ReviewBiological psychiatry2023
Computational Mechanisms of Addiction and Anxiety: A Developmental Perspective.
Review in Biological psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Detecting Gambling Addiction: How Text Mining of Customer-Operator Online Chats Reveals Behavioral Risks.Journal of gambling studies · 2026Article
- Difficult-to-Treat Anxiety: A Neurocomputational Framework.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Review
- An Active Inference Model of the Optimism Bias.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Increasing the Construct Validity of Computational Phenotypes of Mental Illness Through Active Inference and Brain Imaging.Brain sciences · 2024Review
- Ethological computational psychiatry: Challenges and opportunities.Current opinion in neurobiology · 2024Review
- A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals.Cognitive, affective & behavioral neuroscience · 2024Article
- Informing the treatment of social anxiety disorder with computational and neuroimaging data.Psychoradiology · 2024Article
- Current status, challenges and future prospects in computational psychiatry: a narrative review.Consortium psychiatricum · 2023Review
- Factors increasing the risk for food addiction in Ecuadorian students.Frontiers in psychiatry · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
A central goal of computational psychiatry is to identify systematic relationships between transdiagnostic dimensions of psychiatric symptomatology and the latent learning and decision-making computations that inform individuals' thoughts, feelings, and choices. Most psychiatric disorders emerge prior to adulthood, yet little work has extended these computational approaches to study the development of psychopathology. Here, we lay out a roadmap for future studies implementing this approach by developing empirically and theoretically informed hypotheses about how developmental changes in model-based control of action and Pavlovian learning processes may modulate vulnerability to anxiety and addiction. We highlight how insights from studies leveraging computational approaches to characterize the normative developmental trajectories of clinically relevant learning and decision-making processes may suggest promising avenues for future developmental computational psychiatry research.
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What Socratic holds
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 Socratic graph.