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Conflict in Group Therapy of Chronic Schizophrenics

2000· article· en· W23637639 on OpenAlexaff
Sheila Hassan, Caroline Cinq-Mars, Maxine Sigman

Bibliographic record

VenueAmerican Journal of Psychotherapy · 2000
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsJewish General Hospital
FundersMinistry of Education, IndiaMinistry of Earth Sciences
KeywordsPsychologyAggressionAngerCountertransferenceCoping (psychology)FeelingPsychotherapistAffect (linguistics)Clinical psychologySocial psychology

Abstract

fetched live from OpenAlex

This paper describes a pivotal group session in which there was a major conflict between two members of a group that has met for many years. The group serves chronically ill outpatients suffering primarily from schizophrenia or schizoaffective illness. The aftershocks of the explosive outburst, the leaders' understanding of the contributing factors, countertransference feelings, and coping mechanisms are described. The literature recommends two pathways concerning the expression of anger and aggression in groups of severely disturbed individuals: restriction of intense negative affect or expression of such affect as a helpful component of a therapeutic process. We reflect on this question in sharing detailed clinical material and conclude that coping with aggression in such groups is dependent not only on the group context, but also on the relative fragility, strength, and tolerance of both members and leaders. A crucial step in dealing with eruptive crises consists of reflecting upon the leaders conscious and unconscious intervention motives and affects.

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)0.003
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.345
Teacher spread0.327 · 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

Citations5
Published2000
Admission routes1
Has abstractyes

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