Vitality tracking in Kenyan adults using wearable devices and ecological momentary assessments

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Publicado en:Alzheimer's & Dementia vol. 21 (Dec 1, 2025)
Autor principal: Blackmon, Karen
Otros Autores: Alaka, Benard, Onyancha, Catherine Bikeri, Musili, Litha, Kamau, Raechel, Mostert, Cyprian M, Saleh, Mansoor, Merali, Zul, Udeh‐Momoh, Chinedu T, Thesen, Thomas
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John Wiley & Sons, Inc.
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022 |a 1552-5260 
022 |a 1552-5279 
024 7 |a 10.1002/alz70856_103471  |2 doi 
035 |a 3286365018 
045 0 |b d20251201 
100 1 |a Blackmon, Karen  |u Geisel School of Medicine at Dartmouth, Hanover, NH, USA, 
245 1 |a Vitality tracking in Kenyan adults using wearable devices and ecological momentary assessments 
260 |b John Wiley & Sons, Inc.  |c Dec 1, 2025 
513 |a Journal Article 
520 3 |a Background Vitality is essential to healthy aging but is elusive to define and measure. Dynamic capture of fluctuations in vitality can uncover abnormal trajectories that could be a harbinger of frailty in older adults. Yet, these fluctuations are missed by static and/or sparse sampling strategies. To address the need for dynamic and high‐density capture of vitality in older adults, we developed a passive sensing and active probing digital platform using wearable devices and smartphones. We deployed this paradigm in older Kenyan adults and evaluated its potential for use in research on the dynamics of accelerated aging. Method Cognitively unimpaired (CU) Kenyan adults ≥ 35 years of age (N&#xa0;=&#xa0;79) were provided with the Fitbit Inspire 3 device to sense heart rate, sleep, and physical activity over the course of 12 months. At baseline, they completed neurocognitive screening to confirm CU status. A novel 10‐item Vitality Index (VI) was developed and delivered weekly through a mobile phone app to assess fluctuations in health, strength, energy, pain, sleep, mood, and focus, alongside a brief spatial working memory task. Here, we evaluate adherence, internal consistency, test‐retest reliability, and convergent validity of the VI against gold standard measures of depression (PHQ‐9), anxiety (GAD‐7), and flourishing. Results Data from 79 participants [53 m / 25 f /1 intersex; median education: 12 y; mean age (sd)=49 (9.7) y; age range: 35‐74 y] show that 97% of participants wear their device at least 95% of the time. Weekly VI completion averages 85% and weekly spatial memory task completion averages 96%. The VI shows good internal consistency (week 1 α&#xa0;=&#xa0;0.75) and test‐retest reliability (r=0.73; p&#xa0;<0.001). VI is positively negatively correlated with depression (r=‐0.34; p&#xa0;<0.01) and anxiety (r=‐0.37; p&#xa0;<0.01) but positively correlated with flourishing (r=0.27; p&#xa0;<0.01). Conclusion A high degree of compliance with wearable sensors and weekly assessments, and sound psychometrics, demonstrates the feasibility of our vitality tracking paradigm in older Kenyan adults. Future analyses will uncover biopsychosocial risk factors that contribute to irreversible loss of vitality. Findings will provide essential information for future interventional studies that aim to trial behavioral and pharmaceutical approaches to rescuing vitality in at‐risk adults. 
653 |a Physical fitness 
653 |a Task completion 
653 |a Aging 
653 |a Reliability 
653 |a Heart rate 
653 |a Generalized anxiety disorder 
653 |a Age 
653 |a Anxiety 
653 |a Risk factors 
653 |a Politics 
653 |a Software 
653 |a Older people 
653 |a Test validity and reliability 
653 |a Intersexuality 
653 |a Biopsychosocial aspects 
653 |a Mobile phones 
653 |a Feasibility 
653 |a Convergent validity 
653 |a Mental depression 
653 |a Sampling 
653 |a Emotions 
653 |a Short term memory 
653 |a Ecological momentary assessment 
653 |a At risk populations 
653 |a Adults 
653 |a Mental health 
653 |a Sleep 
653 |a Physical activity 
653 |a Medical screening 
653 |a Wearable computers 
653 |a Tracking 
653 |a Paradigms 
653 |a Evaluation 
653 |a Quantitative psychology 
653 |a Spatial memory 
700 1 |a Alaka, Benard  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
700 1 |a Onyancha, Catherine Bikeri  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
700 1 |a Musili, Litha  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
700 1 |a Kamau, Raechel  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
700 1 |a Mostert, Cyprian M  |u Aga Khan University, The Brain and Mind Institute, Nairobi, Kenya, 
700 1 |a Saleh, Mansoor  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
700 1 |a Merali, Zul  |u Aga Khan University, The Brain and Mind Institute, Nairobi, Nairobi, Kenya, 
700 1 |a Udeh‐Momoh, Chinedu T  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
700 1 |a Thesen, Thomas  |u Brain and Mind Institute, Aga Khan University, Nairobi, Kenya, 
773 0 |t Alzheimer's & Dementia  |g vol. 21 (Dec 1, 2025) 
786 0 |d ProQuest  |t Consumer Health Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3286365018/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3286365018/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch