MétaCan
Menu
Back to cohort

Treatment Compliance in Different Types of Group Psychotherapy

2006· article· en· W2063833138 on OpenAlexaff
John S. Ogrodniczuk, William E. Piper, Anthony S. Joyce

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2006
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAttendanceGroup psychotherapyClinical psychologyPsychologyGroup cohesivenessMediationMultilevel modelMedicine

Abstract

fetched live from OpenAlex

This study examined the effect of age on attending and completing different types of group therapy among psychiatric outpatients, and whether cohesion among group members mediates the effect of age on attendance. The sample consisted of 139 outpatients who began short-term interpretive or supportive group psychotherapy. Hierarchical regression analysis and Kaplan-Meier survival analysis were used to test the effect of age on attending and completing therapy. Mediation analysis was used to examine whether cohesion mediated the effect of age. Significant associations between age, session attendance, and termination status were found for patients receiving supportive group therapy. Age was directly related to attending and completing therapy. Quality of the relationships among patients (i.e., cohesion) was found to mediate the effect of age on attendance. Depending of the type of group therapy offered, younger patients may be at risk for poor treatment adherence. Difficulty forming positive relationships with other group members may contribute to this risk.

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)0.008
metaresearch head score (Gemma)0.061
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.341
Teacher spread0.312 · 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

Citations23
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Nervous and Mental DiseaseSame topicPsychotherapy Techniques and ApplicationsFrench-language works237,207