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Record W2103715196 · doi:10.1177/1534650111411293

Inference-Based Therapy for Compulsive Hoarding

2011· article· en· W2103715196 on OpenAlex
Marie-Ève St-Pierre-Delorme, Magali Purcell Lalonde, Valérie Perreault, Natalia Koszegi, Kieron O’Connor

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Case Studies · 2011
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsUniversité du Québec en OutaouaisInstitut universitaire en santé mentale de Montréal
Fundersnot available
KeywordsHoarding (animal behavior)Beck Anxiety InventoryBeck Depression InventoryPsychologyAnxietyClinical psychologyCognitionCognitive therapyCognitive behavioral therapySubclinical infectionCompulsive behaviorDepression (economics)InferencePsychiatryPsychotherapistMedicineInternal medicine

Abstract

fetched live from OpenAlex

Compulsive hoarding (CH) is a chronic and debilitating condition that generally shows poor treatment response to both psychopharmacotherapy and cognitive-behavioral therapy. The present case study describes the application of a cognitive inference-based therapy program to the treatment of a 39-year-old woman diagnosed with CH. During a 24-week treatment period, her hoarding behavior and associated beliefs significantly decreased. Specifically, Yale–Brown Obsessive-Compulsive Scale scores became subclinical at the 6-months follow-up. There was also a clinically significant decrease in Beck Depression Inventory–II, Beck Anxiety Inventory, Overvalued Ideas Scale, and Saving Inventory–Revised scores. The single case study has implications for the treatment of CH and other problems showing ego-syntonic beliefs.

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.

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)0.001
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 score0.235
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.263
GPT teacher head0.486
Teacher spread0.223 · 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