Evidence map›Paper›PMID 34027017›Full record

ArticleAlzheimer's & dementia (Amsterdam, Netherlands)2021

Outdoor life in dementia: How predictable are people with dementia in their mobility?

Sayeh Bayat, Alex Mihailidis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Alzheimer's & dementia (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sayeh BayatInstitute of Biomedical Engineering University of Toronto Toronto Ontario Canada.
Alex MihailidisInstitute of Biomedical Engineering University of Toronto Toronto Ontario Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPeople with dementia (PWD) often become disoriented, which increases their risk of getting lost. This article explores the extent to which we can predict future whereabouts of PWD by learning from their past mobility patterns using Global Positioning System (GPS) tracking devices.

methodsSeven older adults with dementia and eight healthy older adults completed 8 weeks of GPS data collection. We computed the probability that an appropriate algorithm can correctly predict the participant's future destinations using spatial and temporal patterns in each participant's GPS trajectories.

resultsRelying on both spatial and temporal patterns, our results suggest that a 4-week record of mobility patterns displays 95% potential predictability across the dementia group, which is significantly higher than 92% potential predictability among the controls, t(13) = -3.39, DISCUSSIONS: Our findings on predictability of mobility patterns among PWD offer new perspectives on predictive mobility models that can be used to locate missing persons with dementia.

Indexed as

assistive technologycognitive declinedisorientationGlobal Positioning Systemlife‐spacemachine learningmobility

Identifiers

PMID34027017
PMCPMC8118112

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.