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Record W1985204191 · doi:10.1080/16506073.2010.520730

Examining Autobiographical Memory Content in Patients with Depression and Anxiety Disorders

2010· article· en· W1985204191 on OpenAlexaff
Kate S. Witheridge, Christine M. Cabral, Neil A. Rector

Bibliographic record

VenueCognitive Behaviour Therapy · 2010
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoHealth Sciences Centre
Fundersnot available
KeywordsPsychologyAutobiographical memorySchema (genetic algorithms)AnxietyClinical psychologyPanic disorderCognitionAgoraphobiaMajor depressive disorderBeck Anxiety InventoryDepression (economics)Anxiety disorderContent (measure theory)Beck Depression InventoryPsychiatry

Abstract

fetched live from OpenAlex

The purpose of this study was to move beyond the traditional specificity model of autobiographical memory (ABM) and to examine the content of memories with a focus on disorder and schema-relevant content. The sample (N = 82) included 25 patients with major depressive disorder (MDD), 24 with social phobia (SP), and 33 with panic disorder with agoraphobia (PDA) who were referred to a large outpatient clinic for group treatment of depression or anxiety. Participants completed the Autobiographical Memory Test (AMT) and Beck Depression Inventory-II as part of the clinical intake process. Responses to the AMT were coded for disorder-specific content based on diagnostic criteria for each disorder as well as for schema-relevant (sociotropy vs. autonomy) content. A repeated measures multiple analysis of variance demonstrated significant differences in disorder-specific content, with patients in the MDD group reporting more depressotypic ABMs than those in the PDA group but not the SP group. Similarly, in the analysis of schema-relevant content, significant differences were found between MDD and PDA regarding the presence of autonomy-based ABM ratings. Study results provide partial support for the cognitive specificity hypothesis with ABM content. The results are discussed in relation to the cognitive models of depression and anxiety.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.828

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 integrity0.0000.001
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 head0.028
GPT teacher head0.280
Teacher spread0.252 · 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
Published2010
Admission routes1
Has abstractyes

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