Evidence map›Paper›PMID 31054258›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2020

The Five W's of Falls: Weekly Online Health Survey of Community-Dwelling Older Adults: Analysis of 4 Years Prospective Follow-up.

Antoine Piau, Nora Mattek, Colette Duncan, Nicole Sharma, Thomas Riley, Jeffrey Kaye

Abstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Review
  3. Observational
  4. Article
  5. When Will My Patient Fall? Sensor-Based In-Home Walking Speed Identifies Future Falls in Older Adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2020
    Article
  6. Article
  7. 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

6 authors.

Antoine PiauInternal Medicine and Gerontology, University Hospital of Toulouse, UPS, Toulouse, France.
Nora MattekDepartment of Neurology, Oregon Center for Aging and Technology (ORCATECH), Oregon Health and Science University, Portland.
Colette DuncanDepartment of Neurology, Oregon Center for Aging and Technology (ORCATECH), Oregon Health and Science University, Portland.
Nicole SharmaDepartment of Neurology, Oregon Center for Aging and Technology (ORCATECH), Oregon Health and Science University, Portland.
Thomas RileyDepartment of Neurology, Oregon Center for Aging and Technology (ORCATECH), Oregon Health and Science University, Portland.
Jeffrey KayeDepartment of Neurology, Oregon Center for Aging and Technology (ORCATECH), Oregon Health and Science University, Portland.

Funding

Outreach, Recruitment and Education CoreP30AG008017 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 1990 to 2019
$27.7M
Pilot CoreP30AG024978 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 2004 to 2023
$9.0M
Resource CoreU2CAG054397 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 2016 to 2019
$7.0M
Intelligent Systems for Detection of Aging ChangesR01AG024059 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 2006 to 2010
$6.7M
NIA NIH HHS P30 AG008017NIA NIH HHS P30 AG024978NIA NIH HHS R01 AG024059NIA NIH HHS U2C AG054397
6 · The paper itself

Abstract

backgroundAn in-depth examination of prospectively collected falls details may facilitate more effective falls prevention. Who was involved? What happened? Where did the fall take place? When did it happen? Why did it occur? This study aimed to provide previously unavailable details about the circumstances surrounding fall events and their consequences.

methodA retrospective analysis of falls prospectively self-reported by older adults via an online weekly health form over 4 years.

resultsWe collected 371 falls during the 4 year time period from 120 clinically characterized fallers (74% women, mean age 83.3 years). Most of the 371 falls occurred indoors (62%) and in well-lit areas (81%). Bedrooms were the most common places for in-home falls. Commonly observed precipitating factors included loss of balance, slipping or tripping. Almost one-third (31%) of falls were defined as injurious whereas 22% resulted in a change in the walking ability of which 26% led to the use of a cane or walker. Among falls that did not give rise to any formal health care intervention, 8% resulted in a modification of walking ability.

conclusionsA relatively high rate of fall-related injuries compared to the existing literature was observed. Online weekly surveys and the richness of details provided through these data capture method allowed us to identify falls that did not result in health care utilization but did result in decreased mobility. This finding suggests why some falls classified in the literature as noninjurious may nevertheless increase the risk of loss of autonomy and undesired outcomes.

Indexed as

Accidental FallsIndependent LivingAgedAged, 80 and overFemaleFollow-Up StudiesHealth SurveysHumansMaleProspective StudiesFallsInformation and communication technologiesInternetOnline survey

Identifiers

PMID31054258
PMCPMC7164523

What OpenQuestion holds

Textmetadata
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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.