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Preliminary validation of a commercially available smartwatch for the clinical assessment of health and psychosocial risk factors for dementia

Sophia Holmqvist, Temple University, Philadelphia, United States
Marina Kaplan, Temple University, Philadelphia, United States
Riya Chaturvedi, Temple University, Philadelphia, United States
Moira McKniff, Temple University, Philadelphia, United States
Molly Tassoni, Temple University, Philadelphia, United States
Stephanie Simone, Temple University, Philadelphia, United States
Tania Giovannetti, Temple University, Philadelphia, United States



Objective:

Modifiable psychosocial and health factors associated with dementia risk are commonly assessed with self-report, which may be biased by insight, social desirability, poor recall, etc. Commercially available wearable devices may capture health risk in older adults earlier and more objectively than existing self-report measures, but they require further validation. The current study validated metrics from a Garmin vivosmart 4 smartwatch against clinical measures of cognition/function and psychosocial factors in older adults with and without cognitive impairment.

Participants and Methods:

Twenty-two community dwelling older adults with healthy cognition (n =18; 45% Black/African American) or mild cognitive impairment (MCI; n = 4) completed baseline questionnaires of psychosocial dementia risk factors, including perceived stress (Perceived Stress Scale), anxiety (Geriatric Anxiety Inventory), depression (Geriatric Depression Scale), loneliness (UCLA Loneliness Scale), medical comorbidities (Charlson Comorbidity Index), and physical activity (MET minutes from the International Physical Activity Questionnaire). The spatial extent of movement in everyday life was assessed with the Life Space Questionnaire. Global and domain cognitive composites (average across demographically corrected t scores) were computed from baseline cognitive tests of language, processing speed, memory, executive function, and attention. After baseline testing, participants completed a 23 hours/day 30-day monitoring period during which they wore a Garmin vivosmart 4 smartwatch that captured physical activity (daily steps, active time, moderate intensity duration, vigorous intensity duration, distance travelled, basal metabolic rate calories burned), heart rate (daily average resting heart rate), and stress level (average stress level). Smartwatch measures for each participant were averaged across the 30-day monitoring period. Relations between smartwatch and clinical measures were analyzed using Spearman correlations.

Results:

All Garmin physical activity metrics were significantly associated with self-reported physical activity, depressive symptoms, and the Life Space Questionnaire (r’s .3-.7). Garmin activity metrics (daily active time and steps) were also associated with overall cognition (r’s .3-.4). Greater Garmin resting heart rate was significantly associated with greater depressive symptoms (r=.438, p=.047) and a lower memory composite (r=-.438, p=.042). Higher resting heart rate also was associated with a higher Charlson Comorbidity Index score, which indicates risk of death within one year from comorbid health conditions (r=.389, p=.082). Greater Garmin average stress level was significantly associated with greater anxiety, loneliness, perceived stress, and a higher medical comorbidities score (r’s .3-.5).

Conclusions:

The Garmin measures of physical activity, heart rate and stress were associated with clinical measures of cognition and psychosocial risk factors, supporting the validity of the smartwatch for the assessment of health and psychosocial risk factors for dementia. Garmin physical activity metrics were notably closely related to self-reported physical activity while Garmin stress level and resting heart rate appeared to be more strongly related to psychosocial factors and health comorbidity. Overall, results show promise for wearable metrics to capture psychosocial risk and cognitive decline in a racially diverse community dwelling sample of older adults.

Category: Teleneuropsychology/ Technology

Keyword 1: teleneuropsychology
Keyword 2: aging disorders