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Record W2972118582 · doi:10.1017/s1754470x19000278

Cultural adaptations of CBT: a summary and discussion of the Special Issue on Cultural Adaptation of CBT

2019· article· en· W2972118582 on OpenAlexaff
Farooq Naeem

Bibliographic record

VenueThe Cognitive Behaviour Therapist · 2019
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersUniversity of Cambridge
KeywordsVariety (cybernetics)PsychologyAdaptation (eye)Psychological interventionCompetence (human resources)AnxietyPsychotherapistCultural competenceService delivery frameworkPopulationCognitionService (business)Social psychologyMedicinePsychiatryComputer sciencePedagogy

Abstract

fetched live from OpenAlex

Abstract Cognitive behavioural therapy (CBT) in its current form might not be acceptable to service users from a variety of backgrounds. Therefore, it makes sense to adapt CBT when working with diverse populations. Contributors to this special issue of the Cognitive Behaviour Therapist have tackled the issues around the cultural adaptation of CBT from various perspectives, using a variety of methods, and have addressed topics ranging from cultural adaptation to improving access to CBT. Here, I briefly summarize and discuss the papers in this special issue. I start with a systematic review of CBT for social anxiety across cultures. Seven articles cover aspects of adaptation of therapies for people from different backgrounds. Three papers discuss the issues of gender and sexuality when using CBT, while another three papers focus on refugees, asylum seekers and the homeless, and two papers describe the application of CBT with religious populations. Finally, there are seven papers on issues related to service delivery, practice and training and supervision when working with a diverse population. Collectively, papers in this special issue provide us with sufficient evidence that cultural considerations play a vital role when using CBT, offer practical suggestions for improving cultural competence and most importantly, can catalyse future research. However, the full potential of culturally adapted interventions will not be realized until and unless access to CBT is improved. Therefore, there is a need to build robust evidence to convince funders, policy makers and service managers.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.030
GPT teacher head0.301
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations48
Published2019
Admission routes1
Has abstractyes

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