Evidence map›Paper›PMID 40227145›Full record

ArticleSchizophrenia bulletin2026

Insight and Its Trajectory: Predicting the Risk of Psychiatric Hospitalizations Among First-Episode Psychosis During the First Year of Coordinated Specialty Care.

Hadar Hazan, Maria Ferrara, Toni Gibbs-Dean, Sümeyra N Tayfur, Silvia Corbera, Sneha Karmani, Zhiqian Song, Fangyong Li, Ilias Vlachos, Mirjana Selakovic and 2 more

Abstract read
In one paragraph

Article in Schizophrenia bulletin, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Early clinical insight in first-episode psychosis.Schizophrenia research. Cognition · 2026
    Article
  4. Article
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

12 authors.

Hadar HazanDepartment of Psychiatry, Program for Specialized Treatment Early in Psychosis (STEP), Connecticut Mental Health Center (CMHC), Yale University School of Medicine, New Haven, CT 06477, United States.
Maria FerraraInstitute of Psychiatry, University of Ferrara, Via Fossato di Mortara 64, 44121, Ferrara, Italy.
Toni Gibbs-DeanDepartment of Psychiatry, Program for Specialized Treatment Early in Psychosis (STEP), Connecticut Mental Health Center (CMHC), Yale University School of Medicine, New Haven, CT 06477, United States.
Sümeyra N TayfurDepartment of Psychiatry, Program for Specialized Treatment Early in Psychosis (STEP), Connecticut Mental Health Center (CMHC), Yale University School of Medicine, New Haven, CT 06477, United States.
Silvia CorberaDepartment of Psychological Science, Central Connecticut State University, New Britain, CT 06050, United States.
Sneha KarmaniDepartment of Psychiatry, Program for Specialized Treatment Early in Psychosis (STEP), Connecticut Mental Health Center (CMHC), Yale University School of Medicine, New Haven, CT 06477, United States.
Zhiqian SongYale Center for Analytical Sciences, New Haven, CT 06520, United States.ORCID 0009-0009-4083-0723
Fangyong LiYale Center for Analytical Sciences, New Haven, CT 06520, United States.
Ilias VlachosYale Center for Analytical Sciences, New Haven, CT 06520, United States.ORCID 0000-0001-9044-7081
Mirjana SelakovicDepartment of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, 12462,  Greece.
Cenk TekDepartment of Psychiatry, Program for Specialized Treatment Early in Psychosis (STEP), Connecticut Mental Health Center (CMHC), Yale University School of Medicine, New Haven, CT 06477, United States.
Vinod H SrihariDepartment of Psychiatry, Program for Specialized Treatment Early in Psychosis (STEP), Connecticut Mental Health Center (CMHC), Yale University School of Medicine, New Haven, CT 06477, United States.ORCID 0000-0003-1556-2332

Funding

STEP-ED:Reducing Duration of Untreated Psychosis and its Impact in the U.S.R01MH103831 · NIMH · YALE UNIVERSITY · PI SRIHARI, VINOD H. · 2013 to 2017
$3.9M
NIMH NIH HHS R01 MH103831
6 · The paper itself

Abstract

backgroundThis study explored how baseline insight predicts psychiatric hospitalization risk among 186 individuals with first-episode psychosis in coordinated specialty care (CSC). We hypothesized that insight, a potentially modifiable factor, moderates the relationship between CSC enrollment and outcomes, with a high baseline and stable high insight predicting greater reductions in hospitalizations and lengths of stay (LOS).

designInsight was assessed using the G12 item of the positive and negative syndrome scale, categorizing participants into low (G12 ≥ 4; n = 87) or high (G12 < 4; n = 99) insight groups at baseline. Six longitudinal trajectories were identified: stable high (n = 48), increasing (n = 41), declining (n = 31), stable low (n = 27), high-low-high (n = 20), and low-high-low (n = 19). Hospitalization data were collected for 12 months pre- and post-CSC enrollment.

resultsParticipants with high baseline insight demonstrated a 95% greater relative reduction in hospitalizations (relative risk reduction = 1.95, P = .002), indicating that insight moderated the relationship between CSC enrollment and hospitalization outcomes. Longitudinally, the stable high insight group exhibited the most substantial reductions in hospitalizations (risk ratio [RR] = 0.12, P < .001) and LOS (RR = 0.04, P < .001), outperforming the stable low and fluctuating insight groups.

conclusionInsight moderates the relationship between CSC enrollment and hospitalization outcomes, predicting clinical improvements in early psychosis. Interventions targeting insight may enhance CSC benefits by reducing hospitalizations and improving recovery trajectories.

Indexed as

HospitalizationLength of StayOutcome Assessment, Health CarePsychotic DisordersSchizophreniaAdolescentAdultFemaleHumansLongitudinal StudiesMaleYoung Adultfirst-episode psychosishospitalizationinsightlength of staylongitudinal study

Identifiers

PMID40227145
PMCPMC12809808

What OpenQuestion holds

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Registered trials

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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.