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Ethical Practice of Cognitive Behavior Therapy

2015· book· en· W2172478256 on OpenAlexaff
Debbie Sookman

Bibliographic record

VenueOxford University Press eBooks · 2015
Typebook
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychological interventionConceptualizationCompetence (human resources)PsychologyPsychotherapistInformed consentCognitionMental healthEthical issuesClinical psychologyMedicinePsychiatryAlternative medicineEngineering ethicsSocial psychology

Abstract

fetched live from OpenAlex

Contemporary cognitive behavior therapy (CBT) comprises complex interventions that have demonstrated efficacy and/or are currently the evidence-based psychotherapeutic treatment of choice for many psychiatric disorders. This chapter discusses management of ethical issues that may arise during evidence-based CBT: initial assessment, informed consent, exposure-based therapy, out of office sessions, management of boundaries, homework, and risk management. The patient-therapist relationship and conceptualization of resistance during CBT are discussed. A crucial requirement of ethical mental health care is additional dissemination of CBT expertise. In this current era of specialization, interventions that target disorder specific symptoms and related difficulties (American Psychiatric Association,2013) show special promise. It is the ethical responsibility of clinicians regardless of orientation to be guided by current empirical research and their own specific areas of competence when making treatment recommendations. A priority for clinical research is further examination of the specific therapeutic ingredients that impact outcome and optimize recovery.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.019
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0090.003

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 head0.078
GPT teacher head0.294
Teacher spread0.215 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2015
Admission routes1
Has abstractyes

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