Trial reportBiological psychiatry2019
Computational Modeling Applied to the Dot-Probe Task Yields Improved Reliability and Mechanistic Insights.
Trial report in Biological psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
What it found
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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.
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Who cites it
49 citing papers in PubMed.
- Trial
- Effects of attention bias modification for anxiety: Neurophysiological indices and moderation by symptom severity.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2023Trial
- Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.Journal of abnormal psychology · 2021Trial
- Reliability of computational versus noncomputational metrics of working memory and episodic memory in serious mental illness.Journal of psychopathology and clinical science · 2026Article
- Sleep-Related Attentional Bias in Insomnia: A Drift Diffusion Model Approach.Journal of sleep research · 2026Article
- The Role of Neurobehavioral Attention Bias on Relations between Preference for Digital Media Use and Social Anxiety Symptoms Across Adolescence.Brain and environment · 2026Article
- Attenuated learning rates for negative outcomes in substance use disorders: A replication and extension of prior longitudinal computational modeling results.Drug and alcohol dependence · 2026Article
- Neural Bases of Affect-Based Impulsivity: A Decision Neuroscience Account.Computational psychiatry (Cambridge, Mass.) · 2026Review
- Linking attention bias to youth social anxiety and depression: Insights from computational modeling of the affective Posner task.Journal of affective disorders · 2025Article
- The role of affective states in computational psychiatry.The international journal of neuropsychopharmacology · 2025Review
- Psychometrics of drift-diffusion model parameters derived from the Eriksen flanker task: Reliability and validity in two independent samples.Cognitive, affective & behavioral neuroscience · 2025Article
- No Evidence of Reliability Across 36 Variations of the Emotional Dot-Probe Task in 9,600 Participants.Clinical psychological science : a journal of the Association for Psychological Science · 2025Article
- Investigating trajectories linking social cognitive capacity, bias, and social isolation using computational modeling.Social cognitive and affective neuroscience · 2025Article
- Computational Mechanisms of Approach-Avoidance Conflict Predictively Differentiate Between Affective and Substance Use Disorders.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Attention Allocation for Dysphoric Information in Adults with Depression Symptoms Using Eye-tracking and Mouse-tracking.PloS one · 2025Article
- Reinforcement-Learning-Informed Queries Guide Behavioral Change.Clinical psychological science : a journal of the Association for Psychological Science · 2024Article
- Preference for digital media use, biobehavioral attention bias, and anxiety symptoms in adolescents.Computers in human behavior reports · 2024Article
- Individuals vary in their overt attention preference for positive images consistently across time and stimulus types.Scientific reports · 2024Article
- Normalization of Fronto-Parietal Activation by Cognitive-Behavioral Therapy in Unmedicated Pediatric Patients With Anxiety Disorders.The American journal of psychiatry · 2024Article
- Test-Retest Reliability of Two Computationally-Characterised Affective Bias Tasks.Computational psychiatry (Cambridge, Mass.) · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundBiased patterns of attention are implicated as key mechanisms across many forms of psychopathology and have given rise to automated mechanistic interventions designed to modify such attentional preferences. However, progress is substantially hindered by limitations in widely used methods to quantify attention, bias leading to imprecision of measurement.
methodsIn a sample of patients who were clinically anxious (n = 70), we applied a well-validated form of computational modeling (drift-diffusion model) to trial-level reaction time data from a two-choice "dot-probe task"-the dominant paradigm used in hundreds of attention bias studies to date-in order to model distinct components of task performance.
resultsWhile drift-diffusion model-derived attention bias indices exhibited convergent validity with previous approaches (e.g., conventional bias scores, eye tracking), our novel analytic approach yielded substantially improved split-half reliability, modestly improved test-retest reliability, and revealed novel mechanistic insights regarding neural substrates of attention bias and the impact of an automated attention retraining procedure.
conclusionsComputational modeling of attention bias task data may represent a new way forward to improve precision.
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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.