Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 07 12 2020
accepted: 29 08 2021
entrez: 24 9 2021
pubmed: 25 9 2021
medline: 15 12 2021
Statut: epublish

Résumé

Many individuals visit rural telemedicine centres to obtain safe and effective health remedies for their physical and emotional illnesses. This study investigates the antecedents of patients' satisfaction relating to telemedicine adoption in rural public hospitals settings in Bangladesh through the adaptation of Expectation Disconfirmation Theory extended by Social Cognitive Theory. This research advances a theoretically sustained prediction model forecasting patients' satisfaction with telemedicine to enable informed decision making. A research model explores four potential antecedents: expectations, performance, disconfirmation, and enjoyment; that significantly contribute to predicting patients' satisfaction concerning telemedicine adoption in Bangladesh. This model is validated using two-staged structural equation modeling and artificial neural network approaches. The findings demonstrate the determinants of patients' satisfaction with telemedicine. The presented model will assist medical practitioners, academics, and information systems practitioners to develop high-quality decisions in the future application of telemedicine. Pertinent implications, limitations and future research directions are endorsed securing long-term telemedicine sustainability.

Identifiants

pubmed: 34559840
doi: 10.1371/journal.pone.0257300
pii: PONE-D-20-38520
pmc: PMC8462681
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0257300

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Khondker Mohammad Zobair (KM)

Department of Business Strategy and Innovation, Griffith Business School, Griffith University, Brisbane, QLD, Australia.

Louis Sanzogni (L)

Department of Business Strategy and Innovation, Griffith Business School, Griffith University, Brisbane, QLD, Australia.

Luke Houghton (L)

Institute for Integrated and Intelligent Systems, Griffith Sciences-Centres and Institutes, Griffith University, Brisbane, QLD, Australia.

Md Zahidul Islam (MZ)

Department of Computer Science and Engineering, Khulna University, Khulna, Bangladesh.

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Classifications MeSH