Evidence map›Paper›PMID 35081953›Full record

ReviewBMC medical informatics and decision making2022

The most used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health.

Sadrieh Hajesmaeel-Gohari, Firoozeh Khordastan, Farhad Fatehi, Hamidreza Samzadeh, Kambiz Bahaadinbeigy

2 registry-linked trialsAbstract readReview
In one paragraph

Review 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. It is linked to 2 registered trials, which are not on this map. Cited by 82 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 4 pooled it
–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.

NCT06983808 narecruitingnot on this mapstarted 2026, after this paper: background citation

The PREBEAT Trial: Digital PREhaBilitation in thE Cardiac Surgical populATion

TypeinterventionalSponsorClaire HinesRan2026 to 2027Enrolled40ConditionsCardiovascular DiseasesArmsDigital Cardiac Prehabilitation, Control (Standard treatment)
NCT07593742 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Smoking Cessation Programme in Telerehabilitation Assisted by Telemonitoring With Non-Invasive Wearable Devices for the Improvement of Oral Health, General Health and Quality of Life

TypeinterventionalSponsorUniversity of SalernoRan2026 to 2027Enrolled102ConditionsSmoking ( Cigarette), Smoking (Tobacco) Addiction, Smoking Behaviors, Smoking CessationArmsTelemedicine-Based Smoking Cessation Program, Conventional Smoking Cessation Behavioral Program
3 · Its place in the literature

Who cites it

82 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  3. Quality Assessment of Digital Health Apps: Umbrella Review.Journal of medical Internet research · 2024
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22 more citing papers are in PubMed but not listed here.

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.

Sadrieh Hajesmaeel-GohariMedical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Firoozeh KhordastanDepartment of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Farhad FatehiCentre for Health Services Research, The University of Queensland, Brisbane, Australia.
Hamidreza SamzadehDepartment of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran.
Kambiz BahaadinbeigyGastroenterology and Hepatology Research Center, Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences, Kerman, Iran. Kbahaadini@kmu.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVarious questionnaires are used for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health (mHealth) services. Using the best one to meet the needs of an mHealth study is a challenge for researchers. Therefore, this study aimed to review and determine the frequently used questionnaires for evaluating the mentioned outcomes of mHealth services.

methodsThe PubMed database was searched for conducting this review in April 2021. Papers that used a referenced questionnaire to evaluate the satisfaction, usability, acceptance, or quality outcomes of mHealth were included. The first author's name, year of publication, evaluation outcome, and evaluation questionnaire were extracted from relevant papers. Data were analyzed using descriptive statistics.

resultsIn total, 247 papers were included in the study. Questionnaires were used for usability (40%), quality (34.5%), acceptance (8.5%), and satisfaction (4%) outcomes, respectively. System usability scale (36.5%), mobile application rating scale (35.5%), post study system usability questionnaire (6%), user mobile application rating scale (5%), technology acceptance model (4.5%), computer system usability questionnaire (2.5%), net promoter score (2%), health information technology usability evaluation scale (2%), the usefulness, satisfaction, and ease of use (1.5%), client satisfaction questionnaire (1.5%), unified theory of acceptance and use of technology (1.5%), questionnaire for user interaction satisfaction (1%), user experience questionnaire (1%), and after-scenario questionnaire (1%) were the most used questionnaires, respectively.

conclusionDespite the existence of special questionnaires for evaluating several outcomes of mHealth, general questionnaires with fewer items and higher reliability have been used more frequently. Researchers should pay more attention to questionnaires with a goal-based design.

Indexed as

Surveys and QuestionnairesTelemedicineHumansMobile ApplicationsOutcome Assessment, Health CarePatient Acceptance of Health CarePatient SatisfactionReproducibility of ResultsUser-Computer InterfaceEvaluationMobile healthQuestionnaire

Identifiers

PMID35081953
PMCPMC8793175

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.