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Record W1937525932 · doi:10.1080/15299732.2012.710185

Dissociative Identity Disorder and the Process of Couple Therapy

2012· article· en· W1937525932 on OpenAlexaff
Heather B. MacIntosh

Bibliographic record

VenueJournal of Trauma & Dissociation · 2012
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychotherapistPsychologyDissociative identity disorderContext (archaeology)DistressSexual abuseFamily therapyMarital TherapyPsychoanalysisMedicinePoison controlSuicide prevention

Abstract

fetched live from OpenAlex

Couple therapy in the context of dissociative identity disorder (DID) has been neglected as an area of exploration and development in the couple therapy and trauma literature. What little discussion exists focuses primarily on couple therapy as an adjunct to individual therapy rather than as a primary treatment for couple distress and trauma. Couple therapy researchers have begun to develop adaptations to provide effective support to couples dealing with the impact of childhood trauma in their relationships, but little attention has been paid to the specific and complex needs of DID patients in couple therapy (H. B. MacIntosh & S. Johnson, 2008 MacIntosh, H. B. and Johnson, S. 2008. Emotionally focused therapy for couples and childhood sexual abuse survivors. Journal of Marital and Family Therapy, 34(3): 298–315. doi:http://dx.doi.org/10.1111/j.1752-0606.2008.00074.x[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). This review and case presentation explores the case of “Lisa,” a woman diagnosed with DID, and “Don,” her partner, and illustrates the themes of learning to communicate, handling conflicting needs, responding to child alters, and addressing sexuality and education through their therapy process. It is the hope of the author that this discussion will renew interest in the field of couple therapy in the context of DID, with the eventual goal of developing an empirically testable model of treatment for couples.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.362
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.385
Teacher spread0.365 · 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 teacher head, 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

Citations7
Published2012
Admission routes1
Has abstractyes

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