Evidence map›Paper›PMID 32141835›Full record

ArticleJournal of medical Internet research2020

Assessment of the Frequency of Online Searches for Symptoms Before Diagnosis: Analysis of Archival Data.

Irit Hochberg, Raviv Allon, Elad Yom-Tov

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
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

28 citing papers in PubMed, 58 citations in OpenAlex.

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  4. Accuracy of chat-based artificial intelligence for patient education on orthostatic hypotension.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2025
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  5. A Mixed Methods Exploration of Social Media Use for Health Information in Under-Resourced Communities.International journal of environmental research and public health · 2025
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  17. A content-quality and optimization analysis of YouTube as a source of patient information for bipolar disorder.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024
    Article
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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 at 1 institution in 1 country.

Irit HochbergInstitute of Endocrinology, Diabetes, and Metabolism, Rambam Health Care Campus, Haifa, Israel.ORCID 0000-0002-4232-5191
Raviv AllonBruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.ORCID 0000-0001-6639-9219
Elad Yom-TovMicrosoft Research, Herzeliya, Israel.ORCID 0000-0002-2380-4584
Technion – Israel Institute of Technology · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurveys suggest that a large proportion of people use the internet to search for information on medical symptoms they experience and that around one-third of the people in the United States self-diagnose using online information. However, surveys are known to be biased, and the true rates at which people search for information on their medical symptoms before receiving a formal medical diagnosis are unknown.

objectiveThis study aimed to estimate the rate at which people search for information on their medical symptoms before receiving a formal medical diagnosis by a health professional.

methodsWe collected queries made on a general-purpose internet search engine by people in the United States who self-identified their diagnosis from 1 of 20 medical conditions. We focused on conditions that have evident symptoms and are neither screened systematically nor a part of usual medical care. Thus, they are generally diagnosed after the investigation of specific symptoms. We evaluated how many of these people queried for symptoms associated with their medical condition before their formal diagnosis. In addition, we used a survey questionnaire to assess the familiarity of laypeople with the symptoms associated with these conditions.

resultsOn average, 15.49% (1792/12,367, SD 8.4%) of people queried about symptoms associated with their medical condition before receiving a medical diagnosis. A longer duration between the first query for a symptom and the corresponding diagnosis was correlated with an increased likelihood of people querying about those symptoms (rho=0.6; P=.005); similarly, unfamiliarity with the association between a condition and its symptom was correlated with an increased likelihood of people querying about those symptoms (rho=-0.47; P=.08). In addition, worrying symptoms were 14% more likely to be queried about.

conclusionsOur results indicate that there is large variability in the percentage of people who query the internet for their symptoms before a formal medical diagnosis is made. This finding has important implications for systems that attempt to screen for medical conditions.

Indexed as

Early DiagnosisFemaleHumansInternetMaleSearch EngineSurveys and Questionnairesdiagnosisscreeningsearch engines

Identifiers

PMID32141835
PMCPMC7084283
OpenAlexW3010612950

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.