Evidence map›Paper›PMID 37995116›Full record

ArticleJMIR serious games2023

Effects of a Gamified Agent-Based System for Personalized Elderly Care: Pilot Usability Study.

Diogo Martinho, Vítor Crista, João Carneiro, Kenji Matsui, Juan Manuel Corchado, Goreti Marreiros

Open access · goldAbstract read
In one paragraph

Article in JMIR serious games, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 9% 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

6 authors at 3 institutions in 3 countries.

Diogo MartinhoResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto - School of Engineering (ISEP), Porto, Portugal.ORCID https://orcid.org/0000-0003-1683-4950
Vítor CristaResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto - School of Engineering (ISEP), Porto, Portugal.ORCID https://orcid.org/0000-0002-8794-6354
João CarneiroResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto - School of Engineering (ISEP), Porto, Portugal.ORCID https://orcid.org/0000-0003-1430-5465
Kenji MatsuiOsaka Institute of Technology, Osaka, Japan.ORCID https://orcid.org/0009-0007-4980-6151
Juan Manuel CorchadoGrupo de investigación en Bioinformática, Sistemas Informáticos Inteligentes y Tecnología Educativa, Salamanca, Spain.ORCID https://orcid.org/0000-0002-2829-1829
Goreti MarreirosResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto - School of Engineering (ISEP), Porto, Portugal.ORCID https://orcid.org/0000-0003-4417-8401
Polytechnic Institute of Porto · PTOsaka Institute of Technology · JPUniversidad de Salamanca · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe global percentage of older people has increased significantly over the last decades. Information and communication technologies have become essential to develop and motivate them to pursue healthier ways of living. This paper examines a personalized coaching health care service designed to maintain living conditions and active aging among older people. Among the technologies the service includes, we highlight the use of both gamification and cognitive assistant technologies designed to support older people and an application combining a cognitive virtual assistant to directly interact with the older person and provide feedback on their current health condition and several gamification techniques to motivate the older person to stay engaged with the application and pursuit of healthier daily habits.

objectiveThis pilot study aimed to investigate the feasibility and usability of a gamified agent-based system for older people and obtain preliminary results on the effectiveness of the intervention regarding physical activity health outcomes.

methodsThe study was designed as an intervention study comparing pre- and posttest results. The proposed gamified agent-based system was used by 12 participants over 7 days (1 week), and step count data were collected with access to the Google Fit application programming interface. Step count data after the intervention were compared with average step count data before the intervention (average daily values over a period of 4 weeks before the intervention). A 1-tailed Student t test was used to determine the relationship between the dependent and independent variables. Usability was measured using the System Usability Scale questionnaire, which was answered by 8 of the 12 participants in the study.

resultsThe posttest results showed significant pre- to posttest changes (P=.30; 1-tailed Student t test) with a moderate effect size (Cohen d=0.65). The application obtained an average usability score of 78.

conclusionsThe presented pilot was validated, showing the positive health effects of using gamification techniques and a virtual cognitive assistant. Additionally, usability metrics considered for this study confirmed high adherence and interest from most participants in the pilot.

Indexed as

agent-based systemcoaching systemcognitivecognitive assistantselderly caregamificationinterventionolder peoplephysical activitytechnologyusabilityvirtual assistant

Identifiers

PMID37995116
PMCPMC10704320
OpenAlexW4385080547

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.