The research, led by Florian Giesche of Goethe University Frankfurt together with colleagues in Germany and Luxembourg, enrolled 231 community-dwelling adults aged 60 and above, of whom 103 reported at least one fall in the previous twelve months. All participants were functionally independent and living at home, the population in which subtle early warning signs are hardest to detect. The investigators deliberately excluded falls with obvious non-motor causes such as dizziness, fainting, or loss of consciousness, ensuring that the comparison between fallers and non-fallers reflected genuine differences in movement control and cognition rather than unrelated medical events. Participants completed a comprehensive assessment program spanning established motor tests, seated computer-based cognitive tasks, and a novel interactive test battery performed on a device called the SKILLCOURT.

The centerpiece of the new approach was the Random Star Run, a reactive agility assessment in which participants started in the center of a four-by-four or five-by-five meter court and sprinted to eight outer target fields that lit up in random, unpredictable order on a large screen. A LiDAR system sampling at 40 hertz continuously tracked each participant’s position, allowing the device to measure total completion time automatically and objectively. Because the target sequence was never repeated, participants could not plan their movements in advance; every sprint, deceleration, and change of direction had to be initiated in reaction to a visual stimulus. This unplanned, reactive quality is precisely what distinguishes agility from simple change-of-direction speed, and it mirrors the demands of everyday situations such as dodging a pedestrian, stepping around an obstacle, or recovering from an unexpected stumble.

Alongside the agility test, participants performed motor-cognitive stepping tasks while standing on the court. In the simple reaction task they executed rapid sidesteps toward a target field whenever an orange square appeared; in the choice reaction task they had to interpret color-coded stimuli and step left or right accordingly. Three further stepping tasks probed executive functions: a task-switching paradigm assessing cognitive flexibility, a 2-back task taxing working memory, and a Stroop word-color condition measuring interference control. Performance on these tasks was quantified with an inverse efficiency score that combined response time and error rate, and trials with error rates above 30 percent were excluded to guarantee valid task execution. For comparison, the same cognitive functions were also assessed in a conventional seated setup using keyboard responses, while motor function was evaluated with the Timed-Up-and-Go test, the 30-second Sit-to-Stand test, grip strength, and walking speed, the latter three performed under both single-task and dual-task conditions with concurrent backward counting.

The statistical analysis was rigorous and pre-specified. General linear models adjusted for age and study location, with interaction terms to detect site-specific heterogeneity, were used to compare fallers and non-fallers across every outcome, with p-values Holm-adjusted within each domain. Only two measures survived this stringent filtering: the Random Star Run and the simple stepping reaction task. Participants without a history of falls completed the agility course and responded to the simple stepping stimuli significantly faster than those who had fallen, with partial eta-squared effect sizes of roughly 0.04. Strikingly, none of the established motor or cognitive assessments, including the Timed-Up-and-Go, Sit-to-Stand, walking speed, dual-task variants, grip strength, and the seated cognitive battery, showed group differences that met the predefined threshold, with effect sizes ranging only from 0.001 to 0.013.

The discriminative power of the agility test was then quantified with adjusted logistic regression and receiver operating characteristic analysis. Each standard-deviation increase in Random Star Run completion time was associated with an 82 percent increase in the odds of having a fall history, an odds ratio of 1.82 that remained significant after adjustment. The resulting model achieved an area under the curve of 0.73, with 70 percent sensitivity, 71 percent specificity, and roughly 70 percent overall classification accuracy. Crucially, this significantly outperformed the Timed-Up-and-Go test, the most widely used functional mobility screen in fall clinics, which managed an AUC of only 0.63. Adding the agility measure to a model containing age and study location alone improved discrimination from 0.63 to 0.73, a statistically significant increment, and bootstrap validation with 1,000 resamples showed only modest shrinkage to an optimism-corrected AUC of 0.70, indicating limited overfitting. An exploratory clinical cutoff of 28.6 seconds was derived from unadjusted data for practical interpretation.

The simple stepping reaction task told a more nuanced story. It was likewise associated with fall history, with an odds ratio of 1.58 and an adjusted AUC of 0.72 at 63 percent sensitivity and 75 percent specificity. However, when compared directly with the corresponding seated PC-based simple reaction test, which achieved an AUC of 0.63, the stepping version did not demonstrate statistically superior discrimination. The same held for the choice reaction task. In other words, the added value of reactive stepping over conventional cognitive testing could not be confirmed, and the authors’ second hypothesis was not supported. The executive-function stepping tasks, including the 2-back and Stroop conditions, showed no relevant group differences at all, though substantial missing data, particularly for the demanding 2-back task, may have reduced statistical power and complicated interpretation.

One of the most intriguing findings emerged from the interaction between age and fall history on agility performance. The gap between fallers and non-fallers was widest among the younger-old participants but steadily narrowed with advancing age, converging and even reversing at approximately 80 years. This suggests that reactive agility testing may be most informative in relatively high-functioning adults in their sixties and seventies, precisely the group in which conventional clinical thresholds, such as a Timed-Up-and-Go time of 13.5 seconds, often fail because most participants clear them easily. Meta-analytic evidence cited in the paper indicates the Timed-Up-and-Go achieves only about 31 percent sensitivity at that cutoff, leaving a large share of subtly impaired older adults undetected. Ceiling effects in higher-functioning populations appear to blunt the established tests, whereas the physically and cognitively demanding agility task retains the resolution to separate the groups.

The authors are careful to frame these results as a cross-sectional snapshot rather than proof of predictive power. Fall history was assessed retrospectively by self-report, which carries a risk of recall bias, and the study cannot establish whether poor agility precedes falling or reflects its consequences, including heightened fear of falling, which was itself elevated among fallers. Differences in testing organization between the German and Luxembourg sites, and the exclusion of participants with high error rates, introduce further caveats, although sensitivity analyses adjusting for sex, education, and physical functioning largely confirmed the stability of the main findings. The research team calls for prospective longitudinal studies to determine whether reactive agility can predict future first and recurrent falls beyond established measures, whether it adds value over planned change-of-direction tests without a reactive component, and whether specific cognitive elements such as response inhibition enhance stepping-based paradigms.

If those prospective studies succeed, the implications for fall prevention could be substantial. Agility-based assessments could be folded into multicomponent screening batteries for community-dwelling seniors, and similar paradigms could be implemented with more accessible light-sensor systems rather than dedicated laboratory equipment. Beyond diagnosis, the same reactive movement demands that make the test diagnostic may point toward a new generation of training interventions emphasizing stop-and-go movements, rapid directional changes, and decision-making under time pressure, capacities that conventional strength and balance programs rarely challenge. For a field that has long assessed the aging body and the aging mind in separate rooms, the message of this study is clear: the most revealing test of fall risk may be the one that forces both to work together, unpredictably, and at speed.

Subject of Research: Reactive agility and motor-cognitive assessment for distinguishing older adults with and without a history of falls

Article Title: Reactive agility and motor-cognitive assessments for distinguishing community-dwelling older adults with and without a history of falls: a dual-centre cross-sectional study

Article References: Giesche, F., Abobakr, A. H., Banzer, W., Groneberg, D. A., Vogt, L., Hoffmann, M., Albert, I., & Hülsdünker, T. (2026). Reactive agility and motor-cognitive assessments for distinguishing community-dwelling older adults with and without a history of falls: a dual-centre cross-sectional study. GeroScience. https://doi.org/10.1007/s11357-026-02477-4

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02477-4

Keywords: reactive agility, fall prevention, older adults, motor-cognitive assessment, Timed-Up-and-Go, SKILLCOURT, executive function, dual-task, GeroScience, healthy aging, reaction time, functional mobility