METHODS: This cross-sectional study was conducted at the University of Jordan Hospital in Amman, Jordan. During the study period, a convenience sample of patients admitted to the internal medicine and surgical wards were approached to take part in this study. Following patients' recruitments, patients were interviewed and their medical files were reviewed to obtain demographic and clinical information regarding their medical conditions and their regular use of medicines. Then, the prevelence of patients with polypharmacy were identified, and factors predicting polypharmacy among them were determined.
RESULTS: Among the 300 participants who agreed to participate in this study, females represented 45.3% of the recruited sample (n = 139), and around 48.0% (n = 144) of the study sample were elderly people (≥65 years old). Most of the recruited patients (n = 248, 82.7%) were found to use polypharmacy (≥ 5 medications). Hypertension was the most frequent medical condition among study participants (n = 240, 80.0%) followed by diabetes (n = 185, 61.7%). Results of logistic regression analysis showed that polypharmacy was only significantly affected by patients' age (OR = 2.149, P-value = .024) and monthly income (OR = 0.336, P-value = .009), while other factors were not associated with polypharmacy. Elderly patients (≥65 years) were found to have polypharmacy more significantly than non-elderly patients. Also, those with lower monthly income (<500 JD) were found to use lower polypharmacy compared with those with higher monthly income (>500 JD).
CONCLUSION: The present study showed that polypharmacy is prevalent among patients in Jordan. While polypharmacy was not affected by smoking status, gender, BMI and educational level, it was significantly affected by monthly income and age. Further plans should be put in place to reduce polypharmacy, starting with effective pharmaceutical care services leading to treatment optimisation and ensuring desired treatment outcomes.
METHODS: This cross-sectional study was carried out between May and June 2023 to assess the potential and problems that pharmacists observed while integrating chatbots powered by AI (ChatGPT) in pharmacy practice. The correlation between perceived benefits and concerns was evaluated using Spearman's rho correlation due to the data's non-normal distribution.Any pharmacists licensed by the Jordanian Pharmacists Association were included in the study. A convenient sampling technique was used to choose the participants, and the study questionnaire was distributed utilizing an online medium (Facebook and WhatsApp). Anyone who expressed interest in taking part was given a link to the study's instructions so they may read them before giving their electronic consent and accessing the survey.
RESULTS: The potential advantages of ChatGPT in the pharmacy practice were widely acknowledged by the participants. The majority of participants (69.9%) concurred that educational material about pharmacy items or therapeutic areas can be provided using ChatGPT, with 66.9% of respondents believing that ChatGPT is a machine learning algorithm. Concerns about the accuracy of AI-generated responses were also prevalent. More than half of the participants (55.7%) raised the possibility that AI systems such as ChatGPT could pick up on and replicate prejudices and discriminatory patterns from the data they were trained on. Analysis shows a statistically significant positive link, albeit a minor one, between the perceived advantages of ChatGPT and its drawbacks (r = 0.255, p
METHODS: A cross-sectional study was conducted between April and May 2023 to assess PharmD students' perceptions, concerns, and experiences regarding the integration of ChatGPT into clinical pharmacy education. The study utilized a convenient sampling method through online platforms and involved a questionnaire with sections on demographics, perceived benefits, concerns, and experience with ChatGPT. Statistical analysis was performed using SPSS, including descriptive and inferential analyses.
RESULTS: The findings of the study involving 211 PharmD students revealed that the majority of participants were male (77.3%), and had prior experience with artificial intelligence (68.2%). Over two-thirds were aware of ChatGPT. Most students (n= 139, 65.9%) perceived potential benefits in using ChatGPT for various clinical tasks, with concerns including over-reliance, accuracy, and ethical considerations. Adoption of ChatGPT in clinical training varied, with some students not using it at all, while others utilized it for tasks like evaluating drug-drug interactions and developing care plans. Previous users tended to have higher perceived benefits and lower concerns, but the differences were not statistically significant.
CONCLUSION: Utilizing ChatGPT in clinical training offers opportunities, but students' lack of trust in it for clinical decisions highlights the need for collaborative human-ChatGPT decision-making. It should complement healthcare professionals' expertise and be used strategically to compensate for human limitations. Further research is essential to optimize ChatGPT's effective integration.