Exploratory research in clinical and social pharmacy最新文献

Introduction: Community pharmacies, as unique and accessible healthcare venues, are ideal locations to implement interventions aiming to improve patient care. However, these interventions may increase workload or disrupt workflow for community pharmacists, technicians, and other staff members, threatening long-term sustainment. There are growing calls from the field of implementation science to design for intervention sustainment and maintenance by maximizing innovation fit. Senior Safe™, an intervention to facilitate safer over-the-counter (OTC) product selection by older adults, serves as a case study to examine the congruence between Innovation Factors and community pharmacy Inner Context constructs and their implications for workload and sustainment.

Methods: Using the Exploration, Preparation, Implementation, Sustainment (EPIS) framework, this qualitative study identified factors surrounding Senior Safe implementation. Semi-structured interviews were conducted with staff from pharmacies where Senior Safe was implemented. Two coders independently analyzed interview transcripts using deductive analysis based on EPIS constructs. Thematic analysis was used to generate three themes that encapsulated innovation fit.

Results: Nineteen pharmacy staff members participated, with the majority reporting no significant change in their workload or workflow due to Senior Safe. Interview feedback supported a pre-existing culture of the healthcare system to engage patients, of leadership commitment to patient safety initiatives, and of an amplified role of pharmacy technicians.

Discussion and Conclusion: Pharmacy staff interviews revealed congruence between Innovation Factors and Inner Context that likely yielded intervention workload neutrality. This study highlighted the importance for researchers to consider maintenance and sustainability when designing and implementing an intervention and the critical influence of culture and leadership support during this process.

Background

Self-medication among university students is becoming a health concern, especially during examinations and stress. This pattern of medication use among students could lead to adverse health consequences if it is not addressed and tackled. Thus, this study investigated the most associated factors with this practice among students.

Methods

An observational cross-sectional study was conducted among university students in Northern Borders Province, Saudi Arabia. A total of 220 students were selected and took part in the survey. Data was collected through a self-administered questionnaire. The survey was distributed among participants to answer five sections: demographic and socioeconomic characteristics, health status problems, satisfaction with academic performance, and self-medication questions. The content validity was tested using a pilot sample of 30 students. The descriptive, univariate, and multivariate analyses were conducted using the Statistical Package for Social Science program.

Results

In the present sample of university students, the response rate was 100%. Approximately one-third reported using medications without prescriptions, and 83% of them have used medications three times at most during the past 12 months. Headache was the most common reason for use (59%), followed by fever (20%). Adjusted multivariate analysis showed that students who were 21–24 years of age (OR = 3.79, 95% CI = 1.21–11.82), female (OR = 2.43, 95% CI = 1.03–5.72), and living alone in private housing (OR = 3.62, 95% CI = 1.32–9.90) were at high risk of self-medication as compared to their counterparts. However, students in the last years of college (fourth (OR = 0.14, 95% CI = 0.03–0.62), fifth (OR = 0.21, 95% CI = 0.05–0.95), sixth (OR = 0.05, 95% CI = 0.01–0.35)) were at lower risk as compared to their counterparts.

Conclusion

The study found that self-medication was common among university students, with higher rates among those who were 21–24 years old, female, and living alone in private housing, but lower rates among students in the later years of college. Educational programs and awareness campaigns should target students who are at higher risk of practicing self-medication to avoid misuse of over-the-counter medications.

Background

In the U.S. alone, medication non-adherence is estimated to cause 1 in 10 hospitalizations, approximately 125,000 deaths annually, and cost the U.S. healthcare system just under $300 billion each year. Patients in medically underserved areas (MUAs) are particularly vulnerable to all forms of non-adherence and downstream morbidity and mortality; however, the extent to which primary medication non-adherence (i.e., prescription abandonment) affects the underserved is still largely unknown.

Objectives

To assess the difference in rates of abandonment of quality measured prescriptions in areas that are medically underserved compared to areas that are not. The secondary objective is to assess the impact that the COVID-19 pandemic had on rates of prescription abandonment in both MUAs and those that are not.

Methods

In this retrospective study, data on abandoned, quality measured prescriptions were collected and analyzed using Chi-Square analyses from one regional division of a large grocery-chain pharmacy containing ninety-one pharmacies located in Tennessee, Mississippi, Arkansas, Kentucky, and Missouri. The primary objective used 2019 data while the secondary objective used data from April – November of both 2019 and 2020.

Results

Patients from MUAs abandoned quality measured prescriptions at a higher rate of 5.44% compared to 4.77% of those not living in these areas (P < 0.01). This study also discovered that during the COVID-19 pandemic, MUAs had a decrease in abandonment from 6.14% in 2019 to 6.02% in 2020 (P < 0.01). Those from non-MUAs had non-significant change in abandonment (P = 0.87).

Conclusion

Patients in MUAs abandon quality measured prescriptions at a statistically significant higher rate when compared to patients who live in areas that are not considered to be medically underserved. Moreover, during the COVID-19 pandemic patients living in MUAs had a statistically significant decrease in prescription abandonment while those in non-MUAs did not statistically change.

Introduction

Students in pharmacy are positive towards integrating artificial intelligence and ChatGPT into their practice. The aim of this study was to investigate the direct short-term learning effect of using Chat GPT by pharmacy students.

Methods

This was an experimental randomized study. Students were allocated into two groups; the intervention group (n = 15) used all study tools and ChatGPT, while the control group (n = 16) used all study tools, except ChatGPT. Differences between groups was measured by how well they performed on a knowledge test before and after a short study period.

Results

No significant difference was found between the intervention and control groups in level of competence in the pretest score (p = 0.28). There was also no significant effect of using ChatGPT, with a mean adjusted difference of 0.5 points on a 12-point scale. However there was a trend towards a higher proportion of ChatGPT participants having a large (at least four point) increase in score (4 out of 15) vs control group (1 out of 16).

Conclusion

There is a potential for positive effects of ChatGPT on learning outcomes in pharmacy students, however the current study was underpowered to measure a statistically significant effect of ChatGPT on short term learning.

Background

While suboptimal medication adherence remains an obstacle to the management of hypertension and diabetes in China, few studies have investigated associated factors with medication adherence on different dimensions simultaneously.

Objective

To systematically examine associated patient, family, and community factors with suboptimal medication adherence among people with hypertension and/or type 2 diabetes in China.

Methods

The study stratified a random sample of 622 adults aged 45 years or older with hypertension and/or type 2 diabetes from three southeast cities in China in 2019. Trained interviewers used the Morisky Green Levine Medication Adherence Scale, Self-Efficacy to Manage Chronic Disease (SEMCD) Scale, and the Family Adaptability, Partnership, Growth, Affection, and Resolve (APGAR) Scale to assess medication adherence, self-efficacy, and family function, respectively. Participants also reported their perceived satisfaction with community health services (quantity, quality, affordability, and overall acceptance). The study used the multivariable logistic regression to assess the association of patient, family, and community factors with suboptimal medication adherence.

Results

Among the participants, 42.9% reported suboptimal medication adherence. In the multivariable logistic regression model, male participants (odds ratio [OR] = 0.55, p = 0.001) had higher medication adherence compared to females. Having a self-efficacy score that was lower than or equal to the sample mean was significantly associated with lower adherence (OR = 1.44, p = 0.039). Participants unsatisfied with the affordability of community health services and medicine had lower adherence (OR = 2.18, p = 0.028) than those neutral or satisfied. There were no significant associations between family function and medication adherence.

Conclusions

Sex, self-efficacy, and perceived affordability of community health services were important factors associated with medication adherence. Healthcare professionals are recommended to consider multiple factors and leverage services and resources in community health centers when promoting medication adherence.

Introduction

Generative artificial intelligence (Gen-AI), exemplified by the widely adopted ChatGPT, has garnered significant attention in recent years. Its application spans various health education domains, including pharmacy, where its potential benefits and drawbacks have become increasingly apparent. Despite the growing adoption of Gen-AI such as ChatGPT in pharmacy education, there remains a critical need to assess and mitigate associated risks. This review exploresthe literature and potential strategies for mitigating risks associated with the integration of Gen-AI in pharmacy education.

Aim

To conduct a scoping review to identify implications of Gen-AI in pharmacy education, identify its use and emerging evidence, with a particular focus on strategies which mitigate potential risks to academic integrity.

Methods

A scoping review strategy was employed in accordance with the PRISMA-ScR guidelines. Databases searched includedPubMed, ERIC [Education Resources Information Center], Scopus and ProQuestfrom August 2023 to 20 February 2024 and included all relevant records from 1 January 2000 to 20 February 2024 relating specifically to LLM use within pharmacy education. A grey literature search was also conducted due to the emerging nature of this topic. Policies, procedures, and documents from institutions such as universities and colleges, including standards, guidelines, and policy documents, were hand searched and reviewed in their most updated form. These documents were not published in the scientific literature or indexed in academic search engines.

Results

Articles (n = 12) were derived from the scientific data bases and Records (n = 9) derived from the grey literature. Potential use and benefits of Gen-AI within pharmacy education were identified in all included published articles however there was a paucity of published articles related the degree of consideration to the potential risks to academic integrity. Grey literature recordsheld the largest proportion of risk mitigation strategies largely focusing on increased academic and student education and training relating to the ethical use of Gen-AI as well considerations for redesigning of current assessments likely to be a risk for Gen-AI use to academic integrity.

Conclusion

Drawing upon existing literature, this review highlights the importance of evidence-based approaches to address the challenges posed by Gen-AI such as ChatGPT in pharmacy education settings. Additionally, whilst mitigation strategies are suggested, primarily drawn from the grey literature, there is a paucity of traditionally published scientific literature outlining strategies for the practical and ethical implementation of Gen-AI within pharmacy education. Further research related to the responsible and ethical use of Gen-AI in pharmacy curricula; and studies related to strategies a