A new study published in PLOS Digital Health highlights how smartphone browsing data could serve as a tool to identify people at risk of developing dementia. Researchers found that older adults with subjective cognitive decline, a condition linked to increased risk of Alzheimer’s disease, showed distinct movement patterns during a real-world orientation task. Specifically, the frequency of “orientation stops” or pauses to reorient during navigation effectively distinguished these individuals from cognitively healthy older adults.
Dementia, including Alzheimer’s disease, is a growing public health crisis, with cases expected to triple globally by 2050. Early diagnosis is key to implementing interventions that can slow the progression of dementia. the disease. However, current diagnostic tools often fail to detect cognitive decline in the early stages, especially when standard memory tests appear normal.
Advances in mobile technology offer a promising avenue to fill this gap. Smartphones can unobtrusively collect real-world behavioral data, providing insight into cognitive functioning in everyday scenarios. Researchers sought to leverage these capabilities to determine whether smartphone navigation data could reveal subtle cognitive changes in individuals with subjective cognitive decline.
“We were interested in this topic because the prevalence of dementia is expected to increase in the future and, therefore, impose significant challenges on health systems,” said study author Jonas Marquardt, a doctoral student at the German Center neurodegenerative diseases.
“Therefore, early detection of cognitive decline is essential for rapid intervention in dementia, with Alzheimer’s disease being the most common form. Our goal was to combine advances in smartphone technology to assess early deficits in a real-world scenario with a spatial navigation task, one of the cognitive skills that first declines during Alzheimer’s disease, thereby bridging the gap. gap between neuropsychological laboratory assessments. and the tasks of daily life.
The study involved 72 participants divided into three groups: 24 young adults, 25 elderly people in good cognitive health and 23 people with subjective cognitive decline. Participants were asked to navigate a college campus using a specially developed smartphone app called “Explorer.” The app guided them to five locations by showing them a map with their location and the destination marked. Once participants started walking, the map disappeared and they relied on their memory and spatial navigation skills to find their way. Participants could revisit the map if they felt lost and were asked to scan a QR code at each destination to confirm their arrival.
The app collected GPS data every two seconds during the task, tracking participants’ routes, time spent navigating, and any instances of pausing or rechecking the map. Researchers analyzed this data to identify patterns in movement and navigation behavior.
The researchers observed clear differences in browsing behavior between the three groups. Younger adults performed better, completing tasks faster and more efficiently, with fewer pauses or card checks. Cognitively healthy older adults and those with subjective cognitive decline exhibited slower performance, but the latter group stood out by making significantly more orienting stops—brief pauses likely related to cognitive challenges in the treatment of their environment.
“We were a little surprised to find that the biggest difference between the group of elderly people at high risk of dementia and those without risk was in the number of short stops, presumably made for orientation,” Marquardt told PsyPost. “It is difficult to fully explain what this performance measure captures, but we hypothesize that the number of short stops is indicative of navigation abilities and executive function, as we have seen associations with other related tasks to executive function as well as an increased likelihood of stopping at intersections, probably to recall and plan the correct path.
Statistical analysis confirmed that the number of orientation stops was a strong predictor of subjective cognitive decline. When used in a predictive model, this measure correctly identified individuals with subjective cognitive decline approximately 67% of the time, a level of accuracy comparable to more resource-intensive virtual reality-based navigation studies .
“The takeaway is that subtle changes in daily behavior, such as the number of orientation stops in our task, which may go unnoticed in daily life, can provide meaningful information about the cognitive health and an individual’s risk of dementia,” Marquardt explained. “Moreover, these differences might be detectable before deficits in conventional neuropsychological tests are present, thus allowing for earlier diagnosis.”
Interestingly, total distance walked and average walking speed did not differ significantly between older adult groups, suggesting that orientation failures specifically reflect cognitive rather than physical impairments. This finding is consistent with previous research linking orientation difficulties to early changes in brain regions affected by Alzheimer’s disease.
“A major caveat is that we focused on a group of older adults with subjective cognitive decline, which we used as a model for higher risk of dementia,” Marquardt noted. “However, subjective cognitive decline is a very heterogeneous group; While some people with subjective cognitive decline will progress to dementia, others may remain cognitively healthy. The use of genetic markers, such as APOE status, biomarkers such as tau or amyloid, or neuroimaging data, would have allowed a more precise characterization of our older participants. Additionally, collecting longitudinal rather than cross-sectional data could further strengthen our predictive capabilities.
Despite these limitations, research suggests that smartphone-based tasks could facilitate early detection and monitoring of cognitive decline, potentially transforming how Alzheimer’s disease is diagnosed and managed.
“Our long-term goal is to validate smartphone-based approaches using real-world data for early detection of dementia in broader populations,” Marquardt said. “Our goal is to develop tools that are easy to integrate into daily life. In doing so, it would enable individuals and healthcare providers to proactively and independently monitor their cognitive health. Ultimately, we hope that this research will contribute to the earlier diagnosis of dementia and enable better deployment of intervention strategies.
“This study was funded by a DZNE Innovation 2 Application Award (awarded to Nadine Diersch) and by a collaborative research grant (DFG, German Research Foundation – project ID 425899996). The Collaborative Research Center emphasizes the value of interdisciplinary collaboration, as demonstrated in this study through the combination of neuroscience, digital health and real-world applications. We believe that such interdisciplinary approaches can revolutionize the way we understand, detect and treat neurodegenerative diseases.
The study, “Identifying older adults at risk for dementia based on smartphone data obtained during a real-world wayfinding task,” was authored by Jonas Marquardt, Priyanka Mohan, Myra Spiliopoulou, Wenzel Glanz, Michaela Butryn, Esther Kuehn, Stefanie Schreiber, Anne Maass and Nadine Diersch.
