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Record W4322617394 · doi:10.1017/s0954579423000056

Examining the psychobiological response to acute social stress across clinical stages and symptom trajectories in the early psychosis continuum

2023· article· en· W4322617394 on OpenAlexaff
Jai Shah, Vincent Paquin, Sarah V. McIlwaine, Ashok Malla, Ridha Joober, Marita Pruessner

Bibliographic record

VenueDevelopment and Psychopathology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsMcGill University
Fundersnot available
KeywordsTrier social stress testPsychosisHeart ratePsychologyBlood pressureSocial stressClinical psychologyFight-or-flight responseYoung adultPsychiatryDevelopmental psychologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

Abstract The stress-vulnerability model has been repeatedly highlighted in relation to the risk, onset and course of psychosis, and has been independently studied in clinical high-risk (CHR) and first-episode psychosis (FEP) populations. Notable in this literature, however, is that there are few studies directly comparing markers of stress response across progressive stages of illness. Here we examined the psychobiological response to the Trier Social Stress Test in 28 CHR (mean age 19.1) and 61 FEP (age 23.0) patients, in order to understand the stage(s) or trajectories in which differences in subjective stress or physiological response occur. The overall clinical sample had greater perceived stress and blunted cortisol (FEP + CHR, n = 89, age 21.7) compared with healthy controls ( n = 45, age 22.9). Additional analyses demonstrated elevated heart rate and systolic blood pressure in FEP compared with CHR, but there were no further differences in physiological parameters (cortisol, heart rate, or blood pressure) between stage- or trajectory-based groups. Together, this suggests that individual stress response markers may differentially emerge at particular stages en route to psychosis – and demonstrates how stage-based analyses can shed light on the emergence and evolution of neurobiological changes in mental illness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.107
GPT teacher head0.395
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2023
Admission routes1
Has abstractyes

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