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Record W3134611863

[Effectiveness of Behavioral Activation for the Treatment of Severe Depression in Clinical Settings].

2020· article· en· W3134611863 on OpenAlexaff
Valérie Blanchet, Martin D. Provencher

Bibliographic record

VenuePubMed · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBehavioral activationDepression (economics)Randomized controlled trialPsychological interventionAnxietyClinical psychologyPopulationIntervention (counseling)ModerationQuality of life (healthcare)ComorbidityMedicinePsychiatryClinical trialPsychologyPsychotherapistInternal medicineCognition
DOInot available

Abstract

fetched live from OpenAlex

Objectives Among interventions that have been shown to be efficacious in the treatment of depression, behavioural activation (AC) is receiving increasing attention as the evidence supporting its effectiveness continues to accumulate. Although the efficacy of AC for the treatment of depression has been established through numerous randomized controlled trials, studies evaluating the effectiveness of AC when implemented in mental health settings are rare and there is insufficient supportive data. This step is, however, essential to the validity and the generalization of the treatment to the reality of clinical settings. This study focuses on AC applied to take into account the reality of clinical settings and patients seeking treatment. It evaluates the effectiveness of group-based AC for the treatment of severe depression in a clinical setting in a heterogeneous population in terms of diagnosis (unipolar and bipolar depression) and comorbidity (Axis I and II). Methods A sample of 45 participants with severe depression was recruited in a psychiatric hospital. Participants received a 10 sessions group intervention of AC. Questionnaires were administered to obtain pretreatment, post-treatment and four-week post-treatment data. The impact of the intervention was observed on measures of depression, behavioural activation, reinforcement, anxiety, social adjustment and quality of life. Various moderation effects associated with the heterogeneity of the sample were tested on the evolution of depressive symptoms. The integrity of the treatment administered by the therapists and the acceptability of the intervention by participants were also documented. Results Mixed model analyses of variance were performed to assess whether (a) AC caused a significant change at the end of treatment on depressive symptoms, behavioural activation, reinforcement, anxiety, social adjustment and quality of life and whether (b) gains were maintained after four weeks. A significant change was obtained between the pre-post measures on the average score of all these variables, with the exception of a subscale of the quality of life measure. Analyses were also performed to verify various moderating effects on the evolution of depressive symptoms, level of activation and reinforcement. No interaction effects are observed on depression, activation and reinforcement measures. There is no significant difference according to pretreatment severity category, diagnosis (unipolar vs bipolar), presence of comorbidity (other Axis I and/or Axis II disorder) or co-morbidity of Axis II disorder. As for the activation measure in people with bipolar depression versus unipolar depression, it should be noted that the result is at the threshold of statistical significance. Conclusion The results support the effectiveness of group-based AC for the treatment of severe depression in clinical settings in a heterogeneous population, as well as for the maintenance of gains after four weeks. The effectiveness of AC was also observed across all associated psychosocial measures.

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)0.002
metaresearch head score (Gemma)0.004
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
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.144
GPT teacher head0.448
Teacher spread0.304 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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