Tag: Academic research

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Early Detection of Alzheimer’s Disease and Related Dementias From Spontaneous Speech Using Foundation Speech and Language Models: Comparative Evaluation

<strong>Background:</strong> Alzheimer’s disease and related dementias (ADRD) are progressive neurodegenerative conditions where early detection is critical for timely intervention and care planning. However, current diagnostic methods are often inaccessible, costly, and delayed, especially for underserved populations. There is a growing need for scalable, noninvasive tools that can support timely diagnosis. Spontaneous speech contains rich acoustic and linguistic markers that can serve as noninvasive behavioral markers for cognitive decline. Foundation models, pretrained on large-scale audio or text data, generate high-dimensional embeddings that encode rich contextual and acoustic information. <strong>Objective:</strong> This study benchmarks open-source foundation language and speech models to evaluate their effectiveness in detecting ADRD from spontaneous speech as a potential solution for early, noninvasive, and scalable ADRD detection. <strong>Methods:</strong> In this study, we used the Pioneering Research for Early Prediction of Alzheimer’s and Related Dementias EUREKA (PREPARE) Challenge dataset, which consists of audio recordings from over 1600 participants with 3 distinct categories of cognitive decline: healthy control (HC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD). We further excluded samples that are non-English, nonspontaneous speech, or of poor quality. Our final samples included 703 (59.13%) HC, 81 (6.81%) MCI, and 405 (34.06%) AD cases. We systematically benchmarked 18 open-source foundation speech and language models to classify cognitive status into 3 categories (HC, MCI, or AD). Post hoc interpretability analysis was performed for the best-performing model using Shapley additive explanations linking high-dimensional embeddings with explainable acoustic and linguistic markers. <strong>Results:</strong> Whisper-medium model achieved the highest performance among speech models at 0.731 accuracy and 0.802 area under the curve, while Bidirectional Encoder Representations from Transformers with pause annotation achieved the top accuracy of 0.662 and 0.744 area under the curve among language models. Overall, ADRD detection based on state-of-the-art automatic speech recognition model-generated audio-embeddings outperformed other models, and the inclusion of nonsemantic information, such as pause patterns, consistently improved the classification performance of text-embedding–based models. <strong>Conclusions:</strong> Our work presents a comprehensive comparative evaluation of state-of-the-art speech and language models for AD and MCI detection on a large, clinically relevant dataset. Embeddings derived from acoustic models, which capture both semantic and acoustic information, show promising performance and highlight the potential for developing a more scalable, noninvasive, and cost-effective early detection tool for ADRD.
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iCARE Self-Guided Digital Intervention for Postpartum Depression in Danish Mothers: Formative Research Using User-Centered Design

<strong>Background:</strong> Postpartum depression (PPD) is a major public health concern. Despite advancements in treatment, many barriers to accessing care remain. There has been a growing interest in digital interventions for the prevention and treatment of PPD. However, for mothers with mild and moderate symptoms of depression, there is a limited offer of self-guided internet-based interventions developed with user input and with considerations on how to integrate the intervention into stepped care models for PPD. <strong>Objective:</strong> The aim of this study was (1) to describe the process of the design and development of iCARE, a self-guided digital psychological intervention for mothers with mild and moderate symptoms of PPD in Denmark, (2) present the program’s theory illustrated by a logic model, and (3) explore its initial usability and prospective acceptability. <strong>Methods:</strong> Applying user-centered design methods, the intervention development followed six steps: (1) a literature review to identify evidence‑based therapeutic components of self‑guided interventions for PPD, (2) interviews with women with lived experience of PPD and group discussions with mental health experts and home‑visiting providers to identify user needs, (3) iterative design and content development with stakeholder feedback in collaboration with the Department of Digital Psychiatry, (4) prototype testing using think‑aloud usability sessions and interviews with 5 mothers, (5) a group cognitive walkthrough with mental health experts, and (6) final refinement and implementation of the iCARE program with developers and designers. <strong>Results:</strong> Initial interviews with mothers and maternal health care providers emphasized the importance of a digital intervention offering timely psychoeducation, coping strategies, and pathways to in-person care while addressing the diversity of expressions of PPD symptoms. Stakeholders recommended a flexible program, multimodal content, and integration into maternal care systems with community health nurses supporting engagement and participation. The prototype was designed to be user-centered, engaging, and with multiple interactive features. It included components on psychoeducation, cognitive exercises grounded in cognitive behavioral therapy, acceptance and commitment principles, and mood-monitoring. The prototype was designed to be user-centered and engaging, with interactive features and components on psychoeducation, cognitive exercises grounded in cognitive behavioral and acceptance and commitment principles, and mood-monitoring. Prototype testing indicated high prospective acceptability and led to refinements across 6 themes: appropriateness of content; motivation and engagement; inclusivity and gender representation; clarity of instructions and data use; understanding of therapeutic method; and usability, layout, and navigation. <strong>Conclusions:</strong> iCARE is a self-guided internet-based psychological intervention for mothers with mild and moderate symptoms of PPD in Denmark. It was developed with user input by using qualitative methods, user-centered design, and psychological theory. Further research is needed to evaluate the feasibility and effectiveness of the program in a randomized controlled trial and its integration into maternal health care models such as universal PPD screening and home-visiting.
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Federated training of spiking neural networks on edge hardware for audio processing

Spiking Neural Networks have caught significant attention recently for their potential for energy-efficient computation on neuromorphic hardware and their event-driven processing. Spiking Neural networks employ spike-based learning paradigms, which require specialized training procedures such as Surrogate Gradient Descent. At the same time, Federated Learning allows collaborative model training on decentralized devices with preservation of data privacy protection. However, to date, few research has examined the suitability of Federated learning with ARM-based hardware. This work primarily investigates whether Federated Spiking Neural Networks training on ARM-based hardware is feasible with the Raspberry Pi 5 as a widely available and low-cost edge computing device for audio signal processing tasks. We perform a comparative analysis of federated Spiking Neural Network and federated convolutional neural networks on ARM processors and evaluate their performance on different data partitioning strategies using Dirichlet-based splits and various federated averaging algorithms. Using Federated learning, this work investigates the impact of data heterogeneity and aggregation strategies on model convergence, communication overhead, and latency in distributed training paradigms. The results provided showcases the important insights into the trade-offs of FL-SNN implementations on Von Neumann architectures and their applications in decentralized neuromorphic computing for audio processing.
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Roles of NRXN1 in neuropsychiatric disorders: from genetic lesion to molecular mechanism

Numerous neuropsychiatric disorders frequently exhibit overlapping genetic risk factors, implying the molecular basis for their comorbidity. Nevertheless, the pathogenesis of these disorders remains elusive, particularly regarding how genetic variations impair the physiological function of risk genes and contribute to disease phenotypes. Neurexin 1 protein, encoded by NRXN1 gene, belongs to the neurexin family of presynaptic adhesion molecules. And neurexin 1 is involved in synaptogenesis and the maintenance of synaptic action. Genetic variations of NRXN1 have been demonstrated to be associated with a spectrum of neuropsychiatric disorders. Herein, this review focuses on the most recent and relevant literature concerning the genetic and molecular mechanisms through which NRXN1 variants contribute to the pathogenesis of neuropsychiatric disorders, particularly schizophrenia and autism spectrum disorder. Among them, we propose the isoform-dependent excitation-inhibition imbalance hypothesis of NRXN1 in autism spectrum disorder. And this hypothesis may account for both the elevated and decreased excitation-inhibition ratios observed in diverse individuals with autism spectrum disorder. Moreover, both schizophrenia and autism spectrum disorder involve deletions and alternative splicing of NRXN1, offering molecular evidence for their comorbidity. Then, we analyzed and summarized the current research status of NRXN1 in other neuropsychiatric disorders, including attention-deficit hyperactivity disorder, insomnia, epilepsy, suicide, and depression. Additionally, available limited researches on NRXN1-targeted therapeutic strategies and associated pharmacological studies are also incorporated. Finally, we discussed existing challenges in NRXN1 research within the context of neuropsychiatric disorders and proposed potential avenues to overcome these obstacles.
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Romanian male patients with the dual diagnosis of schizophrenia and alcohol use disorder: a prospective study of clinical, social, and treatment-related factors affecting quality of life

BackgroundSchizophrenia frequently co-occurs with alcohol use disorder (AUD), resulting in a complex clinical profile associated with poor functional outcomes and reduced quality of life (QoL). Although both conditions independently impair psychosocial functioning, few studies have examined the combined effects of clinical, social, and treatment-related factors on QoL in patients with this dual diagnosis.MethodsThis prospective observational study included 88 male inpatients diagnosed with schizophrenia and comorbid AUD and who were followed over a 6-month period. Quality of life was assessed using the World Health Organization Quality of Life–BREF (WHOQoL–BREF). The clinical variables included severity of psychotic symptoms (Positive and Negative Syndrome Scale), alcohol use severity (Michigan Alcohol Screening Test), and treatment characteristics. Social and personal factors, such as self-care capacity, social support, education, and legal problems, were also evaluated. Multivariable regression analyses were conducted to identify predictors of QoL at baseline and follow-up.ResultsAt baseline, higher QoL was significantly associated with greater self-care capacity, social support, and higher positive symptom scores, while the need for antipsychotic treatment was associated with lower QoL. At the 6-month follow-up, better QoL was predicted by greater self-care capacity, higher educational level, and receipt of anti-craving medication. By contrast, negative and general psychopathology, medico-legal problems, and the need for antidepressant treatment were associated with poorer QoL. Alcohol use severity, as measured by the MAST, was not independently associated with QoL at either timepoint.ConclusionsIn patients with schizophrenia and comorbid AUD, QoL is shaped by a complex interaction of clinical severity, functional capacity, and treatment-related factors. Beyond symptom control, interventions targeting self-care, social functioning, and integrated addiction treatment appear essential to improve long-term outcomes. These findings support the implementation of a multidimensional, recovery-oriented approach for the management of patients with the dual diagnosis.
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Assessing directional connections between symptoms, cognition, insight, and real-life functioning in schizophrenia: a partial ancestor graphs analysis

IntroductionSchizophrenia is a severe chronic mental disorder causing significant global disability. Understanding the intricate relationships between symptoms, cognitive functions, and real-life outcomes is essential for developing effective interventions. Prior research, while informative, could not often determine the direction of the association between these illness-related factors. This study aimed to investigate the possible causal connections within the interrelationships of these variables. MethodsThis cross-sectional study included 215 clinically stable patients diagnosed with schizophrenia. Comprehensive assessments covered psychopathology, neurocognition, social cognition, metacognition, clinical insight, and real-life functioning. Causal relationships were explored using Partial Ancestral Graphs, a causal discovery framework that accounts for mediators and confounders. The Greedy Fast Causal Inference algorithm was employed with 1,000 bootstrap replications to assign edge orientations.ResultsA central neurocognitive–metacognitive–functional system of directed connection emerged: visual learning was linked to attention/vigilance and working memory. Working memory showed a direct relationship with metacognition, which, in turn, was connected to real-life functioning. Two partly independent contributions to real-life functioning were also identified: conceptual disorganization and experiential negative symptoms, which were directly related to expressive deficits. Positive symptoms, depressive symptoms, and social cognition occupied peripheral positions, showing no significant connection with other variables. Unawareness and misattribution of symptoms showed an indeterminate association disconnected from the main network.DiscussionThe findings show a set of directed associations that start with neurocognitive abilities, pass through working memory and metacognition, and terminate in real-life functioning. Independently, conceptual disorganization and expressive negative symptoms also exert direct influences. These directed systems of connections provide operational guidance for clinical practice, highlighting critical targets for interventions such as cognitive remediation focused on working memory, metacognitive therapies, and strategies addressing disorganization and avolition, all aimed at improving real-life outcomes in schizophrenia.
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Internalizing and externalizing pathways to internet gaming disorder: the roles of anger and social anxiety

BackgroundInternet Gaming Disorder (IGD) represents a significant behavioral health concern, yet the roles of internalizing and externalizing psychological vulnerabilities in its development remain underexplored, particularly in Arabic-speaking populations.ObjectiveThis study examined anger and social anxiety as distinct externalizing and internalizing predictors of IGD severity in a Saudi Arabian community sample.MethodsA cross-sectional survey was administered to 303 participants (60.1% female; estimated mean age = 29.79 years, SD = 8.83) across five regions of Saudi Arabia. Participants completed the Internet Gaming Disorder Scale–Short Form (IGDS9-SF), a three-item Anger Screening Scale, and a two-item Social Anxiety screener. Hierarchical linear regression and structural equation modeling (SEM) were conducted to examine unique and incremental contributions of anger and social anxiety to IGD symptoms.ResultsAnger and social anxiety were strongly intercorrelated (r = .86, p <.001) but demonstrated divergent patterns in multivariate models. Hierarchical regression indicated that both predictors contributed unique variance when entered simultaneously, with anger positively and social anxiety negatively predicting IGD after controlling for shared variance. However, SEM clarified that only social anxiety significantly predicted latent IGD severity (β = .32, p = .027), whereas anger did not (β = .07, p = .68). The final model explained approximately 13% of variance in IGD symptoms.ConclusionsSocial anxiety was associated with IGD severity as a distinct internalizing correlate, consistent with avoidance-based coping and online social preference accounts. These preliminary, cross-sectional findings suggest that social anxiety warrants consideration in future IGD screening and research efforts in Arabic-speaking contexts.
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Perception of social support and psychological well-being among mothers of individuals with intellectual disabilities: the mediating role of self-efficacy

BackgroundThe aim of this study is to examine the mediating role of self-efficacy in the relationship between social support perception and psychological well-being among mothers of individuals with intellectual disabilities.MethodsA correlational survey model was used in this study in line with the research objectives. The study group consisted of mothers of individuals with intellectual disabilities (n=80) in two central districts of Malatya province. Convenience sampling was employed in the study. The Psychological Well-being Scale was used to measure the psychological well-being of the participating mothers, the “Perceived Support Scale for Families of Children with Disabilities” was used to measure their perceived levels of social support, and the “Parental Self-Efficacy Scale” was used to measure their self-efficacy. In addition, a personal information form was used to introduce the socio-demographic characteristics of the participants. Descriptive statistics were calculated for the variables, and the normality assumption was examined using the Kolmogorov-Smirnov and Shapiro-Wilk tests. The relationships between the variables were evaluated using Pearson’s product-moment correlation analysis. Mediation analyses were performed using the PROCESS Macro (Model 4) developed by Hayes, and the significance of indirect effects was tested using the bootstrap method (5000 samples). The internal consistency reliability of the scales used in this study sample was assessed using Cronbach’s alpha coefficient.ResultsThere are positive and significant relationships between each of the perceived social support sub-dimensions of appreciation, informational, emotional, and companionship and self-efficacy (r = 0.28–0.36; p <0.05). A positive and significant relationship was also found between the total perceived social support score and self-efficacy (r = 0.37, p <0.01). In contrast, no direct significant relationships were found between perceived social support and its sub-dimensions and psychological well-being (p> 0.05). Psychological well-being showed only a moderate, positive and significant relationship with self-efficacy (r = 0.45, p <0.01).ConclusionsIn conclusion, it can be said that the relationship between perceived social support and psychological well-being is not direct, but indirect, mediated by self-efficacy.
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From cats to cortex: T. gondii and psychosis, depression, and anxiety

This review examines whether cat ownership, via exposure to the neurotropic parasite T. gondii, contributes to vulnerability for psychotic, depressive, and anxiety symptoms. T. gondii establishes lifelong latent infection in the brain and muscle, where it can modulate dopaminergic signaling, neuroinflammation, and tryptophan–kynurenine metabolism, providing a biologically plausible pathway to altered cognition, mood, and behavior. Epidemiological and meta-analytic data indicate small-to-moderate associations between T. gondii seropositivity and schizophrenia, with more variable but suggestive links to depression and anxiety. Evidence for cat ownership as an independent risk factor is inconsistent: some cohorts and recent meta-analyses report elevated odds of schizophrenia-related outcomes in those exposed to cats, whereas rigorously controlled studies frequently find attenuated or null effects. Methodological limitations, alternative explanations, and cultural implications are discussed, and priorities for mechanism-informed, longitudinal and interventional research are outlined.