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Record W2514107032 · doi:10.1080/00207144.2016.1171095

Use of Hypnotic Techniques in Children and Adolescents with Chronic Pain:<i>Do the Ages of Patients or Years of Practice and Theoretical Orientation of Clinicians Matter?</i>

2016· article· en· W2514107032 on OpenAlexaff
Catarina Tomé‐Pires, Ester Solé, Mélanie Racine, Rocío de la Vega, Elena Castarlenas, Mark P. Jensen, Jordi Miró

Bibliographic record

VenueInternational Journal of Clinical and Experimental Hypnosis · 2016
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsWestern University
FundersFundação para a Ciência e a TecnologiaFundació la Marató de TV3
KeywordsHypnosisPsychologyChronic painHypnoticOrientation (vector space)Pain managementPediatric psychologyHealth professionalsClinical psychologySelection (genetic algorithm)Health careMedicineAlternative medicinePsychiatryPhysical therapy

Abstract

fetched live from OpenAlex

Hypnosis is known to be effective in the treatment of pediatric pain. To better understand which strategies might be most useful, more knowledge is needed regarding the strategies that are actually used by experienced clinicians and the factors that influence their use. To address this knowledge gap, 35 health care professionals completed an online survey on the use of hypnosis in the management of pediatric chronic pain. The findings indicate that clinicians vary their use of hypnotic strategies primarily as a function of a patient's age but not as a function of theoretical orientation or amount of experience. The findings may be useful for guiding clinicians in their selection of strategies and suggestions when working with children with pain.

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)0.028
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.354
Teacher spread0.330 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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