The Clinical Researcher Journey in the Artificial Intelligence Era: The PAC-MAN’s Challenge

Abstract

Artificial intelligence (AI) is a powerful tool that can assist researchers and clinicians in various settings. However, like any technology, it must be used with caution and awareness as there are numerous potential pitfalls. To provide a creative analogy, we have likened research to the PAC-MAN classic arcade video game. Just as the protagonist of the game is constantly seeking data, researchers are constantly seeking information that must be acquired and managed within the constraints of the research rules. In our analogy, the obstacles that researchers face are represented by “ghosts”, which symbolize major ethical concerns, low-quality data, legal issues, and educational challenges. In short, clinical researchers need to meticulously collect and analyze data from various sources, often navigating through intricate and nuanced challenges to ensure that the data they obtain are both precise and pertinent to their research inquiry. Reflecting on this analogy can foster a deeper comprehension of the significance of employing AI and other powerful technologies with heightened awareness and attentiveness.

Maladaptive personality traits are associated with burnout risk in Italian anesthesiologists and intensivists: a secondary analysis from a cross-sectional study

“…Some examples of possible interventions are as follows: Measuring burnout levels of anesthesiologists and intensivists periodically by the occupational medicine service in collaboration with a team of psychologists Following the measurements of burnout levels, planning interventions within the anesthesia unit to redistribute workloads, make tasks more varied, and resolve conflicts between colleagues Implementing relaxation techniques, such as mindfulness, and establishing a psychological support program (through voluntary interviews) with a team of psychologists, also based on personality traits: increase coping strategies and resilience capacity Reducing the number of consecutive hours of work ensuring adequate rest Rethinking the career system, ensuring horizontal progression with increasing responsibilities, based on areas of expertise with particular reference to new technological developments in anesthesia, critical care, and pain medicine [ 38 – 40 ] Reducing medical-legal litigation which is a source of work-related stress Training anesthesia chiefs to manage conflicts within the team and to manage, if not actually enhance, the difficult human resources …”

“…Rethinking the career system, ensuring horizontal progression with increasing responsibilities, based on areas of expertise with particular reference to new technological developments in anesthesia, critical care, and pain medicine [ 38 – 40 ]…”

Envisioning gamification in anesthesia, pain management, and critical care: basic principles, integration of artificial intelligence, and simulation strategies

“…The convergence of gamification and AI represents a compelling synergy that has the potential to reshape various aspects of research and healthcare delivery. For example, using a creative analogy, Bignami et al [ 31 ] drew a comparison between the role of a clinical researcher and the iconic PAC-MAN video game character. Just as PAC-MAN tirelessly devours dots and energy pills, the clinical researcher relentlessly seeks knowledge and pursues significant scientific goals.…”

Scientific writing with artificial intelligence: key considerations and alerts

“…Checking something twice is often done to ensure accuracy, avoid errors, or maintain quality. In the AI scenario the terms "garbage in, garbage out" (GIGO) refer to the concept that the quality of output or results from a system is directly dependent on the quality of the input or data provided to it [7]. It suggests that if you feed a system with faulty, inaccurate, or low-quality data, the output or results produced by the system will also be flawed, inaccurate, or of low quality.…”

“…It serves as a reminder that even the most advanced algorithms or technologies can only work with the information provided to them and are not capable of compensating for poorquality or flawed data. Consequently, by ensuring that high-quality data is fed into a system, we increase the likelihood of obtaining meaningful and trustworthy results [7,8].…”