Ch 4: Cognitive Science & Informatics

• Cognitive science is a multidisciplinary field studying the mind and its role in intelligent behavior, combining psychology, AI, neuroscience, linguistics, anthropology, and philosophy.

Introduction

• From an informatics perspective, cognitive science helps analyze and model how humans perform complex tasks in technology-driven environments.
• Basic research in cognitive science focuses on fundamental aspects of cognition, including attention, memory, reasoning, and language acquisition.
• Applied research focuses on creating and evaluating cognitive artifacts, tools that enhance human abilities to perceive, remember, and solve problems more effectively.
• Cognitive artifacts include software interfaces, medical devices, and decision-support systems.
• Smartphones are cognitive artifacts that help store and retrieve information, offloading the need to remember everything and reducing mental effort.
• Cognitive science overlaps with human-computer interaction (HCI) and human factors, aiming to design systems that are easy to use and align with human cognitive abilities.

Cognitive Science and Biomedical Informatics

• Cognitive science plays a crucial role in designing and improving healthcare information systems.
• Cognitive science helps to understand how clinicians interact with technology.
• Informatics looks at how medical decisions are made and how to effectively train healthcare professionals and patients.
• Informatics examines ways to create safer work environments.
• Theories about human memory and problem-solving guide the design of medical decision-support systems.
• Research on text comprehension improves how clinicians interpret medical records or guidelines.
• Translating cognitive science research findings into practical solutions requires careful consideration of how humans interact with technology in complex real-world settings like hospitals.

Behaviorism vs. Cognitive Science

• Behaviorism, which dominated psychology in the early 20th century, focuses on observable actions and avoids studying mental processes.
• By the 1950s, researchers began to question the behaviorist approach.
• Advances in computer science, information theory, and artificial intelligence shifted the focus to mental processes and information processing.
• Cognitive science emerged as a response to behaviorism, emphasizing internal mental states like memory and reasoning.
• The "computer metaphor" views the mind as an information-processing system, similar to how computers manipulate data.

Key Developments in Cognitive Science

• Early problem-solving research used tasks like the Tower of Hanoi to understand how people solve problems and develop models of human cognition.
• Protocol analysis involves participants "thinking aloud" while solving problems, providing insights into their thought processes.
• Cognitive science has shifted from studying artificial tasks to real-world domains like medical diagnosis and physics problem-solving.

Human Information Processing

• Cognitive science explores how the mind processes and stores information.
• Working memory holds information temporarily while performing tasks but has limited capacity, making multitasking challenging.
• Long-term memory is a vast store of knowledge and experiences.
• Experts in medicine have highly organized long-term memory.
• Cognitive architectures, like ACT-R, simulate human task performance by modeling memory, attention, and problem-solving.
• These models help design systems that align with human cognitive limitations.

Knowledge Organization

• Experts organize knowledge differently than novices.
• Experts focus on relevant propositions, the basic units of meaning in language, while novices may get bogged down by irrelevant details.
• Schemata are mental frameworks that help to interpret information.
• An example of a schema is a doctor using a schema for "heart attack" to quickly recognize symptoms like chest pain and shortness of breath.
• Mental models are internal representations of how systems work.
• An example of a mental model is a clinician having a mental model of how blood flows through the heart, which helps them diagnose and treat patients.

Medical Cognition

• Experts in medicine outperform novices in pattern recognition, forward reasoning (data-driven), and error detection/recovery.
• Experts quickly recognize patterns in patient data, allowing them to diagnose conditions more efficiently.
• Experts use patient data to guide their reasoning, moving from symptoms to diagnosis in a data-driven manner, in contrast to novices who often start with hypotheses.
• Experts are better at spotting and correcting their own mistakes, especially in high-pressure environments like intensive care units.
• Expertise involves how knowledge is organized and applied.
• A cardiologist’s deep understanding of heart conditions allows them to make faster, more accurate diagnoses than a general practitioner.
• Intermediate learners sometimes perform worse than novices due to reorganizing their knowledge, leading to confusion and errors.
• With practice and experience, intermediate learners develop the structured knowledge needed to perform like experts.

Human Factors Research and Patient Safety

• Human factors research focuses on designing systems that are safe, efficient, and easy to use.
• In healthcare, human factors involves understanding how clinicians interact with technology and its effect on patient safety.
• Systems should align with users’ mental models, such as a well-designed electronic health record (EHR) that helps doctors easily find and interpret patient data.
• Systems should minimize cognitive load, as overloading working memory can lead to errors, especially in high-stress environments.

Patient Safety

• Slips are errors in executing a correct plan, while mistakes are errors in planning.
• Latent conditions are underlying system issues, such as poor interface design or lack of training, that increase the risk of errors.

Unintended Consequences of Technology

• Usability issues of complex interfaces can confuse users, leading to mistakes such as entering incorrect dosages.
• Fragmented data can cause clinicians to miss critical details if systems don’t integrate information effectively.

Distributed Cognition

• Cognition is distributed across people, tools, and environments, as seen in team collaboration in hospitals.
• EHRs shape how clinicians think and make decisions, changing how doctors organize and process information.
• EHRs do not just store data, they act as cognitive tools.