Evidence map›Paper›PMID 30322835›Full record

ArticleJMIR mHealth and uHealth2018

mHealth App Patient Testing and Review of Educational Materials Designed for Self-Management of Gout Patients: Descriptive Qualitative Studies.

Amy D Nguyen, Lauren J Frensham, Michael Xc Wong, Sylvain Mm Meslin, Paige Martin, Annie Ys Lau, Melissa T Baysari, Richard O Day

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
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  7. Article
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  9. Article
  10. Better outcomes for patients with gout.Inflammopharmacology · 2020
    Article
  11. Review
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 2 institutions in 1 country.

Amy D NguyenSt Vincent's Clinical School, University of New South Wales Sydney, Sydney, Australia.ORCID http://orcid.org/0000-0003-4603-564X
Lauren J FrenshamSt Vincent's Clinical School, University of New South Wales Sydney, Sydney, Australia.ORCID http://orcid.org/0000-0001-8533-2917
Michael Xc WongSt Vincent's Clinical School, University of New South Wales Sydney, Sydney, Australia.ORCID http://orcid.org/0000-0002-3419-7126
Sylvain Mm MeslinSt Vincent's Clinical School, University of New South Wales Sydney, Sydney, Australia.ORCID http://orcid.org/0000-0003-1082-505X
Paige MartinCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0002-6157-4740
Annie Ys LauCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0002-3028-4222
Melissa T Baysari *St Vincent's Clinical School, University of New South Wales Sydney, Sydney, Australia.ORCID http://orcid.org/0000-0003-1645-9126
Richard O Day *St Vincent's Clinical School, University of New South Wales Sydney, Sydney, Australia.ORCID http://orcid.org/0000-0002-6045-6937
UNSW Sydney · AUMacquarie University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGout is a form of chronic arthritis caused by elevated serum uric acid (SUA) and culminates in painful gout attacks. Although effective uric acid-lowering therapies exist, adherence is low. This is partly due to the lack of support for patients to self-manage their disease. Mobile health apps have been used in the self-management of chronic conditions. However, not all are developed with patients, limiting their effectiveness.

objectiveThe objective of our study was to collect feedback from gout patients to design an effective gout self-management app.

methodsTwo descriptive qualitative studies were conducted. In Study 1, researchers developed a short educational video and written materials about gout management, designed to be embedded into an app; 6 interviews and 1 focus group were held with gout patients to gather feedback on these materials. Usability testing in Study 2 involved additional gout patients using a pilot version of Healthy.me Gout, a gout self-management app, for 2 weeks. Following the trial, patients participated in an interview about their experiences using the app.

resultsPatients viewed the gout educational material positively, appreciating the combined use of video, text, and images. Patients were receptive to using a mobile app to self-manage their gout. Feedback about Healthy.me Gout was generally positive with patients reporting that the tracking and diary features were most useful. Patients also provided suggestions for improving the app and educational materials.

conclusionsThese studies involved patients in the development of a gout self-management app. Patients provided insight to improve the app's presentation and usability and general lessons on useful features for chronic disease apps. Gout patients enjoyed tracking their SUA concentrations and gout attack triggers. These capabilities can be translated into self-management apps for chronic diseases that require monitoring of pathological values, medication adherence, or symptoms. Future health app design should integrate patient input and be developed iteratively to address concerns identified by patients.

Indexed as

chronic diseasegoutmobile appsself-managementuric acid

Identifiers

PMID30322835
PMCPMC6305897
OpenAlexW2809874821

What OpenQuestion holds

Textmetadata
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.