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Record W4407589544 · doi:10.1007/s10862-025-10201-3

Multicomponent Multimethod Assessment of Emotional Change in Psychotherapy Research: Initial Validation of a Neurobehavioral Paradigm

2025· article· en· W4407589544 on OpenAlexaff
Loris Grandjean, Hélène Beuchat, Antonio Pascual‐Leone, Chantal Martin-Söelch, Bogdan Draganski, Uëli Kramer

Bibliographic record

VenueJournal of Psychopathology and Behavioral Assessment · 2025
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversity of Windsor
FundersUniversité de Lausanne
KeywordsPsychologyPsychotherapistClinical psychology

Abstract

fetched live from OpenAlex

Abstract Self-contempt and emotional arousal are two key concepts associated with psychological distress but have been little studied in a daily life context. This work explores the use of individualized self-contemptuous stimuli extracted from a self-critical two-chair dialogue into an fMRI scanner. 28 female controls participated in psychological investigations (at three time points) and a self-critical emotion-eliciting two-chair dialogue followed by an fMRI assessment. We observed the neurofunctional activation during this task and compared neural activation during the exposition to self-critical individualized stimuli versus negative non-individualized stimuli. We also investigated emotional arousal change during the psychological session. The fMRI data analysis showed no significant difference in activation between the first and second fMRI assessments. We found no significant activation when comparing the neural activation between the exposition to self-contemptuous individualized stimuli and non-individualized negative stimuli. Controls do show an increased self-reported emotional arousal when expressing self-contempt. Our neurobehavioral design seems promising as proof of concept in combining an analogue psychotherapy session and an fMRI session to investigate expressed self-contempt and emotional arousal in healthy controls. Using this design in clinical populations seems feasible and may be important in clinical populations known for emotional difficulties such as BPD.

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 score0.055
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.186
GPT teacher head0.544
Teacher spread0.358 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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