Cited by 1,101Health Literacy and Information AccessibilityPatient-Provider Communication in HealthcareElectronic Health Records Systems

Internet Health Information Seeking and the Patient-Physician Relationship: A Systematic Review

Open access
Tan, Sharon Swee-Lin, Goonawardene, Nadee·2017·Journal of Medical Internet Research

Abstract

BACKGROUND: With online health information becoming increasingly popular among patients, concerns have been raised about the impact of patients' Internet health information-seeking behavior on their relationship with physicians. Therefore, it is pertinent to understand the influence of online health information on the patient-physician relationship. OBJECTIVE: Our objective was to systematically review existing research on patients' Internet health information seeking and its influence on the patient-physician relationship. METHODS: We systematically searched PubMed and key medical informatics, information systems, and communication science journals covering the period of 2000 to 2015. Empirical articles that were in English were included. We analyzed the content covering themes in 2 broad categories: factors affecting patients' discussion of online findings during consultations and implications for the patient-physician relationship. RESULTS: We identified 18 articles that met the inclusion criteria and the quality requirement for the review. The articles revealed barriers, facilitators, and demographic factors that influence patients' disclosure of online health information during consultations and the different mechanisms patients use to reveal these findings. Our review also showed the mechanisms in which online information could influence patients' relationship with their physicians. CONCLUSIONS: Results of this review contribute to the understanding of the patient-physician relationship of Internet-informed patients. Our main findings show that Internet health information seeking can improve the patient-physician relationship depending on whether the patient discusses the information with the physician and on their prior relationship. As patients have better access to health information through the Internet and expect to be more engaged in health decision making, traditional models of the patient-provider relationship and communication strategies must be revisited to adapt to this changing demographic.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/jmir.5729

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Healthcare professionals have mixed views in relation to patients resorting to the internet and mobile apps, with reservations about sources and accuracy, yet highlighting that active patient engagement can support a positive patient-physician interaction.

    “Healthcare professionals have mixed views in relation to patients resorting to the internet [114] and mobile apps [115], with reservations about the sources and accuracy of information, yet highlighting that active patient engagement can support a positive patient-physician interaction [116,117].”

    From Polycystic Ovary Syndrome and the Internet of Things: A Scoping Review (2024) · cites this paper as [116]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

3 of the 42 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. [19]Critical Appraisal Skills Programme (CASP) CASP checklists 2013 2016-09-28 Oxford, UK CASP UK http://www.casp-uk.net/checklists

Cited by

Sorted by citations

Authors
Tan, S. S.-L., & Goonawardene, N.
Affiliations
  • National University of Singapore (SG)
  • Singapore Management University (SG)
Corresponding author
Tan, Sharon Swee-Lin
Venue
Journal of Medical Internet Research
Published
2017-01-19
Volume
19
Issue
1
Pages
e9
ISSN
1438-8871 (ISSN-L)
OpenAlex
W2576167606
Cited by
1,101
References
42
Citations by year
2026: 102 · 2025: 123 · 2024: 139 · 2023: 145 · 2022: 155 · 2021: 166 · 2020: 114 · 2019: 100 · 2018: 45 · 2017: 10 · 2012: 1
FWCI
12.94
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (submittedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords
online health information seeking, physician-patient relationship, patient-provider communication
MeSH terms
Humans, Physician-Patient Relations, Health Behavior, Internet, Information Seeking Behavior

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review