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Record W4317951955 · doi:10.1891/emdr-2022-0052

The TraumaClinic Model of EMDR Basic Training in Brazil: A Country Case Study for In-Person and Online Training

2023· article· en· W4317951955 on OpenAlexaff
Esly Regina Carvalho, Raquel C. Hoersting

Bibliographic record

VenueJournal of EMDR Practice and Research · 2023
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsTraining (meteorology)Adaptation (eye)DistancingCultural sensitivitySocial distanceGovernment (linguistics)PsychologyCoronavirus disease 2019 (COVID-19)Medical educationApplied psychologyPsychotherapistMedicineGeography

Abstract

fetched live from OpenAlex

This article utilizes a country case study design to describe the implementation of eye movement desensitization and reprocessing (EMDR) therapy training in Brazil. The primary focus is on the methodology, adaptations, adjustments, and cultural considerations necessary to incorporate in-person and virtual training in this country. Additionally, the article will explore the impact of the COVID-19 pandemic to address National Government Guidance related to social distancing. This guidance required adjustments to training delivery, clinical and self-practice, clinical supervision, and consultation. Finally, the article outlines the advantages and disadvantages of implementing EMDR therapy training in Brazil, expanding to how models of good practice could be implemented in other countries, such as Angola and Mozambique, to include cultural adaptation, sensitivity, and replication.

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)0.020
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.590
GPT teacher head0.603
Teacher spread0.013 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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