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Enregistrement W4403801882 · doi:10.1101/2024.10.26.24316171

Syntax and Schizophrenia: A meta-analysis of comprehension and production

2024· preprint· en· W4403801882 sur OpenAlexaffabout
Dalia Elleuch, Yinhan Chen, Qiang Luo, Lena Palaniyappan

Notice bibliographique

RevuemedRxiv · 2024
Typepreprint
Langueen
DomaineMathematics
ThématiqueCognitive and developmental aspects of mathematical skills
Établissements canadiensMcGill UniversityDouglas Mental Health University Institute
Organismes subventionnairesWellcome Trust
Mots-clésSyntaxComprehensionSchizophrenia (object-oriented programming)Meta-analysisProduction (economics)Computer scienceNatural language processingPsychologyLinguisticsCognitive psychologyProgramming languageMedicinePhilosophyEconomicsInternal medicine

Résumé

récupéré en direct d'OpenAlex

Summary Background People with schizophrenia exhibit notable difficulties in the use of everyday language. This directly impacts one’s ability to complete education and secure employment. An impairment in the ability to understand and generate the correct grammatical structures (syntax) has been suggested as a key contributor; but studies have been underpowered, often with conflicting findings. It is also unclear if syntactic deficits are restricted to a subgroup of patients, or generalized across the broad spectrum of patients irrespective of symptom profiles, age, sex, and illness severity. Methods We conducted a systematic review and meta-analysis, registered on OSF, adhering to PRISMA guidelines, searching multiple databases up to May 1, 2024. We extracted effect sizes (Cohen’s d) and variance differences (log coefficient of variation ratio) across 6 domains: 2 in comprehension (understanding complex syntax, detection of syntactic errors) and 4 in production (global complexity, phrasal/clausal complexity, utterance length, and integrity) in patient-control comparisons. Study quality/bias was assessed using a modified Newcastle–Ottawa Scale. Bayesian meta-analysis was used to estimate domain-specific effects and variance differences. We tested for potential moderators with sufficient data (age, sex, study quality, language spoken) using conventional meta-regression to estimate the sources of heterogeneity between studies. Findings Overall, 45 studies (n=2960 unique participants, 64·4% English, 79 case-control contrasts, weighted mean age(sd)=32·3(5·6)) were included. Of the patient samples, only 29·2% were women. Bayesian meta-analysis revealed extreme evidence for all syntactic domains to be affected in schizophrenia with a large-sized effect (model-averaged d =0·65 to 1·01, with overall random effects d =0·86, 95% CrI [0·67-1·03]). Syntactic comprehension was the most affected domain. There was notable heterogeneity between studies in global complexity (moderated by the age), production integrity (moderated by study quality), and production length. Robust BMA revealed weak evidence for publication bias. Patients had a small-to-medium-sized excess of inter-individual variability than healthy controls in understanding complex syntax, and in producing long utterances and complex phrases (overall random effects lnCVR =0·21, 95% CrI [0·07-0·36]), hinting at the possible presence of subgroups with diverging syntactic performance. Interpretation There is robust evidence for the presence of grammatical impairment in comprehension and production in schizophrenia. This knowledge will improve the measurement of communication disturbances in schizophrenia and aid in developing distinct interventions focussed on syntax - a rule-based feature that is potentially amenable to cognitive, educational, and linguistic interventions. Research in Context Evidence before this study Prior studies have documented significant language deficits among individuals with psychosis across multiple levels. However, syntactic divergence—those affecting sentence structure and grammar—have not been consistently quantified or systematically reviewed. An initial review of the literature indicated that the specific nature and severity of syntactic divergence, as well as their impact on narrative speech production, symptom burden, and daily functioning, remain poorly defined. We conducted a comprehensive search of the literature up to May 1, 2024, using databases such as PubMed, PsycINFO, Scopus, Google Scholar, and Web of Science. Our search terms combined psychosis, schizophrenia, language production, comprehension, syntax, and grammar, and we identified a scarcity of meta-analytic studies focusing specifically on syntactic comprehension and production divergence in psychosis. Added value of this study This systematic review and meta-analysis is the first to quantitatively assess syntactic comprehension and production divergence in individuals with psychosis. This study provides estimated effect sizes associated with syntactic impairments as well as a quantification of the variance within patient groups for each domain of impairment. Besides a detailed examination of this under-researched domain, we also identify critical research gaps that need to be addressed to derive benefits for patients from knowledge generated in this domain. Implications of all the available evidence This study provides robust evidence of grammatical impairments in individuals with schizophrenia, particularly in syntactic comprehension and production. These findings can enhance early detection approaches via speech/text readouts and lead to the development of targeted cognitive, educational, and linguistic interventions. By highlighting the variability in linguistic deficits, the study offers valuable insights for future therapeutic trials. It also supports the creation of personalized formats of information and educational plans aimed at improving the effectiveness of any therapeutic intervention offered to patients with schizophrenia via verbal medium.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,021
score de la tête « metaresearch » (Gemma)0,040
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: Méta-analyse
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,021
Score d'incertitude au seuil0,113

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0210,040
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0180,058
Bibliométrie0,0070,007
Études des sciences et des technologies0,0010,001
Communication savante0,0040,002
Science ouverte0,0020,002
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,103
Tête enseignante GPT0,334
Écart entre enseignants0,232 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeMéta-analyse
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2024
Routes d'admission2
Résumé présentoui

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