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Record W2150417607 · doi:10.1080/15299732.2012.694841

An Exploration of Young Adults' Progress in Treatment for Dissociative Disorder

2012· article· en· W2150417607 on OpenAlexaff
Amie C. Myrick, Bethany L. Brand, Scot McNary, Catherine Classen, Ruth A. Lanius, Richard J. Loewenstein, Clare Pain, Frank W. Putnam

Bibliographic record

VenueJournal of Trauma & Dissociation · 2012
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychologyDissociative identity disorderDissociativeDevelopmental psychologyPsychotherapistClinical psychology

Abstract

fetched live from OpenAlex

Although treatment outcome research on dissociative disorders (DD) is increasing, an examination of treatment progress in young adults with these disorders remains noticeably absent from the literature. Many studies of DD patients report mean ages over 35. The present study examined the response to treatment of a subsample of young adults ages 18-30 with dissociative identity disorder and dissociative disorder not otherwise specified who participated in a naturalistic, longitudinal study of DD treatment outcome. Over 30 months, these patients demonstrated decreases in destructive behaviors and symptomatology as well as improved adaptive capacities. Compared to the older adult participants in the study, the young adults were more impaired initially. However, these younger patients improved at a rapid pace, such that their clinical presentations were similar to or more improved than those of the older adults at the 30-month follow-up. This brief report suggests not only that young adult DD patients can benefit from a trauma-focused, phasic treatment approach but that their treatment may progress at a faster pace than that of older adults with DD.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.035
GPT teacher head0.353
Teacher spread0.317 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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