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Diagnostics
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Neurodiagnostics in Public Health: Cognitive Decline, Mental Health, and Emerging...
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Neurodiagnostics in Public Health: Cognitive Decline, Mental Health, and Emerging Technologies

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2033

Special Issue Editors

Dr. Evgenia Gkintoni

E-Mail Website
Guest Editor
Department of Psychiatry, University General Hospital of Patras, 26504 Patras, Greece
Interests: clinical psychology; neuropsychology; cognitive neuroscience; psychopathology; neuroeducation; psychotherapeutic processes; applied psychology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Apostolos Vantarakis

E-Mail Website
Guest Editor
Department of Public Health, School of Medicine, University of Patras, Patras, Greece
Interests: environmental health; environmental microbiology; epidemiology of foodborne and waterborne diseases; risk assessment; molecular epidemiology; environmental virology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neurocognitive disorders such as dementia, mild cognitive impairment (MCI), and neuropsychiatric diseases are increasing globally and impose a substantial burden on healthcare systems and public health policy. Their detection in the earliest stages and precise diagnosis are important for early intervention and better patient outcomes.

This Special Issue covers the interface between neurodiagnostics, public health, and cognitive neuroscience with a focus on new diagnostic approaches, psychological testing, and influences of environmental and epidemiological factors on cognitive capacity. Developments in biomarkers, artificial intelligence, digital diagnosis, and public health interventions provide encouraging avenues for early detection and intervention.

We invite original studies, systematic reviews, and clinical case studies examining novel diagnostic strategies that harness the strengths of neuropsychology, cognitive neuroscience, and public health frameworks.

Topics of Interest Include:

  • Cognitive Neuroscience and Neuropsychology:
    • Novel neuropsychological tools for early cognitive impairment detection;
    • The relationship between cognitive decline and psychiatric disorders (e.g., depression, anxiety, or schizophrenia);
    • Cognitive dysfunction in post-viral syndromes (e.g., post-COVID-19 cognitive impairment).
  • Biomarkers and Imaging in Neurodiagnostics:
    • Advances in neuroimaging (fMRI, PET, EEG) for diagnosing cognitive disorders;
    • Blood-based and cerebrospinal fluid biomarkers for neurodegenerative diseases;
    • Multi-omics approaches (genomics, proteomics, and metabolomics) in cognitive decline.
  • Public Health and Epidemiological Aspects of Cognitive Decline:
    • Environmental risk factors for cognitive impairment (air pollution, toxins, or infections);
    • Public health screening programs for the early detection of dementia and neurodegenerative diseases;
    • Socioeconomic and lifestyle determinants of cognitive health.
  • Digital and AI-Driven Diagnostics:
    • AI and machine learning applications in cognitive assessment and early diagnosis;
    • Wearable and mobile technologies for cognitive monitoring;
    • Digital biomarkers and remote neuropsychological testing.

By bringing together cognitive neuroscience, clinical neuropsychology, and public health, this Special Issue seeks to drive early diagnostic solutions for neurocognitive and neuropsychiatric disorders. It will deliver a roadmap for how interdisciplinarity can lead to more accurate, affordable, and scalable diagnostics.

You may choose our Joint Special Issue in Healthcare.

Dr. Evgenia Gkintoni
Prof. Dr. Apostolos Vantarakis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neurocognitive disorders
  • dementia
  • mild cognitive impairment (MCI)
  • neuropsychiatric diseases
  • biomarkers
  • imaging
  • artificial intelligence
  • digital diagnosis

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Published Papers (3 papers)

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Research

13 pages, 242 KB  
Article
Increased Worry Associated with Self-Reported, but Not Informant-Reported, Subjective Cognitive Decline Predicts Increased Risk of Incident Dementia
by Katya T. Numbers, Ben C. P. Lam, Suraj Samtani, Russell J. Chander, Ashleigh S. Vella, Perminder S. Sachdev and Henry Brodaty
Diagnostics 2025, 15(23), 3073; https://doi.org/10.3390/diagnostics15233073 - 3 Dec 2025
Viewed by 289
Abstract
Background: Subjective cognitive complaints (SCC) have emerged as an important predictor of future dementia, with the SCD-plus framework emphasizing the prognostic value of cognitive concern and informant corroboration. Most research has focused on the presence or persistence of concern rather than examining [...] Read more.
Background: Subjective cognitive complaints (SCC) have emerged as an important predictor of future dementia, with the SCD-plus framework emphasizing the prognostic value of cognitive concern and informant corroboration. Most research has focused on the presence or persistence of concern rather than examining trajectories of change over time. Objective: To determine if baseline levels and longitudinal trajectories of SCC concern from both participants and informants independently predict incident dementia over 10 years. Methods: Data were from 873 community-dwelling older adults (mean age 78.65 years) in the Sydney Memory and Ageing Study. Employing latent growth curve modelling, we analyzed binary SCC and concern variables. Cox proportional hazards models examined the association between concern trajectories and incident dementia over a 10-year follow-up, controlling for demographic and clinical factors. Results: Both participant-reported (Hazard Ratio [HR] = 1.21) and informant-reported (HR = 1.32) SCC concern at baseline independently predicted dementia risk. Notably, increasing participant SCC concern over time conferred substantial additional risk (HR = 10.23), while changes in informant concern did not significantly improve dementia risk prediction. Conclusions: Both participant and informant reports of SCC concern provide valuable but distinct prognostic information for dementia risk. The substantial predictive value of increasing participant concern over time highlights the importance of monitoring subjective cognitive experiences longitudinally. These findings support the clinical utility of tracking concern trajectories and suggest that the patient’s evolving perspective may be particularly sensitive to underlying pathological processes. Full article
(This article belongs to the Special Issue Neurodiagnostics in Public Health: Cognitive Decline, Mental Health, and Emerging Technologies)
10 pages, 579 KB  
Article
Cross-Cultural Adaptation and Psychometric Validation of the Polish Version of Rowland Universal Dementia Assessment Scale (RUDAS)
by Monika Piotrowska-Matyszczak, Joanna Furman, Mateusz Roszak, Julia Żurawkowa and Beata Łabuz-Roszak
Diagnostics 2025, 15(23), 3005; https://doi.org/10.3390/diagnostics15233005 - 26 Nov 2025
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Abstract
Background: There is a growing demand for sensitive and accurate screening tools for the early detection of cognitive impairment. The Rowland Universal Dementia Assessment Scale (RUDAS) has shown promise in multicultural populations. It may offer advantages over the widely used Mini-Mental State [...] Read more.
Background: There is a growing demand for sensitive and accurate screening tools for the early detection of cognitive impairment. The Rowland Universal Dementia Assessment Scale (RUDAS) has shown promise in multicultural populations. It may offer advantages over the widely used Mini-Mental State Examination (MMSE), which has limited sensitivity, particularly in assessing executive functions. The aim of this study was to adapt and validate the Polish version of the RUDAS and to compare its diagnostic performance with the MMSE in detecting cognitive impairment among patients with Alzheimer’s disease (AD) and vascular dementia (VaD). Methods: A total of 126 subjects were evaluated, including 37 with AD, 30 with VaD, and 59 healthy controls. All participants were assessed with both the MMSE and RUDAS, and their test results were subsequently compared. Results: A strong correlation was found between total scores on the RUDAS and MMSE (RS = 0.81, p < 0.001). The area under the ROC curve was slightly higher for RUDAS (AUC = 0.94) than for MMSE (AUC = 0.89), suggesting better diagnostic accuracy. At a cut-off score of 25, RUDAS showed a sensitivity of 0.84 and a specificity of 0.87; MMSE showed a sensitivity of 0.74 and a specificity of 0.91. Conclusions: The Polish version of RUDAS demonstrates strong diagnostic utility and may offer a slightly more sensitive alternative to MMSE for dementia screening, especially in its early stages. Further normalization studies on larger and more diverse clinical populations are recommended. Full article
(This article belongs to the Special Issue Neurodiagnostics in Public Health: Cognitive Decline, Mental Health, and Emerging Technologies)
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17 pages, 587 KB  
Article
Normative Data for the Montreal Cognitive Assessment (MoCA) in Mexican Adults: A Regression-Based Approach
by Lorena Parra-Rodríguez, Juan Silva-Pereyra, Sergio Sánchez-García, Carmen García-Peña, Juan Francisco Flores-Vázquez and Paloma Roa-Rojas
Diagnostics 2025, 15(22), 2920; https://doi.org/10.3390/diagnostics15222920 - 19 Nov 2025
Viewed by 1035
Abstract
Background/Objectives: The Montreal Cognitive Assessment (MoCA) is a widely used cognitive screening tool designed to detect cognitive impairment. However, evidence indicates that the original cut-off score of 26 and the one-point correction for low education may not be appropriate across diverse populations. In [...] Read more.
Background/Objectives: The Montreal Cognitive Assessment (MoCA) is a widely used cognitive screening tool designed to detect cognitive impairment. However, evidence indicates that the original cut-off score of 26 and the one-point correction for low education may not be appropriate across diverse populations. In Latin America, and particularly in Mexico, existing validation studies are scarce and limited by small sample sizes. The objective of this study was to examine the effects of age and education on MoCA performance in Mexican adults and to develop regression-based normative data for more accurate interpretation. Methods: MoCA performance of 2546 cognitively healthy participants aged 18–99 years from two public health institutions in Mexico City was analyzed. Inclusion criteria required preserved cognition, functionality, independence, and absence of conditions directly affecting brain health. The Spanish version 8.1 of the MoCA was administered. Age-adjusted normative values were obtained. Then, regression analyses were applied to generate age- and education-adjusted norms. Results: MoCA total scores correlated negatively with age and positively with education, while sex showed no significant effect. Regression-based norms revealed that identical raw total scores have different normative interpretations depending on age and education. Conclusions: This study provides the first regression-based MoCA norms for Mexican adults, demonstrating that both age and education exert a substantial influence on test performance. These norms enable a more precise, culturally sensitive interpretation than fixed cut-off scores and reduce the risk of misclassification in clinical and research settings. Full article
(This article belongs to the Special Issue Neurodiagnostics in Public Health: Cognitive Decline, Mental Health, and Emerging Technologies)
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