MétaCan
Menu
Back to cohort
Record W2554500880 · doi:10.1002/jclp.22428

Patients’ Perceptions of Corrective Experiences in Naturalistically Delivered Psychotherapy

2016· article· en· W2554500880 on OpenAlexaff
Michael J. Constantino, Nicholas R. Morrison, Alice E. Coyne, Brien J. Goodwin, G Santorelli, Lynne Angus

Bibliographic record

VenueJournal of Clinical Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsYork University
FundersAmerican Psychological Association
KeywordsPsychologyPsychotherapistContext (archaeology)Transformative learningInterpersonal communicationIntegrative psychotherapyPerceptionAttachment theoryTherapeutic relationshipClinical psychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Corrective experiences (CEs), which suggest transformative experience(s) for the psychotherapy patient, have a rich theoretical history; yet there is little empirical information on patients' own perceptions of what gets "corrected" from therapy, and what is "corrective" (i.e., the mechanisms driving the CE). To address this gap, we investigated 14 patients' posttreatment accounts of both CE elements in the context of naturalistically delivered individual psychotherapy, using a consensual qualitative research methodology. Extending prior research focused on patients' accounts of CEs while still engaged in treatment (Heatherington et al., 2012), the present results revealed that patients retrospectively identified an array of categories that were deemed corrected, such as positive changes in cognitions, interpersonal problems, self-concepts, symptoms, and behaviors. Patients also identified CEs that may have led to those shifts/transformations, including their therapist's actions (especially giving feedback), their own agentic actions (especially engaging in the therapeutic process), and the patient-therapist collaborative and engaged relationship. Clinical practice implications are discussed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.100
GPT teacher head0.517
Teacher spread0.417 · 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.

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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical PsychologySame topicPsychotherapy Techniques and ApplicationsFrench-language works237,207