Evidence map›Paper›PMID 28877864›Full record

ArticleJournal of medical Internet research2017

Internet Searches and Their Relationship to Cognitive Function in Older Adults: Cross-Sectional Analysis.

Johanna Austin, Kristy Hollingshead, Jeffrey Kaye

Registry-linked trialAbstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02566239 (Ambient Independence Measures for Guiding Care Transitions), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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.

NCT02566239 nacompletednot on this map

Ambient Independence Measures for Guiding Care Transitions

TypeinterventionalSponsorOregon Health and Science UniversityRan2014 to 2019Enrolled96ConditionsAgingArmsShare activity data with care team
3 · Its place in the literature

Who cites it

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

  1. Pooled it
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  4. Observational
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  15. Technology-Enabled Assessment of Functional Health.IEEE reviews in biomedical engineering · 2019
    Review
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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

3 authors.

Johanna AustinDepartment of Neurology, Oregon Health & Science University, Portland, OR, United States.ORCID 0000-0002-8912-0396
Kristy HollingsheadFlorida Institute for Human & Machine Cognition, Pensacola, FL, United States.ORCID 0000-0002-4900-0517
Jeffrey KayeDepartment of Neurology, Oregon Health & Science University, Portland, OR, United States.ORCID 0000-0002-9971-3478

Funding

Outreach, Recruitment and Education CoreP30AG008017 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI DODGE, HIROKO HAYAMA · 1990 to 2019
$27.7M
Pilot CoreP30AG024978 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 2004 to 2023
$9.0M
Ambient Independence Measures for Guiding Care TransitionsR01AG042191 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 2013 to 2017
$2.7M
NIA NIH HHS P30 AG008017NIA NIH HHS P30 AG024978NIA NIH HHS R01 AG042191
6 · The paper itself

Abstract

backgroundAlzheimer disease (AD) is a very challenging experience for all those affected. Unfortunately, detection of Alzheimer disease in its early stages when clinical treatments may be most effective is challenging, as the clinical evaluations are time-consuming and costly. Recent studies have demonstrated a close relationship between cognitive function and everyday behavior, an avenue of research that holds great promise for the early detection of cognitive decline. One area of behavior that changes with cognitive decline is language use. Multiple groups have demonstrated a close relationship between cognitive function and vocabulary size, verbal fluency, and semantic ability, using conventional in-person cognitive testing. An alternative to this approach which is inherently ecologically valid may be to take advantage of automated computer monitoring software to continually capture and analyze language use while on the computer.

objectiveThe aim of this study was to understand the relationship between Internet searches as a measure of language and cognitive function in older adults. We hypothesize that individuals with poorer cognitive function will search using fewer unique terms, employ shorter words, and use less obscure words in their searches.

methodsComputer monitoring software (WorkTime, Nestersoft Inc) was used to continuously track the terms people entered while conducting searches in Google, Yahoo, Bing, and Ask.com. For all searches, punctuation, accents, and non-ASCII characters were removed, and the resulting search terms were spell-checked before any analysis. Cognitive function was evaluated as a z-normalized summary score capturing five unique cognitive domains. Linear regression was used to determine the relationship between cognitive function and Internet searches by controlling for variables such as age, sex, and education.

resultsOver a 6-month monitoring period, 42 participants (mean age 81 years [SD 10.5], 83% [35/42] female) conducted 2915 searches using these top search engines. Participants averaged 3.08 words per search (SD 1.6) and 5.77 letters per word (SD 2.2). Individuals with higher cognitive function used more unique terms per search (beta=.39, P=.002) and employed less common terms in their searches (beta=1.39, P=.02). Cognitive function was not significantly associated with the length of the words used in the searches.

conclusionsThese results suggest that early decline in cognitive function may be detected from the terms people search for when they use the Internet. By continuously tracking basic aspects of Internet search terms, it may be possible to detect cognitive decline earlier than currently possible, thereby enabling proactive treatment and intervention.

Indexed as

Aged, 80 and overCognitionCross-Sectional StudiesFemaleHumansInternetMalecognitionexecutive functiongeriatricsInternet

Identifiers

PMID28877864
PMCPMC5607437

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.