Rationale: Extensive research has shown that implicit trait inferences from facial appearance can bias everyday life in a pervasive way, influencing our decisions in different social contexts such as mate choice, political vote and criminal sentence. In situations characterized by time pressure and scant information, decisions based on inferences from facial appearance may have particularly critical and serious consequences, such as in emergency healthcare. No studies today have investigated this aspect in an actual emergency. Objective: The aim of the present study was to go beyond this gap and to determine whether implicit inferences from patients’ facial appearance could be predictive of disparities in clinical evaluations and priority of treatment. Methods: In total, 183 cases of patients were evaluated by independent judges at zero acquaintance on the basis of different implicit facial appearance-based inferences, including trustworthiness and distress. Color-based priority code (White, Green, or Yellow) attributed by the triage nurse at the end of the registration process were recorded. Results: Our results showed that more trustworthy- and distressed- looking patients' faces have been associated with a higher priority code. Conclusions: The present study shows that specific facial appearance-based inferences influence the attribution of priority code in healthcare that require quick decisions based on scarce clinical information such as in emergency. These results suggest the importance to bring to the attention of the healthcare professionals’ the possibility of being victims of implicit inferences, and prompt to design educational interventions capable to increase their awareness of this bias in clinical evaluation.

Judging health care priority in emergency situations: Patient facial appearance matters / Bagnis, A., Caffo, E., Cipolli, C. , De Palma, A., Farina, G., Mattarozzi, K.. - In: SOCIAL SCIENCE & MEDICINE. - ISSN 0277-9536. - ELETTRONICO. - 260:(2020), pp. 1-6. [10.1016/j.socscimed.2020.113180]

Judging health care priority in emergency situations: Patient facial appearance matters

Bagnis A.;Cipolli C.;G. Mattarozzi
2020

Abstract

Rationale: Extensive research has shown that implicit trait inferences from facial appearance can bias everyday life in a pervasive way, influencing our decisions in different social contexts such as mate choice, political vote and criminal sentence. In situations characterized by time pressure and scant information, decisions based on inferences from facial appearance may have particularly critical and serious consequences, such as in emergency healthcare. No studies today have investigated this aspect in an actual emergency. Objective: The aim of the present study was to go beyond this gap and to determine whether implicit inferences from patients’ facial appearance could be predictive of disparities in clinical evaluations and priority of treatment. Methods: In total, 183 cases of patients were evaluated by independent judges at zero acquaintance on the basis of different implicit facial appearance-based inferences, including trustworthiness and distress. Color-based priority code (White, Green, or Yellow) attributed by the triage nurse at the end of the registration process were recorded. Results: Our results showed that more trustworthy- and distressed- looking patients' faces have been associated with a higher priority code. Conclusions: The present study shows that specific facial appearance-based inferences influence the attribution of priority code in healthcare that require quick decisions based on scarce clinical information such as in emergency. These results suggest the importance to bring to the attention of the healthcare professionals’ the possibility of being victims of implicit inferences, and prompt to design educational interventions capable to increase their awareness of this bias in clinical evaluation.
2020
Judging health care priority in emergency situations: Patient facial appearance matters / Bagnis, A., Caffo, E., Cipolli, C. , De Palma, A., Farina, G., Mattarozzi, K.. - In: SOCIAL SCIENCE & MEDICINE. - ISSN 0277-9536. - ELETTRONICO. - 260:(2020), pp. 1-6. [10.1016/j.socscimed.2020.113180]
Bagnis, A., Caffo, E., Cipolli, C. , De Palma, A., Farina, G., Mattarozzi, K.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/777409
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