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Record W2515214748 · doi:10.13109/zptm.2016.62.3.207

Affective Change in Psychodynamic Psychotherapy: Theoretical Models and Clinical Approaches to Changing Emotions

2016· review· en· W2515214748 on OpenAlexaff
Claudia Subič-Wrana, Leslie S. Greenberg, Richard D. Lane, Matthias Michal, Jörg Wiltink, Manfred E. Beutel

Bibliographic record

VenueZeitschrift für psychosomatische Medizin und Psychotherapie · 2016
Typereview
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsPsychoanalytic theoryPsychodynamicsPsychologyPsychotherapistPsychodynamic psychotherapyAffect (linguistics)

Abstract

fetched live from OpenAlex

OBJECTIVES: Affective change has been considered the hallmark of therapeutic change in psychoanalysis. Psychoanalytic writers have begun to incorporate theoretically the advanced understanding of emotional processing and transformation of the affective neurosciences. We ask if this theoretical advancement is reflected in treatment techniques addressing the processing of emotion. METHODS: We review psychoanalytic models and treatment recommendations of maladaptive affect processing in the light of a neuroscientifically informed model of achieving psychotherapeutic change by activation and reconsolidation of emotional memory. RESULTS: Emotions tend to be treated as other mental contents, resulting in a lack of specific psychodynamic techniques to work with emotions. Manualized technical modifications addressing affect regulation have been successfully tested in patients with personality pathology, but not for psychodynamic treatments of axis I disorders. CONCLUSIONS: Emotional memories need to be activated in order to be modified, therefore, we propose to include techniques into psychodynamic therapy that stimulate emotional experience.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.202
GPT teacher head0.470
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2016
Admission routes1
Has abstractyes

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