The Journal for Transdisciplinary Research (TD) is a journal dedicated to promoting the concept of transdisciplinary research. It is aimed at creating knowledge with the collaboration of the formal sectors of the natural and human sciences as base. Over and above this, the intention is to focus on levels of knowledge that are to be found at grassroots level. It is important to explore this knowledge because it becomes the groundwork for further knowledge, which is often not confined to a fixed formal discipline or area of knowledge. The editorial team of the journal welcomes contributions of a theoretical nature, as well as material based on empirical research. Preference is given to southern Africa as a region of focus. However, should submitted articles show the potential for making a contribution towards our understanding of science beyond the confines of single disciplines, it would enjoy favourable consideration.

Artificial Intelligence (AI) tools have been used across various sectors of the global economy. The use of AI has been associated with both benefits and drawbacks, which is why the goal of this research was to identify the attitudes of academic staff of higher education institutions (HEIs) towards using AI for both academic and research purposes. To attain the goal, there was designed a questionnaire, which was distributed to members of academic staff of different biological genders and ages from 10 European countries. Irrespective of biological gender, age, or country, responses were similar. First, academic staff emphasized the importance of having AI-related regulations at HEIs. Second, academic staff were positive about using AI for information searchers and preparation of teaching materials. Third, academic staff were concerned about AI-related plagiarism issues, which is why they were reluctant to approve the AI use for research and thesis writing. Fourth, slightly more than 40% of the respondents indicated the use of AI. This points to the lack of AI skills among academic staff, which was further supported by a set of basic purposes for which AI was claimed to have been used. One implication of this research relates to the organization of the study process. Managers of HEIs should introduce institutionalized training in AI for academic and research purposes for academic staff to promote digital equality. Another implication of the study relates to the areas of AI training for academic staff. It should cover the topics of AI for the design of teaching materials, formative and summative assessment, and plagiarism check.

Background: Infectious disease outbreaks are common in sub-Saharan Africa (SSA). Consequently, integrated public health surveillance has become increasingly essential for the region. Health surveillance systems enable early detection and monitoring of emerging and re-emerging disease outbreaks, thus informing preparedness and response measures. However, complex and intertwined factors obstruct a successful integrated public health surveillance in SSA, with dire consequences. Objectives: The objective of this article was to establish how big data analytics can be used to enhance integrated infectious disease surveillance and response in SSA. Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to identify and select relevant articles. A total of 10 studies that addressed the article’s objective were selected. Results: Findings reveal several barriers to the application of big data analytics for public health surveillance in SSA. These include the absence of regulatory and data governance frameworks for big data management in healthcare, disparities in digital health infrastructure across SSA’s healthcare systems, and the digital and analytical skills required for data capture and interpretation. The development of regulatory frameworks is essential for the ethical application of analytical technologies such as artificial intelligence. Conclusion: This article’s contributions emphasise the need for comprehensive strategies for the application of big data analytics for public health surveillance, as well as addressing barriers to its successful application by highlighting the requirements for an integrated infectious disease surveillance and response system in SSA. Contribution: The article contributes to the body of knowledge on the interplay between the public health space and digital health interventions by emphasising the beneficial applications of big data analytics for surveillance and response to address emerging and re-emerging infectious disease outbreaks in the health systems of sub-Saharan Africa.

Background: With the rise of noncommunicable diseases (NCDs) in sub-Saharan Africa (SSA), the concept of digital self-management presents great opportunities for relieving some of the burdens healthcare systems face. However, for this to be realised, effective use of digital health in self-management and assessment is essential.Objective: The objective of this scoping review was to identify social determinants and cognitive factors with potential influence on digital health use in self-management of chronic medical conditions associated with NCDs in SSA.Method: The 5-stage scoping review framework was used to search, identify, and filter publications over a 10-year period from two major databases, Google Scholar and Pubmed. Based on the inclusion criteria, a total of 12 documents were chosen for analysis.Results: Findings reveal that social determinants such as cultural values and societal practices demand a rethinking of how digital health for self-management of chronic diseases are designed and developed for use in SSA, whereas a cognitive factor such as self-efficacy is central in digital health use in self-management of chronic conditions, particularly in areas like adherence to medication, diet and exercise programmes.Conclusion: Owing to the unique characteristics of digital health users in SSA, technologies and content (particularly those for self-management of chronic diseases) should be tailored to the diverse needs of the population. It is through this that the region can fully benefit from the potential of digital health use in self-management of chronic diseases associated with NCDs.