Evidence map›Paper›PMID 36514043›Full record

ArticleBMC medical informatics and decision making2022

A mobile app (IDoThis) for multiple sclerosis self-management: development and initial evaluation.

Zeinab Salimzadeh, Shahla Damanabi, Reza Ferdousi, Sheida Shaafi, Leila R Kalankesh

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2022. 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

5 authors.

Zeinab SalimzadehDepartment of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Daneshgah Ave, Tabriz, Iran.
Shahla DamanabiDepartment of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Daneshgah Ave, Tabriz, Iran.
Reza FerdousiDepartment of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Daneshgah Ave, Tabriz, Iran.
Sheida ShaafiDepartment of Neurology, Tabriz University of Medical Sciences, Tabriz, Iran.
Leila R KalankeshDepartment of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Daneshgah Ave, Tabriz, Iran. Leila.kalankesh@gmail.com.

Funding

Tabriz University of Medical Sciences IR.TBZMED.REC.1396.531
6 · The paper itself

Abstract

backgroundMultiple sclerosis (MS) is one of the most common neurological disorders worldwide, and self-management is considered an essential dimension in its control. This study aimed to develop an evidence-based mobile application for MS self-management and evaluate it.

methodsThis study was undertaken in three phases: content preparation, design, and evaluation. In the content preparation phase, the researchers extracted MS self-management needs based on related guidelines and guides, existing apps on the self-management of MS, and the field experts' views and confirmation. The design phase was conducted in five steps: defining app functionalities, depicting the wireframe, preparing the media, coding the app, and testing the app's performance. The app was developed using the Android Studio environment and Java programming language for the Android operating system. The performance of the developed app was tested separately in several turns, and existing defects were corrected in each turn. Finally, after using the app for three weeks, the app was evaluated for its short-term impact on MS management and user-friendliness using a researcher-constructed questionnaire from participants' (N = 20) perspectives.

resultsThe IDoThis app is an offline app for people with MS that includes five main modules: three modules for training or informing users about different aspects of MS, one module for monitoring the user's MS condition, and a reporting module. In the initial evaluation of the app, 75% (n = 15) of participants mentioned that using this app improved MS self-management status at intermediate and higher levels, but 25% (n = 5) of the participants mentioned that the effect of using the app on the self-management tasks was low or was very low. The majority of users rated the user-friendliness of the app as high. The users found the sections "exercises in MS" and "monitoring of MS status" beneficial to their self-management. Still, the fatigue and sleep management sections are needed to meet users' expectations.

conclusionUsing IDoThis app as a self-management tool for individuals with MS appears feasible, that can meet the need for a free and accessible self-management tool for individuals with MS. Future directions should consider the users' fatigue and sleep management expectations.

Indexed as

Mobile ApplicationsMultiple SclerosisSelf-ManagementFatigueHumansSurveys and QuestionnairesM-HealthMobile applicationsMobile healthMultiple sclerosisSelf-management

Identifiers

PMID36514043
PMCPMC9745928

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.