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Record W3018396944 · doi:10.1097/nmd.0000000000001176

The Effect of Hopelessness and Perceived Group Compatibility on Treatment Outcome for Patients With Personality Dysfunction

2020· article· en· W3018396944 on OpenAlexaff
Katie Aafjes‐van Doorn, David Kealy, Johannes C. Ehrenthal, John S. Ogrodniczuk, Anthony S. Joyce, Rainer Weber

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2020
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsPsychologyPersonalityClinical psychologyPsychosocialFeelingDistressLife satisfactionPsychopathologyPsychotherapistPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Improvement in life satisfaction is hard to achieve for any patient with personality psychopathology, and possibly even moreso for those who feel hopeless at the start of treatment. The present research investigated the potential influence of hopelessness in the treatment of patients with personality dysfunction, using data from patients who completed an intensive group therapy program designed to reduce symptom distress and support optimal psychosocial functioning (N = 80). In the present study, we sought to examine whether hopelessness would moderate (i.e., strengthen or weaken) relations between compatibility ratings and life satisfaction outcome. Hopelessness had a significant moderating effect on the relationship between compatibility and outcome, suggesting that, for patients who entered treatment feeling more hopeless, higher appraisals of fit within the group facilitated better gains in life satisfaction. If replicated, the findings underlie the importance of focusing on increasing hope and perceived group affiliation in the treatment of personality dysfunction.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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