ReviewBiological psychiatry global open science2023
From Computation to Clinic.
Review in Biological psychiatry global open science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Prior Expectations of Volatility Following Psychotherapy for Delusions: A Randomized Clinical Trial.JAMA network open · 2025Trial
- Threading the Needle: Practical Considerations for Merging Theory-Driven Computational Psychiatry With Data-Driven Analytics to Enhance Precision Health at Scale.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Review
- Neurocomputational mechanisms underlying the distinct motivational influences of reward and punishment on cognitive control.bioRxiv : the preprint server for biology · 2025Article
- Negative affectivity drivers of impulsivity in opioid use disorder.Nature reviews. Psychology · 2025Article
- Signatures of Perseveration and Heuristic-Based Directed Exploration in Two-Step Sequential Decision Task Behaviour.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Does the reliability of computational models truly improve with hierarchical modeling? Some recommendations and considerations for the assessment of model parameter reliability : Reliability of computational model parameters.Psychonomic bulletin & review · 2024Review
- Neural and Computational Mechanisms of Motivation and Decision-making.Journal of cognitive neuroscience · 2024Article
- Bridging minds and policies: supporting early career researchers in translating computational psychiatry research.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Article
- Cognitive Control in Schizophrenia: Advances in Computational Approaches.Current directions in psychological science · 2024Article
- Test-retest reliability of behavioral and computational measures of advice taking under volatility.PloS one · 2024Article
- Listening to the Data: Computational Approaches to Addiction and Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Review
- Self-judgment dissected: A computational modeling analysis of self-referential processing and its relationship to trait mindfulness facets and depression symptoms.Cognitive, affective & behavioral neuroscience · 2023Article
- Computational models of subjective feelings in psychiatry.Neuroscience and biobehavioral reviews · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Theory-driven and data-driven computational approaches to psychiatry have enormous potential for elucidating mechanism of disease and providing translational linkages between basic science findings and the clinic. These approaches have already demonstrated utility in providing clinically relevant understanding, primarily via back translation from clinic to computation, revealing how specific disorders or symptoms map onto specific computational processes. Nonetheless, forward translation, from computation to clinic, remains rare. In addition, consensus regarding specific barriers to forward translation-and on the best strategies to overcome these barriers-is limited. This perspective review brings together expert basic and computationally trained researchers and clinicians to 1) identify challenges specific to preclinical model systems and clinical translation of computational models of cognition and affect, and 2) discuss practical approaches to overcoming these challenges. In doing so, we highlight recent evidence for the ability of computational approaches to predict treatment responses in psychiatric disorders and discuss considerations for maximizing the clinical relevance of such models (e.g., via longitudinal testing) and the likelihood of stakeholder adoption (e.g., via cost-effectiveness analyses).
Indexed as
Identifiers
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.