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药学实践中的人工智能:社区药剂师的态度与意愿及其实施障碍

Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation.

作者信息

Jarab Anan S, Al-Qerem Walid, Alzoubi Karem H, Obeidat Haneen, Abu Heshmeh Shrouq, Mukattash Tareq L, Naser Yara A, Al-Azayzih Ahmad

机构信息

Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology. P.O. Box 3030. Irbid 22110, Jordan.

College of Pharmacy, AL Ain University, Abu Dhabi, United Arab Emirates.

出版信息

Saudi Pharm J. 2023 Aug;31(8):101700. doi: 10.1016/j.jsps.2023.101700. Epub 2023 Jul 7.

Abstract

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.

摘要

背景

人工智能(AI)是指机器执行通常需要人类智能才能完成的任务的能力。人工智能可用于各种制药应用,且耗时更少、成本更低。

目的

评估社区药剂师在药房环境中采用人工智能技术的意愿和态度,以及阻碍人工智能实施的障碍。

方法

本横断面研究通过在线问卷对约旦的社区药剂师进行。除社会人口统计学信息外,该调查还评估了药剂师在药房采用人工智能的意愿、态度和障碍。采用二元逻辑回归分析来确定与人工智能实施意愿和态度独立相关的变量。

结果

本研究共纳入401名药剂师参与者。年龄中位数为30(29 - 33)岁。大多数药剂师为女性(66.6%),拥有药学学士学位(56.1%),收入较低(54.6%),工作经验为1至5年(35.9%)。药剂师对在药房实施人工智能表现出良好的意愿和态度(n = 401)。人工智能最常见的障碍是缺乏与人工智能相关的软件和硬件(79.2%)、需要人工监督(76.4%)以及人工智能运行成本高(74.6%)。每周工作时间较长(态度:OR = 1.072,95%置信区间(1.040 - 1.104),P < 0.001;意愿:OR = 1.069,95%置信区间1.039 - 1.009,P值 = 0.011)以及对人工智能应用的了解程度较高(态度:OR = 1.697,95%置信区间(1.327 - 2.170);意愿:OR = 1.790,95%置信区间(1.396 - 2.297),两者P值均 < 0.001)与对人工智能更好的意愿和态度显著相关,而工作经验年限较长(OR = 20.859, 95%置信区间(5.241 - 83.017),P值 < 0.001)与更高的意愿相关。相比之下,高收入药剂师(OR = 0.382, 95%置信区间(0.183 - 0.795),P值 = 0.010)以及每天访客少于10人(OR = 0.172, 95%置信区间(0.035 - 0.838),P值 = 0.029)或31至50人的药剂师(OR = 0.392, 95%置信区间(0.162 - 0.944),P值 = 0.037)采用人工智能的意愿较低。

结论

尽管药剂师对人工智能持积极的意愿和态度,但仍发现了一些障碍,这凸显了提供教育和培训项目以提高药剂师对人工智能的了解的重要性,以及确保充足的资金支持以克服人工智能高运营成本问题的重要性。

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