Rapid Onset Functional Tic-Like Disorder Outbreak: A Challenging Differential Diagnosis in the COVID-19 Pandemic.
Bibliographic record
Abstract
During the COVID-19 pandemic, several countries have observed an unexpected increase in the number of adolescents and young adults presenting with rapid onset functional tic-like behaviours after being exposed to social media content of others displaying a similar pattern of functional tics. Many of these patients have been referred to Movement Disorders Clinics with misdiagnoses of late-onset refractory Tourette Syndrome after failing different pharmacological treatments for tics. Tourette Syndrome is a well-known condition with clear clinical diagnostic criteria and which presents with the insidious onset of simple motor and phonic tics in a rostro-caudal evolution starting in early childhood. Clinical and demographic aspects can differentiate rapid onset functional tic-like behaviours from Tourette Syndrome, including the former having abrupt and explosive presentation of severe symptoms, later age of onset, female gender predominance, lack of suppressibility, comorbid anxiety and depression, atypical premonitory urge and history of exposure to social media content displaying tic-like behaviours. This new presentation of a functional neurological disorder may be explained in part by the relationship between social media exposure to tic-like behaviours, and maladaptive response to anxiety caused by life stressors (e.g. COVID-19 pandemic), especially in young individuals. Rapid onset functional tic-like behaviours may be considered a spreading neuropsychiatric disorder that is potentially fostered by the psychosocial impact caused by the COVID-19 pandemic.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".