Evidence map›Paper›PMID 41053030›Full record

ArticleSchizophrenia (Heidelberg, Germany)2025

Shift in sex and age of individuals at a clinical high risk (CHR) for psychosis: relation to differences in recruitment methods and effect on sample characteristics.

Emily A Farina, Catalina Mourgues-Codern, Katie Stimler, Joshua Kenney, Abhishek Saxena, Hesham Mukhtar, Jean Addington, Carrie E Bearden, Kristin S Cadenhead, Tyrone D Cannon and 16 more

Abstract read
In one paragraph

Article in Schizophrenia (Heidelberg, Germany), 2025. 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. Observational
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

26 authors.

Emily A FarinaYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA. Emily.Farina@yale.edu.ORCID http://orcid.org/0000-0002-9916-8561
Catalina Mourgues-CodernYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
Katie StimlerYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
Joshua KenneyYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
Abhishek SaxenaYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.ORCID http://orcid.org/0000-0001-9825-6693
Hesham MukhtarYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.ORCID http://orcid.org/0009-0007-5298-4063
Jean AddingtonDepartment of Psychiatry, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.ORCID http://orcid.org/0000-0002-8298-0756
Carrie E BeardenDepartment of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-8516-923X
Kristin S CadenheadDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-5952-4605
Tyrone D CannonYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
Barbara CornblattDepartment of Psychiatry, Zucker Hillside Hospital, Long Island, NY, USA.
Lauren EllmanDepartment of Psychology, Temple University, Philadelphia, PA, USA.
James GoldMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Matcheri KeshavanDepartment of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston, MA, USA.
Daniel H MathalonDepartment of Psychiatry, UCSF, and SF VA Medical Center, San Francisco, CA, USA.ORCID http://orcid.org/0000-0001-6090-4974
Vijay A MittalInstitutes for Policy Research (IPR) and Innovations in Developmental Sciences (DevSci), Departments of Psychology, Psychiatry, Medical Social Sciences, Northwestern University, Evanston, IL, 60208, USA.ORCID http://orcid.org/0000-0001-9017-5119
Diana O PerkinsDepartment of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.ORCID http://orcid.org/0000-0001-9396-2206
Jason SchiffmanDepartment of Psychological Science, University of California Irvine, Irvine, CA, USA.
Steven M SilversteinCenter for Visual Science, Departments of Psychiatry, Neuroscience and Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA.ORCID http://orcid.org/0000-0002-0699-0960
Gregory P StraussDepartments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA.
William S StoneDepartment of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0003-2932-7288
Elaine F WalkerDepartments of Psychology and Psychiatry, Emory University, Atlanta, GA, USA.ORCID http://orcid.org/0000-0002-9798-8101
James WaltzMaryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-9236-3719
Philip CorlettYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-5368-1992
Albert R PowersYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.ORCID http://orcid.org/0000-0003-3057-5043
Scott W WoodsYale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-3103-5228

Funding

1/9 Predictors and Mechanisms of Conversion to PsychosisU01MH081902 · NIMH · YALE UNIVERSITY · PI CANNON, TYRONE D · 2008 to 2018
$12.4M
5/9 Predictors and Mechanisms of Conversion to PsychosisU01MH082004 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PERKINS, DIANA O. · 2008 to 2018
$7.5M
Administrative Supplement Harmonization of At Risk Multisite Observational Networks for Youth(HARMONY)U01MH081928 · NIMH · BETH ISRAEL DEACONESS MEDICAL CENTER · PI STONE, WILLIAM SETH · 2008 to 2018
$7.1M
4/9-Predictors and Mechanisms of Conversion to PsychosisU01MH081857 · NIMH · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · PI CORNBLATT, BARBARA A. · 2008 to 2018
$6.2M
8/9 Predictors and Mechanisms of Conversion to PsychosisU01MH082022 · NIMH · YALE UNIVERSITY · PI WOODS, SCOTT W · 2008 to 2018
$6.0M
2/9 - Predictors and Mechanisms of Conversion to PsychosisU01MH081988 · NIMH · EMORY UNIVERSITY · PI WALKER, ELAINE FRAN · 2008 to 2018
$5.4M
6/9-Predictors and Mechanisms of Conversion to PsychosisU01MH081944 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CADENHEAD, KRISTIN S. · 2008 to 2018
$4.9M
"7/9" Predictors and Mechanisms of Conversion to PsychosisU01MH081984 · NIMH · UNIVERSITY OF CALGARY · PI ADDINGTON, JEAN M · 2008 to 2018
$4.2M
9/9-Predictors and Mechanisms of Conversion to PsychosisU01MH076989 · NIMH · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MATHALON, DANIEL H · 2014 to 2018
$3.9M
5/5 CAPER: Computerized Assessment of Psychosis RiskR01MH120089 · NIMH · YALE UNIVERSITY · PI CORLETT, PHILIP, WOODS, SCOTT W · 2020 to 2024
$3.1M
Prodromal Inventory for Negative Symptoms (PINS): A Development and Validation StudyR01MH116039 · NIMH · UNIVERSITY OF GEORGIA · PI MITTAL, VIJAY A, STRAUSS, GREGORY P · 2019 to 2023
$3.1M
1/5 CAPER: Computerized Assessment of ProdromE RiskR01MH120090 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI GOLD, JAMES M. · 2020 to 2024
$2.9M
NIMH NIH HHS R01 MH112545NIMH NIH HHS R01 MH112612NIMH NIH HHS R01 MH112613NIMH NIH HHS R01 MH116039NIMH NIH HHS R01 MH120088NIMH NIH HHS R01 MH120089NIMH NIH HHS R01 MH120090NIMH NIH HHS R01 MH120091NIMH NIH HHS R01 MH120092NIMH NIH HHS R21 MH119438NIMH NIH HHS U01 MH076989NIMH NIH HHS U01 MH081857NIMH NIH HHS U01 MH081902NIMH NIH HHS U01 MH081928NIMH NIH HHS U01 MH081944NIMH NIH HHS U01 MH081984NIMH NIH HHS U01 MH081988NIMH NIH HHS U01 MH082004NIMH NIH HHS U01 MH082022U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01 MH1120088U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01MH120089U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH076989U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH081902U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH081928U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH081944U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH081984U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH081988U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH082004U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01MH082022U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) UO1MH081857
6 · The paper itself

Abstract

Historically, large samples of individuals at clinical high risk (CHR) for psychosis have mirrored overt psychotic disorders in both sex (predominantly male) and age representation (adolescent to early adulthood onset). We report on a recent CHR sample suggesting a shift in these distributions and explore contributing factors and clinical implications. We hypothesized that demographic differences would be related to recruitment sources and that age, sex, and recruitment sources would be related to baseline clinical profiles. Baseline data were included from the recent computerized assessment of psychosis risk (CAPR) study and the second and third waves of the North American Prodrome Longitudinal Study (NAPLS-2 and 3). Hierarchical regression was used to examine differences in sex, age, and recruitment sources between samples and relationships with clinical characteristics. Univariate analyses revealed a significant shift to female predominance, older age, and a change in recruitment source from NAPLS to CAPR. Multivariate analyses indicated that between-study differences in sex and age were conditional on recruitment source, with the apparent study effect driven by differences in the non-self-referred groups. More than 60% of participants recruited through internet self-referrals were female across samples. Clinical heterogeneity was partly related to age, sex, and recruitment source differences. Internet-based self-referrals were older and showed less severe negative symptoms, disorganization, and general symptoms and higher role functioning than non-self-referred participants. Findings highlight the importance of recruitment sources for CHR sample characteristics. Recruitment source effects, including those from internet sources, should be investigated in other CHR samples.

Identifiers

PMID41053030
PMCPMC12501016

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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.