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Existing no-reference (NR) image quality assessment (IQA) metrics are still not convincing for evaluating the quality of the camera-captured images. Toward tackling this issue, we, in this article, establish a novel NR quality metric for quantifying the quality of the camera-captured images reliably. Since the image quality is hierarchically perceived from the low-level preliminary visual perception to the high-level semantic comprehension in the human brain, in our proposed metric, we characterize the image quality by exploiting both the low-level image properties and the high-level semantics of the image. Specifically, we extract a series of low-level features to characterize the fundamental image properties, including the brightness, saturation, contrast, noiseness, sharpness, and naturalness, which are highly indicative of the camera-captured image quality. Correspondingly, the high-level features are designed to characterize the semantics of the image. The low-level and high-level perceptual features play complementary roles in measuring the image quality. To infer the image quality, we employ the support vector regression (SVR) to map all the informative features to a single quality score. Thorough tests conducted on two standard camera-captured image databases demonstrate the effectiveness of the proposed quality metric in assessing the image quality and its superiority over the state-of-the-art NR quality metrics. The source code of the proposed metric for camera-captured images is released at https://github.com/YT2015?tab=repositories.

Many stereoscopic image retargeting (SIR) methods have been developed for automatically and intelligently resizing stereoscopic images and we cannot always rely on time-consuming subjective user studies to validate the performance of different SIR methods. It is therefore required to design reliable objective metrics for SIR quality evaluation. This paper extends our previous 2D aspect ratio similarity (ARS) metric to a stereo 3D version termed as StereoARS where the key idea is to investigate into retargeting inconsistency between the original stereo correspondences. Our proposed StereoARS operates via two stages: monocular quality estimation and binocular inconsistency detection. In the first stage, monocular quality estimation is performed by applying a modified ARS measure on the left and right views separately to quantify the quality degradation within each monocular view. In the second stage, binocular inconsistency detection is performed in both pixel-level and grid-level to characterize the influence of binocular rivalry and stereo visual discomfort on SIR quality. In addition, we also measure to what extent the original pixel visibility relation is preserved after SIR as another binocular quality factor. Finally, these monocular and binocular quality estimates are fused to produce an overall SIR quality score. Extensive experiments have demonstrated that StereoARS achieves better alignment with human subjective ratings than the existing metrics by a large margin.

PurposeThe purpose is to assess the impact of clinical costing approaches on the quality of cost information in seven countries (Denmark, England, France, Germany, Ireland, the Netherlands and Portugal).Design/methodology/approachCosting practices in seven countries were analysed via questionnaires, interviews and relevant published material.FindingsAlthough clinical costing is intended to support a similar range of purposes, countries display considerable diversity in their approaches to costing in terms of the level of detail contained in regulatory guidance and the percentage of providers subject to such guidance for tariff setting. Guidance in all countries involves a mix of costing methods.Research limitations/implicationsThe authors propose a two-dimensional Materiality and Quality Score (2D MAQS) of costing systems that can support the complex trade-offs in managing the quality of cost information at both policy and provider level, and between financial and clinical concerns.Originality/valueThe authors explore the trade-offs between different dimensions of the quality (accuracy, decision relevance and standardization) and the cost of collecting and analysing cost information for disparate purposes.

Purpose This study aimed to evaluate the content quality, reliability, and audience participation analysis of YouTube videos as a source of information about COVID-19 for children. Design and methods This study was conducted in a descriptive design. The keywords “COVID-19, explain, children” were searched on the YouTube platform on March 17, 2021, and 294 videos were reviewed. The content of the selected videos was analyzed by 2 independent reviewers. Meet the inclusion criteria, 57 videos were evaluated according to the presenter source and the presented audience with the COVID-19 for Children Checklist (CCC), DISCERN score and the Global Quality Score (GQS). Results When the contents of 57 videos included in the study were reviewed, it was determined that 56.1% (n = 32) were informative and 43.9% (n = 25) were misleading. Kappa value among the two independent observers was 0.89. 17.5% (n = 10) of the videos scored 5 points from DISCERN and 31.6% (n = 18) scored 4 points from GQS. The mean scores of GQS, DISCERN and CCC of videos with the grouped as informative were found to be statistically higher. There was a significant difference between the DISCERN mean score of ministry/academic/hospital/physician channel videos was higher than the mean score of entertainment/individual channel videos. Conclusions This study has shown that videos explaining COVID-19 to children have high viewing rates, but also videos that are low in terms of quality and reliability. Practice implications It is thought that this study will reduce the rates of hospitalization by protecting children from COVID-19 by providing them access to healthier and more reliable sources.

With Industry 4.0, temporal relations between process and quality variables become increasingly complex. Some dynamic supervised learning algorithms are designed to extract their dynamic cross-relations, but auto-correlations among quality variables are rarely considered, which, however, can provide additional valuable information. This article proposes a novel dynamic auto-regressive latent variable model (DALVM) to capture both auto and cross correlations from high-dimensional time series data. DALVM is designed to maximize the covariance between current quality score and the weighted sum of past quality and process scores, and an auto-regressive exogenous inner model is developed for consistency purpose. Further, a concurrent anomaly detection system is developed based on DALVM, referred to as ConDALVM, which conducts subsequent decompositions in the extracted latent spaces. ConDALVM realizes a comprehensive monitoring for both static and dynamic anomalies in process and quality spaces. The superiority of the methods is demonstrated through a numerical simulation and two industrial processes.

Aims To determine the impact of a quality improvement (QI) initiative in the area of paediatric echocardiography (echo) in a low- to middle-income country (LMIC). Care for patients with congenital heart disease is challenging, especially in LMICs. Collaborative learning through QI projects is imperative to ensure improvement in delivery processes leading to better patient outcomes. Methods and results This QI initiative was taken by a team consisting of physicians and sonographers. Problems were identified, a key driver diagram (KDD) was created, and simple process re-engineering was done using interventions based on the KDD. Metrics (five process and one outcome) were assessed to determine the effectiveness of the QI project. The process metrics assessed were comprehensiveness of exam, timeliness of reporting, diagnostic accuracy and error, and sedation adverse event rates of transthoracic echocardiograms, while a novel comprehensive echo laboratory (lab) quality score was developed as an outcome metric. Data were collected quarterly and analysed in the post-implementation phase. Significant improvement was seen in comprehensive mean score (20.4–29.7), timeliness (40–95%), and diagnostic accuracy rate (91–100%), while a decrease was seen in the diagnostic error rate (7.5–3.5%) and the sedation adverse event rate (6.8–0%), pre- vs. post-implementation. The overall quality outcome score improved from 7 to 19 and the echo lab was able to achieve adequate quality. Conclusion This QI initiative produced improvement in all the processes, and the overall quality of the echo lab without any substantial increase in resources or cost.

Background To select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses supervised machine learning for the quality scoring of genome assemblies and does not require an existing reference genome for accuracy assessment. Results EvalDNA calculates a list of quality metrics from an assembled sequence and applies a model created from supervised machine learning methods to integrate various metrics into a comprehensive quality score. A well-tested, accurate model for scoring mammalian genome sequences is provided as part of EvalDNA. This random forest regression model evaluates an assembled sequence based on continuity, completeness, and accuracy, and was able to explain 86% of the variation in reference-based quality scores within the testing data. EvalDNA was applied to human chromosome 14 assemblies from the GAGE study to rank genome assemblers and to compare EvalDNA to two other quality evaluation tools. In addition, EvalDNA was used to evaluate several genome assemblies of the Chinese hamster genome to help establish a better reference genome for the biopharmaceutical manufacturing community. EvalDNA was also used to assess more recent human assemblies from the QUAST-LG study completed in 2018, and its ability to score bacterial genomes was examined through application on bacterial assemblies from the GAGE-B study. Conclusions EvalDNA enables scientists to easily identify the best available genome assembly for their organism of interest without requiring a reference assembly. EvalDNA sets itself apart from other quality assessment tools by producing a quality score that enables direct comparison among assemblies from different species.

Background: The internet is a broadly preferred source of information both by patients and medical professionals. YouTube™ is a significant information source that may be a useful tool to inform the public, medical students, and residents, and may improve the learning experience if used adequately. In this study, we aimed to estimate the quality and accuracy of videos regarding Transoral Endoscopic Thyroidectomy Vestibular Approach (TOETVA) aired on YouTube, which is the most popular video platform of the online world. Materials and Methods: We evaluated the first 50 videos, returned by the YouTube research engine, in reply to the "TOETVA" keyword. The popularity of the videos was assessed using the video power index (VPI). The educational quality, accuracy, and transparency of the content regarding TOETVA were estimated by using the DISCERN questionnaire score (DISCERNqs), Journal of American Medical Association benchmark criteria (JAMABC), and global quality score (GQSc). The technical quality was ranked through TOETVA Scoring System (TOETVA-SS) by a TOETVA practicioning endocrine surgeon. Results: The content of the videos were about surgical technique with a rate of 68%. According to sources, videos uploaded by physicians had significantly higher DISCERNqs, JAMABC, GQSc, and TOETVA-SS scores. Unlike, videos uploaded by physicians had a lower VPI than videos uploaded by nonmedical sources. The videos of surgical technique had significantly higher DISCERNqs, JAMABC, GQSc, and TOETVA-SS scores. Surgical technique videos also had higher VPI scores than "information about disease or surgery" videos. Also, negative correlations were found between the VPI (popularity index) and educational value (GQSc), transparency (JAMABC), and technical quality (TOETVA-SS) scores. Conclusions: The data acquired from YouTube videos regarding TOETVA is of below expected quality and reliability. Nevertheless, the educative potential of the online video platform, YouTube, cannot be underestimated.

INTRODUCTION To improve compliance with voiding diaries in children with primary monosymptomatic nocturnal enuresis (PMNE), a new modified 3-day weekend frequency-volume chart (FVC) was designed, and the compliance and validity of this modified FVC was evaluated by comparing with the International Children's Continence Society (ICCS) recommended voiding diary. METHODS A total of 1200 patients with PMNE were enrolled in the study from 13 centers in China and were randomly assigned to record this modified FVC or the ICCS-recommended voiding diary. The primary outcome measure was the compliance, assessed by comparing the completing index and the quality score of diaries between two groups. The secondary outcome measure was the validity, evaluated by comparing the constituent of subtypes, micturition parameters and response rate to desmopressin. RESULTS Among the 1200 participants enrolled in the study, 447 patients completed the ICCS-recommended voiding diary and 469 completed the modified diary. The diurnal completing index and the quality score of the modified FVC group were better than those of the ICCS group. In addition, there was no significant difference between these two groups in the subtype classification, or in the response rate to desmopressin. CONCLUSIONS The modified FVC could be applied to obtain the voiding characteristics of children with PMNE as the ICCS-recommended voiding diary does and offers a reasonable and better choice for children with PMNE from the unselected population in the future.

Aim To perform a systematic review of available mHealth apps for menstrual cycle monitoring in Brazil. Methods A search for menstrual cycle mHealth apps from the Google Play Store and AppStore in Brazil was performed by two independent reviewers on October 2020, and the quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS). Results Our review identified 2400 potentially relevant mHealth apps, of which 56 were eligible for inclusion. The majority of the apps offered tools to track menstruation symptoms (63%) and educational content for users (32%). The mean ( ±SD) MARS app quality score for the 28 evaluated apps in Android was 3.5 ± 0.6 on a 0-5 scale. For the 28 evaluated apps in iOS, the mean app quality score was 3.8 ± 0.4. Most of the included apps, for both systems, scored average for credibility, user interface, and engagement. Conclusion The majority of available tools in Brazil are of moderate quality and limited functionality for menstrual cycle monitoring. This study highlights the top three mHealth apps available on each online store for individuals seeking menstrual cycle monitoring options.

Background Expert elicitation (EE) has been used across disciplines to estimate input parameters for computational modeling research when information is sparse or conflictual. Objectives We conducted a systematic review to compare EE methods used to generate model input parameters in health research. Data Sources PubMed and Web of Science. Study Eligibility Modeling studies that reported the use of EE as the source for model input probabilities were included if they were published in English before June 2021 and reported health outcomes. Data Abstraction and Synthesis Studies were classified as “formal” EE methods if they explicitly reported details of their elicitation process. Those that stated use of expert opinion but provided limited information were classified as “indeterminate” methods. In both groups, we abstracted citation details, study design, modeling methodology, a description of elicited parameters, and elicitation methods. Comparisons were made between elicitation methods. Study Appraisal Studies that conducted a formal EE were appraised on the reporting quality of the EE. Quality appraisal was not conducted for studies of indeterminate methods. Results The search identified 1520 articles, of which 152 were included. Of the included studies, 40 were classified as formal EE and 112 as indeterminate methods. Most studies were cost-effectiveness analyses (77.6%). Forty-seven indeterminate method studies provided no information on methods for generating estimates. Among formal EEs, the average reporting quality score was 9 out of 16. Limitations Elicitations on nonhealth topics and those reported in the gray literature were not included. Conclusions We found poor reporting of EE methods used in modeling studies, making it difficult to discern meaningful differences in approaches. Improved quality standards for EEs would improve the validity and replicability of computational models. Highlights We find extensive use of expert elicitation for the development of model input parameters, but most studies do not provide adequate details of their elicitation methods. Lack of reporting hinders greater discussion of the merits and challenges of using expert elicitation for model input parameter development. There is a need to establish expert elicitation best practices and reporting guidelines.

Background With the improvement of therapeutic strategies from cytotoxic chemotherapy to immunotherapy, the possibility of achieving timely intervention for lung cancer has dramatically increased. This study aimed to systematically evaluate the reporting quality of randomized controlled trials (RCT) on immunotherapy in lung cancer. Methods The RCTs evaluating the efficacy of immunotherapy in lung cancer published up to 2021 were searched and collected from PUBMED and EMBASE by two investigators. The 2010 Consolidated Standards for Test Reports (CONSORT) statement‐based 28‐point overall quality score (OQS) and the 2001 CONSORT statement‐based 19‐point OQS was utilized for assessing the overall quality of each report. Results One hundred and fifty‐two related RCTs were retrieved in this study, including 81,931 patients. The average OQS in 2010 was 17.89 (range, 7.5–24.5). Overall, studies have sufficiently reported the eligibility criteria (143/152; 94.07%), described the scientific background (150/152; 98.7%) and discussed interventions (147/152; 96.7%). However, the RCTs did not consistently report the changes to trial after commencement (48/152; 31.6%), allocation, enrollment and assignment personnel (34/152; 22.4%), blinding (48/152; 31.6%), or randomization method (58/152; 38.2%). Conclusions The overall reporting quality of RCTs on immunotherapy in lung cancer was found to be unsatisfactory despite the fact that the CONSORT statement was issued more than a decade ago. Furthermore, there was virtual selectivity and heterogeneity in reporting some key issues in these trials. This is the first study to enlighten lung cancer researchers especially focusing on immunotherapy, and also to remind editors and peer reviewers to strengthen their due diligence., The 2010 Consolidated Standards for Test Reports (CONSORT) statement‐based 28‐point overall quality score (OQS) and the 2001 CONSORT statement‐based 19‐point OQS was utilized to assess the quality of randomized controlled trials (RCTs) on immunotherapy in lung cancer published in PUBMED and EMBASE, demonstrating an unsatisfactory overall reporting quality, enlightening lung cancer researchers to pay more attention to CONSORT projects when designing and reporting trials, and bringing up the necessity for editors and peer reviewers to be more scrutinizing and diligent for RCTs on immunotherapy in lung cancer.

Searching for information on the Internet, especially YouTubeTM, is gaining popularity for cancer survivors. Based on the topic of online health information, the importance of studies using YouTube data for various cancer types and treatment methods has increased. This study aims to investigate the quality, reliability, and accuracy of YouTube videos on cancer rehabilitation (CR). YouTube search was performed on February 26th, 2021, with two keyword sets: “cancer rehabilitation” and “oncology rehabilitation.” The modified DISCERN, the Journal of the American Medical Association (JAMA) scoring system, and the Global Quality Score (GQS) were used to evaluate the quality and reliability of the videos. The features of each video such as the number of likes, dislikes, and views, upload date, duration, like ratio, and the uploader profile were also collected. Fifty-three of the first 200 videos shown in the search results met the criteria. Most of the videos were low quality. The most common uploader profile was academic institute/university hospital. The three most common subjects in the videos were CR definition, physical therapy and occupational therapy, and patient experiences. The mean modified DISCERN, JAMA, and GQS scores were 2.14, 2.03, and 2.78, respectively. Higher quality videos had longer duration, greater number of views, and better reliability scores. The results showed that most of the rated videos were of low-quality and didn’t provide sufficient information on the topic discussed. Higher-quality and more accurate YouTube videos are needed to increase awareness of CR. For cancer survivors, CR-related YouTube video content often provides information of low reliability. In this context, it is necessary to focus on the production of video content that includes clinical guides, references, and are based on clinical-based practices.

Objectives: We aim was to evaluate the quality and reliability of the information on knee arthroplasty available on YouTube in Turkish. Methods: A systematic search was conducted using the term “diz protezi” (knee prosthesis) on 1 June 2020.Videos were filtered based on their degree of relevance alone. Videos that were not in Turkish, not on knee prosthesis or without audio and/or image were excluded. Copied videos were evaluated as a single video. The first 50 videos that came up in the search were included in the study. Video quality was scored using Global Quality Score (GQS). To assess reliability, modified DISCERN scale was used. Results: The mean view count per video was 31.533 ± 100.921 and the total view count was 1.576.633. The mean duration per video was 337 ± 475 seconds. The median number of likes per video was 13 (0-426). The median number of dislikes per video was 2.5 (0-83). The mean GQS of the videos was 3.25 ± 0.9. When the reliability of the sources was evaluated using DISCERN, the mean score of the videos was 2.18 ± 1.2. It is striking that all videos were prepared by an orthopedic surgeon. Of the medical doctors preparing the resources, 44% had academic titles. Conclusions: It was found that Turkish resources on arthroplasty on YouTube are promising in terms of quality. Content creators must make effort to increase their reliability according to DISCERN.

The commercial light field camera is able to capture four-dimensional Light Field Image (LFI), which can be visualized to LFI contents on 2D displays by means of the Pseudo Video (PV) or the Refocused Images (RIs) generated with the refocusing function of LFI. However, the quality degradation of LFI will affect user’s visual experience of LFI contents. Hence, it is crucial to develop an effective LFI quality assessment method to monitor the LFI quality. Most existing subjective databases of LFI use PV and RIs visualization techniques to assess the quality of LFI. Therefore, as the way of presenting LFI on 2D display, PV and RIs are closely related to the subjective perception of LFI by human eyes. Based on these two visualization techniques, this article proposes a novel PV and RIs based blind LFI quality assessment method, in which the feature extraction is divided into two parts. In the first part, the PV’s structure, motion and disparity information are extracted with multi-scale and multi-directional Shearlet transform. In the other part, the spatial structure, depth and semantic information of the RIs are obtained. Finally, support vector regression is used to nonlinear map the perceptual features to quality score of LFI. The experimental results on four LFI databases show that the proposed method has better correlation with human visual perception, compared with the classical 2D image quality assessment methods as well as the state-of-the-art LFI quality assessment methods.

Face quality assessment has grown into a necessary pre-requisite for better performance of the face recognition (FR) algorithm pipeline. In this work, we proposed a novel face quality assessment algorithm for face recognition algorithms. We named it simplified face quality assessment (SFQA) for its simple provision to be used in accompaniment with any FR algorithm. We first proposed a hashing based deep learning model for the prediction of face quality from the features of the corresponding FR algorithm. The last layer of the deep hash net gives binary bits as output which is then converted to the decimal value to get the face quality score (FQS) ranging between 0 and 100. The mutual quality of the probe and gallery images are mathematically clubbed to get the Face Quality Confidence Score (FQCS). We have experimentally shown the effects of FQCS on the recognition algorithm. We trained the prediction model using the FR algorithm for the quality estimation on the face images from CAS-PEAL, LFW, and QDF database. The performance of SFQA is found to outperform the state-of-the-art methods, as discussed in the paper.

The study aimed to analyze the visual quality of the Educational Institutions and their Surroundings (EITS) in the campus of Ataturk University in Erzurum city of Turkey. Visual Quality Analysis Questionnaire was applied to 74 students studying at the Faculty of Architecture and Design. The questionnaire consisted of 21 EITS. Results were analyzed using Variance and Duncan multiple comparison. It was determined that Faculty of Fishery (EITS13) had the highest visual quality score (3.243), followed by Agriculture Faculty (EITS1: 3.134) and the Divine Faculty (EITS2: 2.906). The Faculty of Veterinary Medicine had the lowest visual quality score (EITS11: 2.165), followed by High-Tech Research Centre (EITS20: 2.243) and Faculty of Law (EITS16: 2.315). Statistically significant relationship was found between the department of the students and the scores they gave to Sports Science Faculty (EITS1), Education Faculty (EITS4), Faculty of Medicine (EITS10), Faculty of Veterinary Medicine (EITS11), Faculty of Fine Arts and Tourism (EITS15), and Rectorate Building (EITS19). Among the Visual Quality Criteria (VQC) of EITS, accessibility to the structure (VQC12) was the most effective criterion (2.927, p

Objective quality assessment aims towards evaluating the perceptual quality of a signal using a machine-based algorithm. Due to different challenges involved in the subjective evaluation of speech quality, it is necessary to develop objective measures. The goal of any non-intrusive quality assessment metric for noise-suppressed speech is to assess the quality of a noise-suppressed signal in the absence of any clean reference signal. As per the ITU-T P.835 recommendations, the quality assessment of noise-suppressed speech involves predicting three quality scores, namely, signal quality, background quality, and overall quality score, and hence, considered in this study. In recent literature, the non-intrusive quality assessment problem is presented as a regression problem, in which the mapping between a set of acoustic features and corresponding quality scores is found using a perceptual model. Recently, we proposed the use of Deep Autoencoder (DAE) features and Subband Autoencoder (SBAE) features for acoustic representation and an Artificial Neural Network (ANN) as a regression model. DAE and SBAE are variants of autoencoder architecture that have bottleneck structure in the hidden layers. Such architecture represents the class of generalized nonlinear Principal Component Analysis (PCA) that guarantees reconstruction of the input features with arbitrary accuracy. Both the features (DAE and SBAE) are extracted using unsupervised deep learning architectures, and they demonstrated better performance than the state-of-the-art spectral feature set, namely, Mel Filterbank Energies (FBEs). In this paper, we present more detailed analysis of previously proposed features, i.e., DAE and SBAE features, and analyze the usefulness of these features in predicting signal as well as background quality scores in addition to the overall quality score. We compare the performance of all the three features with each other as well as with current ITU-T P.563 metric for non-intrusive speech quality assessment. The results of our experiments performed on NOIZEUS database suggest that DAE and SBAE features perform relatively better than the FBEs while predicting signal and overall quality. On the other hand, FBE features perform slightly better than the DAE and SBAE features in predicting the background quality. Moreover, another major contribution of this paper is that we employ an ANN to predict all the three quality scores simultaneously, and present the results. It was observed that using this approach, it is possible to predict all the three scores simultaneously with similar accuracy as that of predicting them individually.

Omnidirectional video quality assessment (OVQA) helps to evaluate the viewers’ visual experience and promotes the development of omnidirectional video. The perceived quality of omnidirectional video is affected not only by the video content and distortion, but also by the viewing directions of viewer’s preference. At present, there are some quality assessment methods for omnidirectional video, but most of them are full-reference (FR). Compared with the FR method, the no-reference (NR) method becomes more difficult due to the lack of the reference video. In this paper, a NR OVQA based on generative adversarial networks (GAN) is proposed, which is composed of the reference video generator and the quality score predictor. Generally, a reference image/video is distorted by some distortion types, and each distortion type has some distortion levels. To the best of our knowledge, there are some NR methods using GAN to generate the reference images/videos for quality assessment. In these methods, the reference images/videos is generated by GAN when the distorted images/videos, which are from a distortion type but with different distortion level, are input into the GAN. In order to achieve an accurate quality assessment, the generated reference images/videos, which are from a distortion type but with different distortion level, are expected to have as similar quality as possible with each other. However, the distorted images/videos are independent for GAN, and the GAN will generate a little different reference images/videos for these distorted images/videos. This issue is not considered in the existing GAN-based methods. To solve this issue, we introduced a level loss in OVQA. For the quality score predictor, as a further contribution of this paper, the viewing direction of the omnidirectional video is incorporated to guide the quality and weight regression. The publicly available dataset is used to evaluate the proposed method. The experimental results indicate the effectiveness of the proposed method.

The online question answering (QA) community has been popular in recent years. In this paper, we focus on the online health question answering (HQA) community. The HQA community provides a platform for health consumers to inquire about health information. There are two ways to use this platform. One is to post a question and wait for answers to be provided by authenticated doctors. The other is to search for relevant questions with answers. For the latter, health consumers may prefer an accepted answer marked by the previous health consumer. However, there is a large proportion of questions without an accepted answer and it is inconvenient for people who want to search for relevant questions. To address this issue, we aim to select high-quality answers from the answers without marked accepted answers. We propose a deep learning approach to achieve this goal. To train the model for the prediction of answer quality, we first view the accepted answer as the positive answer and propose a method to label the negative answer. Next, we capture the semantic information on the question and the answer by the deep learning structure. We then combine the information to predict the quality score of the answer. We collect data from one of the biggest Chinese HQA community and divide them into groups by the medical departments for detailed analysis. Finally, we conduct experiments to show the effectiveness of categorization and the labeling method. The results show that our approach outperforms other studies and we further research into the differences among the results of different categories.

The internet is widely used by the public to look for health-related information. The quality of information about shin guard characteristics and protective benefits is lacking. The objectives of this study are the folowing: (1) to summarise currently available knowledge on shin guards. (2) To assess the quality of websites presenting information pertinent to shin guards by using previously validated scoring systems. (3) To develop a novel scoring system to assess the accuracy of the content available online on shin guards. First, scientific knowledge about shin guards was developed by searching the scientific databases. Second, we identified eligible websites containing information about shin guard by searching the top 3 English search engines (Google, Yahoo! and Bing). Finally, to evaluate the websites, we searched peer-reviewed articles to identify appropriate scoring systems to assess the quality of health information on the internet. 25 Web sites were included; the mean overall score was 17.4 out of 35 (49.7%). The average quality score was 5.3 out of 15 (35.3%) and the average reliability score was 12.2 out of 20 (61%). Overall, most of the websites retrieved are of poor quality, with none of the websites’ total score reaching the threshold to be included in the “Excellent Category” and only one website was qualified to be added to the “very good category”. Our study suggests that there is paucity of websites available providing reliable and accurate information about shin guards.

Background: Parkinson’s disease (PD) is the most frequent movement disorder. Patients access YouTube, one of the largest video databases in the world, to retrieve health-related information increasingly often. Objective: We aimed to identify high-quality publishers, so-called “channels” that can be recommended to patients. We hypothesized that the number of views and the number of uploaded videos were indicators for the quality of the information given by a video on PD. Methods: YouTube was searched for 8 combinations of search terms that included “Parkinson” in German. For each term, the first 100 search results were analyzed for source, date of upload, number of views, numbers of likes and dislikes, and comments. The view ratio (views / day) and the likes ratio (likes * 100 / [likes + dislikes]) were determined to calculate the video popularity index (VPI). The global quality score (GQS) and title - content consistency index (TCCI) were assessed in a subset of videos. Results: Of 800 search results, 251 videos met the inclusion criteria. The number of views or the publisher category were not indicative of higher quality video content. The number of videos uploaded by a channel was the best indicator for the quality of video content. Conclusion: The quality of YouTube videos relevant for PD patients is increased in channels with a high number of videos on the topic. We identified three German channels that can be recommended to PD patients who prefer video over written content.

Introduction: An adolescent aggregate is an age group with a high rate of smartphone addiction. Poor sleep quality in adolescents is one of the negative effects resulting from smartphone addiction Objective: To analyse poor sleep quality differences among adolescents with smartphone addiction compared to those without Methods: Analytical observational design with a cross-sectional approach was used in this study, involving 165 secondary school students as the participants. Study variables include smartphone addiction and poor sleep quality. The instruments used for data collection are the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the Smartphone Addiction Scale: Short Version (SAS-SV). The statistical analysis performed was the Mann Whitney test. Results: The statistical test results obtained a p-value < alpha (0,000 < 0,05), which means at a 95% confidence level, there was a difference in the poor sleep quality score between adolescents with smartphone addiction compared to those without. Adolescents with smartphone addiction have higher poor sleep quality scores compared to adolescents without smartphone addiction. Conclusion: Adolescents should be able to limit the use of the smartphone according to their needs and minimise smartphone use before going to bed at night.

Aim: The aim of the study is to evaluate the quality and reliability of videos about Achilles tendon ruptures on YouTube.Material and Methods: The first 50 videos were included in the study by typing the keyword 'achilles tendon rupture' in the YouTube search tab. The videos were analyzed by two orthopedic surgeons. All videos were analyzed by length, number of views, number of likes, dislikes and source of the video. Global Quality score (score range: 1-5), Journal of the American Medical Association (0-4) and DISCERN (15-75) scoring systems were used to evaluate the quality of the videos. The data obtained were analyzed statistically according to these scoring systems. The Video Power Index (VPI) was used to evaluate the popularity of videos.Results: In this study, 50 videos were evaluated. According to the DISCERN score, five (10%) videos were excellent, ten (20%) videos were good, eight (16%) videos were medium, ten (20%) videos were poor and seventeen (34%) videos were observed to be very poor. Average DISCERN, JAMA and GQS of all videos evaluated were 38.85 ± 16.2 (16.5-66), 2.52 ± 0.64 (2-4), and 2.47 ± 1.34 (1-5), respectively. Avarage like ratio was 91.68 ± 14.79, view ratio was 59.99 ± 117 and Video Power Index was 56.98 ± 11.66 (0.01-736.79). There was a weak correlation between Video Power Index, DISCERN and Global Quality Scores, but not with the Journal of the American Medical Association score. (P = 0.22, 0.030, 0.940, cc = 0.330, 0.313, 0.11, respectively). Conclusion: The quality of YouTube videos related to Achilles tendon rupture is poor. Physicians can take online patient education to higher levels by highlighting less discussed topics in these videos.

In this paper, we present a system for automatic evaluation of the quality of a question paper. Question paper plays a major role in educational assessment. The quality of a question paper is crucial to fulfilling the purpose of the assessment. In many education sectors, question papers are prepared manually. A prior analysis of a question paper might help in finding the errors in the question paper, and better achieving the goals of the assessment. In this experiment, we focus on higher education in the technical domain. First, we conducted a student survey to identify the key factors that affect the quality of a question paper. The top factors we identified are question relevance, question difficulty, and time requirement. We explored the strategies to handle these factors and implemented them. We employ various concepts and techniques for the implementation. The system finally assigns a numerical quality score against these factors. The system is evaluated using a set of question papers collected from various sources. The experimental results show that the proposed system is quite promising.

Objectives To evaluate the effectiveness, quality and reliability of YouTube videos that address retinal detachment surgery as a source of information and education for patients. Methods Performing a YouTube search using the keyword ‘retinal detachment surgery for patients’, the first 100 videos in the search results were included in the study. The number of views, age, number of likes, number of dislikes, number of comments, length, upload source, country of origin, type (patient information and education, patient experience), and surgical technique described (pars plana vitrectomy, scleral buckling, pneumatic retinopexy) were recorded for all videos. The quality and accuracy of the information were evaluated by two independent ophthalmologists using the DISCERN, global quality and usefulness scoring systems. Results Of the top 100 videos, 77 met the inclusion criteria. When the videos were evaluated according to the source, 21 (27.3%) had been uploaded by physicians, 30 (39%) by private health institutions, 10 (13%) by health channels, eight (10.4%) by patients, seven (9.1%) by academia (university hospitals), and one (1.3%) by a pharmaceutical company. The mean DISCERN score was 53.36, the mean Global Quality score was 3.49, and the mean usefulness score was 3.86. There was a significant and strong correlation between the usefulness score and the global Quality and DISCERN scores. A significant and strong correlation was also found between the global quality score and the DISCERN score. Conclusion YouTube appears to be a platform with sufficiently informative videos in the area of retinal detachment surgery for patients. Healthcare professionals and professional and academic institutions should use this platform effectively to spread high quality information to patients and their families.

Purpose: This survey aimed to investigate quality of communicating design features for the construction of cobalt chromium removable partial dentures (RPDs) among dentists in Riyadh, Saudi Arabia. Materials and Methods: A survey of nine commercial dental laboratories located in Riyadh was carried out. In each visit, master casts for cobalt chromium RPDs and dentists’ prescriptions were examined. A quality score for the provided instructions was developed and ranged from 0 to 4. A zero score means that no instructions were sent from the dentist for the design of the RPD. A score of 4 means that instructions were provided for the design of four main elements of the RPD, i.e., shape of major connector, type of direct retainers, position of direct retainers, position of dental rests. Results: 162 dentists’ prescriptions for RPDs and related casts were assessed. The majority of RPD cases were designed by the dental technician alone (64.2%). Shape of the major connector was the most frequent element in dentists’ prescriptions (35.8%). The mean quality score of dentists’ instructions was 0.96 (sd=1.54). 18% of the provided instructions achieved quality score equal to 4. Prescriptions for Kennedy Class III cases achieved significantly higher mean quality score compared to Kennedy Class II cases (p

The latent fingerprint examiners often mark minutiae and perform a comparison of latent fingerprints with exemplar fingerprints of known identity. The interpretation of details in the fingerprints is often based on the proficiency of examiners. Different examiners discern fingerprint regions and details differently due to an unconscious choice of certain features driven by their experiences. In this study, we aim to draw inferences from the perceptual behavior by collecting eye gaze of examiners while they mark minutiae and perform comparison. The study shows the patterns observed across different forensic examiners and infers specific heuristics used by examiners to discern features. These practices could be inculcated back into an AFIS system to improve automated comparison and help train novice examiners. To draw inferences, novice and expert examiners perform latent to exemplar fingerprint comparison by following the ACE-V mechanism. During the comparison, examiners provide a value determination, quality score, and minutiae markup with respective confidences. 29 distinct examiners perform a total of 158 trials, where, the eye gaze is recorded simultaneously. Using the eye gaze fixation, we empirically find Regions of Interest (ROI) of examiners on the prints and utilize it towards developing an understanding of the search strategy.

YouTube is a common source of medical information for patients. This is the first study to assess the reliability and educational value of YouTube videos on neurotoxin procedures. YouTube.com was searched on June 15, 2020 using the keyword “Botox” or “neurotoxin.” A total of 100 videos were reviewed. Sixty-one videos met the inclusion criteria and were included in the final analysis. Video characteristics were noted, and a score was assigned to each video using the Journal of the American Medical Association (JAMA) benchmark criteria and the Global Quality Score (GQS) to measure source reliability and educational value, respectively. A total of 61 videos that met the inclusion criteria had an average length of 589 seconds (9 minutes and 49 seconds), 210,673 views, 5,295 likes, 318 dislikes, and 478 comments. A total of 30 videos (49%) were posted with an intention to educate patients while 31 videos (51%) were posted with the intention to detail a personal experience with neurotoxin. Patient education videos were significantly more reliable (P JAMA< 0.001) and had more educational value (P GQS Key Points

© 2021, The Author(s), under exclusive licence to Springer Nature Limited.Although YouTube video is one of the most widely used and easily accessible information sharing sources, its widespread use can carry the risk of spreading misleading and unreliable information. We aimed to evaluate the accuracy, reliability, quality, and content of the most viewed YouTube videos related to Peyronie’s disease treatment. The keywords of “penile curvature”, “penile deformity”, “bent penis” “curved penis”, and “Peyronie’s disease” were searched on YouTube. Among 700 YouTube videos, 267 videos were included in the study. They were categorized by two independent urologists with board certification as accurate information (n = 138, 51.7%) or inaccurate information (n = 129, 48.3%). Accurate videos contained information about the treatment of Peyronie’s disease with proven scientific accuracy according to the current guidelines, whereas inaccurate videos contained scientifically unproven or incorrect information and recommendations not in the guidelines. A 5-point modified DISCERN scale and Global Quality Score were used for reliability and quality assessment. Although the accurate information group had a significantly higher DISCERN Score (3, IQR = 3–4 vs. 1, IQR = 1–2, p

Through this paper, the authors expose “Red Herring” as a kind of logical fallacy used to change conversation topic caused by sensitive topics that attack someone’s face. The authors choose qualitative research design since format data is presented by words. Thus, the utterances in Big Little Lies novel by Liane Moriarty are selected as data. To collect the data, the authors applied a documentary study which covers document analysis and Focus Group Discussion (FGD). FGD is done by raters who have capability of translation studies and linguistics whose role is to recognize translation technique and assess translation qualities as well. There are 10 translation techniques that are used for “Red Herring.” Moreover, after the calculation, the results for translation qualities are as follows 2.96 (accuracy), 2.88 (acceptability), and 2.92 (readability). The translation technique that affects Red Herring’s quality score of accuracy is literal. Meanwhile, borrowing translation technique affects the acceptability and readability score. Although there are translation aspects whose scores are reduced due to translation techniques, its quality is still relatively good. It is because of the majority of translation techniques which are used do not have this impact.

Background The internet is a widely used source for obtaining medical information both by patients and physicians. YouTube is an essential source of information that may be a useful tool to inform the public and may improve the learning experience if used adequately. In this study, we aimed to estimate the quality and accuracy of videos about cardiopulmonary resuscitation videos aired on YouTube, which is the most popular video platform of the online world. Methods We included the first 100 videos, in English, returned by the YouTube search engine in response to “cardiopulmonary resuscitation” keyword query to the study. The popularity of the videos was evaluated with an index called the video power index. The educational quality, accuracy, and transparency of the visual content were measured using the DISCERN questionnaire (DISCERN), Journal of American Medical Association (JAMA-BC) benchmark criteria, and Global Quality Score (GQS). The technical quality was measured by the Cardiopulmonary Resuscitation Scoring System (CPR-SS), which was utilized by three bariatric surgeons. Results The source in 7% of the videos was medical doctors. The content in 89% of the videos was cardiopulmonary resuscitation technique. According to sources, videos uploaded by physicians had significantly higher quality, transparency, educational and technical value. Unlike, videos uploaded by physicians had a lower video power index than videos uploaded by non-medical professionals. Cardiopulmonary resuscitation technique videos had significantly higher quality, transparency, educational and technical value. Cardiopulmonary resuscitation technique videos also had higher popularity scores than “information or lecture” videos. Also, negative correlations were found between the (popularity index and transparency, education and technical quality scores. Conclusions Online information on cardiopulmonary resuscitation is of low quality, and its contents are of unknown source and accuracy. However, the educational potential of the online video platform, YouTube, cannot be neglected.

The aim of this study was to evaluate the content, reliability and quality of YouTube videos related to pelvic floor muscle exercise training. This study was carried out on the descriptive model in order to evaluate the content, reliability and quality of the videos on YouTube related to pelvic floor muscle exercise training. “Pelvic floor muscle exercise” was searched on YouTube in English in March 2020, and a total of 107 videos were watched. Quality Criteria for Consumer Health Information (DISCERN) survey was used to analyze the videos in terms of their reliabilities, and Global Quality Score (GQS) was used to evaluate their qualities. When the contents of 59 videos included in the study were examined, it was determined that 52 of them contained useful information and 7 of them contained misleading information. Comprehensiveness mean scores, DISCERN mean scores and GQS means of the useful videos were found to be statistically higher than that of the moderate and misleading videos (p

Evaluate quality and readability of online information for common rheumatologic diseases. Compare rheumatology patients' internet use and preferences to an objective evaluation of internet quality and readability. Five common rheumatologic diseases were searched on the web browser Google using English language. The first twenty websites from each of the five searches were evaluated for internet quality (e.g. content that is current, balanced, has specific aims, and is appropriately cited) using the DISCERN criteria and readability using the Flesch-Kincaid Grade Level (FKGL). The results were contrasted with a survey sent to patients with rheumatic disease. The survey measured patient likeliness to use and trust identified websites. Internet quality was similar (good) for all five diseases searched while readability was poor. There was an inverse relationship between internet quality and readability. Internet quality significantly differed across website sponsor, and readability significantly differed across disease and website sponsor. Common medical website sponsors with the highest combined quality and readability scores were Mayo Clinic and Web MD. Eight hundred and fifty-eight patients were sent a survey, of which 147 (17%) completed. Patients indicated they were most likely to use and trust a Mayo Clinic-sponsored website when compared to other common sponsored websites from our evaluation, followed by the American College of Rheumatology. Although we found good-quality information, all websites evaluated had readability levels above the recommended sixth-grade reading level. The website sponsor with the highest combined readability and quality score was also the most used and trusted by patients. Patients would like more information about credible and trusted websites from their medical providers.

Aim: YouTube is an essential source of medical information for patients, but may also be misleading, depending on the kind of content quality. The aim of this study is to evaluate the quality of YouTube videos on percutaneous transthoracic lung biopsy. Methods: A search on YouTube was performed with the terms ‘Lung Biopsy,’ ‘CT-Guided Lung Biopsy,’ ‘US-Guided Lung Biopsy,’ and ‘Percutaneous Transthoracic Biopsy.’ Relevant English videos were examined and scored by two reviewers. Video characteristics, uploaded sources, and content quality were assessed using different indices. Correlation analysis was conducted to investigate the possible correlation for global quality score. Results: Fifteen videos (47%) were uploaded by a healthcare professional, nine videos (28%) by a product company, six videos (19%) by an individual user, and 2 (6%) by an academic institution. The videos had a median (IQR) quality score of 2 (range 1-5), and a median (IQR) length of 235 (46-751) seconds. The quality of the videos varied, depending on the uploaded sources as well as whether they were uploaded by academic institutions, which had the highest quality. Some important components regarding the biopsy procedure, such as complications, were not evaluated in most videos. Conclusion: YouTube videos on percutaneous transthoracic lung biopsy (PTLB) had a low median content quality score, while some important points were grossly overlooked. Thus, YouTube videos may be a misleading source of patient information. Academic institutions and healthcare professionals should be creating accurate multimedia content for patients seeking informative medical information.

OBJECTIVEYouTube has become an important information source for pediatric neurosurgical patients and their families. The goal of this study was to determine whether the informative quality of videos of endoscopic third ventriculostomy (ETV) and endoscopic third ventriculostomy with choroid plexus cauterization (ETV + CPC) is associated with metrics of popularity.METHODSThis cross-sectional study used comprehensive search terms to identify videos pertaining to ETV and ETV + CPC presented on the first 3 pages of search results on YouTube. Two pediatric neurosurgeons, 1 neurosurgery resident, and 2 patient families independently reviewed the selected videos. Videos were assessed for overall informational quality by using a validated 5-point Global Quality Score (GQS) and compared to online metrics of popularity and engagement such as views, likes, likes/views ratio, comments/views ratio, and likes/dislikes ratio. Weighted kappa scores were used to measure agreement between video reviewers.RESULTSA total of 58 videos (47 on ETV, 7 on ETV + CPC, 4 on both) of 120 videos assessed met the inclusion criteria. Video styles included “technical” (62%), “lecture” (24%), “patient testimonial” (4%), and “other” (10%). In terms of GQS, substantial agreement was seen between surgeons (kappa 0.67 [95% CI 0.55, 0.80]) and excellent agreement was found between each surgeon and the neurosurgical resident (0.77 [95% CI 0.66, 0.88] and 0.89 [95% CI 0.82, 0.97]). Only fair to moderate agreement was seen between professionals and patient families, with weighted kappa scores ranging from 0.07 to 0.56. Academic lectures were more likely to be rated good or excellent (64% vs 0%, p < 0.001) versus surgical procedure and testimonial video types. There were significant associations between a better GQS and more likes (p = 0.01), views (p = 0.02), and the likes/dislikes ratio (p = 0.016). The likes/views ratio (p = 0.31) and comments/views ratio (p = 0.35) were not associated with GQS. The number of likes (p = 0.02), views (p = 0.03), and the likes/dislikes ratio (p = 0.015) were significantly associated with video style (highest for lecture-style videos).CONCLUSIONSMedical professionals tended to agree when assessing the overall quality of YouTube videos, but this agreement was not as strongly seen when compared to parental ratings. The online metrics of likes, views, and likes/dislikes ratio appear to predict quality. Neurosurgeons seeking to increase their online footprint via YouTube would be well advised to focus more on the academic lecture style because these were universally better rated.

BACKGROUND: Variability in the quality of stroke care is widespread. Identifying performance-based outlier hospitals based on quality indicators (QIs) has become a common practice. OBJECTIVES: To develop a tool for identifying performance-based outlier hospitals based on risk-adjusted adherence rates of process indicators. DESIGN: Hospitals were classified into five-level outliers based on the observed-to-expected ratio and P value. The composite quality score was derived by summation of the points for each indicator for each hospital, and associations between outlier status and outcomes were determined. PARTICIPANTS: Patients diagnosed with acute ischemic stroke, January 1, 2011–May 31, 2017. INTERVENTION: N/A MAIN OUTCOME MEASURES: Independence at discharge (the modified Rankin Scale = 0–2). KEY RESULTS: A total of 501,132 patients from 519 hospitals were identified. From 0.39 to 19.65% of hospitals were identified as high outliers according to various QIs. Composite quality scores ranged from − 20 to 16. Providers that were high outliers based on QI2, QI8, QI9, and QI11 had higher independent rates. For composite quality score, each point increase corresponded to an 8% increase in the odds of independent rate. CONCLUSION: Nationwide variation in the quality of acute stroke care exists at the hospital level. Variability in the quality of stroke care can be captured by our proposed quality score. Applying this quality score as a benchmarking tool could provide audit-level feedback to policymakers and hospitals to aid quality improvement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-020-05923-x) contains supplementary material, which is available to authorized users.

Objective This study sought to review and appraise Apple App Store applications (apps) designed for menstrual cycle tracking, ovulation prediction, and other topics related to fertility or the management of infertility. Methods The Apple App Store was systematically searched using the keywords “period tracker,” “menstrual tracker,” “fertility,” “ovulation,” “IVF,” and “in vitro fertilization.” Apps were downloaded after being screened against pre-defined inclusion criteria. Included apps were independently reviewed by two authors. Data were extracted, and an app quality score (AQS) was calculated according to a premade rubric. Apps were assessed on the basis of their general features, menstrual cycle tracking and prediction features, infertility-related features, and usability. Results A total of 140 apps were included in the final analysis, of which 90 (64.3%) were free. The average AQS was 32.5%. There was no significant difference in AQS between free and paid apps (31.5% vs. 34.2%; P = 0.491). A total of 62 (44.3%) apps made dynamic cycle predictions on the basis of cumulatively input data. Thirty-one apps (22.1%) contained serious inaccuracies in content, tools, or both. Only 25 apps (17.9%) contained information or functions specifically related to infertility or its management. Conclusion Some high-quality menstrual cycle tracking apps are available; however, many more are of low quality, and users should be wary of relying on their predictions to avoid pregnancy or to maximize chances of conception. Few apps specifically address the needs of patients struggling with infertility.

In recent years, people increasingly are accessing health information on the Internet. A significant percentage of the United States (US) population has limited English proficiency with Spanish being the most common other language spoken. There is limited research on the presence or quality of Spanish-language health information, particularly in genetics, on the Internet overall. Therefore, we aimed to assess the availability and quality of patient-specific education resources in Spanish available on US-based support group websites for a wide range of genetic conditions. We assessed 630 websites through the Disease InfoSearch website (www.diseaseinfosearch.org), created by Genetic Alliance, for the presence of Spanish genetic resources for patients with a new diagnosis of a genetic condition. Of these, 261 (41.4%) websites met study criteria for further evaluation. Of the 99 websites (37.9%) that had any Spanish content, 45 Spanish resources and a paired English resource from the same site met criteria for a quality assessment. Scoring was performed by two independent raters using Ensuring Quality Information for Patients (EQIP), a previously validated tool to assess the quality of written health information. The mean scores for Spanish and English resources were 57.3% and 58.4%, respectively, corresponding to a good quality score according to guidelines proposed by authors of EQIP. An independent two-sample t test showed no significant difference in the mean quality scores between Spanish and English resources (p-value = .506). Overall, we found limited availability of Spanish resources on the websites analyzed, but of those identified, there was no difference between the quality of Spanish resources and the paired English resources from the same site. These results highlight the need for genetics professionals to advocate for the creation of more Spanish patient resources. However, genetics professionals can have some reassurance that if a support group does produce a Spanish resource, it likely has comparable quality to its English equivalent.

The increasing availability of Internet as a health-care source causes both positive and negative effects on public health. Though reaching to information about diseases is faster and easier, the contents are not always correct and might be misleading. In our study, we aim to investigate the quality of YouTube™ videos on larynx cancer. A YouTube™ search by using terms “throat cancer” and “larynx cancer” was done and, after eliminating the irrelevant videos, the first 200 videos were evaluated by three authors on quality, content and usefulness by using a pre-developed questionnaire. Videos were categorized according to the type and uploader separately to two (testimonial and educational) and five groups (health care, university, individual users, television channel/news and undetermined), respectively. Videos that are uploaded by university-affiliated accounts have significantly better audiovisual quality score and have significantly higher accuracy and usefulness score results. Furthermore, the accuracy and usefulness scores of the educational group were found to be statistically higher than those of the testimonial group. Videos uploaded by universities and videos that are created for educational purposes are superior to other sources in terms of quality, accuracy and content. Patient information videos discussing common health problems should be prepared and disseminated only by universities or health-care institutions

The screen content (SC) pictures, such as webpages, serve as a visible and convenient medium to well-represent the Internet information, and therefore, the visual quality of SC pictures is highly significant and has attained a growing amount of attention. Accurate quality evaluation of SC pictures not only provides the fidelity of the conveyed information, but also contributes to the improvement of the user experience. In practical applications, a reliable estimation of SC pictures plays a considerably critical role for the optimization of the processing systems as the guidance. Based on these motivations, this paper proposes a novel method for precisely assessing the quality of SC pictures using very sparse reference information. Specifically, the proposed quality method separately extracts the macroscopic and microscopic structures, followed by comparing the differences of macroscopic and microscopic features between a pristine SC picture and its corrupted version to infer the overall quality score. By studying the feature histogram for dimensionality reduction, the proposed method merely requires two features as the reference information that can be exactly embedded in the file header with very few bits. Experiments manifest the superiority of our algorithm as compared with state-of-the-art relevant quality metrics when applied to the visual quality evaluation of SC pictures.

WHAT IS KNOWN AND OBJECTIVE Focusing on the tolerance and pharmacokinetics of new drugs, phase I clinical drug trials are characterized by high risk, poor compliance and management difficulties. High-quality clinical drug trials ensure subjects' safety while extending new drug research and development. Many studies have examined micro-level concerns of trial design and implementation rather than macro-level factors. Accordingly, we evaluated the quality of phase I clinical drug trials (trial quality) and analysed the influence of organizational management factors from a macro-level perspective. METHODS We surveyed staff at clinical trial institutions engaged in phase I clinical drug trials in China using convenience sampling. We employed a five-point Likert-scale questionnaire, comprising five items on phase I clinical drug trial quality and items on organizational management factors. Data from 604 questionnaires were analysed. We utilized a logistic regression model to estimate the influence of organizational management factors on trial quality, using individual demographic factors as controlling variables. RESULTS AND DISCUSSION The trial quality score was 3.81, which indicates that substantial improvement is required. Government regulation, industry management and medical institution management had a positive effect on trial quality: β = 0.842, 0.691 and 0.579, respectively; P

To evaluate the reliability and educational content of YouTube videos concerning the menisci.YouTube was queried using the keyword "meniscus." The first 50 videos were evaluated. Eleven video characteristics were extracted, and videos were categorized by source and content. 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; score range, 0-4) and a meniscus-specific score (MSS; score range, 0-20).The mean video duration was 551.44 ± 1,046.04 seconds (range, 75-7,282 seconds). The mean number of views was 288,597.7 ± 735,275.9. Collectively, the 50 videos accrued 14,141,285 views. The mean JAMA score, GQS, and MSS were 1.55, 2.12, and 3.67, respectively. The video source was predominately non-physician based (24.49% of source uploaders), whereas video content was predominately concerned with disease information (37.50% of content). Significant between-group effects were observed for the JAMA score and video content (P = .0155), with videos concerning disease information, exercise training, and nonsurgical intervention having the highest mean JAMA scores. Significant between-group effects were also observed for the JAMA score based on video upload source (P.001), with videos uploaded by physicians receiving the highest mean JAMA scores. The mean GQS and MSS were significantly greater for videos categorized as having disease-specific content (P = .0377 and P = .0404, respectively) and for physician video uploaders (P = .0133 and P = .0100, respectively). The number of video dislikes was a negative independent predictor of the JAMA score (β = -0.007, P = .003). Disease-specific content was a positive independent predictor of the GQS (β = 1.13, P = .042). There were no independent predictors of the MSS.Information on the meniscus found in YouTube videos is of low quality and reliability.Orthopaedic health practitioners should caution patients about the inaccuracy of YouTube videos regarding the meniscus given the low quality of content. These health care providers should make efforts to provide patients with higher-quality alternatives.

Introduction and objectives Bystander assistance is decisive to enhance the outcomes of out-of-hospital cardiac arrest. Despite an increasing number of basic life support (BLS) training methods, the most effective formula remains undefined. To identify a gold standard, we performed a systematic review describing reported BLS training methods for laypeople and analyzed their effectiveness. Methods We reviewed the MEDLINE database from January 2006 to July 2018 using predefined inclusion and exclusion criteria, considering all studies training adult laypeople in BLS and performing practical skill assessment. Two reviewers independently extracted data and evaluated the quality of the studies using the MERSQI (Medical Education Research Study Quality Instrument) scale. Results Of the 1263 studies identified, 27 were included. Most of them were nonrandomized controlled trials and the mean quality score was 13 out of 18, with substantial agreement between reviewers. The wide heterogeneity of contents, methods and assessment tools precluded pooling of data. Nevertheless, there was an apparent advantage of instructor-led methods, with feedback-supported hands-on practice, and retraining seemed to enhance retention. Training also improved attitudinal aspects. Conclusions While there were insufficiently consistent data to establish a gold standard, instructor-led formulas, hands-on training with feedback devices and frequent retraining seemed to yield better results. Further research on adult BLS training may need to seek standardized quality criteria and validated evaluation instruments to ensure consistency.

Virtual reality (VR) videos, especially 360-degree VR videos, have attracted substantial research interests with the explosion of mobile VR devices in recent years. In this work, we propose a VR quality of experience (QoE) evaluation framework including online, offline and mixed scenarios that can meet the requirement of real applications. Under this framework, we further develop a subjective evaluation method and an objective QoE evaluation model based on network transmission parameters. A VR panoramic video database is established with nine different contents. This database contains 468 different samples coming from nine original contents. Then, in the subjective evaluation part, we propose to adopt four dimensions, i.e., quality score, immersion score, non-spinning sensation score and global score for the subjective evaluation purpose. These dimensions can meet the interaction and immersion features of the VR video service. In the objective evaluation part, an improved two-step neural network (INN) model is developed by using the features of the physiological psychology and cognitive neurology. This model captures the intrinsic link between the initial input network parameters and the final perception in VR transmission. Our results suggest that the proposed INN can achieve a higher pearson correlation coefficients than the other methods. Especially, it increases by 8.9% than the traditional NN method. Our work can make up for the shortage of traditional evaluation methods in term of the VR QoE subjective and objective evaluation in transmission scopes.

Background The correct use of personal protective equipment (PPE) during the Covid-19 pandemic is mandatory to minimize the contagion risk. The current study aimed to evaluate quality information of YouTube™ videos on PPE use during the pandemic. Materials and methods Using Google™ Trend tool, the frequency of worldwide YouTube™ and Google™ searches for "donning and doffing" was examined. We queried YouTube™ with terms related to donning and doffing of PPE. Validated quality information assessment tools were used. Results From the 1st December 2019 to the 31st January 2021, according to YouTube™ and Google™ searches, both peaks occurred in April 2020 (69.5 and 72.0%,respectively). Of all videos, 144 were eligible for the analyses. According to misinformation tool, 90 (62.5%) videos contained inaccuracies. The median DISCERN Section 1 ranged from 3 to 5. The median DISCERN Section 3 was 4. According to Global Quality Score, 8.3% (n=12), 14.6% (n=21), 22.9% (n=33), 30.6% (n=44) and 23.6% (n=34) were classified as poor, partially poor, moderate, partially good and excellent quality videos, respectively. Conclusions Nowadays, YouTube™ may be recommended as a reliable source of information. Nevertheless, a not negligible number of videos contained inaccuracies. Future authors should improve videos contents to provide more complete information.

Purpose The purpose of this paper is to discuss how a mixed-methods approach to assessing student learning was used to determine the efficacy of redesigned library instructional spaces. Design/methodology/approach In 2017, the library at San Diego State remodeled a classroom to support active learning. The author undertook a pilot study to compare outcomes from the active learning classroom (ALC) and the traditional computer lab (CL) classroom. The assessment was done after one-shot library sessions for four sections of the same course in the ALC and the CL. Students completed surveys to assess their reactions to the instruction and e-mailed the librarian copies of the articles that they selected which were analyzed for quality using a rubric. Findings The mean scores from the CL classroom sections were slightly higher for the survey questions, though it was not statistically significant. The articles selected by students in the ALC had a slightly higher average quality score on the rubric, however, it was not large enough to be statistically significant. Research limitations/implications This was a limited assessment project and the results may not be generalizable to other institutions or types of instruction. Overall, students selected high-quality resources and felt positive about the library after instruction in both library classrooms. The data did not demonstrate significant improvements in student learning outcomes or attitudes in the remodeled ALC. Originality/value This mixed-methods assessment technique can be used to evaluate student learning and attitudes about the library and may be adapted by other librarians. It may also be of interest to those interested in designing learning spaces in libraries.

Background The internet has changed the way both physicians and patients search for health information. WebSurg® is a valuable source of information that informs surgeons about new technologies and techniques and aims to promote quality, safety, and patient-centered care. In this study, our aim is to evaluate the popularity, quality, transparency, and accuracy of videos about minimally invasive video-assisted parathyroidectomy (MIVAP). Materials and methods A total of 31 videos related to MIVAP returned by the WebSurg® search engine in response to the keywords “MIVAP”, “video assisted parathyroidectomy’’, and “minimally invasive parathyroidectomy’’ were included in this study. Videos were evaluated in terms of time since upload, run time, country, academic degree, and the number of views and likes. The popularity of videos was determined by the video power index (VPI) formula. The DISCERN questionnaire score (DISCERNqs), global quality score (GQSc), and Journal of American Medical Association benchmark criteria (JAMABC) scoring systems were used to analyze WebSurg® videos for reliability and quality. Results The academic degree of the members was MD in 90.32% of uploaded videos. Forty-eight point thirty-eight percent (48.38%) of the videos were uploaded by members from France. There was no significant difference between the DISCERNqs, JAMABC, GQSc, and MIVAP scoring system (MIVAP-SS) scores in terms of academic degree and country. A statistically significant negative correlation was found between the time since upload and the VPI score (r=-0.683, p

Some apps serve as assistive technologies or digital therapeutic tools that can be used by rehabilitation professionals in the motor disability context, bringing benefits to therapists and people with disabilities. However, websites or catalogs do not provide reliable information, easy search, and intuitive access to these apps, causing access information difficulties. Therefore, this work proposes to develop a digital catalog of software focused on motor disability. This work performed a systematic search of websites and catalogs related to motor disability, a systematic search of the apps that the digital catalog would show, and a quality evaluation of selected apps using the Mobile Application Rating Scale tool. The digital catalog was developed with the information obtained in the previous phases combining the Prototyping and User Experience criteria, then assessed by final users, software testers, and a web accessibility evaluation tool. The catalog obtained a satisfactory quality score based on the end-users’ and therapists’ satisfaction when finding technological resources to use in their professional and health-care activities. This research aims to contribute to those interested in developing software for people with disabilities and encouraging them to create and design their implementations based on this study. This work was supported by the EduTech project (609785-EPP-1-2019-1-ES-EPPKA2-CBHEJP) co-funded by the Erasmus+ Programme of the European Union.

BackgroundMore and more immune-oncology trials have been conducted for treating various cancers, yet it is unclear what the reporting quality of immune-oncology trials is,and characteristics associated with higher reporting quality.ObjectiveThis study aims to evaluate the reporting quality of immune-oncology trials.MethodsThe PubMed and Cochrane library were searched to identify all English publications of clinical trials assessing immunotherapy for cancer. Reporting quality of immune-oncology trials was evaluated by a quality score with 11 points derived from the Trial Reporting in Immuno-Oncology (TRIO) statement, which contained two parts: an efficacy score of 6 points and toxicity score of 5 point. Linear regression was used to identify characteristics associated with higher scores.ResultsOf the 10,169 studies screened, 298 immune-oncology trial reports were enrolled. The mean quality score, efficacy score, and toxicity score were 6.46, 3.61, and 2.85, respectively. The most common well-reported items were response evaluation criteria (96.0%) and toxicity grade (98.7%), followed by Kaplan-Meier survival analyses (80.5%). Treatment details beyond progression (12.8%) and toxicity onset time and duration (7.7%) were poorly reported. Multivariate regression revealed that higher impact factor (IF) (IF >20 vs. IF p < 0.001), specific tumor type (p = 0.018 for lung, p = 0.021 for urinary system, vs. pan cancer), and a certain kind of immune checkpoint blocking agent (p < 0.001 for anti-PD-1 or multiagents, vs. anti-CTLA-4) were independent predictors of higher-quality score. Similar independent predictive characteristics were revealed for high-efficacy score. Only IF >20 had a significant high-toxicity score (p < 0.001).ConclusionImmune-oncology trial reports presented an unsatisfied quality score, especially in the reporting of treatment details beyond progression and toxicity onset time and duration. High IF journals have better reporting quality. Future improvement of trial reporting was warranted to the benefit-risk assessment of immunotherapy.