Evidence map›Paper›PMID 40043150›Full record

ArticleSchizophrenia bulletin2025

Capturing Motor Signs in Psychosis: How the New Technologies Can Improve Assessment and Treatment?

Juliette Lozano-Goupil, Vijay A Mittal

Abstract readEditorial
In one paragraph

Article in Schizophrenia bulletin, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
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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

2 authors.

Juliette Lozano-GoupilDepartment of Psychology, Northwestern University, Evanston, IL 60208, United States.ORCID 0000-0001-5919-7045
Vijay A MittalDepartment of Psychology, Northwestern University, Evanston, IL 60208, United States.ORCID 0000-0001-9017-5119

Funding

NIMH NIH HHS R01 MH120088 and R01 MH134369
6 · The paper itself

Abstract

Motor signs are critical features of psychosis that remain underutilized in clinical practice. These signs, including social motor behaviors, mechanistically relevant motor signs, and other motor abnormalities, have demonstrated potential as biomarkers for early detection and intervention. However, their application in clinical settings remains limited due to challenges such as cost, accessibility, and integration into clinical workflows. Recent advancements in related research fields, such as Human Movement Sciences and Affective Computing, offer promising solutions, enabling scalable and precise measurement of patients motor signs. In this editorial, we explore the spectrum of motor signs and highlight the evolving role of motor assessments in psychosis research. By examining traditional assessment methods alongside alternative and innovative tools, we underscore the potential of leveraging technology and methodology to bridge the gap between research and clinical application, ultimately advancing personalized care and improving outcomes.

Indexed as

Movement DisordersPsychotic DisordersSchizophreniaHumansmotor signsnew technologiespsychosis

Identifiers

PMID40043150
PMCPMC12236321

What OpenQuestion holds

Textmetadata
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.