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Record W2056910195 · doi:10.1097/nmd.0b013e3181b977f7

Defense Mechanisms and Major Depressive Disorder in African American Women

2009· article· en· W2056910195 on OpenAlexaff
John H. Porcerelli, Trevor R. Olson, Michelle D. Presniak, Tsveti Markova, Kristen Miller

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2009
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of SaskatchewanJewish General HospitalMcGill University
Fundersnot available
KeywordsAnticipation (artificial intelligence)Clinical psychologyPsychologyMental healthMajor depressive disorderPsychiatryMood

Abstract

fetched live from OpenAlex

This study explored differences in defense use between a group of predominantly African American women diagnosed with Major Depressive Disorder (MDD; n = 20) and a healthy control sample (n = 20), both from a primary care medical clinic. Patients completed the Patient Health Questionnaire to assess DSM-IV diagnoses and underwent video-recorded interviews, which were assessed for defenses using the Defensive Functioning Scale from the DSM-IV. Groups were compared for differences in overall defensive functioning, defense levels, and individual defenses using independent samples t tests. Results showed that the MDD group scored higher on mental inhibition, minor image distorting, and major image distorting defense levels as well as the individual defenses devaluation, dissociation, and isolation. The control group scored higher on the overall defensive functioning and the individual defense anticipation. The results also showed a trend toward the MDD group scoring higher on the disavowal defense level and the individual defense splitting.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.009
GPT teacher head0.278
Teacher spread0.269 · 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

Citations26
Published2009
Admission routes1
Has abstractyes

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