2026-10-11T07:53:08Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33997982 2026-09-25T17:26:24Z category_7 category_21 category_272 category_734 category_64 category_106 portal_5 item_type_3 month_year_09_2026

<p>Correlation analysis between variables.</p> Hikmet Kıztanır (24364745) Ebru Çetin Özbek (25111145) Medicine Biotechnology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Cancer Science Policy top 25 queries textual contents generated substantial access barrier provide extensive data predefined inclusion criteria pediatric chest pain optimized scores across observed citation biases independent user sessions frequently encountered symptom currently mature enough academic linguistic framework 51 textual responses level linguistic architecture three ai platforms three ai models grade comprehension threshold 001 ), mdiscern regarding content quality linguistic readability levels gemini offered linguistically 001 ), jama 001 ), content quality jama benchmarks high level quality paradox information quality 001 ). texts poses study aims source credibility scientific reliability perplexity outputs perplexity exhibited perplexity achieved performance closest paramount importance modified discern june 1 informational accuracy google trends examined using evaluated instruments emergency departments comparatively analyze audited via artificial intelligence 0167 ). <div><p>Pediatric chest pain represents a frequently encountered symptom in emergency departments and outpatient clinics throughout childhood, often generating substantial parental anxiety. This study aims to comparatively analyze the readability, information quality, and scientific reliability of textual contents generated by the artificial intelligence (AI) chatbots ChatGPT, Gemini, and Perplexity regarding pediatric chest pain, utilizing multidimensional analytical indices. Out of the top 25 queries with the highest global search volume on Google Trends, 17 unique keywords meeting the predefined inclusion criteria were filtered on June 1, 2026. These inquiries were directed to all three AI platforms in distinct, independent user sessions, yielding a total of 51 textual responses. Linguistic readability levels were calculated across six separate digital interfaces using the FKGL, FRES and other formulas, and the results were benchmarked against the sixth-grade reading level” threshold. Scientific reliability was audited via the Modified DISCERN and JAMA benchmarks, while content quality was examined using the GQS and EQIP instruments. The median readability scores computed across all three AI models were found to be statistically and significantly above the targeted sixth-grade comprehension threshold, indicating a high level of difficulty (p < 0.001). Post-hoc pairwise evaluations revealed that ChatGPT and Gemini offered linguistically more accessible and structurally less complex textual architectures; conversely, Perplexity exhibited a significantly more difficult and academic linguistic framework (p < 0.0167). On the other hand, regarding content quality and source credibility, Perplexity demonstrated remarkably superior and more optimized scores across all evaluated instruments, namely GQS (p = 0.002, p = 0.001), JAMA (p < 0.001, p < 0.001), mDISCERN (p = 0.005, p = 0.001), and EQIP (p = 0.003, p < 0.001), compared directly to both ChatGPT and Gemini, respectively. Although generative AI formulations harbor considerable potential to provide extensive data on pediatric chest pain, the sophisticated, university-level linguistic architecture of these texts poses a substantial access barrier for individuals who lack proficient digital health literacy skills. While Perplexity achieved the performance closest to the “gold standard” in terms of informational accuracy, no model is currently mature enough to substitute for a professional medical consultation due to observed citation biases and omissions. It is of paramount importance that clinicians actively guide families to scrutinize online health data through a critical lens.</p></div> 2026-09-25T17:26:15Z Dataset Dataset 10.1371/journal.pone.0359170.t005 https://figshare.com/articles/dataset/_p_Correlation_analysis_between_variables_p_/33997982 CC BY 4.0