Notice bibliographique
Résumé
Biography Dr. Tamara Pringsheim is a Professor with the Department of Clinical Neurosciences, Psychiatry, Pediatrics and Community Health Sciences at the University of Calgary. She is the program lead for the Tourette and Pediatric Movement Disorder program at Alberta Children’s Hospital and the Deputy Director of the Mathison Centre for Mental Health Research and Education. She also works as an evidence-based medicine methodologist for the American Academy of Neurology. She is the president of the Tourette OCD Alberta Network, a nonprofit organization that supports people living with Tourette syndrome and OCD in Alberta, and provides education and training on these disorders to healthcare providers. Objective To describe the clinical characteristics, phenomenology and outcomes of Rapid Onset Functional Tic Like Behaviours (FTLBs) in young people. Methods The presenter will review published data on the clinical characteristics, phenomenology and evolution of FTLBs arising in young people around the world during and after the COVID-19 pandemic. Results Since mid-2020, clinicians at Tourette syndrome clinics around the world have experienced an unprecedented number of referrals of young people who have developed the rapid onset of FTLBs. Case series from several countries have been published, with common phenomenological characteristics between samples. Affected individuals typically range from 12 to 25 years of age. The majority of cases reported were assigned female at birth. Symptom onset is sudden, typically reaching a peak in severity within hours to days. Functional motor tic like behaviours are dominated by large amplitude arm movements, clapping, throwing objects and hitting oneself or others. Functional vocal tic like behaviours include an assortment of random words and phrases, and socially inappropriate or offensive words and phrases. Patients with FTLBs present with high symptom severity and impairment scores and are likely to meet the clinical threshold for an anxiety disorder or major depressive disorder. Theories for such magnification of FTLBs during the COVID-19 pandemic include the possibility of social contagion illness spread through the medium of social media. Additional stressors through the pandemic, including school and extracurricular activity closures, ‘virtual schooling’ and associated academic pressures, social isolation and increased tensions at home during lockdown measures are believed to contribute to this clinical phenomenon. Emerging data on short- and medium-term outcomes suggests symptom improvement in the majority of individuals over a period of months, with treatment focusing on comorbid anxiety and depressive symptoms. Conclusions Rapid onset FTLBs have several distinguishing characteristics, appear strongly socially influenced, and show a positive response to treatment of distress, anxiety and mood disorders.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».