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Record W2566443765 · doi:10.1002/jclp.22431

Corrective Experiences of Psychotherapists in Training

2016· article· en· W2566443765 on OpenAlexaff
Kathrin Moertl, Himanshu Giri, Lynne Angus, Michael J. Constantino

Bibliographic record

VenueJournal of Clinical Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyPsychotherapistPsychological interventionContext (archaeology)Grounded theoryTherapeutic relationshipProcess (computing)Qualitative researchPsychiatry

Abstract

fetched live from OpenAlex

Although the concept of corrective experiences (CEs) is usually linked to the process of change in psychotherapy patients, we investigated them in the professional development of therapists-in-training. Inasmuch as psychotherapy is a relational process, it is important to look closely at how therapists reach the position of a competent partner in corrective experiencing. In this study, we interviewed 10 therapists-in-training undergoing their own training therapy. Responses to these semistructured interviews were analyzed using a computer-assisted grounded theory method. The 499 first-level categories were grouped into 5 main themes: therapist characteristics, therapist technical interventions, therapist relational interventions, relationship experience, and outcome experience. Two core categories representing corrective experiencing were (a) unexpected unconditional support from and trust in their own therapist and (b) unexpected confrontation and limitation with their therapist as well as awareness of self-other boundaries. Results are discussed in the broader context of the CE literature, relational theory, and relational practice.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.299
GPT teacher head0.587
Teacher spread0.288 · 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 designOther design
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
Published2016
Admission routes1
Has abstractyes

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