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Record W2519723915 · doi:10.1037/pst0000060

Creating a climate for therapist improvement: A case study of an agency focused on outcomes and deliberate practice.

2016· article· en· W2519723915 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychotherapy · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsycINFOAgency (philosophy)PsychologyMental healthPsychotherapistOutcome (game theory)MEDLINEClinical PracticeClinical psychologyMedicineNursing

Abstract

fetched live from OpenAlex

Recent evidence suggests that psychotherapists may not increase in effectiveness over accrued experience in naturalistic settings, even settings that provide access to patients' outcomes. The current study examined changes in psychotherapists' effectiveness within an agency making a concerted effort to improve outcomes through the use of routine outcome monitoring coupled with ongoing consultation and the planful application of feedback including the use of deliberate practice. Data were available for 7 years of implementation from 5,128 patients seen by 153 psychotherapists. Results indicate that outcomes indeed improved across time within the agency, with increases of d = 0.035 (p = .003) per year. In contrast with previous reports, psychotherapists in the current sample showed improvements within their own caseloads across time (d = 0.034, p = .042). It did not appear that the observed agency-level improvement was due to the agency simply hiring higher-performing psychotherapists or losing lower-performing psychotherapists. Implications of these findings are discussed in relation to routine outcome monitoring, expertise in psychotherapy, and quality improvement within mental health care. (PsycINFO Database Record

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.730

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 head0.046
GPT teacher head0.418
Teacher spread0.372 · 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