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Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model

Malaysian healthcare institutions still use ineffective paper-based vaccination systems to manage childhood immunization schedules. This may lead to missed appointments, incomplete vaccinations, and outbreaks of preventable diseases among infants. To address this issue, a text messaging vaccination...

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Autores principales: Karkonasasi, Kamal, Cheah, Yu-N, Vadiveloo, Mogana, Mousavi, Seyed Aliakbar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458098/
https://www.ncbi.nlm.nih.gov/pubmed/37631899
http://dx.doi.org/10.3390/vaccines11081331
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author Karkonasasi, Kamal
Cheah, Yu-N
Vadiveloo, Mogana
Mousavi, Seyed Aliakbar
author_facet Karkonasasi, Kamal
Cheah, Yu-N
Vadiveloo, Mogana
Mousavi, Seyed Aliakbar
author_sort Karkonasasi, Kamal
collection PubMed
description Malaysian healthcare institutions still use ineffective paper-based vaccination systems to manage childhood immunization schedules. This may lead to missed appointments, incomplete vaccinations, and outbreaks of preventable diseases among infants. To address this issue, a text messaging vaccination reminder and recall system named Virtual Health Connect (VHC) was studied. VHC simplifies and accelerates immunization administration for nurses, which may result in improving the completion and timeliness of immunizations among infants. Considering the limited research on the acceptance of these systems in the healthcare sector, we examined the factors influencing nurses’ attitudes and intentions to use VHC using the extended technology acceptance model (TAM). The novelty of the conceptual model is the incorporation of new predictors of attitude, namely, perceived compatibility and perceived privacy and security issues. We conducted a survey among 121 nurses in Malaysian government hospitals and clinics to test the model. We analyzed the collected data using partial least squares structural equation modeling (PLS-SEM) to examine the significant factors influencing nurses’ attitudes and intentions to use VHC. Moreover, we applied an artificial neural network (ANN) to determine the most significant factors of acceptance with higher accuracy. Therefore, we could offer more accurate insights to decision-makers in the healthcare sector for the advancement of health services. Our results highlighted that the compatibility of VHC with the current work setting of nurses developed their positive perspectives on the system. Moreover, the nurses felt optimistic about the system when they considered it useful and easy to use in the workplace. Finally, their attitude toward using VHC played a pivotal role in increasing their intention to use it. Based on the ANN models, we also found that perceived compatibility was the most significant factor influencing nurses’ attitudes towards using VHC, followed by perceived ease of use and perceived usefulness.
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spelling pubmed-104580982023-08-27 Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model Karkonasasi, Kamal Cheah, Yu-N Vadiveloo, Mogana Mousavi, Seyed Aliakbar Vaccines (Basel) Article Malaysian healthcare institutions still use ineffective paper-based vaccination systems to manage childhood immunization schedules. This may lead to missed appointments, incomplete vaccinations, and outbreaks of preventable diseases among infants. To address this issue, a text messaging vaccination reminder and recall system named Virtual Health Connect (VHC) was studied. VHC simplifies and accelerates immunization administration for nurses, which may result in improving the completion and timeliness of immunizations among infants. Considering the limited research on the acceptance of these systems in the healthcare sector, we examined the factors influencing nurses’ attitudes and intentions to use VHC using the extended technology acceptance model (TAM). The novelty of the conceptual model is the incorporation of new predictors of attitude, namely, perceived compatibility and perceived privacy and security issues. We conducted a survey among 121 nurses in Malaysian government hospitals and clinics to test the model. We analyzed the collected data using partial least squares structural equation modeling (PLS-SEM) to examine the significant factors influencing nurses’ attitudes and intentions to use VHC. Moreover, we applied an artificial neural network (ANN) to determine the most significant factors of acceptance with higher accuracy. Therefore, we could offer more accurate insights to decision-makers in the healthcare sector for the advancement of health services. Our results highlighted that the compatibility of VHC with the current work setting of nurses developed their positive perspectives on the system. Moreover, the nurses felt optimistic about the system when they considered it useful and easy to use in the workplace. Finally, their attitude toward using VHC played a pivotal role in increasing their intention to use it. Based on the ANN models, we also found that perceived compatibility was the most significant factor influencing nurses’ attitudes towards using VHC, followed by perceived ease of use and perceived usefulness. MDPI 2023-08-06 /pmc/articles/PMC10458098/ /pubmed/37631899 http://dx.doi.org/10.3390/vaccines11081331 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Karkonasasi, Kamal
Cheah, Yu-N
Vadiveloo, Mogana
Mousavi, Seyed Aliakbar
Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model
title Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model
title_full Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model
title_fullStr Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model
title_full_unstemmed Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model
title_short Acceptance of a Text Messaging Vaccination Reminder and Recall System in Malaysia’s Healthcare Sector: Extending the Technology Acceptance Model
title_sort acceptance of a text messaging vaccination reminder and recall system in malaysia’s healthcare sector: extending the technology acceptance model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458098/
https://www.ncbi.nlm.nih.gov/pubmed/37631899
http://dx.doi.org/10.3390/vaccines11081331
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