Exploratory study on student perception on the use of chat AI in process-driven problem-based learning.

INTRODUCTION: With the increasing prevalence of artificial intelligence (AI) technology, it is imperative to investigate its influence on education and the resulting impact on student learning outcomes. This includes exploring the potential application of AI in process-driven problem-based learning (PDPBL). This study aimed to investigate the perceptions of students towards the use of ChatGPT) build on GPT-3.5 in PDPBL in the Bachelor of Pharmacy program. METHODS: Eighteen students with prior experience in traditional PDPBL processes participated in the study, divided into three groups to perform PDPBL sessions with various triggers from pharmaceutical chemistry, pharmaceutics, and clinical pharmacy fields, while utilizing chat AI provided by ChatGPT to assist with data searching and problem-solving. Questionnaires were used to collect data on the impact of ChatGPT on students' satisfaction, engagement, participation, and learning experience during the PBL sessions. RESULTS: The survey revealed that ChatGPT improved group collaboration and engagement during PDPBL, while increasing motivation and encouraging more questions. Nevertheless, some students encountered difficulties understanding ChatGPT's information and questioned its reliability and credibility. Despite these challenges, most students saw ChatGPT's potential to eventually replace traditional information-seeking methods. CONCLUSIONS: The study suggests that ChatGPT has the potential to enhance PDPBL in pharmacy education. However, further research is needed to examine the validity and reliability of the information provided by ChatGPT, and its impact on a larger sample size.

Community pharmacists' perceived value on precision medicine, desired training components, and exposure during pharmacy education: Malaysia's experience.

Background: Precision medicine beckons new horizons for therapy geared to one's genetics, lifestyle, and environmental determinants. Molecular, pathology, and clinical diagnostics can be integrated to provide pharmaceutical care. Aims: The value and appeal of precision medicine to community pharmacists, knowledge attained, and training programmes perceived as necessary were evaluated. Methods: Over 10 months, a published questionnaire, which was also digitally accessible during the COVID-19 outbreak, was distributed by hand, via email and social media. 300 community pharmacists across 9 districts in an urban state in Malaysia, self-administered and returned completed versions (response rate 75%). Three- or five-point Likert scale and multiple-choice responses were analysed using SPSS to assess whether or not exposure through the pharmacy curricula impacted current knowledge, perception and willingness to pursue precision medicine. Results: Respondents were largely: females (N = 196, 65.3%) and practicing for up to 10 years (N = 190, 66.3%). Although knowledge levels were moderate (76%), positive perceptions were showcased (94%), and 80% were willing to integrate precision medicine into their daily practice. Although 61% did not or do not recall having had prior exposure to pharmacogenomics as part of their pharmacy school curricula, many (93%) were willing to attain knowledge by undergoing additional training. Desired training included current pharmacogenetic testing available (17%), interpretation of the test results (15%), and ethical considerations (13%). Community pharmacists who had 0.5-10 years' work experience possessed greater knowledge (µ = 1.48, CI 1.35-1.61, p = 0.017), than the pharmacists who had 21-40 years of work experience (µ = 1.28, CI 1.05-1.51, p = 0.021). Exposure to the subject during pharmacy education positively impacted the willingness to integrate precision medicine in daily practice (p = 0.035). Conclusion: Community pharmacists were receptive to and valued precision medicine. A relatively high number had prior exposure to concepts of precision medicine through the pharmacy curriculum, and were therefore willing to adopt the practice in their day-to-day provision of healthcare. With adequate training centred on bioethics, utilising pharmacogenetic testing, and interpretation of the results, community pharmacists will be equipped for the provision of precision medicine services in the foreseeable future.

Patient-reported outcome measures to detect intentional, mixed, or unintentional non-adherence to medication: a systematic review.

OBJECTIVE: To categorise patient-reported outcome measures (PROMs) into their propensity to detect intentional and/or unintentional non-adherence to medication, and synthesise their psychometric properties. DESIGN: Systematic review and regression analysis. ELIGIBILITY: Medication adherence levels studied at primary, secondary and tertiary care settings. Self-reported measures with scoring methods were included. Studies without proxy measures were excluded. DATA SOURCES: Using detailed searches with key concepts including questionnaires, reliability and validity, and restricted to English, MEDLINE, EMBASE, CINAHL, International Pharmaceutical Abstracts, and Cochrane Library were searched until 01 March 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA-2020) checklist was used. DATA ANALYSIS: Risk of bias was assessed via COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN-2018) guidelines. Narrative synthesis aided by graphical figures and statistical analyses. OUTCOME MEASURES: Process domains [behaviour (e.g., self-efficacy), barrier (e.g., impaired dexterity) or belief (e.g., perception)], and overall outcome domains of either intentional (I), unintentional (UI), or mixed non-adherence. RESULTS: Paper summarises evidence from 59 studies of PROMs, validated among patients aged 18-88 years in America, the United Kingdom, Europe, Middle East, and Australasia. PROMs detected outcome domains: intentional non-adherence, n=44 (I=491 criterion items), mixed intentionality, n=13 (I=79/UI=50), and unintentional, n=2 (UI=5). Process domains detected include belief (383 criterion items), barrier (192) and behaviour (165). Criterion validity assessment used proxy measures (biomarkers, e-monitors), and scoring was ordinal, dichotomised, or used Visual Analogue Scale. Heterogeneity was revealed across psychometric properties (consistency, construct, reliability, discrimination ability). Intentionality correlated positively with negative beliefs (r(57)=0.88) and barriers (r(57)=0.59). For every belief or barrier criterion-item, PROMs' aptitude to detect intentional non-adherence increased by ß=0.79 and ß=0.34 units, respectively (R2=0.94). Primary care versus specialised care predicted intentional non-adherence (OR 1.9; CI 1.01 to 2.66). CONCLUSIONS: Ten PROMs had adequate psychometric properties. Of the ten, eight PROMs were able to detect total, and two PROMs were able to detect partial intentionality to medication default. Fortification of patients' knowledge and illness perception, as opposed to daily reminders alone, is most imperative at primary care levels.