ArticleFrontiers in psychology2023
Quantifying the efficacy of an automated facial coding software using videos of parents.
Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Children's affect: Automated coding, context effects, relations with maternal affect, and heritability.Child development · 2026Article
- Article
- Mismatching Expressions: Spatiotemporal and Kinematic Differences in Autistic and Non-Autistic Facial Expressions.Autism research : official journal of the International Society for Autism Research · 2026Article
- Evaluating the robustness of specialized and general-purpose facial expression recognition systems across varied scenarios.Frontiers in artificial intelligence · 2026Article
- duet: An R package for dyadic analysis of motion data generated by OpenPose.Behavior research methods · 2025Article
- Application of Artificial Intelligence Software to Identify Emotions of Lung Cancer Patients in Preoperative Health Education: A Cross-Sectional Study.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Introduction: This work explores the use of an automated facial coding software - FaceReader - as an alternative and/or complementary method to manual coding. Methods: We used videos of parents (fathers, Results: We found that the automated facial detection rate was low (25.2% for fathers, 24.6% for mothers) compared to manual coding, and discuss some potential explanations for this (e.g., poor lighting and facial occlusion). Our logistic regression analyses found that Surprise and Positive expressions had strong predictive capabilities, whilst Negative expressions performed poorly. Mothers' faces were more important for predicting Positive and Neutral expressions, whilst fathers' faces were more important in predicting Negative and Surprise expressions. Discussion: We discuss the implications of our findings in the context of future automated facial coding studies, and we emphasise the need to consider gender-specific influences in automated facial coding research.
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Registered trials
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.