Evidence map›Paper›PMID 35047901›Full record

ArticleFrontiers in medical technology2021

A Clinical Perspective on the Role of Electronic Devices in Monitoring and Promoting Adherence in Airways Disease.

Vincent Brennan, Christopher Mulvey, Garrett Greene, Elaine Mac Hale, Richard W Costello

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medical technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Measurement of adherence to inhaled corticosteroids by self-report and electronic medication monitoring.The Journal of asthma : official journal of the Association for the Care of Asthma · 2023
    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

5 authors at 2 institutions in 1 country.

Vincent BrennanClinical Research Center, Royal College of Surgeons in Ireland, Dublin, Ireland.
Christopher MulveyClinical Research Center, Royal College of Surgeons in Ireland, Dublin, Ireland.
Garrett GreeneClinical Research Center, Royal College of Surgeons in Ireland, Dublin, Ireland.
Elaine Mac HaleClinical Research Center, Royal College of Surgeons in Ireland, Dublin, Ireland.
Richard W CostelloClinical Research Center, Royal College of Surgeons in Ireland, Dublin, Ireland.
Royal College of Surgeons in Ireland · IEBeaumont Hospital · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poor adherence to treatment is a common reason why patients with chronic disease have worse outcomes than might be expected. Poor treatment adherence is of particular concern among people with airways disease because, apart from not taking treatment as prescribed, inhaled medication can also be administered incorrectly. Recently, a number of technological advances that accurately document when an inhaled treatment has been used and, in certain instances, how it was used have been developed. There is good evidence from a number of research groups that these devices, either by patient reminders or physician feedback, promote adherence to inhaled treatments. What is less certain is how, in a real-world setting, these devices change outcomes. In this perspective article, the role of electronic devices in quantifying treatment use and addressing poor treatment adherence and their potential role in clinical practice outside of clinical validation trials are described.

Indexed as

adherenceasthmaCOPDobjectivepersonalized

Identifiers

PMID35047901
PMCPMC8757727
OpenAlexW3152866883

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.