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Drugs and Alcohol: Spotlight on Substance Misuse Training
No full textAims of the research project was to investigate the health and social care undergraduate students’ knowledge and perceptions about drugs and alcohol, including Novel Psychoactive Substances (NPSs) and Performance and Image Enhancing Drugs (PIEDs), in relation to their future professional roles. Ethical approval was granted by Middlesex University London by the university ethics committee
Impact of Interactive Presence and Self-Efficacy on e-learning Effectiveness
Full text linkAlthough many scholars have argued for a positive perception of learners towards online learning, there are some who have argued that some students, depending upon their demographic or cultural or psychological factors, will still prefer traditional face to face methods because such interaction is contextual and offer a different kind of social interaction. Studies from these scholars have attributed various causes like; lack of interactions with lecturers, co-learners, media, feeling isolated in online, lack of human touch, lost immediacy or spontaneity of actors, technical inability, low self-efficacy, and habit of using a platform for downloading uploading only. Thus, there is a need of research in the UK to establish clear antecedents of effective blended learning. Thus, this research will review ‘Learners’ perceptions on their motives, missing interactive presence & self-efficacy and their impact on perceived learning effectiveness in online learning environment moderated by cultural and other demographic factors’.
The research paper reviews a range of studies and proposes a range of assertions and a conceptual model of enhancing learning in the blended learning environment. The research has obvious theoretical and practical applications in a blended learning environment
Study Protocol: Evaluating artificial intelligence-driven stress echocardiography analysis system (EASE study): mixed method study.
No full textIntroduction
The use and value of Artificial Intelligence (AI)-driven tools and techniques are under investigation in detecting coronary artery disease (CAD). EchoGo Pro is a patented AI-driven stress echocardiography (SE) analysis system produced by Ultromics Ltd. (henceforth Ultromics) to support clinicians in detecting cardiac ischaemia and potential CAD. This manuscript presents the research protocol for a field study to independently evaluate the accuracy, acceptability, implementation barriers, users' experience and willingness to pay, cost-effectiveness, and value of EchoGo Pro.
Methods and analysis
‘Evaluating AI-driven stress echocardiography analysis system’ (EASE) study is a mixed-method evaluation, which will be conducted in 5 work packages (WPs). In WP1, we will examine the diagnostic accuracy by comparing test reports generated by EchoGo Pro and 3 manual raters. In WP2, we will focus on interviewing clinicians, innovation/transformation staff, and patients within the NHS, and staff within Ultromics, to assess the acceptability of this technology. In this WP, we will determine convergence and divergence between EchoGo Pro recommendations and cardiologists’ interpretations and will assess what profile of cases are linked with convergence and divergence between EchoGo Pro recommendations and cardiologists’ interpretations and how these link to outcomes. In WP4, we will conduct a quantitative cross-sectional survey of trust in AI tools applied to cardiac care settings among clinicians, healthcare commissioners, and the general public. Lastly, in WP5, we will estimate the cost of deploying the EchoGo Pro technology, cost-effectiveness and willingness to pay of cardiologists, healthcare commissioners and the general public. The results of this evaluation will support evidence-informed decision-making around the widespread adoption of EchoGo Pro and similar technologies in the NHS and other health systems.
Ethics approval and dissemination
This research has been approved by the NHS Health Research Authority (IRAS No: 315284) and the London South Bank University Ethics Panel (ETH2223-0164). Alongside journal publications, we will disseminate study methods and findings in conferences, seminars, and social media. We will produce additional outputs in appropriate forms, e.g., research summaries and policy briefs, for diverse audiences in NHS.
Strengths and limitations of this study
- The main strength of this study lies in its mixed-method approach to evaluation, which offers comprehensive assessment, data triangulation, and increased validity of, and confidence in, findings.
- The mixed-method approach will yield diverse forms of empirical evidence, financial evidence, and stakeholder evidence.
- By measuring willingness to pay from different users, this study will inform decisions around investment in healthcare AI applications.
- One limitation is that the impact of this AI application at the health system level, in terms of improved outcomes or quality of care, will not be measured in this study