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<p>YouTube is a primary health information source, yet its engagement-driven model may incentivize “clickbait,” potentially compromising quality. We analyzed clickbait prevalence in 3958 Korean medical YouTube videos across five health topics and its relationship with engagement, quality, and source. Videos were assessed for clickbait severity (Clickbait Severity Score; CSS), engagement, and medical information quality using a composite score (Medical Quality Score; MQS) derived from Journal of the American Medical Association Benchmark (credibility/accountability), DISCERN (reliability), and Global Quality Scale (overall quality) criteria. Independent YouTubers produced the lowest quality content (MQS mean = −0.3) with the most clickbait (CSS mean = 1.4), yet garnered the highest viewership. Clickbait severity was positively correlated with log-transformed daily views (<i>r</i> = .231, <i>p</i> &lt; .001) and negatively correlated with medical quality (<i>r</i> = −0.371, <i>p</i> &lt; 0.001). Multiple regression analysis revealed that specific clickbait tactics like exaggeration (<i>β</i> = 0.161, <i>p</i> &lt; 0.001) and teasing (<i>β</i> = 0.068, <i>p</i> &lt; 0.001) were positive predictors of daily views, whereas higher information quality (GQS) was a negative predictor (<i>β</i> = −0.185, <i>p</i> &lt; 0.001). These findings demonstrate a “credibility paradox” where algorithms reward clickbait with higher engagement despite lower content quality. This misalignment with public health principles highlights an urgent need for platform governance reform to better align algorithmic incentives with information quality.</p>

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The credibility paradox: clickbait, engagement, and information quality in YouTube’s medical ecosystem

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月23日

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  • EunKyo Kang,
  • HyeWon Lee,
  • Juyoung Choi,
  • HyoRim Ju

摘要

YouTube is a primary health information source, yet its engagement-driven model may incentivize “clickbait,” potentially compromising quality. We analyzed clickbait prevalence in 3958 Korean medical YouTube videos across five health topics and its relationship with engagement, quality, and source. Videos were assessed for clickbait severity (Clickbait Severity Score; CSS), engagement, and medical information quality using a composite score (Medical Quality Score; MQS) derived from Journal of the American Medical Association Benchmark (credibility/accountability), DISCERN (reliability), and Global Quality Scale (overall quality) criteria. Independent YouTubers produced the lowest quality content (MQS mean = −0.3) with the most clickbait (CSS mean = 1.4), yet garnered the highest viewership. Clickbait severity was positively correlated with log-transformed daily views (r = .231, p < .001) and negatively correlated with medical quality (r = −0.371, p < 0.001). Multiple regression analysis revealed that specific clickbait tactics like exaggeration (β = 0.161, p < 0.001) and teasing (β = 0.068, p < 0.001) were positive predictors of daily views, whereas higher information quality (GQS) was a negative predictor (β = −0.185, p < 0.001). These findings demonstrate a “credibility paradox” where algorithms reward clickbait with higher engagement despite lower content quality. This misalignment with public health principles highlights an urgent need for platform governance reform to better align algorithmic incentives with information quality.