Background: Functional neurological disorder (FND) is common across healthcare settings. The Diagnostic and Statistical Manual of Mental Disorders states that speech and swallowing symptoms can be present in FND. Despite this, there is a dearth of guidelines for speech and language therapists (SLTs) for this client group.
Aims: To address the following question in order to identify gaps for further research: What is known about speech, language and swallowing symptoms in patients with FND?
Methods & Procedures: A scoping review was conducted. Six healthcare databases were searched for relevant literature: CINAHL PLUS, MEDLINE, ProQuest Nursing and Allied Health Professionals, Science Citation Index, Scopus, and PsychINFO. The following symptoms were excluded from the review: dysphonia, globus pharyngeus, dysfluency, foreign accent syndrome and oesophageal dysphagia.
Main Contribution: A total of 63 papers were included in the final review; they ranged in date from 1953 to 2018. Case studies were the most frequent research method (n = 23, 37%). 'Psychogenic' was the term used most frequently (n = 24, 38%), followed by 'functional' (n = 21, 33%). Speech symptoms were reported most frequently (n = 41, 65%), followed by language impairments (n = 35, 56%) and dysphagia (n = 13, 21%). Only 11 publications comment on the involvement of SLTs. Eight papers report direct speech and language therapy input; however, none studied the effectiveness of speech and language therapy.
Conclusions & Implications: Speech, language and swallowing symptoms do occur in patients with FND, yet it is a highly under-researched area. Further research is required to create a set of positive diagnostic criteria, gather accurate data on numbers of patients with FND and speech, language or swallowing symptoms, and to evaluate the effectiveness of direct speech and language therapy involvement.
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http://dx.doi.org/10.1111/1460-6984.12448 | DOI Listing |
Dev Med Child Neurol
January 2025
Speech and Language, Murdoch Children's Research Institute, Parkville, Victoria, Australia.
Aim: To examine the adaptive behaviour profiles of children with monogenic neurodevelopmental disorders (NDDs) to determine whether syndrome-specific or transdiagnostic approaches provide a better understanding of the adaptive behavioural phenotypes of these NDDs.
Method: This cross-sectional study included parents and caregivers of 243 (48% female) individuals (age range = 1-25 years; mean = 8 years 10 months, SD = 5 years 8 months) with genetically confirmed monogenic NDDs (CDK13, DYRK1A, FOXP2, KAT6A, KANSL1, SETBP1, BRPF1, and DDX3X). Parents and caregivers completed the Vineland Adaptive Behavior Scales, Third Edition to assess communication, daily living, socialization, and motor skills.
Proc Conf Assoc Comput Linguist Meet
May 2022
Pharmaceutical Care and Health Systems, University of Minnesota.
Deep learning (DL) techniques involving fine-tuning large numbers of model parameters have delivered impressive performance on the task of discriminating between language produced by cognitively healthy individuals, and those with Alzheimer's disease (AD). However, questions remain about their ability to generalize beyond the small reference sets that are publicly available for research. As an alternative to fitting model parameters directly, we propose a novel method by which a Transformer DL model (GPT-2) pre-trained on general English text is paired with an artificially degraded version of itself (GPT-D), to compute the ratio between these two models' on language from cognitively healthy and impaired individuals.
View Article and Find Full Text PDFFront Hum Neurosci
January 2025
Department of Psychology, Renmin University of China, Beijing, China.
Introduction: While considerable research in language production has focused on incremental processing during conceptual and grammatical encoding, prosodic encoding remains less investigated. This study examines whether focus and accentuation processing in speech production follows linear or hierarchical incrementality.
Methods: We employed visual world eye-tracking to investigate how focus and accentuation are processed during sentence production.
Data Brief
February 2025
Department of Electrical, Electronic and Communication Engineering, Military Institute of Science and Technology (MIST), Dhaka 1216, Bangladesh.
The dataset represents a significant advancement in Bengali lip-reading and visual speech recognition research, poised to drive future applications and technological progress. Despite Bengali's global status as the seventh most spoken language with approximately 265 million speakers, linguistically rich and widely spoken languages like Bengali have been largely overlooked by the research community. fills this gap by offering a pioneering dataset tailored for Bengali lip-reading, comprising visual data from 150 speakers across 54 classes, encompassing Bengali phonemes, alphabets, and symbols.
View Article and Find Full Text PDFPulm Med
January 2025
Post Graduation Department, Escola Superior de Ciências da Saúde (ESCS), Brasilia, Distrito Federal, Brazil.
Lung volume recruitment (LVR) is a stacked-breath assisted inflation technique in which consecutive insufflations are delivered, without exhaling in between, until the maximum tolerable inflation capacity is reached. Although LVR is recommended in some neuromuscular disease guidelines, there is little information detailing when and how allied health professionals (AHPs) prescribe LVR. This study is aimed at describing the use of LVR in practice across Brazil.
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