ArticleSchizophrenia research. Cognition2021
Computational methods for integrative evaluation of confidence, accuracy, and reaction time in facial affect recognition in schizophrenia.
Article in Schizophrenia research. Cognition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of artificial intelligence and psychosocial functioning in psychosis: a systematic review and meta-analysis.Frontiers in psychiatry · 2025Pooled it
- The cognitive-behavioral missing link in myotonic dystrophy type 1: Rethinking social cognition assessment.Journal of neuromuscular diseases · 2026Article
- Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.Translational psychiatry · 2026Article
- Dynamics of task-based confidence in schizophrenia using seasonal decomposition approach.Schizophrenia research. Cognition · 2023Article
- Automatic Detection of Cognitive Impairment with Virtual Reality.Sensors (Basel, Switzerland) · 2023Article
- Revisiting how People with Schizophrenia Spend Their Days: Associations of lifetime milestone Achievements with Daily Activities examined with Ecological Momentary Assessment.Psychiatry research communications · 2022Article
- Mobile facial affect recognition and real-time social experiences in serious mental illness.Schizophrenia research. Cognition · 2022Article
- Brief battery of the Social Cognition Psychometric Evaluation study (BB-SCOPE): Development and validation in schizophrenia spectrum disorders.Journal of psychiatric research · 2022Article
- Using a Meta-cognitive Wisconsin Card Sorting Test to measure introspective accuracy and biases in schizophrenia and bipolar disorder.Journal of psychiatric research · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
People with schizophrenia (SZ) process emotions less accurately than do healthy comparators (HC), and emotion recognition have expanded beyond accuracy to performance variables like reaction time (RT) and confidence. These domains are typically evaluated independently, but complex inter-relationships can be evaluated through machine learning at an item-by-item level. Using a mix of ranking and machine learning tools, we investigated item-by-item discrimination of facial affect with two emotion recognition tests (BLERT and ER-40) between SZ and HC. The best performing multi-domain model for ER40 had a large effect size in differentiating SZ and HC (d = 1.24) compared to a standard comparison of accuracy alone (d = 0.48); smaller increments in effect sizes were evident for the BLERT (d = 0.87 vs. d = 0.58). Almost half of the selected items were confidence ratings. Within SZ, machine learning models with ER40 (generally accuracy and reaction time) items predicted severity of depression and overconfidence in social cognitive ability, but not psychotic symptoms. Pending independent replication, the results support machine learning, and the inclusion of confidence ratings, in characterizing the social cognitive deficits in SZ. This moderate-sized study (
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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.