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Record W3004135808 · doi:10.1037/pst0000281

The perniciousness of perfectionism in group therapy for depression: A test of the perfectionism social disconnection model.

2020· article· en· W3004135808 on OpenAlexafffund
Paul L. Hewitt, Martin M. Smith, Xiaolei Deng, Chang Chen, Ariel Ko, Gordon L. Flett, Randy J. Paterson

Bibliographic record

VenuePsychotherapy · 2020
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsYork UniversityUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPerfectionism (psychology)DisconnectionPsychologyPsycINFOClinical psychologyDepression (economics)Context (archaeology)PsychotherapistMEDLINE

Abstract

fetched live from OpenAlex

= 156) enrolled in short-term postdischarge group cognitive-behavioral therapy for residual depression completed measures of perfectionism at pretreatment; of romantic love, friendships, and familial love at posttreatment; and of depression at pre- and posttreatment. Multilevel modeling showed that other-oriented and socially prescribed perfectionism were associated with lower posttreatment reductions in depression over treatment, and path analysis revealed that self-oriented, other-oriented, and socially prescribed perfectionism indirectly predicted lower posttreatment reductions in depression through a perceived lack of quality friendships. Results lend credence and coherence to the perfectionism social disconnection model in a clinical context and underscore the importance of taking extratherapeutic social disconnection into account when treating perfectionistic patients. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.322
Teacher spread0.286 · 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

Citations42
Published2020
Admission routes2
Has abstractyes

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