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Record W3033530366 · doi:10.1002/gps.5360

Continuation Sessions of Mindfulness‐Based Cognitive Therapy (MBCT‐C) vs. Treatment as Usual in Late‐Life Depression and Anxiety: An Open‐Label Extension Study

2020· article· en· W3033530366 on OpenAlexaff
Elena Dikaios, Sophia Escobar, Marouane Nassim, Chien‐Lin Su, Susana G. Torres‐Platas, Soham Rej

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2020
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMindfulness-based cognitive therapyAnxietyMindfulnessDepression (economics)Randomized controlled trialCognitive therapyPsychologyMedicineClinical psychologyPsychiatryPsychotherapistInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Mindfulness-based cognitive therapy (MBCT) is a novel treatment for depression. Our published randomized controlled trial shows that MBCT improves symptoms of late-life depression (LLD) and anxiety (LLA). We now examine whether continuation sessions of MBCT (MBCT-C) can prevent LLD/LLA symptom recurrence. METHODS/DESIGN: Following an 8-week MBCT intervention, we compared patients who attended open-label weekly 1-hour MBCT-C for another 26 weeks (n = 10) vs those who did not (n = 17) for change in depressive and anxiety symptoms. RESULTS: While there were no significant differences between groups on depressive or anxiety symptom severities between 8- and 34- weeks (Cohen's d = 0.045), we observed a small clinical effect of MBCT-C on symptoms of anxiety (d = 0.29). CONCLUSIONS: These preliminary results suggest that MBCT-C may be somewhat beneficial for symptoms of LLA, but not for LLD. Healthcare providers should consider what is clinically feasible before investing time and resources into MBCT-C in older adults with depression and/or 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.392
Teacher spread0.332 · 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.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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