This review aims to evaluate the current evidence on the use of the Generative Pre-trained Transformer (ChatGPT) in medical research, including but not limited to treatment, diagnosis, or medication provision. This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched Google Scholar, Web of Science, PubMed, and Medline to identify studies published between 2022 and 2023 that aimed to utilize ChatGPT in medical research. All identified references were stored in EndNote. We initially identified 114 articles, out of which six studies met the inclusion and exclusion criteria for full-text screening. Among the six studies, two focused on drug development (33.33%), two on literature review writing (33.33%), and one each on medical report improvement, provision of medical information, improving research conduct, data analysis, and personalized medicine (16.67% each). ChatGPT has the potential to revolutionize medical research in various ways. However, its accuracy, originality, academic integrity, and ethical issues must be thoroughly discussed and improved before its widespread implementation in clinical research and medical practice.

Background: Integrating Artificial Intelligence (AI) into healthcare has transformed the landscape of patient care and healthcare delivery. Despite this, there remains a notable gap in the existing literature synthesizing the comprehensive understanding of AI’s utilization in nursing care. Objective: This systematic review aims to synthesize the available evidence to comprehensively understand the application of AI in nursing care. Methods: Studies published between January 2019 and December 2023, identified through CINAHL Plus with Full Text, Web of Science, PubMed, and Medline, were included in this review. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines guided the identification, screening, exclusion, and inclusion of articles. The convergent integrated analysis framework, as proposed by the Joanna Briggs Institute, was employed to synthesize data from the included studies for theme generation. Results: A total of 337 records were identified from databases. Among them, 35 duplicates were removed, and 302 records underwent eligibility screening. After applying inclusion and exclusion criteria, eleven studies were deemed eligible and included in this review. Through data synthesis of these studies, six themes pertaining to the use of AI in nursing care were identified: 1) Risk Identification, 2) Health Assessment, 3) Patient Classification, 4) Research Development, 5) Improved Care Delivery and Medical Records, and 6) Developing a Nursing Care Plan. Conclusion: This systematic review contributes valuable insights into the multifaceted applications of AI in nursing care. Through the synthesis of data from the included studies, six distinct themes emerged. These findings not only consolidate the current knowledge base but also underscore the diverse ways in which AI is shaping and improving nursing care practices.

Background: Mobile health (mHealth) offers significant benefits for patients with stroke, facilitating remote monitoring and personalized health care solutions beyond traditional settings. However, there is a dearth of comprehensive data, particularly qualitative insights, on the barriers to mHealth access. Understanding these barriers is crucial for devising strategies to enhance mHealth use among patients with stroke. Objective: This study aims to examine the recent literature focusing on barriers to mHealth access among patients with stroke. Methods: A systematic search of PubMed, MEDLINE, Web of Science, and CINAHL Plus Full Text was conducted for literature published between 2017 and 2023. Abstracts and full texts were independently screened based on predetermined inclusion and exclusion criteria. Data synthesis was performed using the convergent integrated analysis framework recommended by the Joanna Briggs Institute. Results: A total of 12 studies met the inclusion criteria. The majority were qualitative studies (about 42%), followed by mixed methods (25%), pilot studies (about 17%), nonrandomized controlled trials (about 8%), and observational studies (about 8%). Participants included patients with stroke, caregivers, and various health care professionals. The most common mHealth practices were home-based telerehabilitation (30%) and poststroke mHealth and telecare services (20%). Identified barriers were categorized into two primary themes: (1) at the patient level and (2) at the health provider-patient-device interaction level. The first theme includes 2 subthemes: health-related issues and patient acceptability. The second theme encompassed 3 subthemes: infrastructure challenges (including software, networking, and hardware), support system deficiencies, and time constraints. Conclusions: This systematic review underscores significant barriers to mHealth adoption among patients with stroke. Addressing these barriers in future research is imperative to ensure that mHealth solutions effectively meet patients’ needs.

Objective: Hypertension (HTN) significantly increases the risk of stroke and heart disease, which are the leading causes of death and disability globally, particularly among older adults. Antihypertensive medication is a proven treatment for blood pressure control and preventing complications. However, medication adherence rates in older adults with HTN are low. In this review, we systematically identified factors influencing medication adherence in older adults with HTN. Methods: We applied the PRISMA guidelines and conducted systematic searches on PubMed, MEDLINE, and Google Scholar in July 2022 to identify preliminary studies reporting factors influencing medication adherence among older adults with HTN. The convergent integrated analysis framework suggested by the Joanna Briggs Institute for systematic reviews was adopted for data synthesis. Results: Initially, 448 articles were identified, and after title and abstract screening, 16 articles qualified for full-text review. During this phase, three articles were excluded for reporting on irrelevant populations or focusing on issues beyond the review’s aim, leaving thirteen studies in the final review. After data synthesis, fifteen themes were extracted from the key findings of the included studies. The most prevalent themes included the number of medications used (53.9%, n=7 studies), financial status (38.5%, n=5), sex (38.5%, n=5), age (30.1%, n=4), duration of disease (23.1%, n=3), comorbidities (23.1%, n=3), and health compliance (23.1%, n=3). Other themes, such as education, health literacy, health belief, medication belief, perception of illness, patient-physician relationship, self-efficacy, and social support, were also identified. Conclusion: The findings of this review highlight critical areas for developing innovative, evidence-based programs to improve medication adherence in hypertensive older adults. Insights from this review can contribute to improving medication adherence and preventing future health complications.

Purpose: To examine the association and the mediating effect among medication beliefs, perception of illness, and medication adherence in ischemic stroke patients. Patients and Methods: This is a cross-sectional study, 306 ischemic stroke patients recruited from The Second Affiliated Hospital of Harbin Medical University, China between June 2018 and October 2018. The Beliefs about Medications Questionnaire (BMQ) was used to assess a patient’s beliefs about medication. The Brief Illness Perceptions Questionnaire (BIPQ) was used to rapidly determine the cognitive and emotional representation of ischemic stroke. Self-reported adherence was assessed using the Medication Adherence Report Scale (MARS). Logistic regression analysis, Pearson correlations, and mediation analysis were used to evaluate the association and mediating effects among medication beliefs, perception of illness, and medication adherence. Results: Overall, 220 (65.48%) participants were non-adherent to their ischemic stroke medications. Non-adherent patients had greater stroke severity (p = 0.031) compared to adherent patients. After adjusting for demographic characteristics, specific concern (odds ratio [OR]: 0.652, 95% confidence interval [CI]: 0.431 to 0.987, p-value [P] = 0.043), and the perception of illness (overall score) (OR: 0.964, 95% CI: 0.944 to 0.985, P = 0.001) were significantly associated with medication adherence in ischemic stroke patients. The mediation analysis showed the significant indirect effects of specific concern, general overuse, and general harm. It suggested that some impacts of medication beliefs have been mediated on medication adherence. Conclusion: Perceived concern about adverse effects of medicines and perception of illness have an influential impact on self-reported medication adherence in ischemic stroke patients. To enhance adherence, patients’ beliefs about medication and perceptions of their disease should be reconsidered. Future work should investigate interventions to influence patient adherence by addressing concerns about their ischemic stroke medications and the perception of the disease.

Objective: To examine the impact of interdisciplinary team-based care (ITBC) on chronically ill patients and their outcomes as reported in relevant contemporary literature. Methods: In this systematic review, PubMed, MEDLINE, Web of Science, CINAHL Plus Full Text, and ten publishers were searched to identify studies published between 2019 and 2024. Titles, abstracts, and full texts were screened for eligible studies and assessed for relevance. Inclusion and exclusion criteria were implemented to ensure that only studies relevant to our objective were included. The convergent integrated analysis framework suggested by the Joanna Briggs Institute was utilized for data synthesis. Results: Ten studies were included in the systematic review. Data synthesis revealed five major themes at different levels: 1) Patient level, including themes of Patients’ Self-Improvement and Patients’ Health Outcomes; 2) Interpersonal level, including themes of Providers’ Work Performance and Shared Decision Making; and 3) Organizational level, including the theme of Healthcare Utilization. Conclusion: ITBC has a significant positive impact on chronically ill patients at multiple levels. At the patient level, it enhances self-management and health outcomes. At the interpersonal level, it improves healthcare providers’ performance and promotes shared decision-making. At the organizational level, it leads to more efficient healthcare utilization.