METHODS: This is a cross-sectional descriptive study that was conducted to evaluate perception and experience of pharmacists with the use of Internet-based medication information by their patients. During the study period, 200 pharmacists were approached to participate in the study using a paper-based survey to assess their perceptions and current experience with the use of Internet-based medication information by their patients. Data were analyzed using descriptive statistics (mean/standard deviation for continuous variables, and frequency/percentages for qualitative variables). Also, simple linear regression was utilized to screen factors affecting pharmacists' perception scores of the use of Internet-based medication information.
RESULTS: Among 161 recruited pharmacists, the majority (n = 129, 80.1%) reported receiving inquiries from patients about Internet-based medication information within the last year. Among them, only 22.6% (n = 29) of pharmacists believed that Internet-based medication information is somewhat or very accurate. Unfortunately, only 24.2% (n = 31) of them stated that they always had enough time for their patient to discuss their Internet-based medication information. Regarding pharmacists' perception of the use of Internet-based medication information by their patients, more than half of the pharmacists (>50%) believe that Internet-based medication information could increase the patient's role in taking responsibility. On the other hand, 54.7% (n = 88) of the pharmacists believed that Internet-based medication information would contribute to rising the healthcare cost by obtaining unnecessary medications by patients. Finally, pharmacists' educational level was found to significantly affect their perception scores toward patient use of Internet-based medication information where those with higher educational level showed lower perception score (r = -0.200, P-value = 0.011).
CONCLUSION: Although pharmacists felt that usage of Internet-based data by patients is beneficial, they also have believed that it has a negative impact in terms of rising the healthcare cost, and it promotes unnecessary fear or concern about medications. We suggest that pharmacists be trained on principles of critical appraisal to become professional in retrieval information on the Internet that might improve their delivery of healthcare information and their recommendations to patients.
METHODS: The Web of Science, SCOPUS, and PUBMED databases were searched to find eligible studies. The standardized mean difference (SMD) and 95% confidence interval (CI) were used to evaluate the differences in NLR, MLR, and PLR levels between SAP and non-SAP patients. The meta-analysis was conducted using the software "Review Manager" (RevMan, version 5.4.1, September 2020). The random-effect model was used for the pooling analysis if there was substantial heterogeneity. Otherwise, the fixed-effect model was adopted.
RESULTS: Twelve studies comprising 6302 stroke patients were included. The pooled analyses revealed that patients with SAP had significantly higher levels of NLR, MLR, and PLR than the non-SAP group. The SMD, 95% CI, p-value, and I2 for them were respectively reported as (0.88, 0.70-1.07, .00001, 77%); (0.94, 0.43-1.46, .0003, 93%); and (0.61, 0.47-0.75, .001, 0%). Subgroup analysis of NLR studies showed no significant differences in the effect size index between the severity of the stroke, the sample size, and the period between the stroke onset and the blood sampling.
CONCLUSION: This systematic review and meta-analysis suggest that an elevated NLR, MLR, and PLR were associated with SAP, indicating that they could be promising blood-based biomarkers for predicting SAP. Large-scale prospective studies from various ethnicities are recommended to validate this association before they can be applied in clinical practice.
METHODS: AI-based chatbots (ie, ChatGPT-3.5, ChatGPT-4, Microsoft Bing AI, and Google Bard) were compared for their abilities to detect clinically relevant DDIs for 255 drug pairs. Descriptive statistics, such as specificity, sensitivity, accuracy, negative predictive value (NPV), and positive predictive value (PPV), were calculated for each tool.
RESULTS: When a subscription tool was used as a reference, the specificity ranged from a low of 0.372 (ChatGPT-3.5) to a high of 0.769 (Microsoft Bing AI). Also, Microsoft Bing AI had the highest performance with an accuracy score of 0.788, with ChatGPT-3.5 having the lowest accuracy rate of 0.469. There was an overall improvement in performance for all the programs when the reference tool switched to a free DDI source, but still, ChatGPT-3.5 had the lowest specificity (0.392) and accuracy (0.525), and Microsoft Bing AI demonstrated the highest specificity (0.892) and accuracy (0.890). When assessing the consistency of accuracy across two different drug classes, ChatGPT-3.5 and ChatGPT-4 showed the highest variability in accuracy. In addition, ChatGPT-3.5, ChatGPT-4, and Bard exhibited the highest fluctuations in specificity when analyzing two medications belonging to the same drug class.
CONCLUSION: Bing AI had the highest accuracy and specificity, outperforming Google's Bard, ChatGPT-3.5, and ChatGPT-4. The findings highlight the significant potential these AI tools hold in transforming patient care. While the current AI platforms evaluated are not without limitations, their ability to quickly analyze potentially significant interactions with good sensitivity suggests a promising step towards improved patient safety.
METHODS: This retrospective cohort study was conducted among stroke patients admitted to Jordan University Hospital from January 2015 to May 2021. Multivariable logistic regression was used to identify independent predictors for SAP. The predictive performance was assessed using C-statistics, described as the area under the receiver-operating characteristic curve (AUC, ROC) with a 95% confidence interval.
RESULTS: Four hundred and six patients were included in the analysis, and the prevalence of SAP was 19.7%. Multivariable logistic analysis showed that males (Adjusted Odds Ratio (AOR): 5.74; 95% Confidence Interval (95%CI): 2.04-1 6.1)], dysphagia (AOR: 5.29; 95% CI: 1.80-15.5), hemiparesis (AOR: 3.27; 95% CI: 1.13-9.47), lower GCS score (AOR: 0.73; 95% CI: 0.58-0.91), higher levels of neutrophil-lymphocyte ratio (NLR) (AOR: 1.15; 95% CI: 1.07-1.24), monocyte-lymphocyte ratio (MLR) (AOR: 1.49; 95% CI: 1.13-1.96), and neutrophil percentage to albumin ratio (NPAR) (AOR: 1.53; 95% CI: 1.33-1.76) were independent predictors of SAP. The NPAR demonstrated a significantly higher AUC than both the NLR (0.939 versus 0.865, Z = 3.169, p = 0.002) and MLR (0.939 versus 0.842, Z = 3.940, p
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
RESULTS: A total of 221 community pharmacists participated in the current study (response rate was not calculated since opt in recruitment strategies were used). Remarkably, nearly half of the pharmacists (n= 107, 48.4%) indicated a willingness to incorporate the ChatGPT into their pharmacy practice. Nearly half of the pharmacists (n=105, 47.5%) demonstrated a high perceived benefit score for ChatGPT, while around 37% of pharmacists (n= 81) expressed a high concern score about ChatGPT. More than 70% of pharmacists believed that ChatGPT lacked the ability to utilize human judgment and make complicated ethical judgements in its responses (n= 168). Finally, logistics regression analysis showed that pharmacists who had previous experience in using ChatGPT were more willing to integrate ChatGPT in their pharmacy practice than those with no previous experience in using ChatGPT (OR= 2.312, p= 0.035).
CONCLUSION: While pharmacists show a willingness to incorporate ChatGPT into their practice, especially those with prior experience, there are significant concerns. These mainly revolve around the tool's ability to make human-like judgments and ethical decisions. These findings are crucial for the future development and integration of AI tools in pharmacy practice.
METHODS: This is a survey-based cross-sectional study involving the general public of Jordan. The study took place in various Jordanian cities from May 2nd to June 1st, 2023. Using Google forms, the questionnaire was shared through various social media channels (such as Facebook and WhatsApp).
RESULTS: The questionnaire received responses from 800 participants. The data showed that a sizable portion of the Jordanian population were unaware of telepharmacy (n= 343, 42.9%), and a majority had never utilized it (n= 131, 16.4%). The participants viewed the main advantage of telepharmacy as minimizing unnecessary trips to pharmacies (n= 668, 83.5%) and reducing travel time and expenses (n= 632, 79.0%). However, the primary concern was the mental effort required to use this service (n= 465, 58.1%). Of the respondents, 61.3% (n= 490) indicated a willingness to adopt telepharmacy services in the future. Regression analysis indicated that men were more likely to use this service compared to women (OR= 1.947, p<0.001), and people living in northern and southern Jordan exhibited a greater willingness compared to those inhabiting the central region (OR= 2.168, p<0.001).
CONCLUSION: The results reveal a positive attitude towards and a significant readiness to embrace telepharmacy among the Jordanian population. However, for broader acceptance and utilization, apprehensions regarding the service need to be addressed. Doing so could improve access to pharmaceutical care, particularly for patients living in far-flung areas of Jordan.
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.
METHODS: A cross-sectional survey was carried out using a self-administered questionnaire that was distributed to eligible participants using convenience sampling.
RESULTS: A total of 1,396 participants completed the questionnaire. The respondents showed a median knowledge score of influenza of 11.0/15.0, and most of them (70%) were able to recognize its modes of transmission. However, only 11.3% of the participants reported receiving the seasonal influenza vaccine. Physicians were the respondents' most preferred information source for influenza (35.2%), and their recommendation (44.3%) was the most cited reason for taking its vaccine. On the contrary, not knowing about the vaccine's availability (50.1%), concerns regarding the safety of the vaccine (17%), and not considering influenza as a threat (15.9%) were the main reported barriers to getting vaccinated.
CONCLUSION: The current study showed a low uptake of influenza vaccines in Yemen. The physician's role in promoting influenza vaccination seems to be essential. Extensive and sustained awareness campaigns would likely increase the awareness of influenza and remove misconceptions and negative attitudes toward its vaccine. Equitable access to the vaccine can be promoted by providing it free of charge to the public.