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Record W2599445525 · doi:10.15453/2168-6408.1287

Satisfaction and Occupational Performance in Patients with Functional Movement Disorder

2017· article· en· W2599445525 on OpenAlexaboutno aff
Sarah E Dahlhauser, Amanda Theuer, John H. Hollman

Bibliographic record

VenueThe Open Journal of Occupational Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyMultidisciplinary approachFunctional movementCognitionMultidisciplinary teamMedicineMovement disordersPsychologyPhysical medicine and rehabilitationClinical psychologyPhysical therapyPsychiatryPathologyDisease

Abstract

fetched live from OpenAlex

Background: Behavioral Shaping Therapy (BeST) is a program that uses a multidisciplinary approach to treat patients diagnosed with functional movement disorder (FMD). While this diagnosis is classified as a psychological disorder by the Diagnostic and Statistical Manual of Mental Disorders, the BeST program focuses on treating the physical manifestations of FMD. Occupational therapists are an integral part of the multidisciplinary team, employing a variety of cognitive behavioral and motor reprogramming techniques to normalize movement patterns. Method: Patients 18 years of age or older with a confirmed diagnosis of FMD participated in this study. This retrospective chart review used the Canadian Occupation Performance Measure to examine the patients’ satisfaction and perceived change in task performance on discharge from the program. Results: Results from the dependent t-test indicated a positive outcome after participating in the BeST program, with a mean change in performance of 3.4 and a mean change in satisfaction of 4.7. Discussion: This study shows that occupational therapy can have a positive effect on patients diagnosed with FMD.

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)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.335
Teacher spread0.284 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Open Journal of Occupational TherapySame topicPsychosomatic Disorders and Their TreatmentsFrench-language works237,207