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Record W1969181668 · doi:10.3402/ejpt.v3i0.8587

Assessment of anhedonia in psychological trauma: psychometric and neuroimaging perspectives

2012· article· en· W1969181668 on OpenAlexaff
Paul Frewen, David J. A. Dozois, Ruth A. Lanius

Bibliographic record

VenueEuropean journal of psychotraumatology · 2012
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsWestern University
Fundersnot available
KeywordsAnhedoniaPsychologyVentromedial prefrontal cortexClinical psychologyNeuroimagingAnxietyAffect (linguistics)Prefrontal cortexDevelopmental psychologySchizophrenia (object-oriented programming)PsychiatryCognition

Abstract

fetched live from OpenAlex

Symptoms of anhedonia, or deficits in the ability to experience positive affect, are increasingly recognized as an outcome of traumatic stress including in individuals with PTSD. However, little research has investigated negative affective responses to what would normally be considered pleasant events (e.g., receiving a compliment or gift, physical affection) in traumatized persons. We demonstrate not only self-reported decreased positive affect but also increased negative affect in response to positive events in 55 women with PTSD, in comparison with 35 women without PTSD, via their response to a Hedonic Deficit & Interference Scale (HDIS). The HDIS demonstrated strong internal validity, convergent and incremental validity relative to other measures of anhedonia, and discriminant validity in relation to depression versus anxiety symptoms in this sample. In addition, in response to imagery of social versus non-social positive events, HDIS scores predicted self-report positive and negative affective responses. In a sub-sample of participants completing the imagery task while undergoing fMRI (n=12), HDIS scores also predicted BOLD response within the left orbitofrontal cortex, ventromedial prefrontal cortex, amygdala, and cerebellum. Future research and clinical directions are discussed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.096
GPT teacher head0.441
Teacher spread0.345 · 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.

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

Citations78
Published2012
Admission routes1
Has abstractyes

Explore more

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