Occupational therapy consensus recommendations for functional neurological disorder
Bibliographic record
Abstract
BACKGROUND: People with functional neurological disorder (FND) are commonly seen by occupational therapists; however, there are limited descriptions in the literature about the type of interventions that are likely to be helpful. This document aims to address this issue by providing consensus recommendations for occupational therapy assessment and intervention. METHODS: The recommendations were developed in four stages. Stage 1: an invitation was sent to occupational therapists with expertise in FND in different countries to complete two surveys exploring their opinions regarding best practice for assessment and interventions for FND. Stage 2: a face-to-face meeting of multidisciplinary clinical experts in FND discussed and debated the data from stage 1, aiming to achieve consensus on each issue. Stage 3: recommendations based on the meeting were drafted. Stage 4: successive drafts of recommendations were circulated among the multidisciplinary group until consensus was achieved. RESULTS: We recommend that occupational therapy treatment for FND is based on a biopsychosocial aetiological framework. Education, rehabilitation within functional activity and the use of taught self-management strategies are central to occupational therapy intervention for FND. Several aspects of occupational therapy for FND are distinct from therapy for other neurological conditions. Examples to illustrate the recommendations are included within this document. CONCLUSIONS: Occupational therapists have an integral role in the multidisciplinary management of people with FND. This document forms a starting point for research aiming to develop evidence-based occupational therapy interventions for people with FND.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.078 | 0.207 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.013 | 0.010 |
| Research integrity | 0.022 | 0.018 |
| Insufficient payload (model declined to judge) | 0.016 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".