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Elucidating Tourette's Syndrome: Perspectives from Hypnosis, Attention and Self-Regulation

2007· article· en· W2141296333 on OpenAlexaff
Amir Raz, Shari Keller, Kim L. Norman, Diana Senechal

Bibliographic record

VenueAmerican Journal of Clinical Hypnosis · 2007
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsVancouver Coastal Health Research InstituteVancouver Coastal Health
Fundersnot available
KeywordsHypnosisTourette syndromePsychologyNeurosciencePsychotherapistCognitive psychologyMedicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

Biological psychiatry favors drug treatment over non-pharmacological intervention and shapes the way clinicians both treat and understand Tourette's Syndrome (TS). However, drug treatments for TS involve side effects and are potentially toxic to the central nervous system. Moreover, current pharmacological treatments are largely ineffective and at best only provide a modest symptom reduction. In this paper, we describe how non-pharmacological treatments such as focused attention can modulate, reduce, or indeed entirely eliminate the symptoms of TS as well as elucidate the underlying neural mechanisms. Showing that the symptoms of TS are susceptible to self-regulatory interventions such as hypnosis, we propose that attentional training could be used to both treat the disorder and better understand it.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.006
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0030.004
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 head0.017
GPT teacher head0.368
Teacher spread0.351 · 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 designCase report
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

Citations15
Published2007
Admission routes1
Has abstractyes

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