Evidence map›Paper›PMID 31045507›Full record

SynthesisJournal of medical Internet research2019

Consumer Evaluation of the Quality of Online Health Information: Systematic Literature Review of Relevant Criteria and Indicators.

Yalin Sun, Yan Zhang, Jacek Gwizdka, Ciaran B Trace

Registry-linked trialAbstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06512792 (Mobile App-Based Remote Management Model for IBD Patients), which is not on this map. Cited by 125 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
125citing papers in PubMed, 6 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.

NCT06512792 naunknown statusnot on this mapstarted 2024, after this paper: background citation

Mobile App-Based Remote Management Model for IBD Patients: A Multi-Center Randomized Controlled Study

TypeinterventionalSponsorChanghai HospitalRan2024 to 2025Enrolled500ConditionsInflammatory Bowel DiseasesArmsTelemedicine management through Mobile APP
3 · Its place in the literature

Who cites it

125 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  2. Prevalence and predictors of medical information avoidance: a systematic review and meta-analysis.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2025
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65 more citing papers are in PubMed but not listed here.

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.

Yalin SunSchool of Information, The University of Texas at Austin, Austin, TX, United States.ORCID 0000-0003-1414-8295
Yan ZhangSchool of Information, The University of Texas at Austin, Austin, TX, United States.ORCID 0000-0002-1130-0012
Jacek GwizdkaSchool of Information, The University of Texas at Austin, Austin, TX, United States.ORCID 0000-0003-2273-3996
Ciaran B TraceSchool of Information, The University of Texas at Austin, Austin, TX, United States.ORCID 0000-0002-7118-6610

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the quality of online health information remains questionable, there is a pressing need to understand how consumers evaluate this information. Past reviews identified content-, source-, and individual-related factors that influence consumer judgment in this area. However, systematic knowledge concerning the evaluation process, that is, why and how these factors influence the evaluation behavior, is lacking.

objectiveThis review aims (1) to identify criteria (rules that reflect notions of value and worth) that consumers use to evaluate the quality of online health information and the indicators (properties of information objects to which criteria are applied to form judgments) they use to support the evaluation in order to achieve a better understanding of the process of information quality evaluation and (2) to explicate the relationship between indicators and criteria to provide clear guidelines for designers of consumer health information systems.

methodsA systematic literature search was performed in seven digital reference databases including Medicine, Psychology, Communication, and Library and Information Science to identify empirical studies that report how consumers directly and explicitly describe their evaluation of online health information quality. Thirty-seven articles met the inclusion criteria. A qualitative content analysis was performed to identify quality evaluation criteria, indicators, and their relationships.

resultsWe identified 25 criteria and 165 indicators. The most widely reported criteria used by consumers were trustworthiness, expertise, and objectivity. The indicators were related to source, content, and design. Among them, 114 were positive indicators (entailing positive quality judgments), 35 were negative indicators (entailing negative judgments), and 16 indicators had both positive and negative quality influence, depending on contextual factors (eg, source and individual differences) and criteria applied. The most widely reported indicators were site owners/sponsors; consensus among multiple sources; characteristics of writing and language; advertisements; content authorship; and interface design.

conclusionsConsumer evaluation of online health information is a complex cost-benefit analysis process that involves the use of a wide range of criteria and a much wider range of quality indicators. There are commonalities in the use of criteria across user groups and source types, but the differences are hard to ignore. Evidently, consumers' health information evaluation can be characterized as highly subjective and contextualized, and sometimes, misinformed. These findings invite more research into how different user groups evaluate different types of online sources and a personalized approach to educate users about evaluating online health information quality.

Indexed as

CommunicationConsumer Health InformationHumansInternetMedical InformaticsQuality Assurance, Health Careconsumer health informaticshealth information qualityhealth information seekingonline health information

Identifiers

PMID31045507
PMCPMC6521213

What OpenQuestion holds

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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.