Background: The 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.
Objective: This 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.
Methods: For 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.
Results: The 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.
Conclusions: User 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.
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http://dx.doi.org/10.2196/56941 | DOI Listing |
JMIR Hum Factors
January 2025
Institute of General Practice, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Background: The 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.
View Article and Find Full Text PDFJMIR Public Health Surveill
January 2025
Division of Global HIV and TB, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, 30322, United States, 1 8103383534.
Background: Population size estimation (PSE) for key populations is needed to inform HIV programming and policy.
Objective: This study aimed to examine the utility of applying a recently proposed method using Google Trend (GT) internet search data to generate PSE (Google Trends Population Size Estimate [GTPSE]) for men who have sex with men (MSM) in 54 countries in Africa, Asia, the Americas, and Europe.
Methods: We examined GT relative search volumes (representing the relative internet search frequency of specific search terms) for "porn" and, as a comparator term, "gay porn" for the year 2020.
J Proteome Res
January 2025
Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, 69120 Heidelberg, Germany.
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, different algorithms come with different strengths and weaknesses and choosing the appropriate algorithm poses a challenge for the user. Here we introduce PeptideForest, a semisupervised machine learning approach that integrates the assignments of multiple algorithms to train a random forest classifier to alleviate that issue.
View Article and Find Full Text PDFRadiology
January 2025
From the Institute of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, Munich 81675, Germany.
Background Studies have explored the application of multimodal large language models (LLMs) in radiologic differential diagnosis. Yet, how different multimodal input combinations affect diagnostic performance is not well understood. Purpose To evaluate the impact of varying multimodal input elements on the accuracy of OpenAI's GPT-4 with vision (GPT-4V)-based brain MRI differential diagnosis.
View Article and Find Full Text PDFJMIR Dermatol
January 2025
NYU Langone Health, 550 1st Ave, New York, NY, 10016, United States, 1 (212) 263-5290.
Background: Lipomas are benign tumors composed of encapsulated adipocytes. Although relatively common, uncertainty remains about the population-level prevalence, the etiology, and the degree of public interest in lipomas and associated removal procedures.
Objective: The spatiotemporal patterns of public interest in lipomas and lipoma removal procedures were characterized.
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