Quality Assessment Of Content Research Articles

Mobile Apps for Vaccination Services: Content Analysis and Quality Assessment.

Vaccination services are increasingly in demand by the public, and mobile apps are an effective tool to meet that demand. However, the characteristics and quality of these apps are unknown. Commonly used vaccination service apps on the market were surveyed with regard to quality, service content, and user experience to evaluate and guide users. The Qimai Data mobile app data analytics platform was used to search for common vaccination service apps by keyword, and the WeChat and Alipay platforms were searched for apps. The apps included in the study were independently evaluated by two reviewers using the Mobile Application Rating Scale, and the service content and user experience of the apps were analyzed. The intragroup correlation coefficient between raters was used to measure interrater reliability. In the app stores of the four major Android platforms and the iOS app store, 1092 and 207 apps were found, respectively; 189 WeChat applets and 30 Alipay applets were also found. A total of 29 apps was ultimately included in this study according to the inclusion criteria, including 21 independent apps, 4 WeChat applets, and 4 Alipay applets. Significant differences were found between independent apps and applets in terms of the quality score (t449.57=-5.301; P<.001) and the subjective quality score (z=-4.753; P<.001). No significant differences were found between iOS and Android platforms in terms of the quality score (t1404=-2.55; P=.80) and the subjective quality score (z=-0.137; P=.89). There was good intragroup consistency among the raters. In this study, independent apps and nonindependent apps that rely on social and payment platforms for implementation were included in the vaccination services category. The overall quality of these apps was acceptable. Nonindependent running apps were found to have slightly lower scores and showed room for improvement, and scores for the participatory apps were found to be generally low overall.

Assessment of Eye Care Apps for Children and Adolescents Based on the Mobile App Rating Scale: Content Analysis and Quality Assessment.

In China, the current situation of myopia among children and adolescents is very serious. Prevention and control of myopia are inhibited by the lack of medical resources and the low awareness about eye care. Nevertheless, mobile apps provide an effective means to solve these problems. Since the health app market in China is still immature, it has become particularly important to conduct a study to assess the quality of eye-care apps to facilitate the development of better eye-care service strategies. This study aimed to evaluate the quality, functionality, medical evidence, and professional background of eye-care apps targeting children and adolescents in the Chinese app stores. A systematic search on iOS and Android app stores was performed to identify eye-care apps for children and adolescents. The general characteristics, development context, and functional features of the apps were described. Quality assessment of the apps was completed by 2 independent researchers using the Mobile App Rating Scale. This study included 29 apps, of which 17 (59%) were developed by commercial organizations and 12 (41%) had a design with relevant scientific basis. The main built-in functions of these apps include self-testing (18/29, 62%), eye exercises (16/29, 55%), and eye-care education (16/29, 55%). The mean overall quality of eye-care apps was 3.49 (SD 0.33), with a score ranging from 2.89 to 4.39. The overall Mobile App Rating Scale score exhibited a significant positive correlation with the subscale scores (r=0.81-0.91; P<.001). In addition, although most apps provided basic eye-care features, there are some deficiencies. For example, only a few apps were developed with the participation of medical organizations or professional ophthalmologists, and most of the apps were updated infrequently, failing to provide the latest eye-care information and technology in a timely manner. In general, the quality of eye-care apps for children and teenagers in Chinese app stores is good. These apps fulfill users' needs for eye-care services to a certain extent, but they still suffer from insufficient medical background, low user engagement, and untimely updates. In order to further improve the effectiveness of eye-care apps, cooperation with medical institutions and professional ophthalmologists should be strengthened to enhance the scientific and authoritative nature of the apps. At the same time, interactive features and regular updates should be added to enhance user participation and the continuity of the apps. This study provides a reference for future development or improvement of eye-care apps, which can help promote myopia prevention and control.

Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.

There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and cross-sectional original research study. In our study, AI chatbots ChatGPT®, Bard®, Gemini®, Copilot®, and Perplexity® were asked to present the answers of the 100 questions most frequently asked by patients about palliative care. Responses from each 5 AI chatbots were analyzed separately. This study did not involve any human participants. Study results revealed significant differences between the readability assessments of responses from all 5 AI chatbots (P < .05). According to the results of our study, when different readability indexes were evaluated holistically, the readability of AI chatbot responses was evaluated as Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, from easy to difficult (P < .05). In our study, the median readability indexes of each of the 5 AI chatbots Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini® responses were compared to the "recommended" 6th grade reading level. According to the results of our study answers of all 5 AI chatbots were compared with the 6th grade reading level, statistically significant differences were observed in the all formulas (P < .001). The answers of all 5 artificial intelligence robots were determined to be at an educational level well above the 6th grade level. The modified DISCERN and Journal of American Medical Association scores was found to be the highest in Perplexity® (P < .001). Gemini® responses were found to have the highest Global Quality Scale score (P < .001). It is emphasized that patient education materials should have a readability level of 6th grade level. Of the 5 AI chatbots whose answers about palliative care were evaluated, Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, their current answers were found to be well above the recommended levels in terms of readability of text content. Text content quality assessment scores are also low. Both the quality and readability of texts should be brought to appropriate recommended limits.

TikTok and pediatric nephrology: content quality assessment of videos related to pediatric kidney disease and kidney transplant.

Social media platforms such as TikTok™ are key sources of health information for young patients and caregivers. Misinformation is prevalent on TikTok™ across healthcare fields, which can perpetuate false beliefs about medical care. Limited data exists on the reliability of pediatric nephrology TikTok™ content. This study aimed to describe the quality of medical content of TikTok™ Videos (TTVs), related to pediatric kidney disease and transplant. TTVs were selected using specific search terms and categorized into pediatric kidney disease and kidney transplant, excluding duplicate and adult-related content. The top 100 TTVs in each category, based on views, were analyzed. TTV characteristics were stratified by account type (physician, non-physician healthcare professional (HCP), non-HCP) and video aim (personal story, education, entertainment). DISCERN scoring, a validated questionnaire evaluating health information reliability, was conducted by 4 independent raters. Inter-rater reliability was assessed using a 2-way random effects model, and differences between content creator types were evaluated using one-way ANOVA and post-Hoc Tukey test. TTVs had a total of 12.5 million likes and 113.1 million views. Over 70% of videos were created by non-HCPs (n = 147/200). DISCERN scoring revealed low reliability of medical information across content creator types. TTVs created by physicians and non-physician HCPs about kidney disease had significantly higher mean DISCERN scores compared to those created by non-HCPs (2.85, p < 0.001 and 2.48, p = 0.005, respectively). Educators within the pediatric nephrology community must keep in mind the lack of reliability of medical information available on TikTok™ and coordinate collective efforts to consider utilizing TikTok™ for patient education.

The Study of Combination of Biodegradable Packaging and Biocoating with Lactic Acid Bacteria as a Green Alternative for Traditional Packaging in Gouda Cheese

Biodegradable packaging, both alone and in combination with acid whey protein coatings, has been used to pack fresh Gouda cheese to improve preservation prior ripening or storage. This study involved three key components: (i) the selection of biodegradable packaging (BP), (ii) the development of a plain liquid acid whey protein concentrate, pectin-based edible coating (BP + Ch + Coating), and (iii) the incorporation of at least 6 log10 CFU (colony forming units) mL−1 Lacticaseibacillus paracasei (BP + Ch + Coating + Lp) and Lactobacillus helveticus (BP + Ch + Coating + Lh) strains. The created compositions were compared with cheese packed in conventional polyethylene (PE) packaging to evaluate their overall synergy effect in reducing microbiological spoilage and influencing chemical parameters in Gouda cheese during 45 days of ripening and cold storage. The evaluation included microbiological analysis (total LAB, Enterobacteriaceae spp., and fungi CFU) and quality assessment of pH, moisture content, water activity, texture, and colour (CEI system) during ripening and shelf life. Although biodegradable packaging (BP) alone did not protect the cheese effectively compared to conventional packaging (EVA/PE/EPC/PVDC), the combination of biodegradable packaging with a coating (BP + Ch + Coating) showed protective properties against Enterobacteriaceae spp. and mould, maintaining moisture, pH, and colour during ripening and storage. Incorporation of L. helveticus (BP + Ch + Coating + Lh) into the coating efficiently decreased the growth of fungi.

Development and Assessment of Review Clips by Disabled Students for a Teenage Soul Healing Program on the TikTok Platform

The purposes of this research were 1) to develop review clips by disabled students for a teenage soul healing program on the TikTok platform 2) to evaluate the quality of the review clips by disabled students 3) to evaluate the perception of the samples 4) to evaluate the satisfaction of the samples. The research tools included 1) the review clips by disabled students for the teenage soul healing program on the TikTok platform 2) the quality assessment form 3) the perception assessment form 4) the satisfaction assessment form. Data were collected from a sample group comprising 60 students chosen by a simple random sampling method from the Department of Educational Communications and Technology in the second semester of the 2023 academic who were exposed the review clips and who were willing to complete the questionnaire. The results were 4 review clips by disabled students using ADDIE Model. The evaluation by experts identified that content and media presentation quality assessment was at a very good level , while the samples’ perception and satisfaction were at the highest level.

Language-Agnostic Modeling of Wikipedia Articles for Content Quality Assessment across Languages

Language-Agnostic Modeling of Wikipedia Articles for Content Quality Assessment across Languages

Assessing the Quality and Clarity of YouTube Videos as an Informational Source for Ankle Fractures: A Study of the Turkish Population.

Background and objective The significance of YouTube as a prominent source of healthcare-related information cannot be overstated. Its influence on patient education is substantial. However, despite its popularity, there has been little research into the quality and comprehensibility of videos related to ankle fractures, a condition with increasing incidence rates, particularly in the context of Turkey. To address this gap in the literature and the growing reliance on digital platforms for health information during the coronavirus disease 2019 (COVID-19) pandemic, this study aims to assess the quality, clarity, and pedagogical value of YouTube videos on ankle fractures for the Turkish population. Methodology A comprehensive examination of 150 YouTube videos concerning ankle fractures, employing exacting inclusion and exclusion criteria to identify 52 videos for in-depth analysis was undertaken. The investigation entailed an assessment of content quality, presentation style, and user interaction, utilizing the criteria established by the Journal of the American Medical Association (JAMA) and the Patient Education Materials Assessment Tool (PEMAT), as well as a novel measurement known as the Ankle Fracture Content Score (AFCS). A statistical analysis was executed to gauge the educational value and dependability of the information presented. Results The majority of ankle fracture management videos were found to be uploaded by medical professionals, covering various aspects such as rehabilitation and patient testimonials. However, the overall educational quality was suboptimal, with patient-shared videos lacking in depth and accuracy. Statistical analysis showed no significant differences in content quality across different uploader categories, except for notably lower educational quality in videos shared by patients. Conclusions The findings underscore a significant need for healthcare professionals and academic institutions in Turkey to produce and share high-quality, reliable, and comprehensible videos on ankle fractures. Leveraging YouTube's extensive reach can significantly improve health literacy among the Turkish public, ensuring access to accurate and trustworthy health information.

Analysis of the physical chemistry of domestic water supply sources in choba, Port Harcourt, rivers state

Water are used for several important purposes but the most essential use considered on the basis of social and economic significance as it relates to the health of the population is human consumption and sanitation. Man needs constant and accessible supply of water to provide necessary prerequisite for important physiological and biochemical processes. On account of the general contention that water is more basic than all other critical stuff to life and in its pure state is commended key to health. This study aimed at to examine the physical characteristics of the water supply sources in Choba as a crucial factor for development and upon which the quality of life depends. Thus, water samples were collected from borehole and well water sources being the only available major sources of water supply in Rumuokocha, Rumuchakara, Igbogo, Owhipa, Ndudor and Rumualoghu communities that make Choba and the parameters investigated include pH, Temperature, Dissolved oxygen (DO), Conductivity, Total Dissolved Solid (TDS) and Salinity. The results of the analyses for temperature was t= 0.751 and t= 0.547 both at p&lt;0.05 for borehole and well water sources implying no significant difference from the allowable limit by WHO whereas for DO, pH, salinity, TDS and conductivity, t= -51.966; -24.027; -24.796, -19.546 ;2.321and t= -51.966; -24.027; -16.966, -20.024; 2.272 for borehole and well water sources respectively indicating a statistically significant difference between the parameters investigated and the allowable limits. Similarly, the ANOVA result shows F= 400.384; 23.262; 19.997; 8502.215at p&lt;0.05 for parameters like temperature, salinity, TDS and conductivity of the available water sources do not vary significantly in the area. Therefore, constant monitoring and assessment of physical water quality parameters, water treatment and assessment of bacteriological content and other relevant water parameters to holistically ascertain it suitability for adequate human use were recommended.

Pilot Testing of a Tool to Standardize the Assessment of the Quality of Health Information Generated by Artificial Intelligence-Based Models.

Background Artificial intelligence (AI)-based conversational models, such as Chat Generative Pre-trained Transformer (ChatGPT), Microsoft Bing, and Google Bard, have emerged as valuable sources of health information for lay individuals. However, the accuracy of the information provided by these AI models remains a significant concern.This pilot study aimed to test a new tool with key themes for inclusion as follows:Completeness of content,Lack of false information in the content,Evidence supporting the content,Appropriateness of the content, andRelevance, referred to as "CLEAR", designed to assess the quality of health information delivered by AI-based models. Methods Tool development involved a literature review on health information quality, followed by the initial establishment of the CLEAR tool, which comprised five items that aimed to assess the following: completeness, lack of false information, evidence support, appropriateness, and relevance. Each item was scored on a five-point Likert scale from excellent to poor. Content validity was checked by expert review. Pilot testing involved 32 healthcare professionals using the CLEAR tool to assess content on eight different health topics deliberately designed with varying qualities. The internal consistency was checked with Cronbach's alpha (α). Feedback from the pilot test resulted in language modifications to improve the clarity of the items. The final CLEAR tool was used to assess the quality of health information generated by four distinct AI models on five health topics. The AI models were ChatGPT 3.5, ChatGPT 4, Microsoft Bing, and Google Bard, and the content generated was scored by two independent raters with Cohen's kappa (κ) for inter-rater agreement. Results The final five CLEAR items were: (1) Is the content sufficient?; (2) Is the content accurate?; (3) Is the content evidence-based?; (4) Is the content clear, concise, and easy to understand?; and (5) Is the content free from irrelevant information? Pilot testing on the eight health topics revealed acceptable internal consistency with a Cronbach's α range of 0.669-0.981. The use of the final CLEAR tool yielded the following average scores: Microsoft Bing (mean=24.4±0.42), ChatGPT-4 (mean=23.6±0.96), Google Bard (mean=21.2±1.79), and ChatGPT-3.5 (mean=20.6±5.20). The inter-rater agreement revealed the following Cohen κ values: for ChatGPT-3.5 (κ=0.875, P<.001), ChatGPT-4 (κ=0.780, P<.001), Microsoft Bing (κ=0.348, P=.037), and Google Bard (κ=.749, P<.001). Conclusions The CLEAR tool is a brief yet helpful tool that can aid in standardizing testing of the quality of health information generated by AI-based models. Future studies are recommended to validate the utility of the CLEAR tool in the quality assessment of AI-generated health-related content using a larger sample across various complex health topics.

Driving Clicks towards Ecommerce Website: The Effect of Beauty Product Review Article Content Quality on Ecommerce Blog

Ecommerce blogs are increasingly popular for providing product information, reviews and driving traffic to ecommerce websites. Recent study reported 76% of ecommerce users trust online reviews as much as recommendations from family or friends. This indicates that the content found in product reviews blog plays a crucial role in driving users to ecommerce websites. This study examines the impact of content quality in beauty product review articles on click intention towards ecommerce websites. Content quality is evaluated based on Substance, Writing and Language, Presentation of Content, References, Authorship, Audience, and Advertisements. Semi-experimental and logistic regression analyses were conducted on survey data from 225 female respondents who evaluated 126 beauty product review articles. Findings indicate a positive association between Substance, Presentation of Content, and Authorship with Click Intention, while Writing and Language, References, and Advertisement show no significant correlation. Furthermore, a negative relationship exists between Audience and Click Intention. This research addresses the literature gap by identifying significant factors of content quality that influence click intention, emphasizing the importance of content quality assessment and providing strategies for improvement. The study offers valuable insights for ecommerce companies to optimize marketing expenses and achieve key performance indicators.

Dietary and herbal supplement consumer health information for pain: A cross-sectional survey and quality assessment of online content

BackgroundPatients are increasingly utilizing the internet to learn about dietary and herbal supplements (DHSs) for various diseases/conditions, including pain management. Online health information has been found to be inconsistent and of poor quality in prior studies, which may have detrimental effects on patient health. This study assessed the quality of online DHSs consumer health information for pain. MethodsSix search items related to DHSs and pain were used to generate the first 20 websites on Google across four English-speaking countries. The identified 480 webpages produced 68 eligible websites, which were then evaluated using the DISCERN tool. The mean scores and standard deviations (SD) of the reviewers’ ratings on each of the 15 DISCERN instrument items as well as the overall total score were calculated. ResultsThe mean summed score for the 68 eligible websites was 46.6 (SD = 10.1), and the mean overall rating was 3.3 (SD = 0.8). Websites lacked information regarding areas of uncertainty, the effects of no treatment being used, and how treatments affect the overall quality of life. These shortcomings were especially apparent across commercial websites, which frequently displayed bias, failed to report the risks of DHS products, and lacked support for shared decision-making regarding the use of DHSs. ConclusionVariability exists in the quality of online consumer health information regarding DHS use for pain. Healthcare providers should be aware of and provide guidance to patients regarding the identification of reliable online resources so that they can make informed decisions about DHS use for pain management.

A cross-sectional quality assessment of TikTok content on benign prostatic hyperplasia.

With an increasing reliance on online sources for medical information, we studied the quality and completeness of health literacy videos on TikTok regarding BPH. A cross-sectional systematic evaluation of TikTok videos using the search term "Benign Prostatic Hyperplasia" was performed on 14th April 2023, and included 49 patient information and educational videos. The videos were then analysed by two reviewers and scored using two instruments: the DISCERN instrument and a completeness analysis. Of the 49 videos, 38 were created by healthcare professionals (HCPs). The average length of each video was 62.7 ± 59.3s, with a large average number of total views (24,990.1 ± 109,534.9 views). The DISCERN score trended higher in every category in videos published by HCPs compared to non-HCPs, with HCPs providing a statistically significant increase in reliability (19.0,14.6, p < 0.05) and total score (29.4,23, p < 0.05). Majority of videos were deemed as poor or worse (91.8%) in quality. The completeness of the videos' content was also evaluated across five categories with an average score of 2.53 ± 2.1 out of the maximum 12. The DISCERN scores did not correlate with the degree of completeness of the videos (r = 0.226). BPH videos on TikTok have a wide reach, but the videos are mostly of low quality and completeness. Future videos should be made with quality and completeness in mind given the large viewership and more can be done to evaluate the extent of BPH misinformation and its impact on patients.

WeChat official accounts' posts on medication use of 251 community healthcare centers in Shanghai, China: content analysis and quality assessment.

The dissemination of online health information (OHI) on medication use via WeChat Official Accounts (WOAs) is an effective way to help primary care practitioners (PCPs) address drug-related problems (DRPs) in the community. Although an increasing number of primary care institutions in China have published WOA posts on medication use, their content and quality have not yet been assessed. This study aimed to explore the general features and content of WOA posts on medication use published by community healthcare centers (CHCs) in Shanghai, China and to assess their quality of content. It also aimed to explore the factors associated with the number of post views. From June 1 to October 31, 2022, two coauthors independently screened WOA posts on medication use published throughout 2021 by the CHCs in Shanghai. Content analysis was performed to analyze their general features (format, length, and source, etc.) and content (types of medicines and diseases). The QUEST tool was used to assess the quality of the posts. We compared the differences among posts published by CHCs in central urban areas and suburban areas, and used multiple linear regression to explore the factors associated with the number of post views. A total of 236 WOAs of interest published 37,147 posts in 2021, and 275 (0.74%) of them were included in the study. The median number of post views was 152. Thirty percent of the posts were reviewed by the CHCs' staff before publication and only 6% provided information on PCPs' consultations. The most commonly mentioned medicines and diseases in the posts were Chinese patent medicines (37.1%) and respiratory diseases (29.5%). The posts frequently provided information on indications (77%) and usage (56%) but rarely on follow-up (13%) and storage (11%). Of the posts, 94.9% had a total QUEST score < 17 (full score = 28). The median number of post views and total post quality scores did not significantly differ among the CHCs in central urban and suburban areas. In the multiple linear regression model, the number of post views was associated with scores of complementarity (B = 56.47, 95% CI 3.05, 109.89) and conflict of interest (B = -46.40, 95% CI -56.21, -36.60). The quantity and quality of WOA posts on medication use published by CHCs in China need improvement. The quality of posts may partially impact the dissemination effect, but intrinsic causal associations merit further exploration.

Deep Neural Network for Blind Visual Quality Assessment of 4K Content

The 4K content can deliver a more immersive visual experience to consumers due to the huge improvement in spatial resolution. However, the high spatial resolution brings a great challenge for video transmission and storage. Therefore, it is necessary to compress or downscale the 4K content before transmitting it to end-users. Existing blind image quality assessment (BIQA) methods are not suitable for 4K contents due to the high spatial resolution and specific distortions caused by upscaling methods. In this paper, we propose a deep learning-based BIQA model for 4K content, aiming to recognize true and pseudo 4K content and meanwhile evaluate their visual quality. Considering the characteristic that high spatial resolution can represent more abundant high-frequency information, we first propose a Grey-level Co-occurrence Matrix (GLCM) based texture complexity measure to select three representative image patches from a 4K image, which can reduce the computational complexity and is proven to be very effective for the overall quality prediction. Then, we extract various visual features from the intermediate layers of the convolutional neural network (CNN) and integrate them into the quality-aware feature representation. Finally, two multilayer perception (MLP) networks are utilized to map the quality-aware features into the class probability and the quality score of each patch respectively. The overall quality index is obtained through averaging the results of all patches. The proposed model is trained via the multi-task learning manner and the uncertainty principle is introduced to balance the losses of the classification and regression tasks. The experimental results show that the proposed model outperforms all compared BIQA metrics on four 4K content quality assessment databases.

Secondary Qualitative Research Methodology Using Online Data within the Context of Social Sciences

Qualitative research using interviews is a crucial and established inquiry method in social sciences to ensure that the study outputs represent the researched people and area rather than those who are researching. However, first hand primary data collection is not always possible, often due to external circumstances. Additionally, the use of secondary data, particularly open data, is progressively preferred to increase efficiency and gain geographical breadth. Therefore, this paper proposes a new step-by-step secondary qualitative inquiry methodology for online, publicly available interview data. Such procedural approach can help increase rigor, explicitly consider and mitigate potential pitfalls, and expand the research community’s datasets. The 7-step methodology is based on a hybrid approach with elements of pragmatic qualitative approach, discursive grounded theory, and narrative approach and refers to research ethical principles of autonomy, equity, and diversity. One of the proposed steps is data quality assessment, which consists of quality assessment of data context and data content with a total of 16 quality dimensions to filter the collected data. The data analysis method comprises of content analysis for dataset categorization and thematic discourse analysis to answer the pre-set research questions. Additionally, the methodology covers the ethical and legal considerations relating to secondary online data and reporting the research findings of such data. By providing an example in the field of forced migration, we demonstrate how the methodology provides structure when conducting secondary qualitative research.

Reliability of open globe injury repair surgical videos on the internet for resident education

Introduction This study aimed to assess quality of surgical training videos for management of open globe injury (OGI) on online platforms. Material and Methods Twenty-three websites with surgical training videos were queried using the search keyword “open globe repair.” Video content characteristics and quality assessment scores using Sandvik score, Health on the Net Foundation Code of Conduct (HON code), mDISCERN scoring, and global quality score (GQS) were recorded. To evaluate the relevance of the surgical videos to the surgical procedure, steps were analyzed as per the Ophthalmology Surgical Competency Assessment Rubric (OSCAR) for Open Globe Surgical Management. Results One hundred and twenty-three videos were evaluated, and 63 analyzed. Majority videos were uploaded by solitary ophthalmologists (53/63; 84.13%). Mean video quality score (VQS) and GIS scores were 6.55 ± 1.59 and 7.95 ± 1.39, respectively. Mean mDISCERN, GQS, HON Code and Sandvik scores for all the videos were 2.87 ± 1.07, 3.77 ± 1.08, 5.14 ± 1.67, 12.06 ± 1.84, respectively. Videos with background audio and descriptive subtitles had significantly better quality ( p &lt; 0.05). All Quality assessment scores showed a statistically significant ( p &lt; 0.000) positive correlation with each other. On linear regression analysis, number of video likes, comments and views had a significant ( p &lt; 0.05) positive relation with quality of video, whereas video length showed a negative relation with different scores. Conclusion Nearly two-thirds of surgical videos showing OGI repair had good quality assessment scores. Consensus guidelines should be developed to guide uploaders as regards the essential features required for good quality surgical videos using a standardized rubric.

Assessment of available online educational resources for patients with atrial fibrillation

A diagnosis of atrial fibrillation (AF) often leads patients to search online for information, which can expose them to information of varied quality. We conducted a qualitative systematic review of websites that contain useful information regarding AF. The following terms were searched on 3 search engines (Google/Yahoo/Bing): (Atrial fibrillation for patients), (What is atrial fibrillation), (Atrial fibrillation patient information), (Atrial fibrillation educational resources). Inclusion criteria included websites with comprehensive AF information and information about treatment options. The Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) and PEMAT for Audiovisual Materials assessed understandability and actionability (score range 0-100). Those with a mean PEMAT-P score of >70, meaning acceptable understandability and actionability, underwent DISCERN score assessment of information content quality and reliability (score range 16-80). The search yielded 720 websites that underwent full review. After exclusions, 49 underwent full scoring. The mean overall PEMAT-P score was 69.3 ± 17.2. The mean PEMAT-AV score was 63.4 ± 13.6. Of the websites that scored >70% on the PEMAT-P, 23 (46%) underwent DISCERN scoring. The mean DISCERN score was 54.7 ± 4.6. There is a wide variation in the understandably, actionability, and quality of websites, many not providing patient-level materials. Knowledge of quality websites could provide an important adjunct for improving patients understanding of AF.

Can Basic Soil Quality Indicators and Topography Explain the Spatial Variability in Agricultural Fields Observed from Drone Orthomosaics?

Crop growth is often uneven within an agricultural parcel, even if it has been managed evenly. Aerial images are often used to determine the presence of vegetation and its spatial variability in field parcels. However, the reasons for this uneven growth have been less studied, and they might be connected to variations in topography, as well as soil properties and quality. In this study, we evaluated the relationship between drone image data and field and soil quality indicators. In total, 27 multispectral and RGB drone image datasets were collected from four real farm fields in 2016–2020. We analyzed 13 basic soil quality indicators, including penetrometer resistance in top- and subsoil, soil texture (clay, silt, fine sand, and sand content), soil organic carbon (SOC) content, clay/SOC ratio, and soil quality assessment parameters (topsoil biological indicators, subsoil macroporosity, compacted layers in the soil profile, topsoil structure, and subsoil structure). Furthermore, a topography variable describing water flow was used as an indicator. Firstly, we evaluated single pixel-wise linear correlations between the drone datasets and soil/field-related parameters. Correlations varied between datasets and, in the best case, were 0.8. Next, we trained and tested multiparameter non-linear models (random forest algorithm) using all 14 soil-related parameters as features to explain the multispectral (NIR band) and RGB (green band) reflectance values of each drone dataset. The results showed that the soil/field indicators could effectively explain the spatial variability in the drone images in most cases (R2 &gt; 0.5), especially for annual crops, and in the best case, the R2 value was 0.95. The most important field/soil features for explaining the variability in drone images varied between fields and imaging times. However, it was found that basic soil quality indicators and topography variables could explain the variability observed in the drone orthomosaics in certain conditions. This knowledge about soil quality indicators causing within-field variation could be utilized when planning cultivation operations or evaluating the value of a field parcel.

Mobile Health Apps for Breast Cancer: Content Analysis and Quality Assessment

The number of mobile health apps is rapidly increasing. This means that consumers are faced with a bewildering array of choices, and finding the benefit of such apps may be challenging. The significant international burden of breast cancer (BC) and the potential of mobile health apps to improve medical and public health practices mean that such apps will likely be important because of their functionalities in daily life. As the app market has grown exponentially, several review studies have scrutinized cancer- or BC-related apps. However, those reviews concentrated on the availability of the apps and relied on user ratings to decide on app quality. To minimize subjectivity in quality assessment, quantitative methods to assess BC-related apps are required. The purpose of this study is to analyze the content and quality of BC-related apps to provide useful information for end users and clinicians. Based on a stepwise systematic approach, we analyzed apps related to BC, including those related to prevention, detection, treatment, and survivor support. We used the keywords "breast cancer" in English and Korean to identify commercially available apps in the Google Play and App Store. The apps were then independently evaluated by 2 investigators to determine their eligibility for inclusion. The content and quality of the apps were analyzed using objective frameworks and the Mobile App Rating Scale (MARS), respectively. The initial search identified 1148 apps, 69 (6%) of which were included. Most BC-related apps provided information, and some recorded patient-generated health data, provided psychological support, and assisted with medication management. The Kendall coefficient of concordance between the raters was 0.91 (P<.001). The mean MARS score (range: 1-5) of the apps was 3.31 (SD 0.67; range: 1.94-4.53). Among the 5 individual dimensions, functionality had the highest mean score (4.37, SD 0.42) followed by aesthetics (3.74, SD 1.14). Apps that only provided information on BC prevention or management of its risk factors had lower MARS scores than those that recorded medical data or patient-generated health data. Apps that were developed >2 years ago, or by individuals, had significantly lower MARS scores compared to other apps (P<.001). The quality of BC-related apps was generally acceptable according to the MARS, but the gaps between the highest- and lowest-rated apps were large. In addition, apps using personalized data were of higher quality than those merely giving related information, especially after treatment in the cancer care continuum. We also found that apps that had been updated within 1 year and developed by private companies had higher MARS scores. This may imply that there are criteria for end users and clinicians to help choose the right apps for better clinical outcomes.