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Cognitive Impairment, Dementia and Depression in Older Adults
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Cognitive Impairment, Dementia and Depression in Older Adults

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Geriatric Medicine".

Deadline for manuscript submissions: 20 September 2026 | Viewed by 6711

Editors

Dr. Seong Jae Kim

E-Mail Website
Guest Editor
Department of Psychiatry, Chosun University School of Medicine, Gwangju 61452, Republic of Korea
Interests: sleep, circadian rhythm, and cognitive function in older adults; circadian rhythm; depression in patients with delayed sleep phase disorder (DSPD)
Prof. Dr. Ilhan Choo

E-Mail Website
Guest Editor
Department of Psychiatry, Chosun University School of Medicine, Gwangju 61452, Republic of Korea
Interests: brain imaging in older adults and patients with dementia; the early detection of cognitive decline; identification of Alzheimer’s disease biomarkers; the clinical significance of subjective memory complaints

Special Issue Information

Dear Colleagues,

Cognitive impairment, dementia, and late-life depression are increasingly prevalent among older adults and are often interconnected through shared pathways and overlapping clinical features. Notably, depression is highly comorbid with neurodegenerative diseases such as Parkinson’s disease and is recognized as both a risk factor and an early symptom of dementia.

This Special Issue aims to investigate the approaches to the diagnosis, management, and treatment of cognitive impairment, dementia, and depression in older adults from a clinical perspective.

We invite submissions that integrate clinical and neuropsychological evaluations, and artificial intelligence (AI)-based predictive modeling. Particular interest is given to interdisciplinary approaches bridging medicine and neuroscience, including the development of AI models for predicting depression and Parkinson’s disease, and understanding their shared pathways with dementia.

This Special Issue seeks ​high-quality clinical research that focuses on the interplay between neurodegeneration and mood disorders, machine learning applications in geriatric mental health, and systems-level models of brain aging. By combining data science and clinical insight, this Special Issue seeks to promote innovative strategies for early detection, personalized prediction, and intervention in aging-related cognitive and affective disorders.

Dr. Seong Jae Kim
Prof. Dr. Ilhan Choo
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine 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

  • cognitive impairment
  • dementia
  • depression
  • Parkinson’s disease
  • artificial intelligence (AI)
  • predictive modeling

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Published Papers (3 papers)

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Research

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17 pages, 455 KB  
Article
Associations of Circadian Rhythms with Cognitive Performance in Patients with Amnestic Mild Cognitive Impairment (aMCI)
by Seong Jae Kim, Jung Hie Lee, Jae-Won Jang, Minseo Choi and In Bum Suh
J. Clin. Med. 2026, 15(8), 3023; https://doi.org/10.3390/jcm15083023 - 15 Apr 2026
Viewed by 1108
Abstract
Background/Objectives: Circadian rhythm disruption is linked to cognitive decline, yet it remains unclear how behavioral and physiological rhythm markers are differently associated with cognition in amnestic mild cognitive impairment (aMCI). The primary aim of this study was to compare sleep–wake timing, rest–activity [...] Read more.
Background/Objectives: Circadian rhythm disruption is linked to cognitive decline, yet it remains unclear how behavioral and physiological rhythm markers are differently associated with cognition in amnestic mild cognitive impairment (aMCI). The primary aim of this study was to compare sleep–wake timing, rest–activity rhythm (RAR), and dim light melatonin onset (DLMO) between patients with aMCI and cognitively normal controls. Exploratory analyses further examined their associations with domain-specific cognitive performance. Methods: Eighteen aMCI patients and 21 cognitively normal controls (NC) enrolled. Cognitive function was assessed using the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Battery (CERAD-K). Participants underwent 5-day actigraphy to assess sleep–wake timing and non-parametric RAR variables, including interdaily stability (IS), intradaily variability (IV), and relative amplitude (RA). DLMO was determined from hourly salivary melatonin samples collected over five hours before sleep onset under dim-light conditions. Group comparisons of circadian markers were conducted as the primary analyses, and generalized linear models were used for exploratory analyses of associations between circadian markers and cognitive outcomes. Results: Groups did not significantly differ in sleep–wake timing, RAR parameters and DLMO. Sleep–wake timing variables and DLMO were not significantly associated with cognitive performance. Higher IS was associated with better visuospatial memory and executive function, whereas higher RA was associated with poorer verbal memory among aMCI patients. Conclusions: Although sleep–wake timing and melatonin phase did not differ between groups nor predict cognitive performance, higher daily rhythm stability was linked to better non-verbal memory and executive functioning. In contrast, high RA may relate to poorer verbal memory in aMCI, suggesting that elevated RA may not reflect true circadian robustness required for optimal cognition. Full article
(This article belongs to the Special Issue Cognitive Impairment, Dementia and Depression in Older Adults)
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19 pages, 307 KB  
Article
Epidemiology of Cognitive Impairments: Demographic and Clinical Predictors of Memory and Attention Challenges—Findings from Twelve National Disability Indicators
by Ahmed Alduais, Hind Alfadda and Hessah Saad Alarifi
J. Clin. Med. 2025, 14(18), 6390; https://doi.org/10.3390/jcm14186390 - 10 Sep 2025
Cited by 2 | Viewed by 2502
Abstract
Background: Cognitive difficulties involving memory and concentration significantly affect individuals’ daily functioning and quality of life, influenced by demographic, clinical, and socio-environmental factors. This study aimed to examine the national prevalence and distribution of cognitive difficulties in Saudi Arabia, explore regional and [...] Read more.
Background: Cognitive difficulties involving memory and concentration significantly affect individuals’ daily functioning and quality of life, influenced by demographic, clinical, and socio-environmental factors. This study aimed to examine the national prevalence and distribution of cognitive difficulties in Saudi Arabia, explore regional and gender disparities, and identify demographic and clinical predictors. Methods: Data were obtained from the 2017 Saudi National Disability Survey, a population-based, cross-sectional study involving 20.4 million Saudi citizens. Twelve indicators related to cognitive difficulty—covering severity, educational and marital status, consanguinity, duration, causes, and regional distribution—were analyzed, integrating baseline population data from three national surveys. Results: Results indicated that 1.1% (224,408 individuals) reported cognitive difficulties, predominantly alongside other disabilities (1.0%), while only 0.2% reported it exclusively. Cognitive difficulties were significantly higher in Al-Riyadh and Makkah Al-Mokarramah, with residents of Aseer and Hail facing doubled odds compared to Najran. Gender disparities were evident; males predominated in extreme severity and congenital or accident-related cases, whereas females showed higher proportions of disease-related causes, mild severity, and prolonged disability (≥25 years). Independent predictors included severe and extreme severity, disease-related causes, consanguinity, and long duration. Conclusions: These findings highlight critical regional and gender-based inequities and underscore the need for targeted policies emphasizing early detection, gender-sensitive interventions, and region-specific resource allocation to meet Saudi Arabia’s Vision 2030 objectives for inclusive health and social services. Full article
(This article belongs to the Special Issue Cognitive Impairment, Dementia and Depression in Older Adults)

Review

Jump to: Research

15 pages, 319 KB  
Review
Cognitive Impairment, Dementia and Depression in Older Adults
by Yoo Jin Jang, June Ho Chang, Daa Un Moon and Hong Jin Jeon
J. Clin. Med. 2026, 15(3), 1198; https://doi.org/10.3390/jcm15031198 - 3 Feb 2026
Cited by 7 | Viewed by 2645
Abstract
This narrative review integrates longitudinal cohort studies, neuroimaging and biomarker research, and major clinical trials to examine how depression and cognitive decline interact across the dementia continuum. Depression and cognitive impairment frequently co-occur in late life and exhibit substantial clinical and biological overlap. [...] Read more.
This narrative review integrates longitudinal cohort studies, neuroimaging and biomarker research, and major clinical trials to examine how depression and cognitive decline interact across the dementia continuum. Depression and cognitive impairment frequently co-occur in late life and exhibit substantial clinical and biological overlap. Meta-analytic and large population-based cohort studies consistently show that late-life depression increases the risk of mild cognitive impairment and dementia, with stronger associations observed for vascular dementia than for Alzheimer’s disease. Neurobiological studies implicate cerebrovascular pathology, neuroinflammation, hypothalamic–pituitary–adrenal axis dysregulation, and fronto-subcortical circuit dysfunction as key mechanisms linking depressive symptoms to later cognitive decline. In a subset of older adults, new-onset depression—particularly when accompanied by executive dysfunction, subjective cognitive decline, or high white-matter hyperintensity burden—are associated with an increased likelihood of near-term cognitive decline and dementia, although evidence for a definitive prodromal state remains limited. Depression is also highly prevalent as part of the behavioral and psychological symptoms of dementia, occurring in 30–50% of individuals with Alzheimer’s disease and even higher proportions in dementia with Lewy bodies or frontotemporal dementia. Comorbid depression in dementia accelerates cognitive and functional decline, increases neuropsychiatric burden, and worsens quality of life for patients and caregivers. Therapeutically, antidepressant treatment may confer modest benefits on mood and selected cognitive domains (e.g., processing speed and executive function) in non-demented older adults, whereas in established dementia, antidepressant efficacy is limited. In contrast, cholinesterase inhibitors, memantine, and multimodal non-pharmacological interventions yield small but measurable improvements in depressive or apathy-related symptoms. Emerging disease-modifying therapies for Alzheimer’s disease have demonstrated cognitive benefits, but current trial data provide insufficient evidence regarding effects on depressive symptoms, highlighting an important gap for future research. These findings underscore the need for stage-specific, integrative strategies to address the intertwined trajectories of mood and cognition in aging. Full article
(This article belongs to the Special Issue Cognitive Impairment, Dementia and Depression in Older Adults)
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