Evidence map›Paper›PMID 22288026›Full record

ArticleHealth and technology2011

Trust between patients and health websites: a review of the literature and derived outcomes from empirical studies.

Laurian C Vega, Enid Montague, Tom Dehart

Abstract read
In one paragraph

Article in Health and technology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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.

Laurian C Vega2202 Kraft Drive, Computer Science Department, Virginia Tech, Blacksburg, Virginia, 24060, United States.
Enid Montague
Tom Dehart

Funding

INSTITUTIONAL CTSA (UW-MADISON): CLINICAL TRIALSUL1RR025011 · NCRR · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2007 to 2011
$29.5M
NCRR NIH HHS UL1 RR025011
6 · The paper itself

Abstract

With the exploding growth of the web, health websites have become a dominant force in the realm of health care. Technically savvy patients have been using the web not only to self inform but to self diagnose. In this paper we examine the trust relationship between humans and health websites by outlining the existing literature on trust in health websites. A total of forty-nine papers were examined using a meta-analytical framework. Using this framework, each paper was coded for the antecedents and facets that comprise user trust in health websites. Our findings show that there is little consensus regarding the defining characteristics of the construct of trust in health websites. Further research in this field should focus on collaboratively defining trust and what factors affect trust in health web sites.

Identifiers

PMID22288026
PMCPMC3266366

What OpenQuestion holds

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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.