Lye Detection Importance and Techniques for Emergency Medicine Practitioners

Mohammad Zarenezhad

Lye Detection Importance and Techniques for Emergency Medicine Practitioners

Authors

Mohammad Zarenezhad Legal Medicine Research Center, Legal Medicine Organization, Tehran, Iran.

Keywords:

Lye Detection, deception, patient fraud, pathological lying, emergency medicine

Abstract

Background: Detecting deception is a necessary task for emergency medicine practitioners in addressing the patient's embarrassment of diseases, patient fraud, exaggeration of the symptoms, potential misdiagnoses, and overuse of medical resources.

Methods: This study reviews the literature on lie detection for medical practitioners, particularly in emergency rooms (ERs), using a narrative review method in databases of PubMed, Science Direct, Web of Science, and the search engine Google Scholar with no publication time limitations.

Results: Although not widely used in healthcare, polygraph tests measure physiological responses like heart rate, blood pressure, and respiratory rate, which can reflect stress or potential deception. In medical settings, observing various cues can help to evaluate patients' truthfulness or emotional state. Body language, including facial expressions and gestures, may show anxiety or deception. Lack of eye contact and excessive blinking might be associated with stress. Verbal cues, such as inconsistencies in a patient's narrative or the inclusion of unusual details, can raise suspicions about the accuracy of their statements. Statement analysis is used to examine the language used in a patient's statements, including details, pronouns, and tense. These methods are not present in the curriculums of education of most physicians. The Cognitive Load (CL) theory or reality monitoring (RM) model could be embedded in such educational activities.

Conclusion: While these observational and analytical techniques are tools that can be practiced in ER, they should be applied judiciously, considering individual differences, to ensure an accurate interpretation of patients' communication cues in a medical setting.‎

Declarations:

Funding: None.

Data availability: None.

Conflicts of interest: None.

Author contributions: MZ contributed to all stages of the work.

Acknowledgments: The ChatGPT was utilized for grammatical revisions; while AI written text was supervised by MZ.

Ethical considerations: Not applicable.

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Lye Detection Importance and Techniques for Emergency Medicine Practitioners