Giorgio Colombo

Background: Falls and fractures are a major clinical concern for older adults. International clinical guidelines recommend annual fall risk screening for all adults aged 60 years and older. However, existing falls risk–screening algorithms have shown limited sensitivity and specificity in detecting future falls. Emerging health technologies, including wearable sensors, in-silico finite element models (FEMs), and virtual reality (VR) technology, show promise in enhancing fall and fracture risk assessments by providing more personalized objective data to support targeted primary prevention. However, large-scale longitudinal studies are required to evaluate their predictive accuracy and cost-effectiveness for systematic community–based screening. Objective: The TARGET (Targeted Assessment and Recruitment of Geriatrics for Effective Fall Prevention Treatments) study is an ongoing national prospective cohort study in Singapore designed to develop cost-effective and scalable frameworks for the early detection and prevention of falls and fractures using novel health technologies. This paper describes the rationale, design, and baseline characteristics of TARGET, and provides preliminary insights into how these novel technologies perform in discriminating between older adults with and with no history of falls at study baseline. Methods: A total of 2291 community-dwelling Singapore residents aged ≥60 years were enrolled between 2022 and 2024. Participants underwent a comprehensive baseline fall risk assessment comprising (1) home-based interview to assess sociodemographic, anthropometric, cognitive, physical, functional, and psychosocial status; (2) gait assessment using wearable inertial measurement units (IMUs) motion sensors; (3) dual-energy X-ray absorptiometry and whole-body 3D scans to construct subject-specific FEMs; and (4) VR-based cognitive assessment to probe spatial navigation deficits. Prospective follow-up for 2 years is ongoing, with linkage to national electronic medical records (EMRs) to obtain detailed clinical, medication, and pathological data. Results: Of the total cohort, 58% (1327/2291) were female, with a mean age of 74.6 years at baseline. TARGET represents a relatively healthy older adult population, with 83% (1898/2291) remaining fully independent, 44% (1016/2290) with mild cognitive impairment, 50% (440/879) with osteopenia, and 15% (358/2291) reporting falls in the past year. Significant baseline functional, psychosocial, cognitive, and biomechanical differences were identified between fallers and nonfallers. Fallers had poorer physical and psychosocial health, greater gait variability, and a higher risk of osteoporotic fractures. Novel risk prediction models integrating epidemiological, IMUs, FEM, VR, and EMR data are in development and being validated against gold standard clinical assessments, with cost-effectiveness evaluations of the economic feasibility of adopting these screening measures at scale. Conclusions: Leveraging comprehensive epidemiological, EMR, and health technology data, TARGET is well positioned to identify novel biomarkers and systemic interactions that may predict falls and fracture risk, with potential application to other age-related diseases with shared pathophysiology. In particular, TARGET’s focus on community-based screening using technologies that can be administered by nonclinical personnel has the potential to reduce substantial burden and costs within the health care sector.

Background: The Clinical Dementia Rating (CDR) scale is widely used for staging mild cognitive impairment (MCI) and dementia but suffers from lengthy administration time (45–60 min). The Montreal Cognitive Assessment (MoCA; 10–15 min) and Quick Dementia Rating System (QDRS; 3–5 min) are promising brief alternatives, although it remains unclear which tool performs better in discriminating between cognitive and functional impairment stages. Objective: To compare the performance of the QDRS and MoCA in identifying MCI, dementia, and individuals eligible for disease modifying therapies and clinical trials (DMTT). Methods: 376 older adults (34.8% NCI, 33.0% MCI, 32.2% dementia) recruited from the memory clinic (n = 284, 75.5%) and community (n = 92, 24.5%) in Singapore completed the QDRS, MoCA, and CDR. No cognitive impairment (NCI), MCI, and dementia were staged as CDR-Global Scores (CDR-GS) of 0, 0.5, and ≥1, respectively. The DMTT subgroup was defined as CDR-GS of 0.5–1. Discriminative performance was determined by area under the curve (AUC) and compared using DeLong's test. Agreement with CDR classifications was determined on McNemar's test. Results: Both QDRS and MoCA demonstrated fair-to-excellent discrimination across CDR-staged groups (MCI: AUC 0.79–0.84; Dementia: AUC 0.92–0.97; DMTT: AUC 0.85–0.91), with no significant differences in discrimination observed. The QDRS correctly identified a greater proportion of MCI (55.6% versus 19.4%; p < 0.001) and DMTT (58.9% versus 41.7%; p < 0.001) versus the MoCA. Conclusions: The QDRS and MoCA are practical brief alternatives to the CDR. The QDRS was advantageous for identifying MCI and DMTT, whereas both were effective screening tools for dementia.

Purpose: Navigational ability develops throughout childhood alongside the maturation of brain regions supporting egocentric and allocentric processing. In Autism Spectrum Disorder (ASD), atypical hippocampal development may impact flexible spatial memory; however, findings on navigational ability in autistic children remain inconsistent. This study aimed to compare both objective and perceived navigation ability in children with ASD and typically developing (TD) peers. Method: Twenty-six children with high-functioning ASD and twenty-five age- and gender-matched TD children (M_age = 12.04 years, SD = 1.64) completed a battery of navigational tasks from the Spatial Performance Assessment for Cognitive Evaluation (SPACE), including Path Integration, Egocentric Pointing, Mapping, Associative Memory, and Perspective Taking. Perceived navigation ability was assessed using the Santa Barbara Sense of Direction (SBSOD) scale. Results: No significant group differences were observed across any objective navigation tasks. However, children with ASD reported significantly lower perceived navigation ability compared to TD peers. Conclusion: These findings suggest a dissociation between perceived and actual navigational ability in ASD. By early adolescence, objective navigation performance appears intact, potentially reflecting sufficient maturation of underlying neural systems or the presence of compensatory mechanisms. The results underscore the importance of incorporating objective, task-based measures when assessing cognitive abilities in autistic populations. Key words: Spatial cognition, Neurodevelopment, Sense of direction, Self-perception

Early detection of Cognitive Impairment (CI) is critical for timely intervention, preservation of independence, and reducing the burden of dementia. Yet, most screening tools remain lengthy, clinic-based, and poorly suited for large-scale unsupervised deployment. This paper evaluates the test-retest reliability, validity, and usability of mini-SPACE, a short iPad-based serious game for detecting early signs of CI. Participants played mini-SPACE at home without supervision once a week for three weeks, with a longer version of the game in the final week. Mini-SPACE showed good test-retest reliability in unsupervised settings. While younger age was the primary predictor of performance, usability, and cognitive load, participants of all ages were able to complete the tasks and reported good usability and low cognitive load. Importantly, the prediction of scores in the Montreal Cognitive Assessment (MoCA) improved with repeated measures. These findings highlight mini-SPACE as a promising digital marker for scalable, age-sensitive screening and potential longitudinal tracking of CI.

Navigation impairments emerge early in Alzheimer’s disease, but assessments targeting these deficits remain underutilised or impractical for cognitive screening. The Spatial Performance Assessment for Cognitive Evaluation (SPACE) is a digital tool that evaluates spatial navigation deficits associated with cognitive impairment. In a memory clinic and community cohort (n = 300), SPACE reliably distinguished Clinical Dementia Rating levels, exceeding the accuracy of demographic models and matching or surpassing most traditional neuropsychological tests. Including SPACE significantly increased the AUC for distinguishing between no dementia from mild dementia (0.76 to 0.94), no dementia from moderate dementia (0.79 to 0.95), and questionable dementia from mild dementia (0.70 to 0.91), all with consistently high sensitivity and specificity. A short version of SPACE (< 11 minutes) reduced administration time by 40% while maintaining high diagnostic accuracy. These findings highlight the potential of digital navigation assessments to advance early detection, contributing to scalable and accessible healthcare.

Background: Blood-brain barrier (BBB) dysfunction is suggested to be a potential mediator between vascular risk factors and cognitive impairment, leading to vascular cognitive impairment. Objective: To investigate the relationships between age, sex, and vascular risk factors and BBB water permeability as well as their relationship with cognition. Methods: To measure BBB permeability, a novel arterial spin labelling MRI technique (ME-ASL) was applied to derive the time of exchange (Tex), arterial time transit (ATT), and cerebral blood flow (CBF). The association of potential risk factors, such as age, sex, body mass index (BMI), blood pressure (BP), and medical history, with these BBB parameters were assessed in 144 community-dwelling adults (median age 59 years, 57% females). The relationship between BBB permeability and cognitive performance measured by the Montreal Cognitive Assessment (MoCA) was also assessed. Results: We found that increased BMI was significantly associated with decreased CBF (β = −0.06). Systolic BP and diastolic BP showed significant associations with all ASL parameters; systolic BP was negatively correlated with Tex (β = −0.02) and CBF (β = −0.01) but positively with ATT (β = 0.02). Diastolic BP was negatively associated with Tex (β = −0.03) and CBF (β = −0.03) but positively with ATT (β = 0.03). MoCA scores had a borderline significant association with Tex (OR = 1.51) and a significant association with CBF (OR = 1.84), which became non-significant after adjusting for confounders. Conclusions: These outcomes underscore the potential of using ME-ASL, warranting further research to strengthen these findings.

Hippocampal atrophy is a hallmark of Alzheimer’s disease and is associated with deficits in navigation. We investigated whether a novel digital assessment, the Spatial Performance Assessment for Cognitive Evaluation (SPACE), can predict hippocampal integrity beyond traditional neuropsychological tests in older adults. Forty older male participants underwent structural MRI and completed the spatial and navigation tasks in SPACE along with a battery of neuropsychological tests typically used to detect cognitive impairment. A regression model revealed that worse performance in the path integration and mapping tasks significantly predicted smaller hippocampal volume above age, education and all neuropsychological tests. Critically, participants who successfully learned the positions of landmarks in a virtual environment during a path integration task and accurately reproduced the configuration in a mapping task had larger hippocampal volumes. These findings indicate that SPACE can serve as a valuable addition to traditional cognitive assessments by providing greater sensitivity for assessing hippocampal volume. *Karolina Minta, Giorgio Colombo, and Mervin Tee contributed equally.

INTRODUCTION Alzheimer’s disease affects spatial abilities that are often overlooked in standard cognitive screening tools. We assessed whether the spatial navigation tasks in the Spatial Performance Assessment for Cognitive Evaluation (SPACE) can complement existing tools such as the Montreal Cognitive Assessment (MoCA). METHODS 348 participants aged 21-76 completed the MoCA, SPACE, and sociodemographic- health questionnaires. Regressions were used to predict MoCA scores with risk factors and SPACE tasks as predictors. We also conducted a factor analysis to investigate the relationships among SPACE tasks and the MoCA. RESULTS Regressions revealed significant effects of age, gender, and SPACE tasks. No risk factors for dementia predicted MoCA scores. The factor analysis revealed that MoCA and perspective taking contributed to a separate factor from other navigation tasks in SPACE. Normative data for SPACE are provided. DISCUSSION Our findings highlight the importance of navigation tasks for cognitive assessment and the early detection of cognitive impairment.