Cognitive Demands and Bias: Challenges Facing Clinical Competency Committees

Critical thinking is a cognitive process with several attributes. The attributes of critical thinking include the following:

According to obedience research, we may harm others under the forceful pressures of an authority figure (Milgram, 1974). How about if the inappropriate orders were delivered with less force? The increasing interdependence between nurses and physicians compelled Hofling and his colleagues to explore nurses’ reactions to a potentially harmful medical request made by the perceived authority figure, the doctor (Hofling, Brotzman, Dalrymple, Graves, & Pierce, 1966). In this situation,...

Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...

Resolving an ethical dilemma in healthcare involves a systematic approach that considers every aspect of the issue, respecting both the patient's needs and values and the healthcare professional's ethical obligations. Here are potential steps to resolve an ethical dilemma:

Cognitive bias results from limitations in thinking and information processing, leading to systematic errors in judgment. Conversely, motivational bias stems from personal desires or emotions, causing distortions in perception to align with self-interest. Motivational bias influences how individuals perceive and attribute causes to events, often shaped by personal needs, goals, and self-esteem preservation. This bias can distort judgment, leading to inaccurate assessments of success, failure,...

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is: