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).

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).

Methods: This is a cross-sectional study conducted among 393 adult individuals in Kuantan, Pahang, Malaysia. Data collection was conducted through face-to-face interviews among the lay public members who were 18-64 years old, excluding healthcare professionals in clinical settings and academic settings. Statistical analysis was performed using chi-square test and logistic regression analysis.

Results: The majority of the individuals identified smoking as a risk factor for heart attack, followed by atrial fibrillation (57.7%), heart disease (54.1%), and obesity (53.8%). However, diabetes (26%) was the risk factor that was least recognized by the participants. A total of 90.6% of participants identified at least one risk factor for heart attack, while 9.8% of the participants did not identify any risk factors for heart attack, whereas 5.6% identified all modifiable heart attack risk factors. Furthermore, participants aged 46-64 years old, married respondents, and Chinese participants, those with higher educational levels, and received prior information demonstrated great awareness of eight modifiable risk factors for heart attack. Multivariable logistic regression presented that participants with aged 55-64, those with family history of heart attack and individuals with dyslipidemia were factors independently related to excellent awareness (p=0.04, OR=6.21, 95% CL= 1.081-35.641), (p=0.049, OR=2.11, 95% CL=0.721-6.230) and (p=0.009, OR= 4.08, 95% CL= 1.427-11.685), respectively.

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.

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.

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: 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).

METHOD: A paper-based cross-sectional survey was performed. A pilot-tested questionnaire consisting of 21 questions (demographics 5, knowledge 6, attitude 6, and preparedness 4) was administered to 900 healthcare students at different years of study. Descriptive and inferential analyses were used.

METHODS: A retrospective observational study was conducted, involving AIS cases admitted to a tertiary hospital in Jordan between 2015 and 2020. Lab data were collected upon admission, and the primary outcome was ICU admission during hospitalization. Descriptive and inferential analyses were performed using SPSS version 29.

METHODS: Healthcare workers (HCWs) from major healthcare facilities participated in this cross-sectional study. A self-administered questionnaire comprising of five main domains (demographics, knowledge, self-preparedness, counselling practice, perceived barriers) was distributed among HCWs after obtaining informed consent. A convenient sampling technique was used. Descriptive and inferential analyses were applied using SPSS software.

RESULTS: A total of 1000 participants were initially targeted to participate in the study with 514 (51.4%) responding, of which 55.3% were female. Physicians and nurses constituted the largest proportion of participants, with 39.5% and 33.3%, respectively. The median scores for knowledge, self-preparedness, and counselling practice were 8 (out of 9), 9 (out of 15), and 25 (out of 30), respectively. The physician group showed a statistically significant association with better knowledge compared to the nurse group only, P<0.001. Males had higher preparedness scores than females, p<0.001. Also, the intensive care unit (ICU) and emergency departments presented a statistically significant difference by which the participants from these departments were more prepared compared to the others (e.g. outpatients, paediatrics and surgery) with P < 0.0001. The lack of awareness among the general population about COVID-19 preventive measures was perceived as the most common barrier for the adequate prevention and control of COVID-19 in Yemen (89.1%).

METHODS: A cross-sectional study was conducted in Amman, the capital and largest city of Jordan, using a validated questionnaire. It was distributed to pharmacists working in community and hospital pharmacies using a convenience sampling technique. Descriptive and inferential statistics were performed in this study.

RESULTS: A total of 340 questionnaires distributed, 300 (88%) pharmacists responded. Over 50% of pharmacists claimed that they have sufficient knowledge regarding FDI. Virtually, the overall median (interquartile range) knowledge score was 18 (15-21), approximately 60%. The highest knowledge scores were for alcohol-drug interactions section (66.6%) followed by both common food-drug interactions and the timing of drug intake to food consumption sections with a score of (58.3%) for each, reflecting a suboptimal knowledge of FDIs among the pharmacists.

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.

METHODS: A cross-sectional online survey was conducted in four major cities in Yemen. The constructed questionnaire consisted of four main sections (sociodemographic data, misinformation, perceptions (perceived susceptibility, severity, and worry), and vaccination acceptance evaluation). Subject recruitment and data collection were conducted online utilizing social websites and using the snowball sampling technique. Descriptive and inferential analyses were performed using SPSS version 27.

RESULTS: The total number of respondents was 484. Over 60% of them were males and had a university education. More than half had less than 100$ monthly income and were khat chewers, while only 18% were smokers. Misinformation prevalence ranged from 8.9% to 38.9%, depending on the statement being asked. Men, university education, higher income, employment, and living in urban areas were associated with a lower misinformation level (p <0.05). Statistically significant association (p <0.05) between university education, living in urban areas, and being employed with perceived susceptibility were observed. The acceptance rate was 61.2% for free vaccines, but it decreased to 43% if they had to purchase it. Females, respondents with lower monthly income, and those who believed that pharmaceutical companies made the virus for financial gains were more likely to reject the vaccination (p <0.05).

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.