Evidence map›Paper›PMID 34629866›Full record

ArticlePatient preference and adherence2021

Potential Development of a Mobile Application for Gout Self-Management: What Support Do Patients Need?

Yao Yin, Huan Wang, Chao-Feng Fan, Hong Chen

Erratum issuedAbstract read
In one paragraph

Article in Patient preference and adherence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yao YinDepartment of Neurology/Evidence-based Nursing Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Huan WangDepartment of Nursing, The Third Hospital of Mianyang, Mianyang, Sichuan Province, People's Republic of China.
Chao-Feng FanDepartment of Neurology/Evidence-based Nursing Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Hong ChenWest China School of Nursing and Department of Nursing, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWith the increasing prevalence and chronic course of gout, the use of mobile health (mHealth) applications (APPs) for gout self-management is attracting considerable research attention as an effective approach to improving health outcomes. However, there is limited knowledge regarding the self-management support that a mHealth APP for gout should provide to patients according to their needs. The aim of this study was to interview patients with gout and identify their needs with respect to gout self-management support. PATIENTS AND

methodsWe conducted qualitative research using a purposive sampling method from January 2019 to August 2019. Individual face-to-face semi-structured interviews were conducted with patients recruited from West China Hospital in Sichuan, China. The qualitative data were transcribed verbatim and analyzed by thematic analysis.

resultsTen male patients with gout were included in the final analysis. Instrumental, psychological, and relational support emerged as themes describing the needs of patients for gout self-management support. The instrumental support included health education, hospital registration, setting reminders, and shopping. Psychological support referred to helping patients mitigate various negative emotions. Relational support included interactions with healthcare providers and fellow patients.

conclusionThe present findings indicate that healthcare providers or companies should develop mHealth APPs for gout self-management based on the needs of patients.

Indexed as

Chinagoutmobile applicationsself-management

Identifiers

PMID34629866
PMCPMC8493006

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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.