YouTube provides poor information regarding anterior cruciate ligament injury and reconstruction

Cassidy, J. Tristan; Fitzgerald, Edmund; Cassidy, Elizabeth; Cleary, May; Byrne, Danielle; Devitt, Brian M.; Baker, Joseph F.

doi:10.1007/s00167-017-4514-x

Cited by 129 publications

(187 citation statements)

References 18 publications

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“…This is in line with the scoring system employed by DISCERN, an educational tool designed primarily to enable patients (or health consumers), their carers and advisers to select and use written information on treatment choices as part of good quality healthcare [6]. This tool also has been previously applied to the evaluation of YouTube videos [4]. Thus, we deemed a video misinformative if it contains guideline-discordant information (e.g., recommends a treatment that is not recommended in the guidelines), heavily relies on anecdotal evidence (e.g., patient narrative asserting that use of dietary ingredient cured his prostate cancer without scientific evidence), or if it contains advertisements or biased content (e.g., promoting a certain therapy without describing risks or alternatives).…”

Section: Data Annotationmentioning

confidence: 61%

“…Second, we separated the audio from the video and converted the signal to a single channel and to a uniform sample rate of 16k using ffmpeg. 4…”

Section: Preprocessingmentioning

confidence: 99%

“…All six attributes are obtained using the official YouTube API. 5 Note that we encountered 14 videos with comments disabled, and in that case, the corresponding features were set to zero. Figure 1 shows the distribution of the different features for both misinformative and trustworthy videos.…”

Section: Viewer Engagement Featuresmentioning

confidence: 99%

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Towards Automatic Detection of Misinformation in Online Medical Videos

Hou

Pérez-Rosas

Loeb

et al. 2019

2019 International Conference on Multimodal Interaction

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Recent years have witnessed a significant increase in the online sharing of medical information, with videos representing a large fraction of such online sources. Previous studies have however shown that more than half of the health-related videos on platforms such as YouTube contain misleading information and biases. Hence, it is crucial to build computational tools that can help evaluate the quality of these videos so that users can obtain accurate information to help inform their decisions. In this study, we focus on the automatic detection of misinformation in YouTube videos. We select prostate cancer videos as our entry point to tackle this problem. The contribution of this paper is twofold. First, we introduce a new dataset consisting of 250 videos related to prostate cancer manually annotated for misinformation. Second, we explore the use of linguistic, acoustic, and user engagement features for the development of classification models to identify misinformation. Using a series of ablation experiments, we show that we can build automatic models with accuracies of up to 74%, corresponding to a 76.5% precision and 73.2% recall for misinformative instances.

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Section: Data Annotationmentioning

confidence: 61%

“…Second, we separated the audio from the video and converted the signal to a single channel and to a uniform sample rate of 16k using ffmpeg. 4…”

Section: Preprocessingmentioning

confidence: 99%

See 1 more Smart Citation

Towards Automatic Detection of Misinformation in Online Medical Videos

Hou

Pérez-Rosas

Loeb

et al. 2019

2019 International Conference on Multimodal Interaction

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“…4,5 The accuracy of patient education videos on YouTube has been investigated in the context of other orthopedic conditions and treatments, including hip and knee arthritis, femoroacetabular impingement, articular cartilage defects, and others. [6][7][8][9][10][11][12][13] Results suggest that these videos have, overall, poor educational content. (The quality of online educational content for other common orthopedic injuries is largely unknown.…”

Section: Introductionmentioning

confidence: 99%

“…An estimated 84% of adults used the internet on a regular basis in 2015, and 60% of adults reported having accessed health-related information online in the previous month. [1][2][3][4][5][6][7][8][9][10][11] Video-sharing sites such as YouTube have become popular resources for health information. More than 1.9 billion users visit The authors report the following potential conflicts of interest or sources of funding: R.F.L.…”

Section: Introductionmentioning

confidence: 99%

YouTube as a Source of Information About the Posterior Cruciate Ligament: A Content-Quality and Reliability Analysis

Kunze

Cohn

Wakefield

et al. 2019

Arthroscopy, Sports Medicine, and Rehabilitation

109

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Purpose: The purpose of this study was to evaluate the reliability and educational content of YouTube videos concerning injuries to the posterior cruciate ligament (PCL) of the knee. Methods: The first 50 videos specific to the PCL identified through the YouTube query posterior cruciate ligament were evaluated by a method of video selection demonstrated to be feasible in prior YouTube studies. Videos were classified by content and upload source. Video reliability was assessed using the Journal of the American Medical Association (JAMA) benchmark criteria (score range 0-5). Video educational content was assessed using the Global Quality Score (GQS) (range 0-4) and the PCL Score (PCLS) (score range 0-18). Analysis of variance was used to determine differences in video reliability and educational content quality based on video content and upload source. Multivariate linear regressions were used to identify predictors of video reliability and educational content quality. Results: The mean number of views per video was 50,477.9 AE 15,036. Collectively, the 50 videos were viewed 14,141,285 times. Video content was classified primarily as information about disease (62.0%). The most common upload sources were physicians (24.0%) and nonphysician health care providers (26.0%). Significant between-group interactions were found between video source and the JAMA score, with physicians and medical sources having significantly higher mean JAMA scores (P ¼ 0.037). Videos uploaded by physicians were an independent positive predictor of greater JAMA scores (b:1.27; P ¼ 0.008). Videos uploaded by a medical source (b:2.06; P ¼ 0.038) were an independent positive predictor of a greater GQS. There were no independent associations between video content category or upload source and the PCLS. Conclusions: Videos concerning the PCL were frequently viewed on YouTube, but the educational quality and reliability of these videos were low. Clinical Relevance: Physicians and health care providers treating PCL pathology should take the initiative to counsel patients about which outside resources are reliable to better inform patients about their treatment decisions. With regard to YouTube videos specifically, providers should caution their patients that this source of information may be unreliable.

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Information videos posted on Instagram by orthopaedics and sports traumatology surgeons mostly explain surgical technique, and the least mentioned topics are injury prevention and complications

Şahbat,

Kocaoğlu,

Ollivier

et al. 2024

Knee surg. sports traumatol. arthrosc.

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PurposeSocial media has become the new information acquisition platform for all content producers. In the current literature, there are no studies examining the content quality and the strengths and weaknesses of videos on Instagram that explain anterior cruciate ligament (ACL) injuries, which is the most discussed topic of sports surgery. The aim of this study was to evaluate the quality, strengths and weaknesses of information pertaining to ACL surgery that is disseminated on Instagram.MethodAn Instagram search was conducted from 30 May 2023 to 30 January 2024. The search encompassed six languages (English, Spanish, German, French, Italian and Turkish) and was performed by six different observers. The investigation focused on eight subheadings derived from current literature on the ACL. These subheadings were addressed in Instagram videos, covering ACL biology or biomechanics, injury mechanism, injury prevention, injury evaluation, surgical technique, injury or surgery complications, injury rehabilitation process and return to sport or work.ResultThe content was assessed of 127 videos from 127 Instagram accounts, spanning six different languages. Across the review of eight subheadings, the average number covered for the entire group was 3 (range, 0–8). Further analysis revealed that surgical technique was the most frequently mentioned subheading for the whole group (68.5%), followed by injury evaluation (54.3%). Prevention (10.2%) and complications (19.6%) were the least mentioned subheadings. The number of followers showed a correlation with video content quality.ConclusionAlthough the video quality scores were found to be moderate, the content often focused on surgery and evaluation subheadings. The prevalence of incomplete information underscores the importance of developing strategies to ensure more comprehensive and accurate dissemination of medical knowledge.Level of EvidenceLevel V.

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YouTube provides poor information regarding anterior cruciate ligament injury and reconstruction

Abstract: The majority of videos viewed on YouTube regarding ACL injury and treatment are of low quality.

Cited by 129 publications

References 18 publications

Towards Automatic Detection of Misinformation in Online Medical Videos

Towards Automatic Detection of Misinformation in Online Medical Videos

YouTube as a Source of Information About the Posterior Cruciate Ligament: A Content-Quality and Reliability Analysis

Information videos posted on Instagram by orthopaedics and sports traumatology surgeons mostly explain surgical technique, and the least mentioned topics are injury prevention and complications

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