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Abstract An artificial intelligence (AI)-based conversational large language model (LLM) was launched in November 2022 namely, “ChatGPT”. Despite the wide array of potential applications of LLMs in healthcare education, research and practice, several valid concerns were raised. The current systematic review aimed to investigate the possible utility of ChatGPT and to highlight its limitations in healthcare education, research and practice. Using the PRIMSA guidelines, a systematic search was conducted to retrieve English records in PubMed/MEDLINE and Google Scholar under the term “ChatGPT”. Eligibility criteria included the published research or preprints of any type that discussed ChatGPT in the context of healthcare education, research and practice. A total of 280 records were identified, and following full screening, a total of 60 records were eligible for inclusion. Benefits/applications of ChatGPT were cited in 51/60 (85.0%) records with the most common being the utility in scientific writing followed by benefits in healthcare research (efficient analysis of massive datasets, code generation and rapid concise literature reviews besides utility in drug discovery and development). Benefits in healthcare practice included cost saving, documentation, personalized medicine and improved health literacy. Concerns/possible risks of ChatGPT use were expressed in 58/60 (96.7%) records with the most common being the ethical issues including the risk of bias, plagiarism, copyright issues, transparency issues, legal issues, lack of originality, incorrect responses, limited knowledge, and inaccurate citations. Despite the promising applications of ChatGPT which can result in paradigm shifts in healthcare education, research and practice, the embrace of this application should be done with extreme caution. Specific applications of ChatGPT in health education include the promising utility in personalized learning tools and shift towards more focus on critical thinking and problem-based learning. In healthcare practice, ChatGPT can be valuable for streamlining the workflow and refining personalized medicine. Saving time for the focus on experimental design and enhancing research equity and versatility are the benefits in scientific research. Regarding authorship in scientific articles, as it currently stands, ChatGPT does not qualify to be listed as an author unless the ICMJE/COPE guidelines are revised and amended. An initiative involving all stakeholders involved in healthcare education, research and practice is urgently needed to set a code of ethics and conduct on the responsible practices involving ChatGPT among other LLMs.

BACKGROUND: Dementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people with mild cognitive impairment (MCI) will progress to dementia but others remain stable or recover full function. There is great interest in finding good predictors of dementia in people with MCI. The Mini-Mental State Examination (MMSE) is the best-known and the most often used short screening tool for providing an overall measure of cognitive impairment in clinical, research and community settings. OBJECTIVES: To determine the diagnostic accuracy of the MMSE at various thresholds for detecting individuals with baseline MCI who would clinically convert to dementia in general, Alzheimer's disease dementia or other forms of dementia at follow-up. SEARCH METHODS: We searched ALOIS (Cochrane Dementia and Cognitive Improvement Specialized Register of diagnostic and intervention studies (inception to May 2014); MEDLINE (OvidSP) (1946 to May 2014); EMBASE (OvidSP) (1980 to May 2014); BIOSIS (Web of Science) (inception to May 2014); Web of Science Core Collection, including the Conference Proceedings Citation Index (ISI Web of Science) (inception to May 2014); PsycINFO (OvidSP) (inception to May 2014), and LILACS (BIREME) (1982 to May 2014). We also searched specialized sources of diagnostic test accuracy studies and reviews, most recently in May 2014: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). No language or date restrictions were applied to the electronic searches and methodological filters were not used as a method to restrict the search overall so as to maximize sensitivity. We also checked reference lists of relevant studies and reviews, tracked citations in Scopus and Science Citation Index, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on MMSE for dementia diagnosis to try to locate possibly relevant but unpublished data. SELECTION CRITERIA: We considered longitudinal studies in which results of the MMSE administered to MCI participants at baseline were obtained and the reference standard was obtained by follow-up over time. We included participants recruited and clinically classified as individuals with MCI under Petersen and revised Petersen criteria, Matthews criteria, or a Clinical Dementia Rating = 0.5. We used acceptable and commonly used reference standards for dementia in general, Alzheimer's dementia, Lewy body dementia, vascular dementia and frontotemporal dementia. DATA COLLECTION AND ANALYSIS: We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. We assessed the identified full papers for eligibility and extracted data to create two by two tables for dementia in general and other dementias. Two authors independently performed quality assessment using the QUADAS-2 tool. Due to high heterogeneity and scarcity of data, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic curve. MAIN RESULTS: In this review, we included 11 heterogeneous studies with a total number of 1569 MCI patients followed for conversion to dementia. Four studies assessed the role of baseline scores of the MMSE in conversion from MCI to all-cause dementia and eight studies assessed this test in conversion from MCI to Alzheimer´s disease dementia. Only one study provided information about the MMSE and conversion from MCI to vascular dementia. For conversion from MCI to dementia in general, the accuracy of baseline MMSE scores ranged from sensitivities of 23% to 76% and specificities from 40% to 94%. In relationship to conversion from MCI to Alzheimer's disease dementia, the accuracy of baseline MMSE scores ranged from sensitivities of 27% to 89% and specificities from 32% to 90%. Only one study provided information about conversion from MCI to vascular dementia, presenting a sensitivity of 36% and a specificity of 80% with an incidence of vascular dementia of 6.2%. Although we had planned to explore possible sources of heterogeneity, this was not undertaken due to the scarcity of studies included in our analysis. AUTHORS' CONCLUSIONS: Our review did not find evidence supporting a substantial role of MMSE as a stand-alone single-administration test in the identification of MCI patients who could develop dementia. Clinicians could prefer to request additional and extensive tests to be sure about the management of these patients. An important aspect to assess in future updates is if conversion to dementia from MCI stages could be predicted better by MMSE changes over time instead of single measurements. It is also important to assess if a set of tests, rather than an isolated one, may be more successful in predicting conversion from MCI to dementia.

Digital transformation of higher education institutions (HEIs) is of paramount importance in today’s technology-driven world. However, there are numerous barriers that hinder the successful implementation of digital transformation initiatives in HEIs. In this article, we identify and classify these barriers based on a systematic literature review. The findings reveal twenty distinct barriers that inhibit digital transformation in higher education. These were then organised into six broad categories, namely environmental, strategic, organisational, technological, people-related and cultural. The study provides a comprehensive understanding of the barriers faced, facilitating the development of effective strategies and interventions. Our analysis provides valuable information for higher education institutions, policy makers and stakeholders involved in digital transformation initiatives.

Cognitive load theory was introduced in the 1980s as an instructional design theory based on several uncontroversial aspects of human cognitive architecture. Our knowledge of many of the characteristics of working memory, long-term memory and the relations between them had been well-established for many decades prior to the introduction of the theory. Curiously, this knowledge had had a limited impact on the field of instructional design with most instructional design recommendations proceeding as though working memory and long-term memory did not exist. In contrast, cognitive load theory emphasised that all novel information first is processed by a capacity and duration limited working memory and then stored in an unlimited long-term memory for later use. Once information is stored in long-term memory, the capacity and duration limits of working memory disappear transforming our ability to function. By the late 1990s, sufficient data had been collected using the theory to warrant an extended analysis resulting in the publication of Sweller et al. (Educational Psychology Review, 10, 251–296, 1998). Extensive further theoretical and empirical work have been carried out since that time and this paper is an attempt to summarise the last 20 years of cognitive load theory and to sketch directions for future research.

Information overload is a problem that is being exacerbated by the ongoing digitalization of the world of work and the growing use of information and communication technologies. Therefore, the aim of this systematic literature review is to provide an insight into existing measures for prevention and intervention related to information overload. The methodological approach of the systematic review is based on the PRISMA standards. A keyword search in three interdisciplinary scientific databases and other more practice-oriented databases resulted in the identification of 87 studies, field reports, and conceptual papers that were included in the review. The results show that a considerable number of papers have been published on interventions on the behavioral prevention level. At the level of structural prevention, there are also many proposals on how to design work to reduce information overload. A further distinction can be made between work design approaches at the level of information and communication technology and at the level of teamwork and organizational regulations. Although the identified studies cover a wide range of possible interventions and design approaches to address information overload, the strength of the evidence from these studies is mixed.

With the rapid development of “Internet plus”, medical care has entered the era of big data. However, there is little research on medical big data (MBD) from the perspectives of bibliometrics and visualization. The substantive research on the basic aspects of MBD itself is also rare. This study aims to explore the current status of medical big data through visualization analysis on the journal papers related to MBD. We analyze a total of 988 references which were downloaded from the Science Citation Index Expanded and the Social Science Citation Index databases from Web of Science and the time span was defined as “all years”. The GraphPad Prism 5, VOSviewer and CiteSpace softwares are used for analysis. Many results concerning the annual trends, the top players in terms of journal and institute levels, the citations and H-index in terms of country level, the keywords distribution, the highly cited papers, the co-authorship status and the most influential journals and authors are presented in this paper. This study points out the development status and trends on MBD. It can help people in the medical profession to get comprehensive understanding on the state of the art of MBD. It also has reference values for the research and application of the MBD visualization methods.

This systematic review synthesised evidence on associations between nature-based early childhood education (ECE) and children’s social, emotional, and cognitive development. A search of nine databases was concluded in August 2020. Studies were eligible if: (a) children (2–7 years) attended ECE, (b) ECE integrated nature, and (c) assessed child-level outcomes. Two reviewers independently screened full-text articles and assessed study quality. Synthesis included effect direction, thematic analysis, and results-based convergent synthesis. One thousand three hundred and seventy full-text articles were screened, and 36 (26 quantitative; 9 qualitative; 1 mixed-methods) studies were eligible. Quantitative outcomes were cognitive (n = 11), social and emotional (n = 13), nature connectedness (n = 9), and play (n = 10). Studies included controlled (n = 6)/uncontrolled (n = 6) before-after, and cross-sectional (n = 15) designs. Based on very low certainty of the evidence, there were positive associations between nature-based ECE and self-regulation, social skills, social and emotional development, nature relatedness, awareness of nature, and play interaction. Inconsistent associations were found for attention, attachment, initiative, environmentally responsible behaviour, and play disruption/disconnection. Qualitative studies (n = 10) noted that nature-based ECE afforded opportunities for play, socialising, and creativity. Nature-based ECE may improve some childhood development outcomes, however, high-quality experimental designs describing the dose and quality of nature are needed to explore the hypothesised pathways connecting nature-based ECE to childhood development (Systematic Review Registration: CRD42019152582).

Many scholars are not well trained in conducting a standalone literature review, a scholarly paper that in its entirety summarizes and synthesizes knowledge from a prior body of research. Numerous guides that exist for information systems (IS) research mainly concentrate on only certain parts of the process; few span the entire process. This paper introduces the rigorous, standardized methodology for the systematic literature review (also called systematic review) to IS scholars. This comprehensive guide extends the base methodology from the health sciences and other fields with numerous adaptations to meet the needs of methodologically diverse fields such as IS research, especially those that involve including and synthesizing both quantitative and qualitative studies. Moreover, this guide provides many examples from IS research and provides references to guides with further helpful details for conducting a rigorous and valuable literature review. Although tailored to IS research, it is sufficiently broad to be applicable and valuable to scholars from any social science field.

BACKGROUND: Adolescents present many challenges in providing them effective preventive services and health care. Yet, they are typically the early adopters of new technology (eg, the Internet). This creates important opportunities for engaging youths via eHealth. OBJECTIVE: To describe how adolescents use technology for their health-information needs, identify the challenges they face, and highlight some emerging roles of health professionals regarding eHealth services for adolescents. METHODS: Using an inductive qualitative research design, 27 focus groups were conducted in Ontario, Canada. The 210 participants (55% female, 45% male; median age 16 years) were selected to reflect diversity in age, sex, geographic location, cultural identity, and risk. An 8-person team analyzed and coded the data according to major themes. RESULTS: Study participants most-frequently sought or distributed information related to school (89%), interacting with friends (85%), social concerns (85%), specific medical conditions (67%), body image and nutrition (63%), violence and personal safety (59%), and sexual health (56%). Finding personally-relevant, high-quality information was a pivotal challenge that has ramifications on the depth and types of information that adolescents can find to answer their health questions. Privacy in accessing information technology was a second key challenge. Participants reported using technologies that clustered into 4 domains along a continuum from highly-interactive to fixed information sources: (1) personal communication: telephone, cell phone, and pager; (2) social communication: e-mail, instant messaging, chat, and bulletin boards; (3) interactive environments: Web sites, search engines, and computers; and (4) unidirectional sources: television, radio, and print. Three emerging roles for health professionals in eHealth include: (1) providing an interface for adolescents with technology and assisting them in finding pertinent information sources; (2) enhancing connection to youths by extending ways and times when practitioners are available; and (3) fostering critical appraisal skills among youths for evaluating the quality of health information. CONCLUSIONS: This study helps illuminate adolescent health-information needs, their use of information technologies, and emerging roles for health professionals. The findings can inform the design and more-effective use of eHealth applications for adolescent populations.