Evidence map›Paper›PMID 36884241›Full record

ArticleJAMA psychiatry2023

Studying Healthy Psychosislike Experiences to Improve Illness Prediction.

Philip R Corlett, Sonia Bansal, James M Gold

Abstract read
In one paragraph

Article in JAMA psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Philip R CorlettDepartment of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.
Sonia BansalMaryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore.
James M GoldMaryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Predictive Coding as a Framework for Understanding PsychosisR01MH112887 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI CORLETT, PHILIP, GOLD, JAMES M. · 2018 to 2022
$3.6M
5/5 CAPER: Computerized Assessment of Psychosis RiskR01MH120089 · NIMH · YALE UNIVERSITY · PI CORLETT, PHILIP, WOODS, SCOTT W · 2020 to 2024
$3.1M
1/5 CAPER: Computerized Assessment of ProdromE RiskR01MH120090 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI GOLD, JAMES M. · 2020 to 2024
$2.9M
NCATS NIH HHS UL1 TR001863NIMH NIH HHS R01 MH112887NIMH NIH HHS R01 MH120089NIMH NIH HHS R01 MH120090
6 · The paper itself

Abstract

Importance: Distinguishing delusions and hallucinations from unusual beliefs and experiences has proven challenging. Observations: The advent of neural network and generative modeling approaches to big data offers a challenge and an opportunity; healthy individuals with unusual beliefs and experiences who are not ill may raise false alarms and serve as adversarial examples to such networks. Conclusions and Relevance: Explicitly training predictive models with adversarial examples should provide clearer focus on the features most relevant to casehood, which will empower clinical research and ultimately diagnosis and treatment.

Indexed as

HallucinationsNeural Networks, ComputerHealth StatusHumans

Identifiers

PMID36884241
PMCPMC10848166

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.