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Record W1588212136 · doi:10.1002/mds.25562

From psychogenic movement disorder to functional movement disorder: It's time to change the name

2013· review· en· W1588212136 on OpenAlexaff
Mark J. Edwards, Jon Stone, Anthony E. Lang

Bibliographic record

VenueMovement Disorders · 2013
Typereview
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsPsychogenic diseaseEponymConversion disorderTerm (time)PsychologyEtiologyMovement (music)Movement disordersArgument (complex analysis)PolitenessPsychiatryCognitive psychologyMedicinePhilosophyDiseaseLinguisticsAesthetics

Abstract

fetched live from OpenAlex

Successive attempts at rebranding may be behind at least some of the proliferation of terms we have at our disposal when describing patients with what are now most often referred to as "psychogenic," "conversion," or "somatoform" symptoms. The most popular term in the movement disorder literature, "psychogenic," provides the aetiology of the disorder within the name, indicating that the symptoms are "born of the mind." Here we argue that it is logical to stop using a term that defines the disorder with regard to a poorly defined aetiology that is not supported by current evidence, and, instead, to use a broad term-functional-not as a "polite eponym" but as a term that is freer from such assumptions and does not reinforce dualistic thinking. The main argument for change is not political or even practical, but scientific.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0010.006
Scholarly communication0.0030.008
Open science0.0020.002
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.307
Teacher spread0.269 · 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

Citations164
Published2013
Admission routes1
Has abstractyes

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