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Evidence for a young adult face bias in accuracy and consensus of age estimates.

07:00 EST 28th December 2018 | BioPortfolio

Summary of "Evidence for a young adult face bias in accuracy and consensus of age estimates."

Adults' face processing may be specialized for the dimensions of young adult faces. For example, young and older adults exhibit increased accuracy in normality judgments and greater agreement in attractiveness ratings for young versus older adult faces. The present study was designed to examine whether there is a similar young adult face bias in facial age estimates. In Experiment 1, we created a face age continuum by morphing an averaged young adult face with an averaged older adult face in 5% increments, for a total of 21 faces ranging from 0 to 100% old. Young and older adults estimated facial age for three stimulus age categories [young (morphs 0-30%), middle-aged (morphs 35-65%), and older adult (morphs 70-100%)]. Both age groups showed the least differentiation in age estimates for young adult faces, despite showing greater consensus across participants in estimates for young faces. In Experiment 2, young and older adults made age estimates for individual young and older adult identities. Both age groups were more accurate and showed greater consensus in age estimates for young faces. Collectively, these results provide evidence for a bias in processing young adult faces beyond that which is often observed in recognition and normality/attractiveness judgment tasks.

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This article was published in the following journal.

Name: British journal of psychology (London, England : 1953)
ISSN: 2044-8295
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Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

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The influence of study results on the chances of publication and the tendency of investigators, reviewers, and editors to submit or accept manuscripts for publication based on the direction or strength of the study findings. Publication bias has an impact on the interpretation of clinical trials and meta-analyses. Bias can be minimized by insistence by editors on high-quality research, thorough literature reviews, acknowledgement of conflicts of interest, modification of peer review practices, etc.

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