Introduction: Advances in information and communication technology (ICT) and post-COVID-19 tectonic changes in healthcare delivery have made it possible for cancer survivors to obtain disease-related information for remote management online rather than through healthcare providers. To comprehend and evaluate health information, digital literacy is crucial. Objectives: This study examined cancer survivors’ information-seeking behaviour, information sources, digital health literacy, and digital trends, as well as potential determinants of e-health information receptivity and online resource use. Methods: A national 30-item cross-sectional survey using a representative random sample of cancer survivors from Jordan’s cancer registry was conducted. Chi-square tests established categorical variable relationships. Using the mean and standard deviation, we calculated the Likert scale’s ordinal data average. A p-value < 0.05 was statistically significant. Logistic regression identified predictors of interest in late-trajectory information acquisition and use of e-health platforms (apps, portals) for cancer self-management. Results: Lower digital literacy and electronic searching were associated with older age and lower income, education, and employment status (p ≤ 0.001). Digital literacy independently predicted m-health app use for remote management and interest in cancer supportive care information. Digitally literate survivors preferred the use of digital platforms (p ≤ 0.001). Information acquisition barriers included “reliability” (26%, n = 25) and “health information trustworthiness” (16.2%, n = 25). Following treatment completion, Internet-seeking behaviour decreased significantly when compared to the early cancer trajectory. Conclusion: Our findings imply that Jordanian cancer survivors’ low digital literacy may hinder information acquisition and technology-enabled cancer care. Digital interventions for cancer survivors should be adaptable to varying levels of digital health literacy. Healthcare policymakers should recognise digital inequities and devise focused initiatives to bridge the digital divide while responding to the urgent need to digitalise cancer care delivery.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Background: The integration of Artificial Intelligence (AI) technology in cancer care has gained unprecedented global attention over the past few decades. This has impacted the way that cancer care is practiced and delivered across settings. The purpose of this study was to explore the perspectives and experiences of healthcare professionals (HCPs) on cancer treatment and the need for AI. This study is a part of the INCISIVE European Union H2020 project's development of user requirements, which aims to fully explore the potential of AI-based cancer imaging technologies. Methods: A mixed-methods research design was employed. HCPs participating in cancer care in the UK, Greece, Italy, Spain, Cyprus, and Serbia were first surveyed anonymously online. Twenty-seven HCPs then participated in semi-structured interviews. Appropriate statistical method was adopted to report the survey results by using SPSS. The interviews were audio recorded, verbatim transcribed, and then thematically analysed supported by NVIVO. Results: The survey drew responses from 95 HCPs. The occurrence of diagnostic delay was reported by 56% (n = 28/50) for breast cancer, 64% (n = 27/42) for lung cancer, 76% (n = 34/45) for colorectal cancer and 42% (n = 16/38) for prostate cancer. A proportion of participants reported the occurrence of false positives in the accuracy of the current imaging techniques used: 64% (n = 32/50) reported this for breast cancer, 60% (n = 25/42) for lung cancer, 51% (n = 23/45) for colorectal cancer and 45% (n = 17/38) for prostate cancer. All participants agreed that the use of technology would enhance the care pathway for cancer patients. Despite the positive perspectives toward AI, certain limitations were also recorded. The majority (73%) of respondents (n = 69/95) reported they had never utilised technology in the care pathway which necessitates the need for education and training in the qualitative finding; compared to 27% (n = 26/95) who had and were still using it. Most, 89% of respondents (n = 85/95) said they would be opened to providing AI-based services in the future to improve medical imaging for cancer care. Interviews with HCPs revealed lack of widespread preparedness for AI in oncology, several barriers to introducing AI, and a need for education and training. Provision of AI training, increasing public awareness of AI, using evidence-based technology, and developing AI based interventions that will not replace HCPs were some of the recommendations. Conclusion: HCPs reported favourable opinions of AI-based cancer imaging technologies and noted a number of care pathway concerns where AI can be useful. For the future design and execution of the INCISIVE project and other comparable AI-based projects, the characteristics and recommendations offered in the current research can serve as a reference.

Background: Recently, continuous administration of piperacillin-tazobactam has been proposed as a valuable alternative to traditional intermittent administration especially in critically ill patients. However, antibiotic dosing remains a challenge for clinicians as antibiotic dosing regimens are usually determined in non-critically ill hospitalized adult patients. The aim was to conduct a systematic review to identify and highlight studies comparing clinical outcomes of piperacillin tazobactam dosing regimens, continuous/prolonged infusion vs intermittent infusion in critically ill patients. Meta-analyses were performed to assess the overall effect of dosing regimen on clinical efficacy. Methods: Studies were identified systematically through searches of PubMed and Science Direct, in compliance with PRISMA guidelines. Following the systematic literature review, meta-analyses were performed using Review Manager. Results: Twenty-three studies were included in the analysis involving 3828 critically ill adult participants in total (continuous/prolonged infusion = 2197 and intermittent infusion = 1631) from geographically diverse regions. Continuous/prolonged resulted in significantly: higher clinical cure rates (Odds Ratio 1.56, 95% Confidence Interval 1.28–1.90, P = 0 .0001), lower mortality rates (Odds Ratio 0.68, 95% Confidence Interval 0.55–0.84, P = 0 .0003), higher microbiological success rates (Odds Ratio 1.52, 95% Confidence Interval 1.10–2.11, P = 0.01) and decreasing the length of hospital stay (Mean Difference − 1.27, 95% Confidence Interval − 2.45—0.08, P = 0.04) in critically ill patients. Conclusion: Results from this study show that there is a significant level of evidence that clinical outcome in critically ill patients is improved in patients receiving piperacillin-tazobactam via continuous/prolonged infusion. However, more rigorous scientific studies in critically ill patients are warranted to reach a sufficient level of evidence and promote further implementation of C/PI as a dosing strategy.

Finding new ways to cost-effectively facilitate population screening and improve cancer diagnoses at an early stage supported by data-driven AI models provides unprecedented opportunities to reduce cancer related mortality. This work presents the INCISIVE project initiative towards enhancing AI solutions for health imaging by unifying, harmonizing, and securely sharing scattered cancer-related data to ensure large datasets which are critically needed to develop and evaluate trustworthy AI models. The adopted solutions of the INCISIVE project have been outlined in terms of data collection, harmonization, data sharing, and federated data storage in compliance with legal, ethical, and FAIR principles. Experiences and examples feature breast cancer data integration and mammography collection, indicating the current progress, challenges, and future directions.