Clinical Manifestations.

Future clinical trials targeting Alzheimer's disease (AD) on new disease modifying drugs necessitate a paradigm shift towards early identification of individuals at risk. Emerging evidence indicates that subtle alterations in language and speech characteristics may manifest concurrently with the progression of neurodegenerative disorders like AD. These changes manifest as discernible variations, assessable through semantic nuances, word choices, sentiment, grammar usage (linguistic features), and phonetic/acoustic traits (paralinguistic features).

Clinical Manifestations.

Background: Changes in speech and language functions have shown to be early symptoms of AD pathology. Recent developments in automatic speech and language processing have opened avenues for objective assessments of these changes. The primary objective of this study is to explore whether speech and language markers extracted from cognitive testing conducted during an automated phone call differ according to underlying AD pathology as measured in cerebrospinal fluid (CSF) in preclinical or early stage individuals.

Clinical Manifestations.

Background: Speech and language impairments are associated with cognitive decline in neurodegenerative dementias, particularly Alzheimer's Disease (AD), where subtle speech changes may precede clinical dementia onset. As clinical trials prioritize early identification for disease-modifying treatments, digital biomarkers for timely screening become imperative. Digital speech-based biomarkers can be employed for screening populations at the earliest AD stages.

Clinical Manifestations.

Background: Traditional pen-and-paper neuropsychological assessments fail to capture subtle cognitive changes in the early stages of Alzheimer's disease (AD). Remote and unsupervised digital assessments available on smartphones, tablets, and personal computers may offer a solution to this by increasing the amount and types of data available to researchers and clinicians, while simultaneously improving ecological validity and alleviating patient burden. As these remote and unsupervised digital cognitive assessment tools become more widely available, it is important that they are validated in a systematic way.

"Good childhood": children's perception and evaluation of transnational families.

In public debates, transnational families are portrayed as a deviation from the norm of "good childhood." In Europe, this is emphasized by the term "Euro-orphans," branding parents' (especially mothers') absence as a violation and scandalizing it. Children's voices are rarely heard in public discourse, and although research is now turning its attention to the "stayer children," they and their perspectives on transnational family life remain underrepresented, especially in Europe.

From "invisible" to "audible": Features extracted during simple speech tasks classify patient-reported fatigue in multiple sclerosis.

Background: Fatigue is a major "invisible" symptom in people with multiple sclerosis (PwMS), which may affect speech. Automated speech analysis is an objective, rapid tool to capture digital speech biomarkers linked to functional outcomes.

Objective: To use automated speech analysis to assess multiple sclerosis (MS) fatigue metrics.

Corrigendum: An automatic measure for speech intelligibility in dysarthrias-validation across multiple languages and neurological disorders.

[This corrects the article DOI: 10.3389/fdgth.2024.

The voice of depression: speech features as biomarkers for major depressive disorder.

Background: Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patients. This project aimed to identify discriminating speech features between patients with major depressive disorder (MDD) and healthy controls (HCs) by examining associations with symptom severity measures.

Detecting fatigue in multiple sclerosis through automatic speech analysis.

Multiple sclerosis (MS) is a chronic neuroinflammatory disease characterized by central nervous system demyelination and axonal degeneration. Fatigue affects a major portion of MS patients, significantly impairing their daily activities and quality of life. Despite its prevalence, the mechanisms underlying fatigue in MS are poorly understood, and measuring fatigue remains a challenging task.

User Experience of a (Semi-) Automated Cognitive Phone-Based Assessment Within a Memory Clinic Population.

Objective: We examined the user experience in different modalities (face-to-face, semi-automated phone-based, and fully automated phone-based) of cognitive testing in people with subjective cognitive decline and mild cognitive impairment.

Method: A total of 67 participants from the memory clinic of the Maastricht University Medical Center+ participated in the study. The study consisted of cognitive tests in different modalities, namely, face-to-face, semi-automated phone-based guided by a researcher, and fully automated phone-based without the involvement of a researcher.

An automatic measure for speech intelligibility in dysarthrias-validation across multiple languages and neurological disorders.

Introduction: Dysarthria, a motor speech disorder caused by muscle weakness or paralysis, severely impacts speech intelligibility and quality of life. The condition is prevalent in motor speech disorders such as Parkinson's disease (PD), atypical parkinsonism such as progressive supranuclear palsy (PSP), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS). Improving intelligibility is not only an outcome that matters to patients but can also play a critical role as an endpoint in clinical research and drug development.

Remote data collection speech analysis in people at risk for Alzheimer's disease dementia: usability and acceptability results.

Introduction: Digital cognitive assessments are gathering importance for the decentralized remote clinical trials of the future. Before including such assessments in clinical trials, they must be tested to confirm feasibility and acceptability with the intended participant group. This study presents usability and acceptability data from the Speech on the Phone Assessment (SPeAk) study.

The Reliability and Clinical Validation of Automatically-Derived Verbal Memory Features of the Verbal Learning Test in Early Diagnostics of Cognitive Impairment.

Background: Previous research has shown that verbal memory accurately measures cognitive decline in the early phases of neurocognitive impairment. Automatic speech recognition from the verbal learning task (VLT) can potentially be used to differentiate between people with and without cognitive impairment.

Objective: Investigate whether automatic speech recognition (ASR) of the VLT is reliable and able to differentiate between subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

Validation of an Automated Speech Analysis of Cognitive Tasks within a Semiautomated Phone Assessment.

Introduction: We studied the accuracy of the automatic speech recognition (ASR) software by comparing ASR scores with manual scores from a verbal learning test (VLT) and a semantic verbal fluency (SVF) task in a semiautomated phone assessment in a memory clinic population. Furthermore, we examined the differentiating value of these tests between participants with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). We also investigated whether the automatically calculated speech and linguistic features had an additional value compared to the commonly used total scores in a semiautomated phone assessment.

Teleconsultations for mental health: Recommendations from a Delphi panel.

Introduction: The use of teleconsultations for mental health has drastically increased since 2020 due to the Covid19 pandemic. In the present paper, we aimed to analyze the advantages and disadvantages of teleconsultations for mental health compared to face-to-face consultations, and to provide recommendations in this domain.

Methods: The recommendations were gathered using a Delphi methodology.

[The contribution of physical activity to motivation in patients with minor to major cognitive impairment].

Alzheimer's disease (AD) brings with it the need to think about the loss of autonomy caused by cognitive impairment, and how to manage it. In this context, adapted physical activity has been shown to benefit the overall quality of life of people suffering from the disease. In our study of thirteen patients with AD or related neurodegenerative diseases, we assessed the impact of physical activity on self-esteem and motivation, with patients taking part in group exercise sessions lasting twelve weeks, one hour a week.

Study protocol: how does parental stress measured by clinical scales and voice acoustic stress markers predict children's response to PTSD trauma-focused therapies?

Introduction: Post-traumatic stress disorder (PTSD) symptoms in youth are influenced by parental anxiety and stress. When parents have high levels of stress or have developed PTSD themselves, children tend to show more anxiety symptoms. Parental stress can affect the severity of children's PTSD and lower the success of recovery.

Correction: Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review.

[This corrects the article DOI: 10.2196/37225.].

The Accuracy of Speech and Linguistic Analysis in Early Diagnostics of Neurocognitive Disorders in a Memory Clinic Setting.

Objective: To investigate whether automatic analysis of the Semantic Verbal Fluency test (SVF) is reliable and can extract additional information that is of value for identifying neurocognitive disorders. In addition, the associations between the automatically derived speech and linguistic features and other cognitive domains were explored.

Method: We included 135 participants from the memory clinic of the Maastricht University Medical Center+ (with Subjective Cognitive Decline [SCD; N = 69] and Mild Cognitive Impairment [MCI]/dementia [N = 66]).

Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review.

Background: Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE.

Detecting subtle signs of depression with automated speech analysis in a non-clinical sample.

Background: Automated speech analysis has gained increasing attention to help diagnosing depression. Most previous studies, however, focused on comparing speech in patients with major depressive disorder to that in healthy volunteers. An alternative may be to associate speech with depressive symptoms in a non-clinical sample as this may help to find early and sensitive markers in those at risk of depression.

Screening for Mild Cognitive Impairment Using a Machine Learning Classifier and the Remote Speech Biomarker for Cognition: Evidence from Two Clinically Relevant Cohorts.

Background: Modern prodromal Alzheimer's disease (AD) clinical trials might extend outreach to a general population, causing high screen-out rates and thereby increasing study time and costs. Thus, screening tools that cost-effectively detect mild cognitive impairment (MCI) at scale are needed.

Objective: Develop a screening algorithm that can differentiate between healthy and MCI participants in different clinically relevant populations.

Feasibility Study of an Internet-Based Platform for Tele-Neuropsychological Assessment of Elderly in Remote Areas.

Today, in rural isolated areas or so-called 'medical deserts', access to diagnosis and care is very limited. With the current pandemic crisis, now even more than ever, telemedicine platforms are gradually more employed for remote medical assessment. Only a few are tailored to comprehensive teleneuropsychological assessment of older adults.