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Record W4384828250 · doi:10.1192/bja.2023.32

Eye movement desensitisation and reprocessing: part 3 – applications in physical health conditions

2023· article· en· W4384828250 on OpenAlexaff
Itoro Udo, Tori-Rose Javinsky, Carol McDaniel

Bibliographic record

VenueBJPsych Advances · 2023
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsVictoria HospitalLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsEye movement desensitization and reprocessingMedicinePsychological interventionAnxietyDistressIntensive care medicinePsychological traumaPhysical therapyPsychotherapistPsychiatryClinical psychologyPsychologyPosttraumatic stress

Abstract

fetched live from OpenAlex

SUMMARY Eye movement desensitisation and reprocessing (EMDR) is a psychological therapy that addresses trauma, stress and emotional distress. It has been successfully used in the management of various psychiatric disorders. This article shows that it may also be safely used to manage the psychological distress arising from a variety of physical health conditions and in so doing, reduce the illness burden from conditions such as various cancers, traumatic childbirth, tokophobia, pre-eclampsia, myocardial infarction, haemodialysis in end-stage renal disease, and acute postoperative pain. It can be a stand-alone treatment for hyperemesis gravidarum and tinnitus. The article examines the rationale and evidence for its use in these conditions and suggests areas where more research is needed. Adding EMDR therapy to the range of available interventions in general hospitals has the potential to improve the health and well-being of patients in these settings.

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)0.002
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.023
GPT teacher head0.377
Teacher spread0.354 · 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
GenreReview

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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