Evidence map›Paper›PMID 31851224›Full record

ArticleEinstein (Sao Paulo, Brazil)2020

Scientometrics on interventions used for adherence of hypertension and diabetes therapies.

Julio de Souza Sá, Lucas França Garcia, Marcelo Picinin Bernuci, Mirian Ueda Yamaguchi

Abstract read
In one paragraph

Article in Einstein (Sao Paulo, Brazil), 2020. 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
–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

1 citing paper in PubMed.

  1. 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

4 authors.

Julio de Souza SáCentro Universitário de Maringá, Maringá, PR, Brazil.ORCID http://orcid.org/0000-0002-0852-017X
Lucas França GarciaCentro Universitário de Maringá, Maringá, PR, Brazil.ORCID http://orcid.org/0000-0002-5815-6150
Marcelo Picinin BernuciCentro Universitário de Maringá, Maringá, PR, Brazil.ORCID http://orcid.org/0000-0003-2201-5978
Mirian Ueda YamaguchiCentro Universitário de Maringá, Maringá, PR, Brazil.ORCID http://orcid.org/0000-0001-5065-481X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify interventions aimed to improve adherence to medical and non-medical antihypertensive and antidiabetic therapy.

methodsScientometric study conducted in February and March 2018, based on data collected on PubMed ® and SciELO databases, using the following search terms: "interventions to improve adherence to diabetes therapy", "interventions to improve adherence to hypertension therapy" and "interventions to improve adherence to therapy for hypertension and diabetes".

resultsA total of 95 articles were selected. Scientific production increased as of 2009, with a higher number of studies published between 2015 and 2017. Most interventions described in literature were aimed at diabetic patients (46.31%). Face-to-face interventions were more common (46.31%), followed by telephone-based (31.58%) and digital (26.31%) interventions. North America stood out as the continent with the highest number of publications (68.42%), followed by Europe (14.74%). Most studies (63.16%) were based on a single type of intervention.

conclusionTraditional intervention methods were more widely used to promote adherence to antihypertensive and antidiabetic therapy; digital technology emerged as a trend in interventions aimed to improve hypertension and diabetes-related health behaviors.

Indexed as

BibliometricsAntihypertensive AgentsDiabetes MellitusFemaleHumansHypertensionHypoglycemic AgentsMaleTime FactorsTreatment Adherence and ComplianceTreatment OutcomeAntihypertensive AgentsHypoglycemic Agents

Identifiers

PMID31851224
PMCPMC6905157

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.