.

objectivesWe aimed to describe different 1-year patterns (groups) of self-monitoring of BP behaviors, identify predictors of those groups, and examine the association of self-monitoring of BP groups with BP levels over time.

methodsWe analyzed device-recorded BP measurements collected by the Health eHeart Study-an ongoing prospective eCohort study-from participants with a wireless consumer-purchased device that transmitted date- and time-stamped BP data to the study through a full 12 months of observation starting from the first day they used the device. Participants received no instruction on device use. We applied clustering analysis to identify 1-year self-monitoring, of BP patterns.

resultsParticipants had a mean age of 52 years and were male and White. Using clustering algorithms, we found that a model with three groups fit the data well: persistent daily use (9.1% of participants), persistent weekly use (21.2%), and sporadic use only (69.7%). Persistent daily use was more common among older participants who had higher Week 1 self-monitoring of BP frequency and was associated with lower BP levels than the persistent weekly use or sporadic use groups throughout the year.

conclusionWe identified three distinct self-monitoring of BP groups, with nearly 10% sustaining a daily use pattern associated with lower BP levels.

Indexed as

Blood Pressure Monitoring, AmbulatoryHypertensionBlood PressureFemaleHumansLongitudinal StudiesMaleMiddle AgedProspective Studies

Identifiers

PMID37350699
PMCPMC10299813
OpenAlexW4381716863

What OpenQuestion holds

Textmetadata
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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.