Evidence map›Paper›PMID 31154515›Full record

ArticleJournal of medical systems2019

Measuring QoE of a Teleconsultation App in Mental Health Using a Pentagram Model.

Isabel de la Torre Díez, Susel Góngora Alonso, Eduardo Motta Cruz, Manuel A Franco

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In one paragraph

Article in Journal of medical systems, 2019. 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

4 authors.

Isabel de la Torre DíezDepartment of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain. isator@tel.uva.es.ORCID http://orcid.org/0000-0003-3134-7720
Susel Góngora AlonsoDepartment of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain.
Eduardo Motta CruzBretagne Loire and Nantes Universities, UMR 6164, IETR Polytech, Nantes, France.
Manuel A FrancoPsiquiatry Service, Hospital Zamora, Hernán Cortés, Zamora, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The QoE measurement has become a novel theme today. To achieve a quality service and minimize the negative impact that traffic on network can cause, it's very important to manage the devices that intervene in this service. Hence, the QoE evaluation allows obtaining benefits both customers and service providers. The main objective of this paper is to measure QoE of a teleconsultation application in Mental Health named Psiconnect, using an approach based on pentagram model. For the QoE evaluation of Psiconnect application we used the pentagram model based on the measurement of 5 factors (integrality, retainability, availability, usability, and instantaneousness). This model allows to design quantifiable metrics for quality evaluations. Using the model cited the value of QoE for Psiconnect is 1.793 (between 1.6 and 1.8). Comparing with Mean Opinion Scores (MOS) test, some users are dissatisfied with the use of the application although the result is near 1.8, so the most of users are satisfied with the use of teleconsultation service based in Skype in the Psiconnect app. There are different models to measure QoE having into account subjective parameters. This is important an estimation of QoE in a quantitative form. Other models can be used to improve the quality of apps.

Indexed as

Mental HealthMobile ApplicationsPatient SatisfactionQuality of Health CareHumansQuality Indicators, Health CareRemote ConsultationMental healthPentagram modelQoESkypeTeleconsultation

Identifiers

What OpenQuestion holds

Textmetadata
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.