A Critical Examination of the Clinical Diagnosis of Functional Tic‐like Behaviors
Bibliographic record
Abstract
BACKGROUND: Since the COVID-19 pandemic, movement disorder clinics have seen an increase in patients with an unusual type of tic-like symptoms: young adults with abrupt onset complex behaviors. It was quickly suspected that these patients suffered from functional neurological symptoms, later named Functional Tic-Like Behaviors (FTLB). Subsequent research on the differential diagnosis between FTLB and tics has been substantial and led to the development of diagnostic checklists. OBJECTIVES: We conducted a theoretical reappraisal of the FTLB literature to clarify the validity of the concept and its diagnostic implications. METHODS: This paper addresses several key aspects of the current FTLB literature: circular reasoning, the complications of the FTLB phenomenology and demographics, the impact of FTLB on tic literature at large, and issues with alignment of the FTLB concept with the diagnostic criteria for functional disorders. RESULTS: The clinical approach to FTLB might involve circular reasoning due to a lack of clinical benchmarks. The FTLB phenomenology and demographics may need more work to ensure a lack of bias and a proper description of this patient group including a clear distinction from tics. The impact of the FTLB discussion on the wider literature needs consideration. The validation of positive signs may help with both these endeavors and pave way to the inclusion of FTLB within psychiatric classification systems. Furthermore, the coexistence of FTLB and tics within the same patient needs to be addressed. CONCLUSION: More research may be needed to fully establish the diagnosis of FTLB and differentiate it from tics.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".