Evidence map›Paper›PMID 40822674›Full record

ArticleApplied cognitive psychology

Training Humans to Detect Children's Lies Through Their Facial Expressions.

Alison M O'Connor, Jennifer Gongola, Kaila C Bruer, Thomas D Lyon, Angela D Evans

Abstract read
In one paragraph

Article in Applied cognitive psychology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Alison M O'ConnorBrock University.
Jennifer GongolaUniversity of Southern California.
Kaila C BruerUniversity of Regina.
Thomas D LyonUniversity of Southern California.
Angela D EvansBrock University.

Funding

Children's Comprehension and Memory of Event Sequences and Its Implications for Maltreatment DisclosureR01HD101617 · NICHD · UNIVERSITY OF CALIFORNIA-IRVINE · PI KLEMFUSS, JESSICA ZOE · 2021 to 2025
$2.5M
NICHD NIH HHS R01 HD101617
6 · The paper itself

Abstract

The accurate detection of children's truthful and dishonest reports is essential as children can serve as important providers of information. Research using automated facial coding and machine learning found that children who were asked to lie about an event were more likely to look surprised when hearing the first question during an interview about said event. The present studies explored if humans can be trained to look for surprised expressions to detect children's deception. Participants made lie-detection judgments after seeing children's expressions in very brief clips. In Study 1, we compared performance across a training condition and control condition, and in Study 2 we modified the training. With training, adults could detect children's lies at above chance levels by viewing their facial expression. Detection accuracy was further improved with modified training (Study 2), but participants held a consistent lie bias. Challenges with using facial expressions to detect deceit are discussed.

Indexed as

childcuefacial expressionlie detectionsurprise

Identifiers

PMID40822674
PMCPMC12352574

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.