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Record W2109334837 · doi:10.1177/0145445503255489

A Brief Behavioral Activation Treatment for Depression

2003· article· en· W2109334837 on OpenAlexaff
Derek R. Hopko, Carl W. Lejuez, James P. LePage, Sandra D. Hopko, Daniel W. McNeil

Bibliographic record

VenueBehavior Modification · 2003
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsCovenant Health
Fundersnot available
KeywordsBehavioral activationContext (archaeology)Depression (economics)Intervention (counseling)PsychologyDepressive symptomsAffect (linguistics)PsychiatryClinical psychologyPsychotherapistCognition

Abstract

fetched live from OpenAlex

The brief behavioral activation treatment for depression (BATD) is a relatively uncomplicated, time-efficient, and cost-effective method for treating depression. Because of these features, BATD may represent a practical intervention within managed care-driven, inpatient psychiatric hospitals. Based on basic behavioral theory and empirical evidence supporting activation strategies, we designed a treatment to increase systematically exposure to positive activities and thereby help to alleviate depressive affect. This study represents a pilot study that extends research on this treatment into the context of an inpatient psychiatric unit. Results demonstrate effectiveness and superiority of BATD as compared with the standard supportive treatment provided within the hospital. A large effect size was demonstrated, despite a limited sample size. The authors discuss the limitations of the study and future directions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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)0.0050.000

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 head0.211
GPT teacher head0.477
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations242
Published2003
Admission routes1
Has abstractyes

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