Dataset Information

Using a GPS Watch to Characterize Life-Space Mobility in Dementia: A Dyadic Case Study.

ABSTRACT: Persons with dementia (PWD) often experience difficulty navigating their environments and performing out-of-home activities. Life-space mobility (LSM) is an effective way of assessing functional levels and independence. We present a dyadic case study to explore the feasibility of using a global positioning system (GPS) watch to measure LSM of a Latino PWD. Methods included travel diary, LSM questionnaire, and qualitative interviews in addition to the GPS-based mobility characterization. GPS data indicated that the PWD made outdoor trips regularly and was active socially, with day-to-day variations. Caregiver and PWD interviews revealed contextual information about mobility patterns captured by other methods. The dyad had positive perceptions of the GPS watch for tracking health and activities. This study demonstrated a use for wearable location tracking technology to support accurate LSM assessment in dementia that can inform nursing practice, policy, and research to promote well-being and delay functional deterioration in PWD. [Journal of Gerontological Nursing, 47(10), 15-22.].

SUBMITTER: Chung J

PROVIDER: S-EPMC10054372 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using a GPS Watch to Characterize Life-Space Mobility in Dementia: A Dyadic Case Study.

Chung Jane J Boyle Joseph J Pretzer-Aboff Ingrid I Knoefel Janice J Young Heather M HM Wheeler David C DC

Journal of gerontological nursing 20211001 10

Persons with dementia (PWD) often experience difficulty navigating their environments and performing out-of-home activities. Life-space mobility (LSM) is an effective way of assessing functional levels and independence. We present a dyadic case study to explore the feasibility of using a global positioning system (GPS) watch to measure LSM of a Latino PWD. Methods included travel diary, LSM questionnaire, and qualitative interviews in addition to the GPS-based mobility characterization. GPS data ...[more]

PMID: 34590977

Similar Datasets

Project description:The home address is a common spatial proxy for exposure assessment in epidemiological studies but mobility may introduce exposure misclassification. Mobility can be assessed using self-reports or objectively measured using GPS logging but self-reports may not assess the same information as measured mobility. We aimed to assess mobility patterns of a rural population in the Netherlands using GPS measurements and self-reports and to compare GPS measured to self-reported data, and to evaluate correlates of differences in mobility patterns.In total 870 participants filled in a questionnaire regarding their transport modes and carried a GPS-logger for 7 consecutive days. Transport modes were assigned to GPS-tracks based on speed patterns. Correlates of measured mobility data were evaluated using multiple linear regression. We calculated walking, biking and motorised transport durations based on GPS and self-reported data and compared outcomes. We used Cohen's kappa analyses to compare categorised self-reported and GPS measured data for time spent outdoors.Self-reported time spent walking and biking was strongly overestimated when compared to GPS measurements. Participants estimated their time spent in motorised transport accurately. Several variables were associated with differences in mobility patterns, we found for instance that obese people (BMI > 30 kg/m2) spent less time in non-motorised transport (GMR 0.69-0.74) and people with COPD tended to travel longer distances from home in motorised transport (GMR 1.42-1.51).If time spent walking outdoors and biking is relevant for the exposure to environmental factors, then relying on the home address as a proxy for exposure location may introduce misclassification. In addition, this misclassification is potentially differential, and specific groups of people will show stronger misclassification of exposure than others. Performing GPS measurements and identifying explanatory factors of mobility patterns may assist in regression calibration of self-reports in other studies.

Project description:ObjectivesTo determine the association of life-space score with subsequent healthcare costs and utilization.DesignProspective cohort study (Osteoporotic Fracture in Men [MrOS]).SettingSix U.S. sites.ParticipantsA total of 1555 community-dwelling men (mean age 79.3 years; 91.5% white, non-Hispanic) participating in the MrOS Year 7 (Y7) examination linked with their Medicare claims data.MeasurementsLife-space during the past month was assessed as 0 (daily restriction to one's bedroom) to 120 (daily trips outside one's town without assistance) and categorized (0-40, 41-60, 61-80, 81-100, 101-120). Total annualized direct healthcare costs and utilization were ascertained during 36 months after the Y7 examination.ResultsMean total annualized costs (2020 U.S. dollars) steadily increased across category of life-space score, from $7954 (standard deviation [SD] 16,576) among men with life-space scores of 101-120 to $26,430 (SD 28,433) among men with life-space scores of 0-40 (p < 0.001). After adjustment for demographics, men with a life-space score of 0-40 versus men with a life-space score of 101-120 had greater mean total costs (cost ratio [CR] = 2.52; 95% confidence interval [CI] = 1.84-3.45) and greater risk of subsequent hospitalization (odds ratio [OR] 4.72, 95% CI 2.61-8.53) and skilled nursing facility (SNF) stay (OR 7.32, 95% CI 3.65-14.66). Life-space score was no longer significantly associated with total healthcare costs (CR for 0-40 vs 101-120 1.29; 95% CI 0.91-1.84) and hospitalization (OR 1.76, 95% CI 0.89-3.51) after simultaneous consideration of demographics, medical factors, self-reported health and function, and the frailty phenotype; the association of life-space with SNF stay remained significant (OR 2.86, 95% CI 1.26-6.49).ConclusionOur results highlight the importance of function and mobility in predicting future healthcare costs and suggest the simple and convenient life-space score may in part capture risks from major geriatric domains and improve identification of older, community-dwelling men likely to require costly care.

Project description:BackgroundIn the Greater Mekong Subregion (GMS), forest-going populations are considered high-risk populations for malaria and are increasingly targeted by national control programmes' elimination efforts. A better understanding of forest-going populations' mobility patterns and risk associated with specific types of forest-going trips is necessary for countries in the GMS to achieve their objective of eliminating malaria by 2030.MethodsBetween March and November 2018, as part of a focal test and treat intervention (FTAT), 2,904 forest-goers were recruited in southern Lao PDR. A subset of forest-goers carried an "i-Got-U" GPS logger for roughly 2 months, configured to collect GPS coordinates every 15 to 30 min. The utilization distribution (UD) surface around each GPS trajectory was used to extract trips to the forest and forest-fringes. Trips with shared mobility characteristics in terms of duration, timing and forest penetration were identified by a hierarchical clustering algorithm. Then, clusters of trips with increased exposure to dominant malaria vectors in the region were further classified as high-risk. Finally, gradient boosting trees were used to assess which of the forest-goers' socio-demographic and behavioural characteristics best predicted their likelihood to engage in such high-risk trips.ResultsA total of 122 forest-goers accepted carrying a GPS logger resulting in the collection of 803 trips to the forest or forest-fringes. Six clusters of trips emerged, helping to classify 385 (48%) trips with increased exposure to malaria vectors based on high forest penetration and whether the trip happened overnight. Age, outdoor sleeping structures and number of children were the best predictors of forest-goers' probability of engaging in high-risk trips. The probability of engaging in high-risk trips was high (~ 33%) in all strata of the forest-going population.ConclusionThis study characterized the heterogeneity within the mobility patterns of forest-goers and attempted to further segment their role in malaria transmission in southern Lao People's Democratic Republic (PDR). National control programmes across the region can leverage these results to tailor their interventions and messaging to high-risk populations and accelerate malaria elimination.

Dataset Information

Using a GPS Watch to Characterize Life-Space Mobility in Dementia: A Dyadic Case Study.

Publications

Using a GPS Watch to Characterize Life-Space Mobility in Dementia: A Dyadic Case Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets