Evidence map›Paper›PMID 39847765›Full record

ArticleJMIR human factors2025

Evaluating the Acceptance and Usability of an Independent, Noncommercial Search Engine for Medical Information: Cross-Sectional Questionnaire Study and User Behavior Tracking Analysis.

Lisa Specht, Raphael Scheible, Martin Boeker, Erik Farin-Glattacker, Nikolas Kampel, Marina Schmölz, Andrea Schöpf-Lazzarino, Stefan Schulz, Christian Schlett, Fabian Thomczyk and 4 more

Abstract read
In one paragraph

Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Article
  2. Article
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

14 authors.

Lisa Specht *Institute of General Practice, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0009-0000-9095-3400
Raphael Scheible *Institute of Artificial Intelligence and Informatics in Medicine, Chair of Medical Informatics, University Hospital rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID 0000-0003-2067-5569
Martin BoekerInstitute of Artificial Intelligence and Informatics in Medicine, Chair of Medical Informatics, University Hospital rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID 0000-0003-2972-2042
Erik Farin-GlattackerInstitute of Medical Biometry and Statistics, Section of Health Care Research and Rehabilitation Research, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0001-6867-0316
Nikolas KampelInstitute of Neuroscience and Medicine, Jülich Aachen Research Alliance, Forschungszentrum Jülich GmbH, Jülich, Germany.ORCID 0009-0004-0629-0456
Marina SchmölzInstitute of General Practice, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0009-0000-2567-1933
Andrea Schöpf-LazzarinoInstitute of General Practice, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-4705-2938
Stefan SchulzInstitute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.ORCID 0000-0001-7222-3287
Christian SchlettInstitute of Medical Biometry and Statistics, Section of Health Care Research and Rehabilitation Research, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-7237-3477
Fabian ThomczykData Integration Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0001-8863-9930
Sebastian Voigt-RadloffInstitute of Medical Biometry and Statistics, Section of Health Care Research and Rehabilitation Research, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0003-2745-3328
Constanze WegnerCochrane Germany, Cochrane Germany Foundation, Freiburg, Germany.ORCID 0009-0008-3800-5815
Katharina WollmannCochrane Germany, Cochrane Germany Foundation, Freiburg, Germany.ORCID 0000-0001-7853-4967
Andy MaunInstitute of General Practice, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-9213-6583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe internet is a key source of health information, but the quality of content from popular search engines varies, posing challenges for users-especially those with low health or digital health literacy. To address this, the "tala-med" search engine was developed in 2020 to provide access to high-quality, evidence-based content. It prioritizes German health websites based on trustworthiness, recency, user-friendliness, and comprehensibility, offering category-based filters while ensuring privacy by avoiding data collection and advertisements.

objectiveThis study aims to evaluate the acceptance and usability of this independent, noncommercial search engine from the users' perspectives and their actual use of the search engine.

methodsFor the questionnaire study, a cross-sectional study design was used. In total, 802 participants were recruited through a web-based panel and were asked to interact with the new search engine before completing a web-based questionnaire. Descriptive statistics and multiple regression analyses were used to assess participants' acceptance and usability ratings, as well as predictors of acceptance. Furthermore, from October 2020 to June 2021, we used the open-source web analytics platform Matomo to collect behavior-tracking data from consenting users of the search engine.

resultsThe study indicated positive findings on the acceptance and usability of the search engine, with more than half of the participants willing to reuse (465/802, 58%) and recommend it (507/802, 63.2%). Of the 802 users, 747 (93.1%) valued the absence of advertising. Furthermore, 92.3% (518/561), 93.9% (553/589), 94.7% (567/599), and 96.5% (600/622) of those users who used the filters agreed at least partially that the filter functions were helpful in finding trustworthy, recent, user-friendly, or comprehensible results. Participants criticized some of the search results regarding the selection of domains and shared ideas for potential improvements (eg, for a clearer design). Regression analyses showed that the search engine was especially well accepted among older users, frequent internet users, and those with lower educational levels, indicating an effective targeting of segments of the population with lower health literacy and digital health literacy. Tracking data analysis revealed 1631 sessions, comprising 3090 searches across 1984 unique terms. Users performed 1.64 (SD 1.31) searches per visit on average. They prioritized the search terms "corona," "back pain," and "cough." Filter changes were common, especially for recency and trustworthiness, reflecting the importance that users placed on these criteria.

conclusionsUser questionnaires and behavior tracking showed the platform was well received, particularly by older and less educated users, especially for its advertisement-free design and filtering system. While feedback highlighted areas for improvement in design and filter functionality, the search engine's focus on transparency, evidence-based content, and user privacy shows promise in addressing health literacy and navigational needs. Future updates and research will further refine its effectiveness and impact on promoting access to quality health information.

Indexed as

Consumer BehaviorConsumer Health InformationSearch EngineAdolescentAdultAgedCross-Sectional StudiesFemaleGermanyHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adultdigital health literacyevidence-based contentGermanyhealth informationhealth literacyinformation-seeking behaviormedical informationnavigational needssearch engineuser behavior

Identifiers

PMID39847765
PMCPMC11803324

What OpenQuestion holds

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LicenceCC BY
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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.