Promoting Well-being Among Informal Caregivers of People With HIV/AIDS in Rural Malawi: Community-Based Participatory Research Approach.

BACKGROUND: People living with HIV/AIDS and their informal caregivers (usually family members) in Malawi do not have adequate access to patient-centered care, particularly in remote rural areas of the country because of the high burden of HIV/AIDS, coupled with a fragmented and patchy health care system. Chronic conditions require self-care strategies, which are now promoted in both developed and developing contexts but are still only emerging in sub-Saharan African countries. OBJECTIVE: This study aims to explore the effects of the implementation of a short-term intervention aimed at supporting informal caregivers of people living with HIV/AIDS in Malawi in their caring role and improving their well-being. The intervention includes the dissemination of 6 health advisory messages on topics related to the management of HIV/AIDS over a period of 6 months, via the WhatsApp audio function to 94 caregivers attending peer support groups in the rural area of Namwera. METHODS: We adopted a community-based participatory research approach, whereby the health advisory messages were designed and formulated in collaboration with informal caregivers, local medical physicians, social care workers, and community chiefs and informed by prior discussions with informal caregivers. Feedback on the quality, relevance, and applicability of the messages was gathered via individual interviews with the caregivers. RESULTS: The results showed that the messages were widely disseminated beyond the support groups via word of mouth and highlighted a very high level of adoption of the advice contained in the messages by caregivers, who reported immediate (short-term) and long-term self-assessed benefits for themselves, their families, and their local communities. CONCLUSIONS: This study offers a novel perspective on how to combine community-based participatory research with a cost-effective, health-oriented informational intervention that can be implemented to support effective HIV/AIDS self-care and facilitate informal caregivers' role.

Artificial Intelligence-Based Ethical Hacking for Health Information Systems: Simulation Study.

BACKGROUND: Health information systems (HISs) are continuously targeted by hackers, who aim to bring down critical health infrastructure. This study was motivated by recent attacks on health care organizations that have resulted in the compromise of sensitive data held in HISs. Existing research on cybersecurity in the health care domain places an imbalanced focus on protecting medical devices and data. There is a lack of a systematic way to investigate how attackers may breach an HIS and access health care records. OBJECTIVE: This study aimed to provide new insights into HIS cybersecurity protection. We propose a systematic, novel, and optimized (artificial intelligence-based) ethical hacking method tailored specifically for HISs, and we compared it with the traditional unoptimized ethical hacking method. This allows researchers and practitioners to identify the points and attack pathways of possible penetration attacks on the HIS more efficiently. METHODS: In this study, we propose a novel methodological approach to ethical hacking in HISs. We implemented ethical hacking using both optimized and unoptimized methods in an experimental setting. Specifically, we set up an HIS simulation environment by implementing the open-source electronic medical record (OpenEMR) system and followed the National Institute of Standards and Technology's ethical hacking framework to launch the attacks. In the experiment, we launched 50 rounds of attacks using both unoptimized and optimized ethical hacking methods. RESULTS: Ethical hacking was successfully conducted using both optimized and unoptimized methods. The results show that the optimized ethical hacking method outperforms the unoptimized method in terms of average time used, the average success rate of exploit, the number of exploits launched, and the number of successful exploits. We were able to identify the successful attack paths and exploits that are related to remote code execution, cross-site request forgery, improper authentication, vulnerability in the Oracle Business Intelligence Publisher, an elevation of privilege vulnerability (in MediaTek), and remote access backdoor (in the web graphical user interface for the Linux Virtual Server). CONCLUSIONS: This research demonstrates systematic ethical hacking against an HIS using optimized and unoptimized methods, together with a set of penetration testing tools to identify exploits and combining them to perform ethical hacking. The findings contribute to the HIS literature, ethical hacking methodology, and mainstream artificial intelligence-based ethical hacking methods because they address some key weaknesses of these research fields. These findings also have great significance for the health care sector, as OpenEMR is widely adopted by health care organizations. Our findings offer novel insights for the protection of HISs and allow researchers to conduct further research in the HIS cybersecurity domain.

Affective temporal experiences and new work modalities: The role of Information and Communication Technologies.

As a result of the Covid-19 pandemic, new ways of working emerged, such as fully remote to hybrid work. As the restrictions with regards to the spatial dimension of work become less rigid, the temporal dimension surfaces as one of the more important aspects of work. In this study, we draw from the Negative Theology of Time to present a more nuanced understanding of how Information and Communication Technologies (ICTs) influence temporal experiences and how these shape work itself. We do this by leveraging the metaphor genre, linking our observations to existing literature, and discussing chronopathic experiences, chronotelic behaviours and uses of ICTs.

Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review.

Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to significantly improve resilience of supply chains and to facilitate more effective management of supply chain resources. Despite such potential benefits and the increase in popularity of AI and BDA in the context of supply chains, research to date is dispersed into research streams that is largely based on the publication outlet. We curate and synthesise this dispersed knowledge by conducting a systematic literature review of AI and BDA research in supply chain resilience that have been published in the Chartered Association of Business School (CABS) ranked journals between 2011 and 2021. The search strategy resulted in 522 studies, of which 23 were identified as primary papers relevant to this research. The findings advance knowledge by (i) assessing the current state of AI and BDA in supply chain literature, (ii) identifying the phases of supply chain resilience (readiness, response, recovery, adaptability) that AI and BDA have been reported to improve, and (iii) synthesising the reported benefits of AI and BDA in the context of supply chain resilience.

Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure.

The COVID-19 pandemic has had an unprecedented impact on many industry sectors, forcing many companies and particularly Small Medium Enterprises (SMEs) to fundamentally change their business models under extreme time pressure. While there are claims that technologies such as analytics can help such rapid transitions, little empirical research exists that shows if or how Business Analytics (BA) supports the adaptation or innovation of SMEs' business models, let alone within the context of extreme time pressure and turbulence. This study addresses this gap through an exemplar case, where the SME actively used location-based business analytics for rapid business model adaptation and innovation during the Covid-19 crisis. The paper contributes to existing theory by providing a set of propositions, an agenda for future research and a guide for SMEs to assess and implement their own use of analytics for business model transformation.

Appropriating Information Technology Artefacts through Trial and Error: The Case of the Tablet.

The concept of appropriation is of paramount importance for the lasting use of an Information Technology (IT) artefact following its initial adoption, and therefore its success. However, quite often, users' original expectations are negatively disconfirmed, and instead of appropriating the IT artefact, they discontinue its use. In this study we examine the use of IT artefacts following negative disconfirmation and use Grounded Theory Method techniques to analyse 136 blogposts, collected between March 2011 - July 2017, to investigate how users appropriate or reject the tablet when technology falls short of users' expectations. Our findings show that users overcome negative disconfirmation through a trial and error process. In doing so, we identify that users appropriate the tablet when the attained benefits significantly outweigh the risks or sacrifices stemming out of its use. We discuss our contribution within the context of the appropriation literature, and highlight that the success of IT lies with the user's success in identifying personal use scenarios within and across diverse contexts of use.