Evaluating the Quality of TikTok Videos on Sudden Cardiac Death Using Multiple Scales: A Cross-Sectional Analysis of Correlations with Video Characteristics and High-Quality Health Information

Evaluating the Quality of TikTok Videos on Sudden Cardiac Death Using Multiple Scales: A Cross-Sectional Analysis of Correlations with Video Characteristics and High-Quality Health Information | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluating the Quality of TikTok Videos on Sudden Cardiac Death Using Multiple Scales: A Cross-Sectional Analysis of Correlations with Video Characteristics and High-Quality Health Information Mitansh Bansal, Ayesha Jalal, Firdous M Usman, Sadhana Sureshkumar, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7746991/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Social media platforms like TikTok have become a source of health information, particularly for younger audiences, but concerns remain about the accuracy and reliability of this content. This study assessed the quality, engagement, and sentiment of TikTok videos on sudden cardiac death (SCD), comparing healthcare professional (HCP) and non-HCP creators. Using Exolyt, the top 100 videos under two popular SCD hashtags were screened, and 83 met inclusion criteria. Engagement metrics (likes, comments, shares) and creator type were recorded, and quality was assessed with DISCERN, modified JAMA benchmarks, and a modified CRAAP test. Non-HCP videos achieved significantly higher engagement, with greater median reshares (p = 0.0050), favorited counts (p = 0.0495), and engagement rates (p = 0.0014). In contrast, HCP videos demonstrated higher quality scores, performing significantly better on the DISCERN (p < 0.0001), JAMA (p < 0.0001), and CRAAP (p < 0.0001) assessments. They were also more likely to present clear aims (p = 0.0023) and to describe benefits (p = 0.0030) and risks (p = 0.0005) of treatments. Sentiment analysis found no significant difference, though non-HCP videos were more often positive (59.1% vs. 40.9%, p = 0.332). In summary, HCPs produce more accurate and reliable content, while non-HCPs achieve greater reach and interaction. Enhancing the visibility of evidence-based content may require collaborations between HCPs and creators or platform-level interventions. Health sciences/Cardiology Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Sudden cardiac death Social media TikTok Digital Health Health Education Access Cardiovascular health Figures Figure 1 Background TikTok has become one of the most popular platforms for sharing health information among younger audiences 1 , 2 . With an estimated 1.8 billion active users by the end of 2024, TikTok is a key site for health content and a breeding ground for misinformation 2 , 3 . Given the freedom of content creation along with TikTok lightly regulates false information 4 , hate speech, or explicit content they also advocate for free speech and freedom of creation 5 . This leads to widespread misinformation because of the lack of regulation to see if the content is factually correct 6 . TikTok's algorithm prioritizes content based on engagement metrics like likes, shares, and comments, which can amplify the reach of videos regardless of their accuracy 7 . As a result, even misleading or dangerous misinformation can go viral, reaching millions of users 7 . This reflects people not knowing the actual truth about health conditions. Given that TikTok is one of the largest platforms for spreading information it is important to see how much of it is the truth. Sudden cardiac death (SCD) is a leading cause of death globally, often occurring without warning, and requiring immediate intervention for survival 8 , 9 . Although prior studies have evaluated the portrayal of cardiomyopathy 10 , heart failure 11 , and coronary artery disease 12 on social media platforms, limited research has specifically addressed the representation of SCD. TikTok, a platform with significant influence among younger audiences, contains a high volume of health-related content generated predominantly by non-medical individuals 13 , 14 . These videos frequently oversimplify complex cardiovascular conditions, propagate misconceptions, and lack adherence to evidence-based information 10 – 12 . This concern is underscored by quantitative assessments of content quality; for instance, a TikTok analysis study on Takotsubo syndrome-related videos on TikTok has shown an average DISCERN score 15 of 36.93 out of 80 and a JAMA Benchmark score 16 of 1.51 out of 4. While none of the evaluated videos met all the JAMA benchmark criteria, this indicates significant concerns regarding the reliability and quality of health information presented on the social media platform 10 . While there has been growing attention to the role of social media in spreading health misinformation, research on the specific topic of sudden cardiac death on TikTok is lacking. This study aims to analyze the prevalence, nature, and impact of misinformation related to sudden cardiac death (SCD) on TikTok. Specifically, the research will investigate how such misinformation contributes to public misunderstanding of cardiac arrest, with a focus on the role of popular hashtags, video content, and the creators behind the videos. The study will assess how misinformation about SCD is spread via TikTok's algorithm. The findings of this research will allow healthcare providers to better address and correct potential misinformation their patients may be receiving from online sources. Method Study Design and Data Collection This cross-sectional study collected data from TikTok using Exolyt, an AI driven analytics platform specific to TikTok, to identify the top-performing hashtags related to sudden cardiac death. The initial sample included 100 videos from the two most popular hashtags (#suddencardiacdeath and #suddencardiacdeathawareness). Seven videos were excluded as duplicates or non-English content (five from #suddencardiacdeath and two from #suddencardiacdeathawareness), and ten were excluded due to insufficient data, resulting in a final sample of 83 videos. Of these, 31 were created by healthcare professionals (HCPs) and 52 by non-HCPs (Fig. 1 ). Videos were systematically reviewed to extract engagement metrics, including likes, comments, and shares, and to classify the creator type as healthcare professional (HCP) or non-HCP. The health information presented in the videos was evaluated using three structured assessment tools: the DISCERN Scale, a modified JAMA benchmark, and a modified version of the Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) test. Three student researchers independently reviewed and scored each video using all three tools, remaining blind to each other’s assessments to reduce bias. Each video was evaluated by at least two researchers, and any discrepancies were resolved through group discussions, involving a careful review of the video content and the application of evaluation criteria. For each tool, scores from individual questions were summed to generate an overall quality score for each video. DISCERN Scale The DISCERN Scale is a validated instrument designed to assess the quality of written consumer health information 15 . It evaluates the reliability of treatment information and the overall quality of a publication. The DISCERN Scale consists of 16 questions, each scored on a 0–4 scale, assessing aspects such as the clarity of aims, the reliability of sources, the balance of information, and the discussion of treatment options. In this study, we adapted the DISCERN Scale to assess the quality of treatment or health information discussed within the video format. We analyzed how clearly the videos presented information about health conditions and their management, assessed the reliability of the sources cited within the video, and evaluated the balance and objectivity of the information provided. Modified JAMA Benchmark Score The JAMA benchmark 16 , originally developed to evaluate health information on web pages based on authorship, attribution, disclosure, and currency, was adapted for this study to assess social media videos. While the benchmark was originally intended for structured, text-based resources, videos incorporate visual, auditory, and textual elements, presenting unique evaluation challenges. To address this, each of the four benchmark domains was scored on a scale of 0 to 4, rather than the original dichotomous approach, to better capture partial disclosures or incomplete author credentials commonly found in video content (e-table 1). This adaptation allows greater sensitivity in distinguishing qualitative differences. In line with prior research 17 , scores were categorized as follows: 0–1 indicating low reliability, 2–3 moderate reliability, and 4 high reliability. A higher score reflects greater trustworthiness, accuracy, and completeness, while a score of zero suggests poor reliability 17 . Modified Currency, Relevance, Authority, Accuracy, Purpose (CRAAP) Test Score The CRAAP test 18 , a framework originally developed at California State University, Chico to evaluate the credibility of online sources, was adapted for this study. The CRAAP test includes five domains: currency, relevance, authority, accuracy, and purpose, and each domain contains multiple guiding questions. For the purposes of healthcare video content analysis, these domains were simplified and modified to better fit the nature of short-form social media content consistent with prior adaptations in health video content analysis (e-table 2) 19,20 . The relevance domain was condensed into a single evaluative question tailored for video analysis. Currency was adjusted to emphasize whether videos referenced recent research, data, or clinical guidelines, rather than focusing on publication dates or link functionality. Authority focused on the creator’s expertise and reputation in healthcare, while accuracy examined factual correctness, consistency with current evidence, and the avoidance of misleading information. Purpose was reframed to differentiate between educational and promotional intent. An additional source domain was incorporated to reflect the wide range of origins of social media content, giving priority to videos produced by reputable institutions or certified professionals. Each domain was scored on a scale from 0, representing poor quality, to 4, representing excellent quality, and the scores were summed to generate an overall quality rating. Statistical Analysis Descriptive statistics were calculated for all study variables, including follower count, video duration (in seconds), view count, number of comments, likes, reshares, times favorited, engagement rate, healthcare professional (HCP) status, DISCERN score, Modified JAMA score, and Modified CRAAP score. Continuous variables were summarized using medians and interquartile ranges, while categorical variables were presented as frequencies and percentages. For comparative analyses, videos were grouped based on creator type (HCP vs. non-HCP). Univariate analyses were conducted to compare differences between these groups. The Wilcoxon rank-sum test was used for continuous variables, Fisher’s exact test for nominal variables, and the chi-square test for ordinal variables. Statistical significance was determined using two-tailed p-values, with a threshold of p < 0.05. To examine associations between video quality scores (DISCERN, Modified JAMA, and Modified CRAAP) and video characteristics such as follower count, video duration, number of views, comments, likes, reshares, times favorited, engagement rate, and HCP status; Spearman’s rank correlation coefficient (rho) (ρ) was used. This non-parametric method was chosen due to its suitability for analyzing monotonic relationships in ordinal or non-normally distributed continuous data. Correlation coefficients and their corresponding p-values were reported to reflect the strength, direction, and statistical significance of these associations. Additionally, sentiment analysis was performed on video captions and comments to categorize the emotional tone as positive, negative, or neutral. Spearman’s rank correlation was also used to assess the relationships between sentiment scores and other variables, including follower count, video duration, number of views, user engagement metrics (comments, likes, reshares, favorites), engagement rate, HCP status, and the three quality scores (DISCERN, Modified JAMA, and Modified CRAAP). Results The comparison of video metrics, quality scores, and sentiment revealed several important differences between healthcare professional (HCP) and non-HCP content (Table 1 ). HCP videos were significantly longer with a median duration of 65 seconds compared with non-HCP (39.5 seconds) (p = 0.0102) and had more reshares (Median 6 vs 2, p = 0.0050) and lower engagement rates (Median 1.3 vs 5.2, p = 0.0014) compared to non-HCP videos(Table 1 ). Conversely, HCP videos demonstrated significantly higher median scores for DISCERN (41.5 vs 26.75, p < 0.0001), JAMA Benchmark (9.5 vs 3.3, p < 0.0001), and Modified CRAAP assessments (26 vs 11, p < 0.0001) (Table 1 ). Regarding sentiment, a higher percentage of non-HCP videos exhibited positive sentiment (59.1%) compared to HCP videos (40.9%), though this difference was not statistically significant (p = 0.332) (Table 1 ). Table 1 Video Characteristics, Engagement Metrics, and Quality Scores of Sudden Cardiac Death (SCD) TikTok Videos by Creator Type (Healthcare Professional vs. Non-Healthcare Professional) Overall (N = 83) HCP (N = 31) Non-HCP (N = 52) P-value Video Metrics Number of followers- Median (IQR) 2537 (1920–4297) 4292 (1920–16000) 2537 (1243–2540) 0.1583 Video duration in seconds- Median (IQR) 56 (24–102) 65 (54–104) 39.5 (16.3–98.8) 0.0102* Number of views- Median (IQR) 1311 (724–2511) 1524 (872–5258) 1286 (497.5- 2201.8) 0.3071 Number of comments- Median (IQR) 7 (1–21) 4 (0–17) 10.5 (3- 21.8) 0.0973 Number of likes- Median (IQR) 78 (23–143) 37 (13–157) 104.5 (40.8- 139.8) 0.1249 Number of reshares- Median (IQR) 2 (1–7) 6 (2–13) 2 (1–4) 0.0050* Number of Favorited- Median (IQR) 2 (1–10) 4 (1–26) 2 (1–4) 0.0495* Engagement Rate- Median (IQR) 3.7 (1.0- 7.7) 1.3 (0.7–3.7) 5.2 (1.8–9.2) 0.0014* DISCERN Score- Median (IQR) 29 (23.5–38) 41.5 (28.5–46) 26.75 (22.5–32) < 0.0001* Jama Benchmark Score- Median (IQR) 5.5 (3.0- 8.5) 9.5 (7.0- 11.5) 3.3 (2- 5.9) < 0.0001* Modified CRAAP Score- Median (IQR) 14 (9.5–24.5) 26 (21- 30.5) 11 (7.5–14.8) < 0.0001* Sentiment of video Positive 44 (53) 18 (40.9) 26 (59.1) 0.332 Neutral 28 (33.7) 11 (39.3) 17 (60.7) Negative 11 (13.3) 2 (18.2) 9 (81.8) * p-value < 0.05 indicates statistical significance. Abbreviation: IQR: Interquartile Range; HCP: Healthcare Professional; Non-HCP: Non-Healthcare Professional Analysis of individual DISCERN domains indicated that HCP videos were significantly stronger in presenting clear aims (median 3 vs 2, p = 0.0023), achieving aims (median 3 vs 2, p < 0.0001), demonstrating relevance (median 3.5 vs 2, p < 0.0001), identifying sources (median 2 vs 1, p < 0.0001), and indicating information clearly (median 2 vs 1, p < 0.0001) (Table 2 ). They also outperformed non-HCPs in providing balanced perspectives (median 3 vs 2.5, p = 0.0272), additional resources (median 2 vs 1, p < 0.0001), and detailed descriptions of treatment mechanisms (median 2.5 vs 1, p < 0.0001), benefits (median 2 vs 1, p = 0.0030), risks (median 2 vs 1, p = 0.0005), consequences of no treatment (median 2 vs 1, p = 0.0022), impact on quality of life (median 2 vs 1, p = 0.0068), and multiple treatment options (median 2 vs 1, p = 0.0007) (Table 2 ). Higher overall quality ratings were also observed (median 3 vs 2, p = 0.0003). No significant differences were found in referral to uncertainty (p = 0.1698) or support for shared decision-making (p = 0.6009) (Table 2 ). Table 2 Comparison of DISCERN Score Domains in TikTok Videos By Healthcare Professionals and Non-Healthcare Professionals status Overall (N = 83) HCP (N = 31) Non-HCP (N = 52) P-value Are the aims clear? Median (IQR) 2.5 (2–3) 3 (2–4) 2 (2–3) 0.0023* Does it achieve its aims? (Skip if answer to first question is No) Median (IQR) 2 (2–3) 3 (2- 3.5) 2 (1.6–2.5) < 0.0001* Is it relevant? Median (IQR) 2.5 (2–3) 3.5 (2–4) 2 (2–3) < 0.0001* Is it clear what sources of information were used to compile the publication (other than the author or producer)? Median (IQR) 1.5 (1–2) 2 (1.5- 3) 1 (1- 1.5) < 0.0001* Is it clear when the information used or reported in the publication was produced? Median (IQR) 1 (1–2) 2 (1–2) 1 (1- 1.4) < 0.0001* Is it balanced and unbiased? Median (IQR) 3 (2–3) 3 (2- 3.5) 2.5 (2–3) 0.0272* Does it provide details of additional sources of support and information? Median (IQR) 1.5 (1–2) 2 (1.5- 3) 1 (1- 1.5) < 0.0001* Does it refer to areas of uncertainty? Median (IQR) 2 (1.5- 3) 2 (2–3) 2 (1.5–2.9) 0.1698 Does it describe how each treatment works? Median (IQR) 1.5 (1- 2.5) 2.5 (1.5- 3) 1 (1–2) < 0.0001* Does it describe the benefits of each treatment? Median (IQR) 1.5 (1- 2.5) 2 (1–3) 1 (1–2) 0.0030* Does it describe the risks of each treatment? Median (IQR) 1 (1–2) 2 (1–3) 1 (1- 1.5) 0.0005* Does it describe what would happen if no treatment is used? Median (IQR) 1.5 (1–2) 2 (1- 2.5) 1 (1- 1.5) 0.0022* Does it describe how the treatment choices affect overall quality of life? Median (IQR) 1.5 (1–2) 2 (1- 2.5) 1 (1–2) 0.0068* Is it clear that there may be more than one possible treatment choice? Median (IQR) 1 (1–2) 2 (1–3) 1 (1- 1.5) 0.0007* Does it provide support for shared decision-making? Median (IQR) 2 (1–3) 2 (1.5–2.5) 2 (1–3) 0.6009 Based on the answers to all of the above questions- rate the overall quality of the publication as a source of information about treatment choices- Median (IQR) 2 (1–3) 3 (2- 3.5) 2 (1- 2.5) 0.0003* *p-value < 0.05 indicates statistical significance. Abbreviation: IQR: Interquartile Range; HCP: Healthcare Professional; Non-HCP: Non-Healthcare Professional Across JAMA Benchmark domains, HCP videos consistently scored higher, with stronger authorship (median 3 vs 0.8, p < 0.0001), attribution of sources (median 2 vs 1, p < 0.0001), currency of content (median 2.5 vs 0.8, p < 0.0001), and avoidance of promotional motives (median 3 vs 1.25, p < 0.0001) (Table 3 ). Similarly, Modified CRAAP scores were higher for HCP content across all domains, including creator credibility (median 2.5 vs 0.5, p < 0.0001), verifiable credentials (median 2 vs 0, p < 0.0001), relevant expertise (median 2.5 vs 1, p < 0.0001), recognized professionals (median 2.5 vs 0, p < 0.0001), presentation of background (median 2 vs 1, p < 0.0001), accuracy of information (median 3 vs 1, p < 0.0001), guideline-based support (median 2 vs 1, p < 0.0001), avoidance of inaccuracies (median 2 vs 2, p = 0.0002), updates to reflect recent changes (median 1 vs 1, p = 0.0138), educational purpose (median 3 vs 2, p < 0.0001), and objectivity (median 3 vs 1.5, p < 0.0001) (Table 3 ). Table 3 Comparison of Modified JAMA Benchmark score and Modified CRAAP test score Domains in TikTok Videos by Healthcare Professionals and Non-Healthcare Professionals status Overall (N = 83) HCP (N = 31) Non-HCP (N = 52) P-value The Journal of the American Medical Association (JAMA) benchmark criteria Authorship (Author and contributor credentials and their affiliations should be provided)- median (IQR) Is the video created by a credible source (e.g.- recognized health institution- medical university- or board-certified professional)? Median (IQR) 1 (0- 2.5) 3 (2–3) 0.8 (0–1) < 0.0001* Attribution (Clearly lists all copyright information and states references and sources for content)- median (IQR) Does the video reference recent studies- data- or treatment protocols? Median (IQR) 1 (0–2) 2 (1.5- 2) 1 (0- 1.5) < 0.0001* Currency (Initial date of posted content and subsequent updates to content should be provided)- median (IQR) Is the content up to date- reflecting the latest research- clinical guidelines- and medical practices? Median (IQR) 1 (0–2) 2.5 (1.5- 3) 0.8 (0- 1.5) < 0.0001* Disclosure (Conflicts of interest- funding- sponsorship- advertising- support- and video ownership should be fully disclosed)- median (IQR) Does the video avoid commercial- promotional- or entertainment-driven motives? Median (IQR) 2 (1–3) 3 (2.5- 3) 1.25 (0.6–2.5) < 0.0001* Modified Currency- Relevance- Authority- Accuracy- and Purpose (CRAAP) Source Is the organization or individual behind the video well-known and respected in the field of health or medicine? Median (IQR) 1 (0–2.5) 2.5 (2–3) 0.5 (0–1) < 0.0001* Can you verify the source's credentials or affiliations? Median (IQR) 0.5 (0–2) 2 (1.5–2.5) 0 (0- 0.5) < 0.0001* Relevance Does this video give useful and reliable health information that fits my research topic and audience? 2.0 (2.0–3.0) 3.0 (2.0–4.0) 2.0 (2.0–2.8) < 0.0001* Authority Does the creator have relevant qualifications or expertise in the topic covered in the video? Median (IQR) 1 (0.5–2) 2.5 (2–3) 1 (0.5- 1) < 0.0001* Is the creator a recognized expert or a board-certified professional in the relevant field (e.g.- medicine- nursing- public health)? Median (IQR) 0.5 (0–2) 2.5 (2–3) 0 (0- 0.5) < 0.0001* Is the creator's experience or background clearly presented in the video? Median (IQR) 1.5 (1–2) 2 (2- 2.5) 1 (0.5–1.5) < 0.0001* Accuracy Is the information presented in the video factually correct and based on current medical evidence? Median (IQR) 2 (1–3) 3 (2–3) 1 (0.6- 2) < 0.0001* Are any claims supported by well-established scientific or clinical guidelines? Median (IQR) 1 (0.5- 2) 2 (1.5- 3) 1 (0–1) < 0.0001* Does the video avoid misleading or inaccurate information? Median (IQR) 2 (1- 2.5) 2 (2–3) 2 (1–2) 0.0002* Currency Has the information been updated to account for any recent changes in guidelines or clinical recommendations? Median (IQR) 1 (0- 1.5) 1 (0.5- 2) 1 (0–1) 0.0138* Purpose Is the primary purpose of the video to inform or educate the viewer? Median (IQR) 2 (1.5- 3) 3 (2.5–3.5) 2 (1- 2.5) < 0.0001* Is the content presented in an unbiased and objective manner- without an underlying agenda or marketing focus? Median (IQR) 2 (1–3) 3 (2.5- 3) 1.5 (1–2) < 0.0001* *p-value < 0.05 indicates statistical significance. Abbreviation: IQR: Interquartile Range; HCP: Healthcare Professional; Non-HCP: Non-Healthcare Professional Correlation analyses showed that video duration was positively associated with DISCERN (ρ = 0.2905, p = 0.0077), JAMA (ρ = 0.2708, p = 0.0133), and CRAAP scores (ρ = 0.3209, p = 0.0031) (Table 4 ). The number of reshares also correlated with higher DISCERN (ρ = 0.2394, p = 0.0293), JAMA (ρ = 0.3395, p = 0.0017), and CRAAP scores (ρ = 0.4182, p < 0.0001) (Table 4 ). Videos marked as favorites were positively associated with JAMA (ρ = 0.2626, p = 0.0165) and CRAAP scores (ρ = 0.3118, p = 0.0041) (Table 4 ). Other metrics, such as likes, comments, and engagement rate, showed no significant associations (Table 4 ). HCP status itself was strongly correlated with all three quality measures: DISCERN (ρ = 0.4456, p < 0.0001), JAMA (ρ = 0.7004, p < 0.0001), and CRAAP (ρ = 0.7103, p < 0.0001) (Table 4 ). Table 4 Correlations of DISCERN, Modified JAMA Benchmark, and Modified CRAAP Test Scores in TikTok Videos with Video Characteristics and Health Care Professional Status Multivariate Correlation (r) Spearman rank correlation coefficient p-value DISCERN Score Number of followers 0.115 0.072 0.516 Video duration in seconds 0.165 0.291 0.008* Number of views 0.173 0.133 0.233 Number of comments 0.034 -0.018 0.872 Number of likes 0.030 0.012 0.914 Number of reshares 0.185 0.239 0.029* Engagement rate 0.013 -0.004 0.973 Favorited 0.201 0.206 0.062 HCP 0.516 0.446 < 0.0001* Sentiment of video ( 1 = Positive- 2 = Neutral- 3 = Negative 4 = not applicable) 0.059 0.004 0.972 Modified JAMA Benchmark Score Number of followers 0.089 0.181 0.102 Video duration in seconds 0.106 0.271 0.013* Number of views 0.013 0.133 0.232 Number of comments -0.043 -0.083 0.458 Number of likes -0.087 -0.041 0.711 Number of reshares 0.032 0.340 0.002* Engagement rate -0.039 -0.215 0.051 Favorited 0.031 0.263 0.017* HCP 0.711 0.700 < 0.0001* Sentiment of video ( 1 = Positive- 2 = Neutral- 3 = Negative 4 = not applicable) -0.032 -0.041 0.714 Modified Currency- Relevance- Authority- Accuracy- Purpose (CRAAP) Test Score Number of followers 0.102 0.164 0.140 Video duration in seconds 0.129 0.321 0.003* Number of views 0.107 0.186 0.092 Number of comments 0.002 -0.055 0.621 Number of likes -0.021 -0.023 0.840 Number of reshares 0.116 0.418 < 0.0001* Engagement rate -0.097 -0.159 0.150 Favorited 0.132 0.312 0.004* HCP 0.734 0.710 < 0.0001* Sentiment of video ( 1 = Positive- 2 = Neutral- 3 = Negative 4 = not applicable) -0.046 -0.066 0.552 *p-value < 0.05 indicates statistical significance. Sentiment in video content showed a statistically significant negative correlation with video duration (ρ = − 0.346, p = 0.001) (Table 5 ). Weak positive but non-significant associations were observed between sentiment and follower count (ρ = 0.177, p = 0.110), number of likes (ρ = 0.181, p = 0.102), and times favorited (ρ = 0.185, p = 0.094) (Table 5 ). No significant correlations were found with number of views (ρ = 0.078, p = 0.481), comments (ρ = 0.009, p = 0.933), reshares (ρ = 0.043, p = 0.697), or engagement rate (ρ = − 0.072, p = 0.517) (Table 5 ). Sentiment did not vary significantly by creator type, with a weak and non-significant correlation for healthcare professional status (ρ = − 0.113, p = 0.311) (Table 5 ). Similarly, no significant associations were observed between sentiment and any of the quality assessment scores, including DISCERN (ρ = 0.004, p = 0.972), Modified JAMA (ρ = − 0.041, p = 0.714), or CRAAP (ρ = − 0.066, p = 0.552) (Table 5 ). Table 5 Correlations of Video Sentiment with TikTok Video Characteristics, Health Care Professional Status, DISCERN Score, Modified JAMA Benchmark Scores, and Modified CRAAP Test Scores Multivariate Correlation (r) Spearman rank correlation coefficient p-value Number of followers 0.158 0.177 0.110 Video duration in seconds -0.310 -0.346 0.001* Number of views coded 0.214 0.078 0.481 Number of comments 0.226 0.009 0.933 Number of likes 0.223 0.181 0.102 Number of reshares 0.196 0.043 0.697 Engagement rate -0.003 -0.072 0.517 Favorited 0.194 0.185 0.094 HCP revised -0.129 -0.113 0.311 Discern Score 0.059 0.004 0.972 JAMA Score -0.032 -0.041 0.714 Modified Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) Score -0.046 -0.066 0.552 *p-value < 0.05 indicates statistical significance. Discussion This cross-sectional analysis highlights the disparities in the quality of TikTok videos related to sudden cardiac death (SCD) content between healthcare professionals (HCPs) and non-HCPs. The findings demonstrate that HCP-generated videos are generally superior in terms of content quality, credibility, and accuracy, but tend to have lower engagement rates and shorter dissemination reach compared to non-HCP videos. The significantly higher DISCERN, JAMA Benchmark, and Modified CRAAP scores for HCP videos underscore their ability to provide evidence-based, factually correct, and unbiased information. Such findings align with previous studies emphasizing the importance of professional expertise in maintaining content accuracy in health communication 21 , 22 . In contrast, non-HCP videos generally achieved lower quality scores but demonstrated higher engagement metrics, including reshares, favorites, and overall engagement. This contrast is consistent with previous research suggesting that non-HCP creators often employ emotionally engaging and relatable tones, which may resonate more effectively with audiences and drive higher engagement metrics 23 . A possible explanation for these findings is that digital platforms favor emotionally engaging content, which may attract more views and interactions, whereas HCP-produced content, although more accurate, may lack such narrative appeal. Supporting evidence from Vargo et al 24 suggests that positive emotion creates a good experience for the audience and a positive image of the sharer, significantly increasing user engagement, However, as noted in prior studies, this emotional appeal can come at the cost of accuracy and credibility 23 , 25 . The correlations between quality assessment scores and video metrics in this study reveal important patterns in audience engagement and content preference. Higher quality scores were negatively correlated with likes, suggesting that videos with more educational depth and accuracy may attract less engagement on social media platforms. This finding aligns with prior research on TikTok content related to gallstone disease, where videos with higher likes, shares, and comments were often of lower quality, indicating a preference for entertaining rather than informative content 26 . Similarly, research on breast cancer-related videos on TikTok and BiliBili revealed a weak negative correlation between video quality and likes and comments, suggesting that viewers have difficulty distinguishing between high-quality and low-quality videos 27 . This is further supported in an analysis of vocal health content on TikTok which suggest that most popular videos were produced by non-clinicians, with measures of popularity either uncorrelated or negatively correlated with quality, reliability, and accuracy 28 . A strong correlation was observed between HCP status and quality assessment scores, highlighting that videos produced by healthcare professionals consistently maintain higher standards of accuracy and reliability. This observation aligns with previous studies, which similarly found that professional content tends to be more trustworthy than videos created by non-professionals 29 , 30 . These trends may be explained by platform algorithms that favor visually appealing, emotionally engaging, or trend-driven content over evidence-based material 31 . Popularity can also be influenced by factors unrelated to quality, such as creator charisma or video aesthetics 31 . This highlights the need for platforms like TikTok to create environments where high-quality, evidence-based health content can reach and impact audiences. This study is one of the first to examine TikTok videos about sudden cardiac death (SCD), providing insights into the quality and engagement of healthcare professional (HCP) and non-HCP content. The use of established evaluation tools, such as DISCERN, JAMA Benchmark, and Modified CRAAP, strengthens the reliability of the analysis. Including both quantitative and sentiment analysis allows for a comprehensive understanding of video quality and audience interaction. By analyzing multiple engagement metrics, such as likes, shares, and comments, this research connects content quality with audience behaviors. This study has several limitations. It provides only a cross-sectional view and does not track changes over time in video content or engagement trends. The use of hashtags to identify videos may exclude relevant content that was not tagged appropriately. The focus on English-language videos limits the generalizability of findings to non-English-speaking populations, and TikTok-specific features, such as algorithms that promote certain types of content, are not fully addressed and may influence video reach and engagement. Furthermore, the modified JAMA and CRAAP scales used for quality assessment are not standardized, as formal internal validation was not conducted, and quality ratings may be influenced by evaluator subjectivity, requiring further evaluation in future studies. Implication and future direction The findings highlight an ongoing tension between engagement and factual accuracy in health-related social media content. While videos from healthcare professionals tend to be more reliable, both professional and non-professional content often lack proper citations and discussion of treatment risks, which can compromise the quality of information provided 25 . In life-threatening or complex medical contexts, such as sudden cardiac death, it is particularly important to balance emotional appeal with evidence-based accuracy. Educational videos on specialized topics should be of sufficient duration to provide comprehensive information, clearly cite authoritative sources, and communicate uncertainties in current knowledge. Digital platforms like TikTok have improved access to health information but often lack the empathetic context of face-to-face interactions, potentially leading to misunderstanding or emotional distress 32 , 33 . Strengthening platform content review mechanisms, limiting misleading advertisements, and implementing AI-driven monitoring or active professional engagement in comment sections could help ensure accurate information dissemination and reduce misinformation. The proliferation of unverified medical content may pose health risks and financial burdens to viewers, underscoring the need for stricter regulation. Future research should compare content quality across multiple video-sharing platforms to identify best practices for effective, trustworthy health communication in the digital space. Conclusion This study found that healthcare professionals produce higher-quality health content on TikTok compared to non-HCP creators, but struggle to achieve the same level of audience engagement. Non-HCP videos often rely on entertainment and emotional appeal, which boosts their reach but may compromise accuracy. The findings emphasize the need for strategies that improve the accessibility and impact of professional health content, such as collaborations or platform adjustments. Future research should explore ways to enhance the visibility and effectiveness of credible health messaging on TikTok. Abbreviations CRAAP: Currency, Relevance, Authority, Accuracy, and Purpose HCP: Health Care Professionals IQR-Interquartile Range non-HCP: non health care professionals SCD: Sudden cardiac death Declarations Conflict of Interest Statement: None of the authors have any conflict of interest to declare. Author Contribution: *Data review and collection done by MB. AJ, FMU and SS. Statistical analysis was done by RK & VB. Study design and critical review done by MR, VB, FAZ, and RK. MR, VB, FAZ, and RK are the guarantor of the paper, taking responsibility for the integrity of the work, from inception to published article. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Acknowledgement: Data from this study has been submitted in abstract form for consideration at the upcoming SCCM 2026 Critical Care Congress. The manuscript underwent English-language review with assistance from Grammarly. 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Supplementary Files SupplementalTables.docx e-table 1: Adapted JAMA Benchmark Criteria for Evaluating Healthcare Video Content with 0–4 Scoring Interpretation e-table 2: Modified CRAAP Criteria for Evaluating Healthcare Video Content with 0–4 Scoring Interpretation Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 22 Dec, 2025 Reviews received at journal 19 Dec, 2025 Reviews received at journal 18 Dec, 2025 Reviewers agreed at journal 01 Dec, 2025 Reviewers agreed at journal 30 Nov, 2025 Reviews received at journal 16 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviewers invited by journal 03 Nov, 2025 Editor assigned by journal 23 Oct, 2025 Editor invited by journal 13 Oct, 2025 Submission checks completed at journal 10 Oct, 2025 First submitted to journal 10 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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16:59:38","extension":"html","order_by":33,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":158328,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7746991/v1/8f3b34798add44a1703e807d.html"},{"id":95857337,"identity":"faa126b5-4b14-4811-a61d-8ff4625a600e","added_by":"auto","created_at":"2025-11-13 16:59:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49307,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow Diagram of Sudden Cardiac Death TikTok Video Selection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7746991/v1/7bb05b6736e108b732a9debf.png"},{"id":105755606,"identity":"52bd6304-ba59-48fb-ba13-d38e89c33945","added_by":"auto","created_at":"2026-03-30 16:28:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3387903,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7746991/v1/52788be3-90cd-44eb-bbb9-82a43bfb15a8.pdf"},{"id":95857338,"identity":"98e1558a-b1ae-427d-a115-ac66e926706d","added_by":"auto","created_at":"2025-11-13 16:59:37","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19555,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ee-table 1: Adapted JAMA Benchmark Criteria for Evaluating Healthcare Video Content with 0–4 Scoring Interpretation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee-table 2: Modified CRAAP Criteria for Evaluating Healthcare Video Content with 0–4 Scoring Interpretation\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementalTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7746991/v1/2c86d38c2f0ee90219643c7f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating the Quality of TikTok Videos on Sudden Cardiac Death Using Multiple Scales: A Cross-Sectional Analysis of Correlations with Video Characteristics and High-Quality Health Information","fulltext":[{"header":"Background","content":"\u003cp\u003eTikTok has become one of the most popular platforms for sharing health information among younger audiences\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. With an estimated 1.8\u0026nbsp;billion active users by the end of 2024, TikTok is a key site for health content and a breeding ground for misinformation\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Given the freedom of content creation along with TikTok lightly regulates false information\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, hate speech, or explicit content they also advocate for free speech and freedom of creation\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. This leads to widespread misinformation because of the lack of regulation to see if the content is factually correct\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. TikTok's algorithm prioritizes content based on engagement metrics like likes, shares, and comments, which can amplify the reach of videos regardless of their accuracy\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. As a result, even misleading or dangerous misinformation can go viral, reaching millions of users\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This reflects people not knowing the actual truth about health conditions. Given that TikTok is one of the largest platforms for spreading information it is important to see how much of it is the truth.\u003c/p\u003e\u003cp\u003eSudden cardiac death (SCD) is a leading cause of death globally, often occurring without warning, and requiring immediate intervention for survival\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Although prior studies have evaluated the portrayal of cardiomyopathy\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, heart failure\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, and coronary artery disease\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e on social media platforms, limited research has specifically addressed the representation of SCD. TikTok, a platform with significant influence among younger audiences, contains a high volume of health-related content generated predominantly by non-medical individuals\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These videos frequently oversimplify complex cardiovascular conditions, propagate misconceptions, and lack adherence to evidence-based information\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. This concern is underscored by quantitative assessments of content quality; for instance, a TikTok analysis study on Takotsubo syndrome-related videos on TikTok has shown an average DISCERN score\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e of 36.93 out of 80 and a JAMA Benchmark score\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e of 1.51 out of 4. While none of the evaluated videos met all the JAMA benchmark criteria, this indicates significant concerns regarding the reliability and quality of health information presented on the social media platform\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile there has been growing attention to the role of social media in spreading health misinformation, research on the specific topic of sudden cardiac death on TikTok is lacking. This study aims to analyze the prevalence, nature, and impact of misinformation related to sudden cardiac death (SCD) on TikTok. Specifically, the research will investigate how such misinformation contributes to public misunderstanding of cardiac arrest, with a focus on the role of popular hashtags, video content, and the creators behind the videos. The study will assess how misinformation about SCD is spread via TikTok's algorithm. The findings of this research will allow healthcare providers to better address and correct potential misinformation their patients may be receiving from online sources.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Data Collection\u003c/h2\u003e\u003cp\u003eThis cross-sectional study collected data from TikTok using Exolyt, an AI driven analytics platform specific to TikTok, to identify the top-performing hashtags related to sudden cardiac death. The initial sample included 100 videos from the two most popular hashtags (#suddencardiacdeath and #suddencardiacdeathawareness). Seven videos were excluded as duplicates or non-English content (five from #suddencardiacdeath and two from #suddencardiacdeathawareness), and ten were excluded due to insufficient data, resulting in a final sample of 83 videos. Of these, 31 were created by healthcare professionals (HCPs) and 52 by non-HCPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Videos were systematically reviewed to extract engagement metrics, including likes, comments, and shares, and to classify the creator type as healthcare professional (HCP) or non-HCP. The health information presented in the videos was evaluated using three structured assessment tools: the DISCERN Scale, a modified JAMA benchmark, and a modified version of the Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) test. Three student researchers independently reviewed and scored each video using all three tools, remaining blind to each other\u0026rsquo;s assessments to reduce bias. Each video was evaluated by at least two researchers, and any discrepancies were resolved through group discussions, involving a careful review of the video content and the application of evaluation criteria. For each tool, scores from individual questions were summed to generate an overall quality score for each video.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDISCERN Scale\u003c/h3\u003e\n\u003cp\u003eThe DISCERN Scale is a validated instrument designed to assess the quality of written consumer health information\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. It evaluates the reliability of treatment information and the overall quality of a publication. The DISCERN Scale consists of 16 questions, each scored on a 0\u0026ndash;4 scale, assessing aspects such as the clarity of aims, the reliability of sources, the balance of information, and the discussion of treatment options. In this study, we adapted the DISCERN Scale to assess the quality of treatment or health information discussed within the video format. We analyzed how clearly the videos presented information about health conditions and their management, assessed the reliability of the sources cited within the video, and evaluated the balance and objectivity of the information provided.\u003c/p\u003e\n\u003ch3\u003eModified JAMA Benchmark Score\u003c/h3\u003e\n\u003cp\u003eThe JAMA benchmark\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, originally developed to evaluate health information on web pages based on authorship, attribution, disclosure, and currency, was adapted for this study to assess social media videos. While the benchmark was originally intended for structured, text-based resources, videos incorporate visual, auditory, and textual elements, presenting unique evaluation challenges. To address this, each of the four benchmark domains was scored on a scale of 0 to 4, rather than the original dichotomous approach, to better capture partial disclosures or incomplete author credentials commonly found in video content (e-table 1). This adaptation allows greater sensitivity in distinguishing qualitative differences. In line with prior research\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, scores were categorized as follows: 0\u0026ndash;1 indicating low reliability, 2\u0026ndash;3 moderate reliability, and 4 high reliability. A higher score reflects greater trustworthiness, accuracy, and completeness, while a score of zero suggests poor reliability\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eModified Currency, Relevance, Authority, Accuracy, Purpose (CRAAP) Test Score\u003c/h3\u003e\n\u003cp\u003eThe CRAAP test\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, a framework originally developed at California State University, Chico to evaluate the credibility of online sources, was adapted for this study. The CRAAP test includes five domains: currency, relevance, authority, accuracy, and purpose, and each domain contains multiple guiding questions. For the purposes of healthcare video content analysis, these domains were simplified and modified to better fit the nature of short-form social media content consistent with prior adaptations in health video content analysis (e-table 2)\u003csup\u003e19,20\u003c/sup\u003e. The relevance domain was condensed into a single evaluative question tailored for video analysis. Currency was adjusted to emphasize whether videos referenced recent research, data, or clinical guidelines, rather than focusing on publication dates or link functionality. Authority focused on the creator\u0026rsquo;s expertise and reputation in healthcare, while accuracy examined factual correctness, consistency with current evidence, and the avoidance of misleading information. Purpose was reframed to differentiate between educational and promotional intent. An additional source domain was incorporated to reflect the wide range of origins of social media content, giving priority to videos produced by reputable institutions or certified professionals. Each domain was scored on a scale from 0, representing poor quality, to 4, representing excellent quality, and the scores were summed to generate an overall quality rating.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were calculated for all study variables, including follower count, video duration (in seconds), view count, number of comments, likes, reshares, times favorited, engagement rate, healthcare professional (HCP) status, DISCERN score, Modified JAMA score, and Modified CRAAP score. Continuous variables were summarized using medians and interquartile ranges, while categorical variables were presented as frequencies and percentages. For comparative analyses, videos were grouped based on creator type (HCP vs. non-HCP). Univariate analyses were conducted to compare differences between these groups. The Wilcoxon rank-sum test was used for continuous variables, Fisher\u0026rsquo;s exact test for nominal variables, and the chi-square test for ordinal variables. Statistical significance was determined using two-tailed p-values, with a threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eTo examine associations between video quality scores (DISCERN, Modified JAMA, and Modified CRAAP) and video characteristics such as follower count, video duration, number of views, comments, likes, reshares, times favorited, engagement rate, and HCP status; Spearman\u0026rsquo;s rank correlation coefficient (rho) (ρ) was used. This non-parametric method was chosen due to its suitability for analyzing monotonic relationships in ordinal or non-normally distributed continuous data. Correlation coefficients and their corresponding p-values were reported to reflect the strength, direction, and statistical significance of these associations. Additionally, sentiment analysis was performed on video captions and comments to categorize the emotional tone as positive, negative, or neutral. Spearman\u0026rsquo;s rank correlation was also used to assess the relationships between sentiment scores and other variables, including follower count, video duration, number of views, user engagement metrics (comments, likes, reshares, favorites), engagement rate, HCP status, and the three quality scores (DISCERN, Modified JAMA, and Modified CRAAP).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe comparison of video metrics, quality scores, and sentiment revealed several important differences between healthcare professional (HCP) and non-HCP content (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). HCP videos were significantly longer with a median duration of 65 seconds compared with non-HCP (39.5 seconds) (p\u0026thinsp;=\u0026thinsp;0.0102) and had more reshares (Median 6 vs 2, p\u0026thinsp;=\u0026thinsp;0.0050) and lower engagement rates (Median 1.3 vs 5.2, p\u0026thinsp;=\u0026thinsp;0.0014) compared to non-HCP videos(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Conversely, HCP videos demonstrated significantly higher median scores for DISCERN (41.5 vs 26.75, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), JAMA Benchmark (9.5 vs 3.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and Modified CRAAP assessments (26 vs 11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Regarding sentiment, a higher percentage of non-HCP videos exhibited positive sentiment (59.1%) compared to HCP videos (40.9%), though this difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.332) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVideo Characteristics, Engagement Metrics, and Quality Scores of Sudden Cardiac Death (SCD) TikTok Videos by Creator Type (Healthcare Professional vs. Non-Healthcare Professional)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHCP\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;31)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-HCP\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eVideo Metrics\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of followers- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2537 (1920\u0026ndash;4297)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4292 (1920\u0026ndash;16000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2537 (1243\u0026ndash;2540)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1583\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVideo duration in seconds- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56 (24\u0026ndash;102)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65 (54\u0026ndash;104)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.5 (16.3\u0026ndash;98.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0102*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of views- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1311 (724\u0026ndash;2511)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1524 (872\u0026ndash;5258)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1286 (497.5- 2201.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of comments- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (1\u0026ndash;21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (0\u0026ndash;17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.5 (3- 21.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0973\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of likes- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78 (23\u0026ndash;143)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37 (13\u0026ndash;157)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e104.5 (40.8- 139.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1249\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of reshares- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (2\u0026ndash;13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0050*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of Favorited- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (1\u0026ndash;26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0495*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEngagement Rate- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.7 (1.0- 7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.3 (0.7\u0026ndash;3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.2 (1.8\u0026ndash;9.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0014*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDISCERN Score- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (23.5\u0026ndash;38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.5 (28.5\u0026ndash;46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.75 (22.5\u0026ndash;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eJama Benchmark Score- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.5 (3.0- 8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.5 (7.0- 11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.3 (2- 5.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModified CRAAP Score- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (9.5\u0026ndash;24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (21- 30.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (7.5\u0026ndash;14.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSentiment of video\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (40.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (59.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.332\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNeutral\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (33.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (39.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (60.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (81.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*\u003cb\u003ep-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistical significance.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eAbbreviation: IQR: Interquartile Range; HCP: Healthcare Professional; Non-HCP: Non-Healthcare Professional\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of individual DISCERN domains indicated that HCP videos were significantly stronger in presenting clear aims (median 3 vs 2, p\u0026thinsp;=\u0026thinsp;0.0023), achieving aims (median 3 vs 2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), demonstrating relevance (median 3.5 vs 2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), identifying sources (median 2 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and indicating information clearly (median 2 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). They also outperformed non-HCPs in providing balanced perspectives (median 3 vs 2.5, p\u0026thinsp;=\u0026thinsp;0.0272), additional resources (median 2 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and detailed descriptions of treatment mechanisms (median 2.5 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), benefits (median 2 vs 1, p\u0026thinsp;=\u0026thinsp;0.0030), risks (median 2 vs 1, p\u0026thinsp;=\u0026thinsp;0.0005), consequences of no treatment (median 2 vs 1, p\u0026thinsp;=\u0026thinsp;0.0022), impact on quality of life (median 2 vs 1, p\u0026thinsp;=\u0026thinsp;0.0068), and multiple treatment options (median 2 vs 1, p\u0026thinsp;=\u0026thinsp;0.0007) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Higher overall quality ratings were also observed (median 3 vs 2, p\u0026thinsp;=\u0026thinsp;0.0003). No significant differences were found in referral to uncertainty (p\u0026thinsp;=\u0026thinsp;0.1698) or support for shared decision-making (p\u0026thinsp;=\u0026thinsp;0.6009) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of DISCERN Score Domains in TikTok Videos By Healthcare Professionals and Non-Healthcare Professionals status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHCP\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;31)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-HCP\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAre the aims clear? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.5 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0023*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it achieve its aims? (Skip if answer to first question is No) Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2- 3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1.6\u0026ndash;2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs it relevant? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.5 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.5 (2\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs it clear what sources of information were used to compile the publication (other\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ethan the author or producer)? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs it clear when the information used or reported in the publication was produced? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1- 1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs it balanced and unbiased? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2- 3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.5 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0272*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it provide details of additional sources of support and information? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it refer to areas of uncertainty? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1.5\u0026ndash;2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1698\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it describe how each treatment works? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it describe the benefits of each treatment? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0030*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it describe the risks of each treatment? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0005*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it describe what would happen if no treatment is used? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0022*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it describe how the treatment choices affect overall quality of life? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0068*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs it clear that there may be more than one possible treatment choice? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0007*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes it provide support for shared decision-making? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5\u0026ndash;2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBased on the answers to all of the above questions- rate the overall quality of the publication as a source of information about treatment choices- Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2- 3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0003*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistical significance.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eAbbreviation: IQR: Interquartile Range; HCP: Healthcare Professional; Non-HCP: Non-Healthcare Professional\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAcross JAMA Benchmark domains, HCP videos consistently scored higher, with stronger authorship (median 3 vs 0.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), attribution of sources (median 2 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), currency of content (median 2.5 vs 0.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and avoidance of promotional motives (median 3 vs 1.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similarly, Modified CRAAP scores were higher for HCP content across all domains, including creator credibility (median 2.5 vs 0.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), verifiable credentials (median 2 vs 0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), relevant expertise (median 2.5 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), recognized professionals (median 2.5 vs 0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), presentation of background (median 2 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), accuracy of information (median 3 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), guideline-based support (median 2 vs 1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), avoidance of inaccuracies (median 2 vs 2, p\u0026thinsp;=\u0026thinsp;0.0002), updates to reflect recent changes (median 1 vs 1, p\u0026thinsp;=\u0026thinsp;0.0138), educational purpose (median 3 vs 2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and objectivity (median 3 vs 1.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Modified JAMA Benchmark score and Modified CRAAP test score Domains in TikTok Videos by Healthcare Professionals and Non-Healthcare Professionals status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHCP\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;31)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-HCP\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eThe Journal of the American Medical Association (JAMA) benchmark criteria\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eAuthorship (Author and contributor credentials and their affiliations should be provided)- median (IQR)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the video created by a credible source (e.g.- recognized health institution- medical university- or board-certified professional)? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAttribution (Clearly lists all copyright information and states references and sources for content)- median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes the video reference recent studies- data- or treatment protocols? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5- 2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCurrency (Initial date of posted content and subsequent updates to content should be provided)- median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the content up to date- reflecting the latest research- clinical guidelines- and medical practices? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8 (0- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDisclosure (Conflicts of interest- funding- sponsorship- advertising- support- and video ownership should be fully disclosed)- median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes the video avoid commercial- promotional- or entertainment-driven motives? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.25 (0.6\u0026ndash;2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModified Currency- Relevance- Authority- Accuracy- and Purpose (CRAAP)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSource\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the organization or individual behind the video well-known and respected in the field of health or medicine? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0\u0026ndash;2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCan you verify the source's credentials or affiliations? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5 (0\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5\u0026ndash;2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0- 0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRelevance\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes this video give useful and reliable health information that fits my research topic and audience?\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.0 (2.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.0 (2.0\u0026ndash;2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAuthority\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes the creator have relevant qualifications or expertise in the topic covered in the video? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.5\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.5- 1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the creator a recognized expert or a board-certified professional in the relevant field (e.g.- medicine- nursing- public health)? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5 (0\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0- 0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the creator's experience or background clearly presented in the video? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.5\u0026ndash;1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAccuracy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the information presented in the video factually correct and based on current medical evidence? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.6- 2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAre any claims supported by well-established scientific or clinical guidelines? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.5- 2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDoes the video avoid misleading or inaccurate information? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCurrency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHas the information been updated to account for any recent changes in guidelines or clinical recommendations? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0- 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.5- 2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0138*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the primary purpose of the video to inform or educate the viewer? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.5\u0026ndash;3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1- 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs the content presented in an unbiased and objective manner- without an underlying agenda or marketing focus? Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.5- 3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.5 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistical significance.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eAbbreviation: IQR: Interquartile Range; HCP: Healthcare Professional; Non-HCP: Non-Healthcare Professional\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eCorrelation analyses showed that video duration was positively associated with DISCERN (ρ\u0026thinsp;=\u0026thinsp;0.2905, p\u0026thinsp;=\u0026thinsp;0.0077), JAMA (ρ\u0026thinsp;=\u0026thinsp;0.2708, p\u0026thinsp;=\u0026thinsp;0.0133), and CRAAP scores (ρ\u0026thinsp;=\u0026thinsp;0.3209, p\u0026thinsp;=\u0026thinsp;0.0031) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The number of reshares also correlated with higher DISCERN (ρ\u0026thinsp;=\u0026thinsp;0.2394, p\u0026thinsp;=\u0026thinsp;0.0293), JAMA (ρ\u0026thinsp;=\u0026thinsp;0.3395, p\u0026thinsp;=\u0026thinsp;0.0017), and CRAAP scores (ρ\u0026thinsp;=\u0026thinsp;0.4182, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Videos marked as favorites were positively associated with JAMA (ρ\u0026thinsp;=\u0026thinsp;0.2626, p\u0026thinsp;=\u0026thinsp;0.0165) and CRAAP scores (ρ\u0026thinsp;=\u0026thinsp;0.3118, p\u0026thinsp;=\u0026thinsp;0.0041) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Other metrics, such as likes, comments, and engagement rate, showed no significant associations (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). HCP status itself was strongly correlated with all three quality measures: DISCERN (ρ\u0026thinsp;=\u0026thinsp;0.4456, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), JAMA (ρ\u0026thinsp;=\u0026thinsp;0.7004, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and CRAAP (ρ\u0026thinsp;=\u0026thinsp;0.7103, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelations of DISCERN, Modified JAMA Benchmark, and Modified CRAAP Test Scores in TikTok Videos with Video Characteristics and Health Care Professional Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultivariate Correlation (r)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpearman rank correlation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDISCERN Score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of followers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.516\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVideo duration in seconds\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of views\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.233\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of comments\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.872\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of likes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of reshares\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.029*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEngagement rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.973\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFavorited\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHCP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSentiment of video ( 1\u0026thinsp;=\u0026thinsp;Positive- 2\u0026thinsp;=\u0026thinsp;Neutral- 3\u0026thinsp;=\u0026thinsp;Negative 4\u0026thinsp;=\u0026thinsp;not applicable)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.972\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModified JAMA Benchmark Score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of followers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVideo duration in seconds\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.013*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of views\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.232\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of comments\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.458\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of likes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of reshares\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEngagement rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFavorited\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHCP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSentiment of video ( 1\u0026thinsp;=\u0026thinsp;Positive- 2\u0026thinsp;=\u0026thinsp;Neutral- 3\u0026thinsp;=\u0026thinsp;Negative 4\u0026thinsp;=\u0026thinsp;not applicable)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModified Currency- Relevance- Authority- Accuracy- Purpose (CRAAP) Test Score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of followers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.140\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVideo duration in seconds\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of views\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of comments\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.621\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of likes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.840\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of reshares\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEngagement rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFavorited\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHCP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSentiment of video ( 1\u0026thinsp;=\u0026thinsp;Positive- 2\u0026thinsp;=\u0026thinsp;Neutral- 3\u0026thinsp;=\u0026thinsp;Negative 4\u0026thinsp;=\u0026thinsp;not applicable)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.552\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistical significance.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSentiment in video content showed a statistically significant negative correlation with video duration (ρ = \u0026minus;\u0026thinsp;0.346, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Weak positive but non-significant associations were observed between sentiment and follower count (ρ\u0026thinsp;=\u0026thinsp;0.177, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.110), number of likes (ρ\u0026thinsp;=\u0026thinsp;0.181, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.102), and times favorited (ρ\u0026thinsp;=\u0026thinsp;0.185, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.094) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). No significant correlations were found with number of views (ρ\u0026thinsp;=\u0026thinsp;0.078, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.481), comments (ρ\u0026thinsp;=\u0026thinsp;0.009, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.933), reshares (ρ\u0026thinsp;=\u0026thinsp;0.043, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.697), or engagement rate (ρ = \u0026minus;\u0026thinsp;0.072, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.517) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Sentiment did not vary significantly by creator type, with a weak and non-significant correlation for healthcare professional status (ρ = \u0026minus;\u0026thinsp;0.113, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.311) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Similarly, no significant associations were observed between sentiment and any of the quality assessment scores, including DISCERN (ρ\u0026thinsp;=\u0026thinsp;0.004, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.972), Modified JAMA (ρ = \u0026minus;\u0026thinsp;0.041, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.714), or CRAAP (ρ = \u0026minus;\u0026thinsp;0.066, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.552) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelations of Video Sentiment with TikTok Video Characteristics, Health Care Professional Status, DISCERN Score, Modified JAMA Benchmark Scores, and Modified CRAAP Test Scores\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultivariate Correlation (r)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpearman rank correlation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of followers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVideo duration in seconds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of views coded\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.481\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of comments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.226\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.933\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of likes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of reshares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.697\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEngagement rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.517\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFavorited\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCP revised\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.311\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiscern Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.972\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJAMA Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModified Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.552\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistical significance.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional analysis highlights the disparities in the quality of TikTok videos related to sudden cardiac death (SCD) content between healthcare professionals (HCPs) and non-HCPs. The findings demonstrate that HCP-generated videos are generally superior in terms of content quality, credibility, and accuracy, but tend to have lower engagement rates and shorter dissemination reach compared to non-HCP videos.\u003c/p\u003e\u003cp\u003eThe significantly higher DISCERN, JAMA Benchmark, and Modified CRAAP scores for HCP videos underscore their ability to provide evidence-based, factually correct, and unbiased information. Such findings align with previous studies emphasizing the importance of professional expertise in maintaining content accuracy in health communication\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In contrast, non-HCP videos generally achieved lower quality scores but demonstrated higher engagement metrics, including reshares, favorites, and overall engagement. This contrast is consistent with previous research suggesting that non-HCP creators often employ emotionally engaging and relatable tones, which may resonate more effectively with audiences and drive higher engagement metrics\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. A possible explanation for these findings is that digital platforms favor emotionally engaging content, which may attract more views and interactions, whereas HCP-produced content, although more accurate, may lack such narrative appeal. Supporting evidence from Vargo et al\u003csup\u003e24\u003c/sup\u003e suggests that positive emotion creates a good experience for the audience and a positive image of the sharer, significantly increasing user engagement, However, as noted in prior studies, this emotional appeal can come at the cost of accuracy and credibility\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe correlations between quality assessment scores and video metrics in this study reveal important patterns in audience engagement and content preference. Higher quality scores were negatively correlated with likes, suggesting that videos with more educational depth and accuracy may attract less engagement on social media platforms. This finding aligns with prior research on TikTok content related to gallstone disease, where videos with higher likes, shares, and comments were often of lower quality, indicating a preference for entertaining rather than informative content\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Similarly, research on breast cancer-related videos on TikTok and BiliBili revealed a weak negative correlation between video quality and likes and comments, suggesting that viewers have difficulty distinguishing between high-quality and low-quality videos\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This is further supported in an analysis of vocal health content on TikTok which suggest that most popular videos were produced by non-clinicians, with measures of popularity either uncorrelated or negatively correlated with quality, reliability, and accuracy\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. A strong correlation was observed between HCP status and quality assessment scores, highlighting that videos produced by healthcare professionals consistently maintain higher standards of accuracy and reliability. This observation aligns with previous studies, which similarly found that professional content tends to be more trustworthy than videos created by non-professionals\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. These trends may be explained by platform algorithms that favor visually appealing, emotionally engaging, or trend-driven content over evidence-based material\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Popularity can also be influenced by factors unrelated to quality, such as creator charisma or video aesthetics\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. This highlights the need for platforms like TikTok to create environments where high-quality, evidence-based health content can reach and impact audiences.\u003c/p\u003e\u003cp\u003eThis study is one of the first to examine TikTok videos about sudden cardiac death (SCD), providing insights into the quality and engagement of healthcare professional (HCP) and non-HCP content. The use of established evaluation tools, such as DISCERN, JAMA Benchmark, and Modified CRAAP, strengthens the reliability of the analysis. Including both quantitative and sentiment analysis allows for a comprehensive understanding of video quality and audience interaction. By analyzing multiple engagement metrics, such as likes, shares, and comments, this research connects content quality with audience behaviors.\u003c/p\u003e\u003cp\u003eThis study has several limitations. It provides only a cross-sectional view and does not track changes over time in video content or engagement trends. The use of hashtags to identify videos may exclude relevant content that was not tagged appropriately. The focus on English-language videos limits the generalizability of findings to non-English-speaking populations, and TikTok-specific features, such as algorithms that promote certain types of content, are not fully addressed and may influence video reach and engagement. Furthermore, the modified JAMA and CRAAP scales used for quality assessment are not standardized, as formal internal validation was not conducted, and quality ratings may be influenced by evaluator subjectivity, requiring further evaluation in future studies.\u003c/p\u003e\n\u003ch3\u003eImplication and future direction\u003c/h3\u003e\n\u003cp\u003eThe findings highlight an ongoing tension between engagement and factual accuracy in health-related social media content. While videos from healthcare professionals tend to be more reliable, both professional and non-professional content often lack proper citations and discussion of treatment risks, which can compromise the quality of information provided\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In life-threatening or complex medical contexts, such as sudden cardiac death, it is particularly important to balance emotional appeal with evidence-based accuracy. Educational videos on specialized topics should be of sufficient duration to provide comprehensive information, clearly cite authoritative sources, and communicate uncertainties in current knowledge. Digital platforms like TikTok have improved access to health information but often lack the empathetic context of face-to-face interactions, potentially leading to misunderstanding or emotional distress\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Strengthening platform content review mechanisms, limiting misleading advertisements, and implementing AI-driven monitoring or active professional engagement in comment sections could help ensure accurate information dissemination and reduce misinformation. The proliferation of unverified medical content may pose health risks and financial burdens to viewers, underscoring the need for stricter regulation. Future research should compare content quality across multiple video-sharing platforms to identify best practices for effective, trustworthy health communication in the digital space.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study found that healthcare professionals produce higher-quality health content on TikTok compared to non-HCP creators, but struggle to achieve the same level of audience engagement. Non-HCP videos often rely on entertainment and emotional appeal, which boosts their reach but may compromise accuracy. The findings emphasize the need for strategies that improve the accessibility and impact of professional health content, such as collaborations or platform adjustments. Future research should explore ways to enhance the visibility and effectiveness of credible health messaging on TikTok.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCRAAP: Currency, Relevance, Authority, Accuracy, and Purpose\u003c/p\u003e\n\u003cp\u003eHCP: Health Care Professionals\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIQR-Interquartile Range\u003c/p\u003e\n\u003cp\u003enon-HCP: non health care professionals\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSCD: Sudden cardiac death\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement:\u0026nbsp;\u003c/strong\u003eNone of the authors have any conflict of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution:\u0026nbsp;\u003c/strong\u003e*Data review and collection done by MB. AJ, FMU and SS. Statistical analysis was done by RK \u0026amp; VB. \u0026nbsp;Study design and critical review done by MR, VB, FAZ, and RK. MR, VB, FAZ, and RK are the guarantor of the paper, taking responsibility for the integrity of the work, from inception to published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eData from this study has been submitted in abstract form for consideration at the upcoming SCCM 2026 Critical Care Congress. The manuscript underwent English-language review with assistance from Grammarly. The manuscript has been reviewed for English language and grammar with assistance from Grammarly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKirkpatrick, C. E. \u0026amp; Lawrie, L. L. TikTok as a Source of Health Information and Misinformation for Young Women in the United States: Survey Study. \u003cem\u003eJMIR Infodemiology May 21\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, e54663. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/54663\u003c/span\u003e\u003cspan address=\"10.2196/54663\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShrivastava, S. 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Internet Res Jan\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e, 27:e60512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/60512\u003c/span\u003e\u003cspan address=\"10.2196/60512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sudden cardiac death, Social media, TikTok, Digital Health, Health Education Access, Cardiovascular health","lastPublishedDoi":"10.21203/rs.3.rs-7746991/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7746991/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSocial media platforms like TikTok have become a source of health information, particularly for younger audiences, but concerns remain about the accuracy and reliability of this content. This study assessed the quality, engagement, and sentiment of TikTok videos on sudden cardiac death (SCD), comparing healthcare professional (HCP) and non-HCP creators. Using Exolyt, the top 100 videos under two popular SCD hashtags were screened, and 83 met inclusion criteria. Engagement metrics (likes, comments, shares) and creator type were recorded, and quality was assessed with DISCERN, modified JAMA benchmarks, and a modified CRAAP test. Non-HCP videos achieved significantly higher engagement, with greater median reshares (p\u0026thinsp;=\u0026thinsp;0.0050), favorited counts (p\u0026thinsp;=\u0026thinsp;0.0495), and engagement rates (p\u0026thinsp;=\u0026thinsp;0.0014). In contrast, HCP videos demonstrated higher quality scores, performing significantly better on the DISCERN (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), JAMA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and CRAAP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) assessments. They were also more likely to present clear aims (p\u0026thinsp;=\u0026thinsp;0.0023) and to describe benefits (p\u0026thinsp;=\u0026thinsp;0.0030) and risks (p\u0026thinsp;=\u0026thinsp;0.0005) of treatments. Sentiment analysis found no significant difference, though non-HCP videos were more often positive (59.1% vs. 40.9%, p\u0026thinsp;=\u0026thinsp;0.332). In summary, HCPs produce more accurate and reliable content, while non-HCPs achieve greater reach and interaction. Enhancing the visibility of evidence-based content may require collaborations between HCPs and creators or platform-level interventions.\u003c/p\u003e","manuscriptTitle":"Evaluating the Quality of TikTok Videos on Sudden Cardiac Death Using Multiple Scales: A Cross-Sectional Analysis of Correlations with Video Characteristics and High-Quality Health Information","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 16:59:33","doi":"10.21203/rs.3.rs-7746991/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-22T18:09:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-19T08:58:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T16:14:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"249244543103852420202958539916772993656","date":"2025-12-01T07:38:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66316785492980871118077586858975031951","date":"2025-11-30T06:45:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-16T22:10:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260618281269581137962460703860552753425","date":"2025-11-04T20:08:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-04T02:35:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-24T02:28:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-13T12:23:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-10T20:31:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-10T20:27:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"be0eca18-8a5b-4259-b03f-e60d4033f02c","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57561278,"name":"Health sciences/Cardiology"},{"id":57561279,"name":"Health sciences/Diseases"},{"id":57561280,"name":"Health sciences/Health care"},{"id":57561281,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-03-30T16:24:59+00:00","versionOfRecord":{"articleIdentity":"rs-7746991","link":"https://doi.org/10.1038/s41598-026-39081-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-03-23 16:12:44","publishedOnDateReadable":"March 23rd, 2026"},"versionCreatedAt":"2025-11-13 16:59:33","video":"","vorDoi":"10.1038/s41598-026-39081-7","vorDoiUrl":"https://doi.org/10.1038/s41598-026-39081-7","workflowStages":[]},"version":"v1","identity":"rs-7746991","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7746991","identity":"rs-7746991","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}