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Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation
BACKGROUND: Artificial intelligence (AI) is the capacity of machines to perform tasks that ordinarily require human intelligence. AI can be utilized in various pharmaceutical applications with less time and cost. OBJECTIVES: To evaluate community pharmacists’ willingness and attitudes towards the ad...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404546/ https://www.ncbi.nlm.nih.gov/pubmed/37555012 http://dx.doi.org/10.1016/j.jsps.2023.101700 |
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author | Jarab, Anan S. Al-Qerem, Walid Alzoubi, Karem H Obeidat, Haneen Abu Heshmeh, Shrouq Mukattash, Tareq L. Naser, Yara A. Al-Azayzih, Ahmad |
author_facet | Jarab, Anan S. Al-Qerem, Walid Alzoubi, Karem H Obeidat, Haneen Abu Heshmeh, Shrouq Mukattash, Tareq L. Naser, Yara A. Al-Azayzih, Ahmad |
author_sort | Jarab, Anan S. |
collection | PubMed |
description | BACKGROUND: Artificial intelligence (AI) is the capacity of machines to perform tasks that ordinarily require human intelligence. AI can be utilized in various pharmaceutical applications with less time and cost. OBJECTIVES: To evaluate community pharmacists’ willingness and attitudes towards the adoption of AI technology at pharmacy settings, and the barriers that hinder AI implementation. METHODS: This cross-sectional study was conducted among community pharmacists in Jordan using an online-based questionnaire. In addition to socio-demographics, the survey assessed pharmacists’ willingness, attitudes, and barriers to AI adoption in pharmacy. Binary logistic regression was conducted to find the variables that are independently associated with willingness and attitude towards AI implementation. RESULTS: The present study enrolled 401 pharmacist participants. The median age was 30 (29–33) years. Most of the pharmacists were females (66.6%), had bachelor’s degree of pharmacy (56.1%), had low-income (54.6%), and had one to five years of experience (35.9%). The pharmacists showed good willingness and attitude towards AI implementation at pharmacy (n = 401). The most common barriers to AI were lack of AI-related software and hardware (79.2%), the need for human supervision (76.4%), and the high running cost of AI (74.6%). Longer weekly working hours (attitude: OR = 1.072, 95% C.I (1.040–1.104), P < 0.001, willingness: OR = 1.069, 95% Cl. 1.039–1.009, P-value = 0.011), and higher knowledge of AI applications (attitude: OR = 1.697, 95%Cl (1.327–2.170), willingness: OR = 1.790, 95%Cl. (1.396–2.297), P-value < 0.001 for both) were significantly associated with better willingness and attitude towards AI, whereas greater years of experience (OR = 20.859, 95% Cl (5.241–83.017), P-value < 0.001) were associated with higher willingness. In contrast, pharmacists with high income (OR = 0.382, 95% Cl. (0.183–0.795), P-value = 0.010), and those with<10 visitors (OR = 0.172, 95% Cl. (0.035–0.838), P-value = 0.029) or 31–50 visitors daily (OR = 0.392, 95% Cl. (0.162–0.944), P-value = 0.037) had less willingness to adopt AI. CONCLUSIONS: Despite the pharmacists' positive willingness and attitudes toward AI, several barriers were identified, highlighting the importance of providing educational and training programs to improve pharmacists' knowledge of AI, as well as ensuring adequate funding support to overcome the issue of AI high operating costs. |
format | Online Article Text |
id | pubmed-10404546 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104045462023-08-08 Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation Jarab, Anan S. Al-Qerem, Walid Alzoubi, Karem H Obeidat, Haneen Abu Heshmeh, Shrouq Mukattash, Tareq L. Naser, Yara A. Al-Azayzih, Ahmad Saudi Pharm J Original Article BACKGROUND: Artificial intelligence (AI) is the capacity of machines to perform tasks that ordinarily require human intelligence. AI can be utilized in various pharmaceutical applications with less time and cost. OBJECTIVES: To evaluate community pharmacists’ willingness and attitudes towards the adoption of AI technology at pharmacy settings, and the barriers that hinder AI implementation. METHODS: This cross-sectional study was conducted among community pharmacists in Jordan using an online-based questionnaire. In addition to socio-demographics, the survey assessed pharmacists’ willingness, attitudes, and barriers to AI adoption in pharmacy. Binary logistic regression was conducted to find the variables that are independently associated with willingness and attitude towards AI implementation. RESULTS: The present study enrolled 401 pharmacist participants. The median age was 30 (29–33) years. Most of the pharmacists were females (66.6%), had bachelor’s degree of pharmacy (56.1%), had low-income (54.6%), and had one to five years of experience (35.9%). The pharmacists showed good willingness and attitude towards AI implementation at pharmacy (n = 401). The most common barriers to AI were lack of AI-related software and hardware (79.2%), the need for human supervision (76.4%), and the high running cost of AI (74.6%). Longer weekly working hours (attitude: OR = 1.072, 95% C.I (1.040–1.104), P < 0.001, willingness: OR = 1.069, 95% Cl. 1.039–1.009, P-value = 0.011), and higher knowledge of AI applications (attitude: OR = 1.697, 95%Cl (1.327–2.170), willingness: OR = 1.790, 95%Cl. (1.396–2.297), P-value < 0.001 for both) were significantly associated with better willingness and attitude towards AI, whereas greater years of experience (OR = 20.859, 95% Cl (5.241–83.017), P-value < 0.001) were associated with higher willingness. In contrast, pharmacists with high income (OR = 0.382, 95% Cl. (0.183–0.795), P-value = 0.010), and those with<10 visitors (OR = 0.172, 95% Cl. (0.035–0.838), P-value = 0.029) or 31–50 visitors daily (OR = 0.392, 95% Cl. (0.162–0.944), P-value = 0.037) had less willingness to adopt AI. CONCLUSIONS: Despite the pharmacists' positive willingness and attitudes toward AI, several barriers were identified, highlighting the importance of providing educational and training programs to improve pharmacists' knowledge of AI, as well as ensuring adequate funding support to overcome the issue of AI high operating costs. Elsevier 2023-08 2023-07-07 /pmc/articles/PMC10404546/ /pubmed/37555012 http://dx.doi.org/10.1016/j.jsps.2023.101700 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Jarab, Anan S. Al-Qerem, Walid Alzoubi, Karem H Obeidat, Haneen Abu Heshmeh, Shrouq Mukattash, Tareq L. Naser, Yara A. Al-Azayzih, Ahmad Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation |
title | Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation |
title_full | Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation |
title_fullStr | Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation |
title_full_unstemmed | Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation |
title_short | Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation |
title_sort | artificial intelligence in pharmacy practice: attitude and willingness of the community pharmacists and the barriers for its implementation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404546/ https://www.ncbi.nlm.nih.gov/pubmed/37555012 http://dx.doi.org/10.1016/j.jsps.2023.101700 |
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