Video Quality Research Articles

A Spatial-Temporal Video Quality Assessment Method via Comprehensive HVS Simulation.

The quality of videos is the primary concern of video service providers. Built upon deep neural networks, video quality assessment (VQA) has rapidly progressed. Although existing works have introduced the knowledge of the human visual system (HVS) into VQA, there are still some limitations that hinder the full exploitation of HVS, including incomplete modeling with few HVS characteristics and insufficient connection among these characteristics. In this article, we present a novel spatial-temporal VQA method termed HVS-5M, wherein we design five modules to simulate five characteristics of HVS and create a bioinspired connection among these modules in a cooperative manner. Specifically, on the side of the spatial domain, the visual saliency module first extracts a saliency map. Then, the content-dependency and the edge masking modules extract the content and edge features, respectively, which are both weighted by the saliency map to highlight those regions that human beings may be interested in. On the other side of the temporal domain, the motion perception module extracts the dynamic temporal features. Besides, the temporal hysteresis module simulates the memory mechanism of human beings and comprehensively evaluates the video quality according to the fusion features from the spatial and temporal domains. Extensive experiments show that our HVS-5M outperforms the state-of-the-art VQA methods. Ablation studies are further conducted to verify the effectiveness of each module toward the proposed method. The source code is available at https://github.com/GZHU-DVL/HVS-5M.

TikTok Videos Related to Rhinoplasty in China: Characteristics and the Quality of the Information.

There are numerous videos related to rhinoplasty on TikTok in China. The objective is to examine videos on Chinese TikTok regarding rhinoplasty surgery and evaluate the content quality of rhinoplasty-related videos on TikTok. We collected 184 Chinese video samples related to rhinoplasty and extracted basic information. We used the PEMAT-A/V tool to evaluate each video. A total of 184 videos were included in the study. The sampled videos received approximately 4.8 million likes, 900,000 comments, and 300,000 favorites. Most of the videos (n = 130, 70.65%) were posted by certified plastic surgeons on the TikTok platform. This study found that 6 (3.26%) videos contained obvious errors or misleading information. Regarding the PEMAT-A/V, the median total score was 85.71 (n = 184, IQR = 78.57-92.45%). Videos created by plastic surgeons had the highest comprehension score (n = 130, median = 100%, IQR = 91.67-100%), while videos from news media (n = 16, median = 75%, IQR = 70.76-77.34%) had the lowest usability and PEMAT-A/V total scores. In terms of video content, the PEMAT-A/V total score for surgical risks/contraindications related content (n = 15, median = 92.86%, IQR = 83.48-92.86%) was the highest, while scores for complaint-related content (n = 20, median = 75, IQR = 71.43-78.57%) were the lowest. This study is the first report in China to evaluate the quality of information in nose plastic surgery-related videos on TikTok. We found that the quality of videos created by plastic surgeons on the TikTok platform is generally high, while videos provided by news media have lower quality. We encourage healthcare professionals to share more high-quality information on TikTok and educate patients on how to properly handle misinformation. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Nasal endoscopy: What have we been missing?

Despite the widespread adoption of nasal endoscopy (NE) in the evaluation of sinonasal disease, its diagnostic potential may still be underutilized. Developments in endoscopic technology have led to significant improvements in video quality and maneuverability. However, there is concern that NE continues to be used primarily for the identification of gross pathology, with relative neglect of more subtle findings such as surface features of inflammation and mucus. With fewer technical limitations to perceive these abnormalities, there is potential to greatly improve the diagnostic value of NE. The reader is herein asked to consider several important visual nuances encountered during NE, with the hope that this engenders an appreciation of the versatility of NE as a diagnostic tool.

Spatio-temporal feature learning for enhancing video quality based on screen content characteristics

With the rising demands for remote desktops and online meetings, screen content videos have drawn significant attention. Different from natural videos, screen content videos often exhibit scene switches where the content abruptly changes from one frame to the next. These scene switches result in obvious distortions in compressed videos. Besides, frame freezing, where the content remains unchanged for a certain duration, is also very common in screen content videos. Existing alignment-based models struggle to effectively enhance scene switch frames and lack efficiency when dealing with frame freezing situations. Therefore, we propose a novel alignment-free method that effectively handles both scene switches and frame freezing. In our approach, we develop a spatial and temporal feature extraction module that compresses and extracts spatio-temporal information from three groups of frame inputs. This enables efficient handling of scene switches. In addition, an edge aware block is proposed for extracting edge information, which guides the model to focus on restoring the high-frequency components in frame freezing situations. The fusion module is then designed to adaptively fuse the features from three groups, considering different positions of video frames, to enhance frames during scene switch and frame freezing scenarios. Experimental results demonstrate the significant advancements achieved by the proposed edge aware with spatio-temporal information fusion network (EAST) in enhancing the quality of compressed videos, surpassing the current state-of-the-art methods.

Educational Level of Laparoscopic Radical Nephrectomy Videos on YouTubeTM.

Purpose: This study aims to evaluate the educational quality and appropriateness of laparoscopic radical nephrectomy videos on YouTube using the LAParoscopicsurgery Video EducationalGuidelineS (LAP-VEGaS) criteria. It focuses on understanding the role of online resources in medical education and objectively assessing their quality. Methods: A search was conducted on YouTube™ for "laparoscopic radical nephrectomy" on August 15, 2023, leading to the selection of the first 125 videos. Videos were chosen based on length (over 1 minute), content (laparoscopic radical nephrectomy), language (English), and nonindustry sponsorship. The LAP-VEGaS criteria, encompassing 16 items under five main categories: video introduction, case presentation, procedures, outcomes, and educational content, were used for evaluation, assigning 0 or 1 point per criterion. Results: Out of 100 videos meeting the criteria, they were divided into two groups: personal uploads by expert surgeons (Group-1) and institutional uploads by hospitals and organizations (Group-2). Group-2 videos had longer durations and higher LAP-VEGaS scores. The transperitoneal approach was preferred in 88% of the videos, and 84% were right laparoscopic nephrectomies. Group-2 had significantly higher LAP-VEGaS scores (6.3 ± 2.2) compared with Group-1 (4 ± 2.1) (P < 0,001). The number of videos published over the years increased, while LAP-VEGaS scores fluctuated. Conclusion: Assessing laparoscopic radical nephrectomy videos on YouTube™ using the LAP-VEGaS criteria helped understand the role of online sources in medical education. Institutional uploads were found to be more successful in educational aspects, emphasizing the need for continuous quality review of online medical education materials. This study also guides how to evaluate and improve medical education materials on online platforms.

Content, educational value and quality analysis of videos about neurorehabilitation in people with multiple sclerosis on YouTube®.

The use of YouTube® has spread among patients with chronic diseases such as multiple sclerosis (MS). These patients consult the available videos to learn more about their disease in terms of diagnosis and making decisions about treatments, including rehabilitation. The aim of this study was to evaluate the content, educational value, and quality analysis of MS videos about neurorehabilitation on YouTube® using quantitative instruments. A search was conducted on YouTube®. The first 30 videos that met the inclusion criteria were reviewed. The videos were classified according to the upload source and the content. All videos included in the review were assessed by the DISCERN questionnaire, the JAMA benchmark, the global quality scale (GQS) and the video information and quality index (VIQI). The mean scores were: 28.3 (±9.33) in DISCERN, 2 (±0.81) in JAMA, 2.57 (±1.22) in GQS, and 11.73 (±4.06) in VIQI. JAMA score statistically significantly differed according to upload source (p = 0.002), video content (p = 0.023) and the speaker (p = 0.002). The DISCERN, JAMA, GQS, and VIQI scores showed significant correlations with each other. The analyzed videos about neurorehabilitation in people with MS on YouTube® were quite old since the upload, with a moderate duration and number of views, but with a poor quality of the content, educational value, and quality analysis of the videos. Our research showed that there were statistically significant differences in terms of quality, transparency, and reliability of the information, depending on the upload source, video content and the speaker.

Instagram Reels Versus Image Posts in Radiology Education

ObjectiveIn January 2016, we created an Instagram page for radiology education. Numerous publications in different fields have reported that Instagram “reels,” introduced in 2020 as a short-form video feature, are more popular than image posts. These findings and our familiarity with Instagram prompted us to analyze our own data to better understand how image posts compared with reels when used in the context of radiology education. Materials and MethodsFor each post category, metric values were extracted from the Instagram platform and analyzed as continuous variables, reported as medians with interquartile ranges (IQR). Metrics were compared between image categories using the Kruskal–Wallis test, with resulting p-values adjusted for multiple comparisons using the Bonferroni correction. Corrected p-values of less than 0.05 were considered statistically significant. ResultsWe included 128 images and 96 reels in the analysis. Images generally reached a larger audience, with a median of 18,745 [IQR: 13,478–27,243] impressions vs. 11,972 [IQR: 9,310.0–13,844.5] for reels (p<0.01). Images also tended to be shared more frequently (median 19 vs. 20, p<0.01), liked more often (median 480 vs. 296, p<0.01), and saved more by users (median 138 vs. 84, p<0.01) than reels, respectively. Both images and reels received a similar number of comments, with a median of 3 comments for both (p>0.99). We also explored the performance differences of image post subcategories. Within images, our “You Make the Call!” (YMTC) questions (n=23) displayed higher performance metrics across the board than the three other types of image posts combined (n=105). When compared, the median number of impressions for YMTC images was 36,735 [IQR: 31,343–40,742] vs. 15,992 [IQR:12,774–21,873] for other types of images (p<0.01). YMTC images were shared more often (median 25 vs. 17, p<0.01), received more likes (median 809 vs. 445, p<0.01) and saves (median 206 vs. 119, p<0.01) than non-YMTC images, respectively. User engagement showed slightly different trends with YMTC reels being the most liked, while quiz reels receiving the most comments and talking clips being the most saved. ConclusionOur findings on the use of Instagram in radiology education suggest that static images perform much better than reels. Consequently, we recommend to radiology educators seeking to establish an Instagram presence that using static image posts is an appropriate approach for reaching a radiology audience, particularly with image posts that engage an audience with participatory opportunities such as answering quiz-like questions aimed at making a diagnosis.

Perancangan Aplikasi Midori Clon (Midori Class Online) Berbasis Mobile dengan Metode Design Thinking

Online learning is widely used by various groups, especially in higher education/schools. Online learning has many benefits for students and lecturers due to its practical and flexible learning process. However, there are complaints in online learning, such as students having difficulty understanding the material shared by lecturers and the lack of interaction between lecturers and students, making the lessons monotonous and boring. Students also cannot review the targeted lecturers. Therefore, the Midori Clon application was created to address students' problems in online learning. The application design was developed using the Design Thinking method. The Midori Clon application offers several advantages, including a Live Video feature for more interactive sessions between students and lecturers, a Bot feature to summarize materials and translate languages, and a Lecturer Review feature to review the targeted lecturers. With these advanced features, it is expected that online learning issues can be resolved and online learning can meet the desired expectations.

Ophthalmology Oral Examination in a Virtual Trans-Atlantic Pilot Study – Evaluating Examiners’ and Examinees’ Perceptions

Background: The COVID-19 pandemic necessitated the transition of in-person examinations into virtual formats. As cases decreased, some examinations returned to in-person, while others remained virtual or instituted hybrid models. Virtual examinations offer benefits including decreased travel costs, and the opportunity to share examiners globally. We assessed a virtual trainee practice examination strategy and investigated perceptions and preferences regarding the virtual formats. Method: Ten ophthalmology residents from the Tennent Institute of Ophthalmology, Glasgow, Scotland, and the University of Arkansas for Medical Sciences, Little Rock, United States, participated in virtual mock oral exams conducted by two examiners. Examiners and examinees answered questions graded on a Likert scale to determine perceptions of the format. Results: Most examinees and examiners were satisfied or very satisfied with the overall examination, as well as the internet connectivity, video quality, and audio quality. The majority of examinees (70%) had either no preference or a preference for in-person examination. One examiner preferred the virtual format, and the other had no preference. Conclusion: Virtual oral examinations can be a feasible and effective alternative to in-person examinations. They have the added benefit of decreased travel costs and the ability to share examiners amongst institutions to replicate a more realistic examination experience for trainees.

Quality and content analysis of tarsal tunnel syndrome videos on YouTube

Aims: In this study, we aimed to evaluate the quality and reliability of the first 50 videos on YouTube, which is a reliable source for sharing medical information, about tarsal tunnel syndrome (TTS), which is difficult to diagnose with low prevalence and which prompts patients to look for information. Methods: To evaluate the first 50 TTS videos on YouTube, the source, upload date, number of views, and like-dislike parameters were selected for analysis. The content was assessed following the Journal of the American Medical Association (JAMA) criteria, the Global Quality Score (GQS), and the DISCERN scale. Results: In the parameters used in the quality and relevance analysis of the videos, the GQS mean score was 3.70, the JAMA mean score was 1.12, and the DISCERN mean score was 45.82. There was no significant relation between the number of views, the days since the video was uploaded to the internet until the review, the number of likes and dislikes, the like rates, the video power index, JAMA, DISCERN, and GQS. There was a positive correlation between GQS, JAMA, and DISCERN. Conclusion: This study revealed that the quality, content, and reliability of available videos in the tarsal tunnel are moderate. We have emphasized the importance of improving the content and quality of the videos so that patients can access more beneficial information.

Perancangan UI/UX pada Toko Rental Outdoor Adventure Sphere Metode Design Thinking

The development of the digital economy in developing countries is expected to encourage economic growth, increase resources and workforce efficiency, provide access to international markets, and reduce transaction costs. The research aims to offer practical and affordable solutions for those who want to explore nature without having to buy their own equipment and provide information and advice on destinations, safety tips and equipment guides, as well as supporting the adventure community. This design uses the Design Thinking method, which is an iterative process that aims to understand users, define problems in depth, and find solutions that meet their needs. The result of this research is the Adventure Sphere Application Prototype, which contains profile, homepage, product display, basket and product video features. It is hoped that this application will make it easier for buyers to rent outdoor equipment and this application will also provide useful information to renters regarding the use of outdoor equipment.

Pornographic video detection based on semantic and image enhancement

Abstract Pornographic video detection is of significant importance in curbing the proliferation of pornographic information on online video platforms. However, existing works often employ generic frame extraction methods that ignore the low-latency requirements of detection scenarios and the characteristics of pornographic videos. Additionally, existing detection methods have difficulties in detail characterization and semantic understanding, resulting in low accuracy. Therefore, this paper proposes an efficient pornographic video detection framework based on semantic and image enhancement. Firstly, a keyframe extraction method tailored for pornographic video detection is proposed to select representative frames. Secondly, a light enhancement method is introduced to facilitate accurate capture of pornographic visual cues. Moreover, a compression-reconstruction network is employed to eliminate adversarial perturbations, enabling models to obtain reliable features. Subsequently, YOLOv5 is introduced to locate and crop human targets in keyframes, reducing background interference and enhancing the expression of human semantic information. Finally, MobileNetV3 is employed to determine if the human targets contain pornographic content. The proposed framework is validated on the publicly available NPDI dataset, achieving an accuracy of 95.9%, surpassing existing baseline methods.

No-reference video quality assessment based on human visual perception

No-reference video quality assessment based on human visual perception

Vascular access on YouTube: Navigating the stream of information for hemodialysis patients

Aim: End-stage renal disease (ESRD) presents significant challenges for patients and healthcare systems. Treatment options include renal transplant, peritoneal dialysis, and hemodialysis, with hemodialysis being the most common, necessitating suitable vascular access like arteriovenous fistula (AVF), graft, or catheter. This study aims to analyze the quality of YouTube videos on vascular access for hemodialysis, using the 2018 Clinical Practice Guidelines of the European Society for Vascular Surgery (ESVS) as a benchmark and employing JAMA, Global Quality, and DISCERN scores. To our knowledge, this is the first study evaluating YouTube content quality on this topic. Material and Methods: A YouTube search for 'arteriovenous fistula' was conducted, analyzing the first 200 videos based on predetermined criteria. Exclusions included videos lacking sound, not in English, off-topic, or duplicates. Data collected included uploader details, upload date, views, comments, likes, and duration. Video accuracy was assessed using the DISCERN tool, JAMA Benchmark Criteria, and Global Quality Scoring System (GQSS). Results: Out of 200 videos, 13 were excluded, leaving 187 for analysis. The interobserver agreement was high (κ=0.967). The videos amassed 12,854,643 views, with a median duration of 5 minutes and a median of 3412 views per video. Most views were for videos with poor DISCERN scores. There was a significant association between DISCERN scores and video characteristics. Videos with higher DISCERN scores had longer durations (p=0.01). However, videos with lower scores received more likes and views (p&lt;0.01). The mean DISCERN score was 33.7, indicating poor quality, with only 18.8% rated as good or excellent. Conclusion: The study underscores the variability in the quality of YouTube content regarding vascular access for hemodialysis. Patients are encouraged to prioritize videos uploaded by healthcare professionals, ensuring both quality and accuracy. Despite limitations, this study contributes to informed decision-making in the context of hemodialysis vascular access.

Telemedicine and Patient Experience Ratings at an Academic Integrative Medicine Practice: Retrospective Examination.

The use of telemedicine (TELE) increased exponentially during the COVID-19 pandemic. While patient experience with TELE has been studied in other medical disciplines, its impact and applicability to integrative medicine practices remain unknown. The aim of this study is to assess the impact of visit modality, TELE versus face-to-face (F2F) encounters, on patient experience at an integrative medicine practice at a single academic medical center. Given the significant role of the patient-physician relationship, therapeutic presence, and touch in integrative medicine, we hypothesized that TELE would result in reduced patient experience compared to traditional F2F encounters. A retrospective examination of Press Ganey surveys at an academic, consultative, and integrative medicine practice was conducted. Anonymous surveys completed by patients, older than 18 years of age, who had TELE or F2F appointments from April 1, 2020, to March 31, 2023, were included. At our medical center, patients commonly travel in from out of state for complex care. We examined percentage "top box" scores (ie, the percentage of respondents who selected the most positive response category on the survey, "very good"), across a variety of experience metrics. ANOVA and chi-square analyses were completed, with a significance threshold of P<.05. Over the 36 months, a total of 1066 surveys were completed and returned (TELE: n=333; F2F: n=733). Overall, 73% (n=778) of respondents were female with an average age of 57.6 (SD 13.84) years. Most patients were English-speaking (n=728, 99.3%), White (n=1059, 92.7%), and not Hispanic or Latino (n=985, 92.4%). There was significantly higher satisfaction with access to care for TELE visits compared to F2F visits. There were no differences in satisfaction with the care provider or in overall experience. When examining the specific aspects of using technology during TELE visits, there were no differences in audio quality, visual quality, or ease of talking to the care provider based on sex. There was, however, a difference in video quality based on age, where those 80 years and older rated significantly lower video quality compared to all other age groups. Top-level patient experience can be attained with TELE integrative medicine visits. Additional studies, particularly those correlating positive experience findings with specific behaviors used during TELE visits, would further our understanding of the integrative medicine patient experience. In the meantime, efforts should be made to ensure a policy that promotes the ongoing provision of TELE in integrative medicine.

Adversarial alignment and graph fusion via information bottleneck for multimodal emotion recognition in conversations

With the rapid development of social media and human–computer interaction, multimodal emotion recognition in conversations (MERC) tasks have begun to receive widespread research attention. The MERC task is to extract and fuse complementary semantic information from different modalities to classify the speaker’s emotion. However, the existing feature fusion methods usually directly map the features of other modalities into the same feature space for information fusion, which cannot eliminate the heterogeneity between different modalities and make the subsequent emotion class boundary learning more difficult. In addition, existing graph contrastive learning methods obtain consistent feature representations by maximizing mutual information between multiple views, which may lead to overfitting of the model. To tackle the above problem, we propose a novel Adversarial Alignment and Graph Fusion via Information Bottleneck for Multimodal Emotion Recognition in Conversations (AGF-IB) method. Firstly, we input video, audio, and text features into a multi-layer perceptron (MLP) to map them into separate feature spaces. Secondly, we build a generator and a discriminator for the three modal features, respectively, through adversarial representation to achieve information interaction between modalities and eliminate the heterogeneity among modalities. Thirdly, we introduce graph contrastive representation learning to capture intra-modal and inter-modal complementary semantic information and learn intra-class and inter-class boundary information of emotion categories. Furthermore, instead of maximizing the mutual information (MI) between multiple views, we use information bottleneck theory to minimize the MI between views. Specifically, we construct a graph structure for the three modal features respectively and perform contrastive representation learning on nodes with different emotions in the same modality and nodes with the same emotion in different modalities, to improve the feature representation ability of nodes. Finally, we use MLP to complete the emotional classification of the speaker. Extensive experiments show that AGF-IB can improve emotion recognition accuracy on IEMOCAP and MELD datasets. Furthermore, since AGF-IB is a general multimodal fusion and contrastive learning method, it can be applied to other multimodal tasks in a plug-and-play manner, e.g., humor detection.

ColorVideoVDP: A visual difference predictor for image, video and display distortions

ColorVideoVDP is a video and image quality metric that models spatial and temporal aspects of vision for both luminance and color. The metric is built on novel psychophysical models of chromatic spatiotemporal contrast sensitivity and cross-channel contrast masking. It accounts for the viewing conditions, geometric, and photometric characteristics of the display. It was trained to predict common video-streaming distortions (e.g., video compression, rescaling, and transmission errors) and also 8 new distortion types related to AR/VR displays (e.g., light source and waveguide non-uniformities). To address the latter application, we collected our novel XR-Display-Artifact-Video quality dataset (XR-DAVID), comprised of 336 distorted videos. Extensive testing on XR-DAVID, as well as several datasets from the literature, indicate a significant gain in prediction performance compared to existing metrics. ColorVideoVDP opens the doors to many novel applications that require the joint automated spatiotemporal assessment of luminance and color distortions, including video streaming, display specification, and design, visual comparison of results, and perceptually-guided quality optimization. The code for the metric can be found at https://github.com/gfxdisp/ColorVideoVDP.

Queen Elizabeth II and Paddington Bear: Some Features of a Popularity-Maintaining Discourse

The paper analyses a short two-and-a-half-minute sketch, a video presented to the U.K. public on the occasion of the Queen’s Platinum Jubilee celebrations in June 2022. The BAFTA-winning video features Queen Elizabeth II receiving Paddington Bear, the fictional character in children’s literature, for tea at the Palace at the time of the Jubilee party. For most people, this was one of the last images of the Queen making a public appearance before her subsequent death in September that year. Her association with the endeared character proved to be exceptionally strong in the public conscience as representative for values that she wished to embody: politeness, kindness and tolerance, as the nation’s „grandmother” reassures, through her presence, that her people has been properly inspired and imprinted by such qualities. The article focuses on linguistic, mainly pragmatic features of the characters’ interaction, trying to determine how the monarch’s Image could be projected as a discourse construct.

The role of a digital twin in supporting criminal investigations - a case report about a possible abuse.

As part of a comprehensive analysis, this case report presents a possible case of child maltreatment that can serve as a basis for forensic and medical examiner investigations. This case concerns the death of an infant who was approximately two months old. During a routine examination by the pediatrician at the end of May 2021, the child was found to have a normal head circumference of 31 cm. No other abnormalities were noted. On June 19, 2021, the child died, and an autopsy revealed a head circumference of 44 cm and a subdural hematoma as the cause of death. Questions arose as to who might have abused the child and when. The only evidence was a low-quality cell phone video taken by the child's parents on June 13, 2021, six days before the child's death, in which the child could be seen lying on a pillow. It was necessary to determine whether the child in this video already had an unnatural head circumference. This study presents a novel workflow that demonstrates how to analyze and deal with low quality video to answer questions like the above. The workflow demonstrates the creation of 3D scenes from digital image and video material. These 3D scenes can be used for object measurement and to support forensic and medical investigations. In the present case, where only low quality smartphone images were available, the presented workflow was used to create a 3D scene of the child lying on the pillow. In this 3D scene, it was possible to determine the child's head circumference. These measurements support the findings of the medical examiner (dated June 24, 2021) and confirm the suspicion that possible child abuse had already taken place on June 13, 2021. The innovative approach makes it possible to identify evidence of possible abuse based on a specific point in time, in this case the child's private footage. It also demonstrates the potential of 3D scene reconstruction in complex forensic and medical scenarios.

A Social Media Content Analysis of Dental Health Information Involving the Use of Miswak (Salvadora persica) Chewing Stick on YouTube™.

Background The widespread availability of Internet access and the rising popularity of social media platforms have facilitated the dissemination of health-related information, including dental health practices. However, assessing the quality and effectiveness of such information remains a challenge, particularly concerning traditional practices such as Miswak (Salvadora persica) usage. This study aims to assess the description, use, and effectiveness of the Miswak (Salvadora persica) chewing stick posted as video clips on YouTube™ and provide considerations for future interventions. Methodology YouTube videos were searched using the terms "Miswak," "Siwak," "Salvadora persica," and "Chewing stick." Each video's descriptive features, i.e., title, links, country of origin, upload date, running time, views, comments, likes, and dislikes, were recorded. Content quality was assessed using the DISCERN tool, which rates the reliability, dependability, and trustworthiness of online sources across 16 items. Scores were aggregated for analysis. The statistical analysis examined video features and associations between the speaker, video type, source, and quality, with significance set at a p-value <0.05 using SPSS Statistics Version 20 (IBM Corp., Armonk, NY, USA). Results A total of 45 videos were included in the study, with the majority (62%) created by the "other professionals" category. Almost three-quarters (73.3%) of the videos were educational. The quality of the video clips was correlated with the speaker source and category of "other," revealing that high-quality information was considered such when the source was other than a dentist. Further, we found that a video's source did not elicit differences in the opinion of the video's quality. Conclusions This social media analysis provides considerations and implications for future research on the potential use of YouTube as a platform for Miswak educational interventions.