Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/27477
ชื่อเรื่อง: Factors influencing patient intention to report adverse drug reaction to community pharmacists: A structural equation modeling approach
ผู้แต่ง: Assanee J.
Sorofman B.A.
Sirisinsuk Y.
Kitisopee T.
วันที่เผยแพร่: 2022
บทคัดย่อ: Background: Under-reporting of adverse drug reactions (ADRs) is the main problem of spontaneous ADR reporting systems, especially reporting from community pharmacists. However, community pharmacists cannot report ADRs if patients do not report them. Objective: To investigate factors that can influence patients’ intention to report ADRs to community pharmacists and to develop a structural model of influencing factors to report ADRs from patients. Method: Self-administered questionnaire via a Google form was used. The study samples were people living in all regions of Thailand. Structural equation modeling (SEM) was used to determine the influencing factors to intention to report ADRs to community pharmacists. Results: A total of 2774 responses were collected. All Pearson correlations among variables were statistically significant. The correlation between intention to report ADR and instrumental attitude was highest. Perceived behavior control had the lowest correlation with intention to report ADRs. The structural equation model was an adequate fit for the data. Intention to report ADRs to community pharmacists was significantly influenced by instrumental attitude, injunctive norm, descriptive norm and self-efficacy. Conclusion: Positive attitude of ADR reporting, self-efficacy and their reference person such as physicians, community pharmacists, their families and friends could encourage and motivate their intention to report ADRs to community pharmacists. © 2021 Elsevier Inc.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106601487&doi=10.1016%2fj.sapharm.2021.05.010&partnerID=40&md5=d6055516281972012acb5292c6ed942a
https://ir.swu.ac.th/jspui/handle/123456789/27477
ISSN: 15517411
Appears in Collections:Scopus 2022

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