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Record W2013240889 · doi:10.1080/14779757.2014.910131

“That chair work thing was great”: a pilot study of group-based emotion-focused therapy for anxiety and depression

2014· article· en· W2013240889 on OpenAlexaff
Adèle Lafrance Robinson, Elizabeth A. McCague, Cynthia Whissell

Bibliographic record

VenuePerson-Centered & Experiential Psychotherapies · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of SudburyLaurentian UniversityHealth Sciences North
Fundersnot available
KeywordsAnxietyDepression (economics)Clinical psychologyPsychologyPsychotherapistGroup psychotherapyPsychiatry

Abstract

fetched live from OpenAlex

Emotion-focused therapy (EFT) is an evidence-based treatment for depression and it has shown promise for the treatment of anxiety. Only one other published study has examined EFT in a group therapy setting. Using mixed-methods, the current study explored the feasibility and outcomes of an EFT group with adults referred for anxiety and depression. Pre-, post-, and 12-month follow-up measures of depression, anxiety, and difficulties in emotion regulation were administered in addition to a semi-structured interview at one-year follow-up. The analysis of individual interviews suggested improvements in various areas of functioning and quantitative data revealed a significant decrease in emotion regulation difficulties. The results of this study provide preliminary support for the application and further study of group-based EFT for clinical presentations of anxiety and depression.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.296
Teacher spread0.233 · 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 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

Citations41
Published2014
Admission routes1
Has abstractyes

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