Evidence map›Paper›PMID 27637581›Full record

ReviewZeitschrift fur Gerontologie und Geriatrie2016

Technology-based measurements for screening, monitoring and preventing frailty.

L Dasenbrock, A Heinks, M Schwenk, J M Bauer

Abstract readReview
PubMed Publisher
In one paragraph

Review in Zeitschrift fur Gerontologie und Geriatrie, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
1.5field-weighted citation impact, top 18% of its field
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

20 citing papers in PubMed, 3 syntheses or guidelines pooled it, 48 citations in OpenAlex.

  1. Pooled it
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  4. Trial
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  11. Article
  12. Review
  13. Review
  14. Perceptual-motor styles.Experimental brain research · 2021
    Review
  15. Article
  16. Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults.International journal of environmental research and public health · 2020
    Review
  17. Article
  18. Observational
  19. [Sarcopenia and frailty 2016 : Going separate ways].Zeitschrift fur Gerontologie und Geriatrie · 2016
    Article
  20. The Activ8 activity monitor: Validation of posture and movement classification.Journal of rehabilitation and assistive technologies engineering
    Article
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

4 authors at 3 institutions in 1 country.

L DasenbrockDepartment of Geriatric Medicine, Klinikum Oldenburg, Carl von Ossietzky University Oldenburg, Oldenburg, Germany. lena.dasenbrock@uni-oldenburg.de.ORCID http://orcid.org/0000-0002-3394-4257
A HeinksDepartment of Geriatric Medicine, Klinikum Oldenburg, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
M SchwenkNetwork Aging Research, Heidelberg University, Heidelberg, Germany.
J M BauerChair of Geriatric Medicine, Heidelberg University, AGAPLESION BETHANIEN KRANKENHAUS HEIDELBERG, Heidelberg, Germany.
Heidelberg University · DECarl von Ossietzky Universität Oldenburg · DEKlinikum Oldenburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveSensor technology, in particular wearable inertial sensors, has the potential to help researchers objectively assess the functionality of older adults. The following review provides an overview about the possible use of sensor technology to detect and prevent pre-frailty and frailty.

methodA systematic literature search in PubMed and the Cochrane Library was conducted. Articles were selected according to the following criteria: frail and/or pre-frail population, use of wearable and non-wearable sensor technology to measure or enhance human movements or activities of daily living and a focus on frailty assessment.

resultsA total of 28 publications were found. Sensor-derived parameters obtained during assessment of gait, functional performances and physical activity were reported to be relevant for screening and monitoring pre-frailty and frailty; however, current findings are limited to cross-sectional studies, which do not allow establishment of a causal relationship between motor performance, physical activity and specific frailty states. No study monitored specific activities of daily living. DISCUSSION: Outcome variables from technology-based assessment seem to provide valuable information for frailty assessment. Strenuous testing conditions as well as increased variability in gait, functional performance and physical activity may be useful in identifying frailty. Outcome variables derived from gait, motor assessment and physical activity must still be validated in large cohorts and under daily living conditions in order to develop robust screening tools for pre-frailty and frailty. Further research should focus on specific activities of daily living in pre-frail or frail older adults and technology-based approaches for intervention and prevention.

Indexed as

Frail ElderlyActigraphyAgedAged, 80 and overEvidence-Based MedicineHumansMass ScreeningMonitoring, AmbulatorySarcopeniaTechnology Assessment, BiomedicalTelemedicineTreatment OutcomeAssessmentFrail older adultsGerontechnologyMonitoringWearable sensors

Identifiers

PMID27637581
OpenAlexW2531263532

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.