Trial reportJAMA psychiatry2020
Computational Mechanisms of Effort and Reward Decisions in Patients With Depression and Their Association With Relapse After Antidepressant Discontinuation.
Trial report in JAMA psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05866575 (Prediction of the Therapeutic Response in Depression Based on an Early Neuro-computational Modeling Assessment of Motivation), which is not on this map. Cited by 56 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.
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.
Prediction of the Therapeutic Response in Depression Based on an Early Neuro-computational Modeling Assessment of Motivation
Who cites it
56 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic models for predicting relapse or recurrence of major depressive disorder in adults.The Cochrane database of systematic reviews · 2021Pooled it
- Amygdala Reactivity, Antidepressant Discontinuation, and Relapse.JAMA psychiatry · 2024Trial
- Motivation to exert effort dynamically adapts to reward context and environmental controllability.Cognitive, affective & behavioral neuroscience · 2026Article
- Fatigue Symptoms Influence Effort-Based Decision-Making in Major Depressive Disorder.Biological psychiatry global open science · 2026Article
- Latent subdimensions of anxiety and depression differentially influence exertion of effort in pursuit of reward versus avoidance of threat.Translational psychiatry · 2026Article
- A computational model of reward learning and habits on social media.Nature communications · 2026Article
- Examining effects of effort and reward magnitude on effort-cost decision-making in people with major depressive disorder.Cognitive, affective & behavioral neuroscience · 2026Article
- Delay discounting correlates with depression but does not predict relapse after antidepressant discontinuation.Molecular psychiatry · 2026Article
- Blunted experience of pleasure, unsystematic subjective value representation, and disrupted goal-directed behaviors: an ecological momentary assessment study across mood and psychotic disorders.Schizophrenia bulletin · 2026Article
- The cognitive and motor determinants of the perception of effort.Cognitive, affective & behavioral neuroscience · 2026Article
- Shared and distinct features of common effort-based decision-making paradigms and their relation to brain structure and neuropsychiatric conditions: An integrated narrative review.Cognitive, affective & behavioral neuroscience · 2026Review
- Cognitive modeling of real-world behavior for understanding mental health.Trends in cognitive sciences · 2026Review
- 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
- Protocol for a randomized trial to predict the efficacy of cognitive and behavioral interventions for symptoms of depression.Frontiers in psychiatry · 2026Article
- Computational modeling reveals cognitive processes in simple rodent depression tests.Cell reports methods · 2025Article
- Fatigue Symptoms Influence Effort-Based Decision-Making in Major Depressive Disorder.medRxiv : the preprint server for health sciences · 2025Article
- A computational approach to understanding effort-based decision-making in depression.Psychological medicine · 2025Article
- A computational approach to understanding effort-based decision-making in depression.bioRxiv : the preprint server for biology · 2025Article
- A common alteration in effort-based decision-making in apathy, anhedonia, and late circadian rhythm.eLife · 2025Article
- Computational Phenotyping of Effort-Based Decision Making in Unmedicated Adults With Remitted Depression.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Nearly 1 in 3 patients with major depressive disorder who respond to antidepressants relapse within 6 months of treatment discontinuation. No predictors of relapse exist to guide clinical decision-making in this scenario. Objectives: To establish whether the decision to invest effort for rewards represents a persistent depression process after remission, predicts relapse after remission, and is affected by antidepressant discontinuation. Design, Setting, and Participants: This longitudinal randomized observational prognostic study in a Swiss and German university setting collected data from July 1, 2015, to January 31, 2019, from 66 healthy controls and 123 patients in remission from major depressive disorder in response to antidepressants prior to and after discontinuation. Study recruitment took place until January 2018. Exposure: Discontinuation of antidepressants. Main Outcomes and Measures: Relapse during the 6 months after discontinuation. Choice and decision times on a task requiring participants to choose how much effort to exert for various amounts of reward and the mechanisms identified through parameters of a computational model. Results: A total of 123 patients (mean [SD] age, 34.5 [11.2] years; 94 women [76%]) and 66 healthy controls (mean [SD] age, 34.6 [11.0] years; 49 women [74%]) were recruited. In the main subsample, mean (SD) decision times were slower for patients (n = 74) compared with controls (n = 34) (1.77 [0.38] seconds vs 1.61 [0.37] seconds; Cohen d = 0.52; P = .02), particularly for those who later relapsed after discontinuation of antidepressants (n = 21) compared with those who did not relapse (n = 39) (1.95 [0.40] seconds vs 1.67 [0.34] seconds; Cohen d = 0.77; P < .001). This slower decision time predicted relapse (accuracy = 0.66; P = .007). Patients invested less effort than healthy controls for rewards (F1,98 = 33.970; P < .001). Computational modeling identified a mean (SD) deviation from standard drift-diffusion models that was more prominent for patients than controls (patients, 0.67 [1.56]; controls, -0.71 [1.93]; Cohen d = 0.82; P < .001). Patients also showed higher mean (SD) effort sensitivity than controls (patients, 0.31 [0.92]; controls, -0.08 [1.03]; Cohen d = 0.51; P = .05). Relapsers differed from nonrelapsers in terms of the evidence required to make a decision for the low-effort choice (mean [SD]: relapsers, 1.36 [0.35]; nonrelapsers, 1.17 [0.26]; Cohen d = 0.65; P = .02). Group differences generally did not reach significance in the smaller replication sample (27 patients and 21 controls), but decision time prediction models from the main sample generalized to the replication sample (validation accuracy = 0.71; P = .03). Conclusions and Relevance: This study found that the decision to invest effort was associated with prospective relapse risk after antidepressant discontinuation and may represent a persistent disease process in asymptomatic remitted major depressive disorder. Markers based on effort-related decision-making could potentially inform clinical decisions associated with antidepressant discontinuation.
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