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INTRODUCTION: Traditional methods for assessing movement quality rely on subjective standardized scales and clinical expertise. This limitation creates challenges for assessing patients with spinocerebellar ataxia (SCA), in whom changes in mobility can be subtle and varied. We hypothesized that a machine learning analytic system might complement traditional clinician-rated measures of gait. Our objective was to use a video-based assessment of gait dispersion to compare the effects of troriluzole with placebo on gait quality in adults with SCA. METHODS: Participants with SCA underwent gait assessment in a phase 3, double-blind, placebo-controlled trial of troriluzole (NCT03701399). Videos were processed through a deep learning pose extraction algorithm, followed by the estimation of a novel gait stability measure, the Pose Dispersion Index, quantifying the frame-by-frame symmetry, balance, and stability during natural and tandem walk tasks. The effects of troriluzole treatment were assessed in mixed linear models, participant-level grouping, and treatment group-by-visit week interaction adjusted for age, sex, baseline modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA), and time since diagnosis. RESULTS: From 218 randomized participants, 67 and 56 participants had interpretable videos of a tandem and natural walk attempt, respectively. At Week 48, individuals assigned to troriluzole exhibited significant (p = 0.010) improvement in tandem walk Pose Dispersion Index versus placebo {adjusted interaction coefficient: 0.584 [95% confidence interval (CI) 0.137 to 1.031]}. A similar, nonsignificant trend was observed in the natural walk assessment [coefficient: 1.198 (95% CI - 1.067 to 3.462)]. Further, lower baseline Pose Dispersion Index during the natural walk was significantly (p = 0.041) associated with a higher risk of subsequent falls [adjusted Poisson coefficient: - 0.356 [95% CI - 0.697 to - 0.014)]. CONCLUSION: Using this novel approach, troriluzole-treated subjects demonstrated improvement in gait as compared to placebo for the tandem walk. Machine learning applied to video-captured gait parameters can complement clinician-reported motor assessment in adults with SCA. The Pose Dispersion Index may enhance assessment in future research. TRIAL REGISTRATION-CLINICALTRIALS. GOV IDENTIFIER: NCT03701399.

Building on the embodied consumption literature, we draw on Merleau-Ponty's theory of art to consider how new modes of visibility arise in interactions between individuals online. Focusing on one particular virtual and collaborative museum programme, we use ethnomethodological analysis of interactions to analyse video recordings of virtual arts conversations. The analysis explores how participants render visible their orientation to each other and to the works of art discussed in the workshop. Thus, we can see how participants produce the sense and significance of works of art in, and through 'intercorporeal interactions' while participating in a virtual arts programme. Observations and findings from our research have significant implications for the strategic management of virtual consumer experiences. [ABSTRACT FROM AUTHOR]

The Timed Up-and-Go (TUG) test has been combined with different verbal/cognitive tasks (i.e., TUG dual task [TUGdt]) as a form of motor-cognitive testing. However, it is still unclear how different TUGdt conditions affect gait among older adults. Thirty community-dwelling older adults, with mean age of 73 years, participated in the study. Data were collected using marker-free video recordings. Gait parameters were extracted using a semiautomatic deep learning system. Comparisons of execution time and gait parameter outcomes were made under TUG and three types of TUGdt test conditions: TUGdt-naming animals, TUGdt-months backwards, and TUGdt-serial 7s. Statistical analyses were based on mean values of the gait parameters for each participant and TUG condition, including TUGdt gait cost, that is, the relative difference between TUGdt and TUG. All the investigated TUGdt conditions resulted in varying degrees of gait parameter changes. Under TUGdt conditions, participants took shorter and slower steps, with TUGdt-serial 7s causing the largest interference. [ABSTRACT FROM AUTHOR]

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ABSTRACT Introduction Method Results Conclusion This article explores the use of clinical vicarious learning dialogue videos as a learning resource for a written summative assessment.A prescribed list of 42 clinical vicarious learning dialogue videos was disseminated to students, and they were informed that these would form the scope of a prosthodontics question in their final year summative exam. The videos captured the learning dialogue between a teacher and student during diagnosis, problem‐solving or clinical decision‐making in relation to prosthodontic patient interactions. Exam questions were created from screen capture images from the videos based on and around the video content. After the exam, video analytics was captured, and students were invited for an interview using a question guide which was recorded and transcribed and a thematic analysis was performed using a deductive inductive approach.Fourteen students were interviewed, and from these three domains and 10 key themes were identified: learning: learning strategy, learning new skills and knowledge, learning clinical skills, application of learnt skills and engagement; assessment: exam scope and stress, clinical relevance, motivation, generalisable; and video as a learning medium: enjoyable, affordance. Students reported that using these videos facilitated and supported their exam preparations, stimulated learning new content as well as higher‐order thinking skills. Students reported they had applied skills learnt from the videos and broadened their cognitive skills and practical experience. The format of the assessment was described as enjoyable and reduced stress. All students reported they watched ‘all’ the videos which appeared to be supported by the analytics.Clinical vicarious learning dialogue videos were found to help learning, assessment literacy, clinical cognitive skills, stress and motivation for learning. [ABSTRACT FROM AUTHOR]

Demonstrating software early and responding to feedback is crucial in agile development. However, it is difficult for stakeholders who are not on‐site customers but end users, marketing people, or designers, and so forth to give feedback in an agile development environment. Successful graphical user interface (GUI) test executions can be documented and then demonstrated for feedback. In our new concept, GUI tests from behavior‐driven development (BDD) are recorded, augmented, and demonstrated as videos. A GUI test is divided into several GUI unit tests, which are specified in Gherkin, a semi‐structured natural language. For each GUI unit test, a video is generated during test execution. Test steps specified in Gherkin are traced and highlighted in the video. Stakeholders review these generated videos and provide feedback, for example, on misunderstandings of requirements or on inconsistencies. To evaluate the impact of videos in identifying inconsistencies, we asked 22 participants to identify inconsistencies between (1) given requirements in regular sentences and (2) demonstrated behaviors from videos with Gherkin specifications or from Gherkin specifications alone. Our results show that participants tend to identify more inconsistencies from demonstrated behaviors, which are not in accordance with given requirements. They tend to recognize inconsistencies more easily through videos than through Gherkin specifications alone. The types of inconsistency are threefold: The mentioned feature can be incorrectly implemented, not implemented, or an unspecified new feature. We use a fictitious example showing how this feedback helps a product owner and her team manage requirements. We conclude that GUI test videos can help stakeholders give feedback more effectively. By obtaining early feedback, inconsistencies can be resolved, thus contributing to higher stakeholder satisfaction. [ABSTRACT FROM AUTHOR]

Previous research highlights challenges in modelling teachers' reflective practice to explore and identify their beliefs and reflections. This paper explores how methodical triangulation, combining reflective dialogues and various reflective tools, enhances teachers' awareness of their beliefs and reflections. It facilitates a deeper exploration of teachers' beliefs and reflections related to learning and teaching. The study is based on a descriptive analysis of reflections generated in three different individual reflective dialogues with six lower secondary teachers. The findings indicate that triangulation strengthens the teachers' reflections, particularly through using visual reflection tools and the researcher as a "reflective catalyst'. This combination increases their awareness of their own beliefs and encourages reflection. [ABSTRACT FROM AUTHOR]

Objective: Digital technology has become increasingly relevant in physiotherapy, but little is known about communication and interaction in video-based physiotherapy. Therefore, this study aimed to explore the experiences among patients and physiotherapists, of communication and interaction in digital, video-based physiotherapy. Methods: A qualitative interview study with a phenomenological approach was conducted. Participants were purposively recruited from primary health care clinics. Semi-structured, in-depth interviews were conducted with 10 physiotherapists and 6 patients. Interviews were recorded, transcribed, and analyzed using a phenomenological approach. Results: The analysis resulted in the overall theme Reaching for connection, which captured the central meaning of the participants' experiences. Four categories emerged from the analysis: 1) Closeness at a distance; 2) Overcoming limited bodily communication; 3) The technology as part of the meeting; and 4) Challenging the physical meeting as a norm. The results suggest that communication and interaction in digital settings differ from physical settings, but there is an ongoing adaptation process to this new paradigm. Conclusions: The results of this study show that video-based physiotherapy, while having several benefits according to both patients and physiotherapists, affects the communication in several ways. Physiotherapists need to acknowledge these limitations and seek strategies to adapt and to compensate for the reduced non-verbal elements and lack of touch. Attention to the physical room and shifting between positions (face/full figure) are suggested practical strategies, but also to practice awareness and embodied communication to improve receptivity in the interaction. [ABSTRACT FROM AUTHOR]

Background: Video-recordings review of patient encounters is reported to improve the clinical performance of medical students. However, evidence on specific remediation strategies or outcomes are lacking. We aimed to implement videorecording-based remediation of standardized patient encounters among medical students, combined with preceptor one-on-one feedback or peer group discussion, and evaluate the effectiveness of the two remediation methods using objective structured clinical examination (OSCE). Methods: Following standardized patient encounters, 107 final-year medical students were divided into two groups based on different remediation methods of video review: (1) precepted video review with preceptor feedback (N = 55) and (2) private video review and subsequent peer group discussion under supervision (N = 52). All students underwent twelve-stations of OSCE both before and after the video review. Students' pre- and post-remediation OSCE scores, self-efficacy level in patient encounters, and level of educational satisfaction with each method were assessed and compared between different video-based remediation methods to evaluate their respective effects. Results: After remediation, the total and subcomponent OSCE scores, such as history taking, physical examination, and patient – physician interaction (PPI), among all students increased significantly. Post-remediation OSCE scores showed no significant difference between two remediation methods (preceptor module, 79.6 ± 4.3 vs. peer module, 79.4 ± 3.8 in the total OSCE score). Students' self-efficacy levels increased after remediation in both modules (both p-value <0.001), with no difference between the two modules. However, students' satisfaction level was higher in the preceptor module than in the peer module (80.1 ± 17.7 vs. 59.2 ± 25.1, p-value <0.001). Among students with poor baseline OSCE performance, a prominent increase in PPI scores was observed in the preceptor-based module. Conclusion: Video-based remediation of patient encounters, either through preceptor review with one-on-one feedback or through private review with peer discussion, was equally effective in improving the OSCE scores and self-efficacy levels of medical students. Underperforming students can benefit from precepted video reviews for building PPI. [ABSTRACT FROM AUTHOR]

This paper describes an Online Teaching Lab model that incorporates elements of lesson study and studio model for teacher learning. We focus on changes in design and facilitation decisions of two specific Online Teaching Labs and study differences in teachers' verbal and written responses to better understand how the process supports teacher learning. Middle grades mathematics teachers took part in the Online Teaching Labs. Data included video recordings of professional development team meetings, lesson implementation, Online Teaching Labsi and teachers' written work on 'Capture Sheets.' Data were analysed based on observable behaviours we intended participating teachers would enact. We found a relationship between the intentional changes facilitators made from the first to second Online Teaching Lab and teacher responses. Facilitators made more explicit mention of the learning goals, increased opportunities for teacher discussion, and included varied video clips. As compared to teachers in the first iteration, teachers in the second Online Teaching Lab more frequently identified teacher discourse moves related to engagement and cognitive demand of tasks and identified connections between teacher pedagogy, student strategies, and mathematical goals. The design, implementation, and outcomes are novel because the model includes features of lesson study and studio model through an online medium. [ABSTRACT FROM AUTHOR]

Interest is key to learning. Video is a promising tool for interest development in education, but professionals in education are in need of more theory-grounded guidance for production, selection, and use of videos. In previous studies, we developed and validated a model on film's interest raising mechanisms in educational contexts, called the FIRM model. In the qualitative study reported here, we used the model to explain how pupils' appraisals of video characteristics relate to their interest in the video. We evaluated the use of five videos in seven 12th-grade science and mathematics classrooms (177 pupils). We measured interest at scene level and grouped pupils on general interest. We performed video analyses, case studies (N = 5), and a cross-case analysis. Our findings resulted in three relationships between appraisals and interest, regarding the video's complexity level and the pupils' knowledge level, pupils' recognition of video categories, and pupils' expectations of videos. [ABSTRACT FROM AUTHOR]

This study utilizes satellite data collected through the Coastal Analyst System from Space Imagery Engine (CASSIE) tools to investigate the variability of coastal dynamics along the Benin coast over four decades. Recognizing the importance of continuous monitoring of coastal zones for effective adaptation to the impacts of climate change, the study employs CASSIE for automatic mapping and analysis of the shoreline. The study’s primary objective is to scrutinize coastal dynamics by assessing the rate of shoreline evolution from 1983 to 2023, evaluating erosion trends across the entire Benin coastal zone, and identifying specific hotspots along the coast. Shoreline data, based on Sentinel 2 and Landsat data, are evaluated using the CASSIE tool and a video camera system. It was found that the shoreline generated by CASSIE aligns with the range of values captured by the camera, indicating a strong correlation between shoreline changes captured by satellites and camera system data. The study reveals a significant erosion trend during the summer, especially in July and August, along the Benin coast. It notes substantial erosion in Grand Popo and Sèmè Podji, stable shoreline changes in Ouidah and Abomey-Calavi, and significant accretion in Cotonou, possibly due to the position of Cotonou Harbor. The study also records zones of very strong erosion on beaches adjacent to protection structures at Sèmè Podji, post the installation of the latest groynes. This comprehensive analysis offers valuable insights into Benin’s coastal dynamics, contributing to the formulation of effective strategies for management and mitigation of coastal erosion. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of digital platforms, the need for optimizing media representations to cater to various aspect ratios is palpable. In this paper, we pioneer an approach that utilizes object detection, scene detection, outlier detection, and interpolation for smart cropping. Using soccer as a case study, our primary goal is to capture the frame salience using object (player and ball) detection and tracking using AI models. To improve the object detection and tracking, we rely on scene understanding and explore various outlier detection and interpolation techniques. Our pipeline, called SmartCrop, is efficient, and supports various configurations for object tracking, interpolation, and outlier detection to find the best point-of-interest to be used as the cropping center of the video frame. An objective evaluation of the performance of individual pipeline components has validated our proposed architecture. Moreover, a crowdsourced subjective user study, assessing the alternative approaches for cropping from 16:9 to 1:1 and 9:16 aspect ratios, confirms that our proposed approach increases the end-user quality of experience. [ABSTRACT FROM AUTHOR]

We propose a method to reproduce dynamic appearance textures with space-stationary but time-varying visual statistics. While most previous work decomposes dynamic textures into static appearance and motion, we focus on dynamic appearance that results not from motion but variations of fundamental properties, such as rusting, decaying, melting, and weathering. To this end, we adopt the neural ordinary differential equation (ODE) to learn the underlying dynamics of appearance from a target exemplar. We simulate the ODE in two phases. At the "warm-up" phase, the ODE diffuses a random noise to an initial state. We then constrain the further evolution of this ODE to replicate the evolution of visual feature statistics in the exemplar during the generation phase. The particular innovation of this work is the neural ODE achieving both denoising and evolution for dynamics synthesis, with a proposed temporal training scheme. We study both relightable (BRDF) and non-relightable (RGB) appearance models. For both we introduce new pilot datasets, allowing, for the first time, to study such phenomena: For RGB we provide 22 dynamic textures acquired from free online sources; For BRDFs, we further acquire a dataset of 21 flash-lit videos of time-varying materials, enabled by a simple-to-construct setup. Our experiments show that our method consistently yields realistic and coherent results, whereas prior works falter under pronounced temporal appearance variations. A user study confirms our approach is preferred to previous work for such exemplars. [ABSTRACT FROM AUTHOR]

Performance Analysis (PA) is viewed as an integral feature of soccer; however, the processes underpinning such practice are often described as simple, linear procedures. This fails to acknowledge the dynamism of PA and given increased investment and employment of analysts in professional soccer, scrutiny of the current processes and duties associated with the role would seem timely. To this purpose, eight full-time analysts in the English Football League (EFL) and English National League (National League) participated in in-depth semi-structured interviews and transcripts were subjected to inductive reflective thematic analysis. The data analysis revealed two higher-order categories (Flying solo / Coach control) and four themes classified as lower-order (PA pragmatism / Identifying indicators / The reticent coach / Autocratic presentations). The findings of this study highlight that the responsibilities of the performance analyst range from acting on their own initiative to responding to requests and instructions from the coach. Subsequently, the responsibility for individual actions/activities related to PA is dependent on what aspects of analysis are to be used, who is the recipient of the data/video/presentation, when in the relationship between analyst and coach the activities are developed and when in the match-play process they are carried out. [ABSTRACT FROM AUTHOR]

Background: Telehealth has become increasingly essential in healthcare provision, also in the Prehospital Emergency Medical Services (EMS), where live video is implemented as a supplemental tool to assess and triage medical emergency calls. So far, using video for emergency calls seems beneficial for patient assessment and dispatcher-assisted first aid. However, the EMS dispatchers' experiences with and perceptions of using video during emergency calls are largely unexplored. Methods: In 2023, a nationwide survey study was conducted in Denmark, which is covered by five Emergency Medical Dispatch Centers. All Danish EMS dispatchers were invited to participate in the study. The survey explored the dispatchers' experience with using video during emergency calls, the perception of their own video use, and the process of implementing video as a new tool in their working procedure. Main questions were answered on a scale from 1 to 7, where higher scores indicate more agreement. Results: Of the 183 EMS dispatchers employed during the study period, 78% completed the survey. They found video easy to use (median = 7) and found video supportive in guidance and dispatch when the patient's problem was unclear (median = 7), but did not find video suitable for all emergency calls and expressed that complications with the technology was a barrier for using video. The EMS dispatchers were least likely to agree that they choose not to use video due to the risk of being emotionally affected by what they might see (median = 1). When dividing the sample based on EMS dispatcher's gender, age, seniority, and educational background, generally few differences between groups were found. Conclusions: Live video during emergency calls is generally experienced as a useful supplemental tool by EMS dispatchers in Denmark, and the greatest self-perceived barriers for using video were not finding video suitable for all situations and the technology. [ABSTRACT FROM AUTHOR]

AbstractDrawing on recent re-conceptualisations of the established concept of literacy events into literacy-as-events, this article furthers empirical and theoretical understandings of spatiality in classroom literacy. Using a socio-material approach, it investigates spatial formations of literacy-as-events in lower secondary education in new techno-scholastic environments, where the digital and the scholastic have become indiscernible from each other. The empirical material consists of video recordings from Swedish and Danish classrooms, using two cameras and screen-recordings of students’ screens. From a rich data material, three examples were selected for analysis, thinking with notions of spatial imaginaries and the metaphors of network, region, resonance and fluidity to investigate spatial formations as students work with literacy tasks. The analysis shows how literacy in these digitally rich classrooms becomes distributed over a range of distances in the physical classroom space, where we identify projector-laptop, student-laptop and through the screen formations as examples of spatial formations important for what it means to be a student in contemporary digitalized classrooms. The article highlights the importance of further discussions on how digital technology contributes both to new potentials for meaning-making, and to challenges related to managing a constant state of fluidity without reverting solely to traditional regulatory practices. [ABSTRACT FROM AUTHOR]

Based on electroencephalography (EEG) and video data, we propose a multimodal affective analysis approach in this study to examine the affective states of university students. This method is based on the findings of this investigation. The EEG signals and video data were obtained from 50 college students experiencing various emotional states, and then they were processed in great detail. The EEG signals are pre-processed to extract their multi-view characteristics. Additionally, the video data were processed by frame extraction, face detection, and convolutional neural network (CNN) operations to extract features. We take a feature splicing strategy to merge EEG and video data to produce a time series input to realize the fusion of multimodal features. This allows us to realize the fusion of multimodal features. In addition, we developed and trained a model for the classification of emotional states based on a long short-term memory network (LSTM). With the help of cross-validation, the experiments were carried out by dividing the dataset into a training set and a test set. The model's performance was evaluated with the help of four metrics: accuracy, precision, recall, and F1-score. When compared to the single-modal method of sentiment analysis, the results demonstrate that the multimodal approach, which combines EEG and video, demonstrates considerable advantages in terms of sentiment detection. Specifically, the accuracy obtained from the multimodal approach is significantly higher. As part of its investigation, the study also investigates the respective contributions of EEG and video aspects to emotion detection. It discovers that these features complement each other in a variety of emotional states and have the potential to improve the overall recognition results. The multimodal sentiment analysis method that is based on LSTM offers a high level of accuracy and robustness when it comes to recognizing the affective states of college students. This is especially essential for enhancing the quality of education and providing support for mental health. [ABSTRACT FROM AUTHOR]

SUMMARY: Following the COVID-19 pandemic, assessments by video link became a standard and acceptable form of medico-legal evaluation. The various challenges to achieving an accurate and robust medico-legal assessment via a remote platform are explored in this clinical reflection. It is concluded that any limitations to a remotely undertaken assessment must be highlighted to the court and an in-person assessment considered as a reasonable alternative in some cases. [ABSTRACT FROM AUTHOR]

• Training in dementia-capable care for nursing assistants and allied health workers in hospital settings remains a significant challenge. • The main objective of the current study was to ascertain the efficacy of a newly developed online dementia training and certification program for hospital staff, the CARES® Dementia 5-Step Method for Hospitals™ Online Training and Certification Program. • Results found that hospital staff who completed the online training and certification indicated more significant increases in sense of competence, approaches to dementia, and patient care than controls who did not receive the online training. • The online training and certification program, the CARES® Dementia 5-Step Method for Hospitals,™ has the potential to serve as a dynamic resource for hospitals nationwide to update training and share experiences, perspectives, and resources. The main objective of the current study was to ascertain the efficacy of a newly developed online, video-based dementia training and certification program for hospital staff, the CARES® Dementia 5-Step Method for Hospitals™ Online Training and Certification Program. A parallel randomized waitlist control design was utilized. Participants (N = 272) completed online pre-evaluation measures. Forty-five days after completion of CARES® (treatment) or pre-evaluation measures (control), participants completed a post-evaluation online assessment. Analyses of variance found that participants in the treatment condition indicated greater and statistically significant (p <.001) increases in sense of competence, approaches to dementia, and patient care. The results implied that the CARES® Dementia 5-Step Method for Hospitals™ program could serve as a dynamic resource for hospitals nationwide to update training and share experiences, perspectives, and resources. The inherent scalability of the program regarding its acceptability, feasibility, and potential to incorporate seamlessly into routine workflows and staff training suggests high implementation potential. [ABSTRACT FROM AUTHOR]

Background/Objectives: The COVID-19 pandemic reduced in-person pediatric visits in the United States by over 50%, while telehealth visits increased significantly. The national use of telehealth for children and the factors influencing their use have been rarely studied. This study aimed to investigate the prevalence of telehealth use during the COVID-19 pandemic and explore the potential factors linked to its use at the state level. Methods: A cross-sectional study of the National Survey of Children's Health (2021–22) sponsored by the federal Maternal and Child Health Bureau was performed. We used the least absolute shrinkage and selection operator (LASSO) regression to predict telehealth use during the pandemic. A bar map showing the significant factors from the multivariable regression was created. Results: Of the 101,136 children, 15.25% reported using telehealth visits due to COVID-19, and 3.67% reported using telehealth visits due to other health reasons. The Northeast states showed the highest telehealth use due to COVID-19. In the Midwest and Southern states, children had a lower prevalence of telehealth visits due to other health reasons. The LASSO regressions demonstrated that telehealth visits were associated with age, insurance type, household income, usual source of pediatric preventive care, perceived child health, blood disorders, allergy, brain injury, seizure, ADHD, anxiety, depression, and special needs. Conclusions: This study demonstrated significant variability in the use of telehealth among states during the COVID-19 pandemic. Understanding who uses telehealth and why, as well as identifying access barriers, helps maximize telehealth potential and improve healthcare outcomes for all. [ABSTRACT FROM AUTHOR]

Movies have the ability to trigger our emotions and affect us in powerful ways. But the impact is not the same among all the audience and, according to our results, also not between women and men. In this study, we used an electroencephalogram (EEG) to register the brain activity of a group of 30 students while they watched a violent scene. The results showed that both male and female groups activated the left temporal lobe. However, the female group also activated the left insula and orbitofrontal areas of both hemispheres. The results of Hotelling's T-squared distribution also showed significant differences in occipital areas of the brain in favour of women. Thus, our findings evidence that the violent scene activated emotional areas in both male and female groups, but in women there was also an activation of brain areas related to shape and colour recognition and to cognitive processes. [ABSTRACT FROM AUTHOR]

Background: Trauma is one of the leading causes of mortality worldwide, and online platforms have become essential sources of information for trauma management. YouTube can play a significant role in helping people access medical information. Methods: YouTube was searched using the keywords management of trauma and assessment of trauma to identify relevant videos. Two authors independently evaluated the videos according to the ATLS (10th edition) guidelines, the modified DISCERN (m‐DISCERN) scale, and the Global Quality Scale (GQS) criteria. The videos that met the study criteria were evaluated based on the provider, video length, and view count. Results: Out of 939 videos, 667 were excluded resulting in 272 videos included in the study. According to the ATLS (10th edition) guidelines, the median score for videos was 8 (IQR 7‐8). Videos uploaded by official institutions and healthcare professionals received higher scores than from uncertain sources (p = 0.003). According to the GQS, 86% of the videos were low or moderate quality; uncertain sources uploaded 78% of low‐quality videos. Conclusion: YouTube is an information source about trauma management that contains videos of varying quality and has a broad audience. Official institutions and healthcare professionals should be aware of this evolving technology and publish up‐to‐date, accurate content to increase awareness about trauma management and help patients distinguish helpful information from misleading content. [ABSTRACT FROM AUTHOR]

Background: Induction of labor (IOL) is common with one in four labors being induced in the United States (US). IOL has been associated with lower birth satisfaction. Video education can address gaps in education and promote anticipatory guidance. Prior studies in obstetrics have focused on randomized designs in English-speaking patients, leaving opportunities to explore how these tools perform in a pragmatic fashion with diverse patient populations. Our objective was to evaluate the effects of a video education tool on patient satisfaction and knowledge of IOL experience in English and Spanish-speaking patients scheduled for IOL at a tertiary care hospital. Methods: This was a single site pragmatic implementation of a quality improvement measure at an academic hospital. A bilingual survey was developed to evaluate the impact of an educational video on birth satisfaction and knowledge of IOL procedures. The video is freely available in English and Spanish. Baseline postpartum surveys were collected from June to July 2021. The video was subsequently recommended by providers when scheduling IOLs. Post-intervention surveys were collected from September to November 2021 after an implementation period. Groups were compared using t-tests for satisfaction scores and chi-square analyses for categorical variables. Results: Thirty-two participants completed the baseline survey and 72 completed the post-implementation survey with response rates of 88.9% and 91.1%, respectively. There were no statistically significant changes between mean total satisfaction scores (26.9 vs 28.0 out of 40.0, p = 0.290). 61 participants were English speaking (58%) and 43 Spanish (42%). Thirty (42%) patients reported watching the video. Correct identification of amniotomy use improved in the post-intervention group (p = 0.002). No changes were seen in anticipated duration of labor nor in whether patients would choose to be induced again. Conclusions: Recommendation of video education before scheduled IOL was associated with little improvement in knowledge about IOL, but no significant improvement in patient satisfaction. While video education has improved these measures in randomized trials, our study demonstrated that real-world implementation and patient uptake may be initially difficult. This study may help providers emphasize direct education and counseling and promote optimal implementation of innovative educational media. [ABSTRACT FROM AUTHOR]

Amorphous films are formed on substrates at room temperature in the process of anodic oxidation of niobium foil. The studies were carried out using methods of electron diffraction and "in situ" transmission electron microscopy (TEM) with video recording of structural changes. It was found that electron beam irradiation of the film with a dose rate (4–7)·104 e−/Å2·s inside the column of the electron microscope causes its layer polymorphous crystallization (LPC) with the formation of Nb2O5 crystals with hexagonal lattice. The dimensionless parameter of the relative crystallization length δ0≈ 5000 − 7000. The dependence on time of the crystal diameter is described by a power function with exponents of 1.55, 1.1 and 1.3. According to this the dependence of the fraction of the crystalline phase on time is described by a power function with exponents of 3.1, 2.2 and 2.6. This non-quadratic nature is explained with the formation of a domain superstructure in the low-temperature modification of α-Nb2O5 and phenomenon of polyamorphism in amorphous films. [ABSTRACT FROM AUTHOR]

Background & purpose: Tremor is a common movement disorder diagnosed employing electrophysiological methods. Today, machine learning (ML) algorithms can efficiently analyze image-based data. Thus, we subjected the dynamics of essential tremor (ET) to video-based analysis. Methods: We enrolled 59 ET patients and 48 age-matched normal controls. The Clinical Rating Scale for Tremor was used to score tremors. All subjects used a smartphone to record an image designed especially for this study while both stationary and in motion. The trajectories were divided into lower bandpass-filtered and bandpass-filtered (BPF) groups based on the frequency. We extracted seven trajectory features, including the angle, velocity, homogeneity, pitch, power, entropy, and cosine. We used Student's t-test to compare the features of the ET patients and normal controls. A Random Forest model was employed to rank feature importance. Five ML models (random forest, k-nearest neighbors, support vector machine, decision tree, and multi-layer perceptron) were applied to estimate diagnostic accuracy. Results: Significant differences in most of the features of the BPF signals were evident between the two groups. The velocity and homogeneity of the BPF trajectory were highest in the stationary and motion phases, respectively. The highest accuracy levels in the stationary, motion, and combined phases for predicting ET were 0.901, 0.757, and 0.892, respectively. Conclusions: Features of ET tremor were evident in image-based data, enabling analysis of the tremor dynamics. ML analyses distinguished ET subjects from normal controls; however, more research is needed. [ABSTRACT FROM AUTHOR]

The present research aimed to determine the use and acceptance of video in the self-creation of assignments or evidence of learning as a strategy to mitigate plagiarism. This research adopted a mixed design, with an experimental, exploratory, and descriptive scope that reflects an innovative approach to meet this challenge. A non-probabilistic sample was considered, comprised of students in their first semester of higher education in the subject of Introduction to Programming at a public university in Mexico. The participants were divided into an intervention group and a control group. The acceptance of the use of the implemented strategy was evaluated using the Technology Acceptance Model and the results revealed the viability and usefulness of the strategy since the students in the intervention group stood out in the creation of their assignments compared to the control group. There was a positive and strong relationship between academic performance and the perceived usefulness of the strategy. We conclude by emphasizing the importance of teachers promoting the active role of students in the development of their work, to promote authentic learning and guarantee educational quality. [ABSTRACT FROM AUTHOR]

With an increasing number of videos integrating instructor's visuals on screen, we know little about the impacts of this design on mind wandering. The study aims to investigate a) how instructor visibility impacts mind wandering; b) the relationship between mind wandering and retention performance; c) how visual behaviour during video-watching influences mind wandering. Each participant watched a video with or without instructor visibility, while their visual behaviour was recorded by an eye tracker. Retention performance was measured at the completion of the video. Mind wandering was inferred via global self-report measure and objective eye tracking measure. Both measures of mind wandering indicated the instructor visible video resulted in less mind wandering. Findings suggested mind wandering impaired retention performance. Additionally, visual attention to the instructor was associated with less mind wandering. [ABSTRACT FROM AUTHOR]

I have lived with chronic back pain for over 20 years. My experience has shown me that my relationship to pain can resonate with what it means to relate with wider ecological pain. I reflect on Pain and I —my autobiographical dance performance that explores the rich complexities of chronic pain and asks "what can pain teach us"? I explore what chronic pain experience can reveal about having a process with pain and staying "with the trouble" of our "wounded Earth." I draw on autoethnographic poetry, performance text, pain theory, and ecological philosophy. [ABSTRACT FROM AUTHOR]

Research in machine learning (ML) algorithms using natural behavior (i.e., text, audio, and video data) suggests that these techniques could contribute to personalization in psychology and psychiatry. However, a systematic review of the current state of the art is missing. Moreover, individual studies often target ML experts who may overlook potential clinical implications of their findings. In a narrative accessible to mental health professionals, we present a systematic review conducted in 5 psychology and 2 computer science databases. We included 128 studies that assessed the predictive power of ML algorithms using text, audio, and/or video data in the prediction of anxiety and posttraumatic stress disorder. Most studies (n = 87) were aimed at predicting anxiety, while the remainder (n = 41) focused on posttraumatic stress disorder. They were mostly published since 2019 in computer science journals and tested algorithms using text (n = 72) as opposed to audio or video. Studies focused mainly on general populations (n = 92) and less on laboratory experiments (n = 23) or clinical populations (n = 13). Methodological quality varied, as did reported metrics of the predictive power, hampering comparison across studies. Two-thirds of studies, which focused on both disorders, reported acceptable to very good predictive power (including high-quality studies only). The results of 33 studies were uninterpretable, mainly due to missing information. Research into ML algorithms using natural behavior is in its infancy but shows potential to contribute to diagnostics of mental disorders, such as anxiety and posttraumatic stress disorder, in the future if standardization of methods, reporting of results, and research in clinical populations are improved. [ABSTRACT FROM AUTHOR]

YouTube is one of the primary platforms for the creation and distribution of audiovisual content. Consequently, brands leverage its potential for the dissemination of branded content projects. This paper examines the case of BBVA's "Aprendemos juntos" ("Learning Together"), whose YouTube channel boasts over four million subscribers. The research objectives are to characterize the distribution model and analyse the content to identify its key elements, delving into the fundamental principles of branded content. In order to achieve this objective, a methodology has been devised which employs a quantitative analysis of the channel's videos between 2019 and 2023, in addition to a content analysis of the most significant pieces. [ABSTRACT FROM AUTHOR]

Objective: To investigate the consistency of Chatbot Generative Pretrained Transformer (ChatGPT)‐4 in the analysis of clinical pictures of common laryngological conditions. Study Design: Prospective uncontrolled study. Setting: Multicenter study. Methods: Patient history and clinical videolaryngostroboscopic images were presented to ChatGPT‐4 for differential diagnoses, management, and treatment(s). ChatGPT‐4 responses were assessed by 3 blinded laryngologists with the artificial intelligence performance instrument (AIPI). The complexity of cases and the consistency between practitioners and ChatGPT‐4 for interpreting clinical images were evaluated with a 5‐point Likert Scale. The intraclass correlation coefficient (ICC) was used to measure the strength of interrater agreement. Results: Forty patients with a mean complexity score of 2.60 ± 1.15. were included. The mean consistency score for ChatGPT‐4 image interpretation was 2.46 ± 1.42. ChatGPT‐4 perfectly analyzed the clinical images in 6 cases (15%; 5/5), while the consistency between GPT‐4 and judges was high in 5 cases (12.5%; 4/5). Judges reported an ICC of 0.965 for the consistency score (P =.001). ChatGPT‐4 erroneously documented vocal fold irregularity (mass or lesion), glottic insufficiency, and vocal cord paralysis in 21 (52.5%), 2 (0.05%), and 5 (12.5%) cases, respectively. ChatGPT‐4 and practitioners indicated 153 and 63 additional examinations, respectively (P =.001). The ChatGPT‐4 primary diagnosis was correct in 20.0% to 25.0% of cases. The clinical image consistency score was significantly associated with the AIPI score (rs = 0.830; P =.001). Conclusion: The ChatGPT‐4 is more efficient in primary diagnosis, rather than in the image analysis, selecting the most adequate additional examinations and treatments. [ABSTRACT FROM AUTHOR]

Purpose: Commonly employed in polyp segmentation, single-image UNet architectures lack the temporal insight clinicians gain from video data in diagnosing polyps. To mirror clinical practices more faithfully, our proposed solution, PolypNextLSTM, leverages video-based deep learning, harnessing temporal information for superior segmentation performance with least parameter overhead, making it possibly suitable for edge devices. Methods: PolypNextLSTM employs a UNet-like structure with ConvNext-Tiny as its backbone, strategically omitting the last two layers to reduce parameter overhead. Our temporal fusion module, a Convolutional Long Short Term Memory (ConvLSTM), effectively exploits temporal features. Our primary novelty lies in PolypNextLSTM, which stands out as the leanest in parameters and the fastest model, surpassing the performance of five state-of-the-art image and video-based deep learning models. The evaluation of the SUN-SEG dataset spans easy-to-detect and hard-to-detect polyp scenarios, along with videos containing challenging artefacts like fast motion and occlusion. Results: Comparison against 5 image-based and 5 video-based models demonstrates PolypNextLSTM's superiority, achieving a Dice score of 0.7898 on the hard-to-detect polyp test set, surpassing image-based PraNet (0.7519) and video-based PNS+ (0.7486). Notably, our model excels in videos featuring complex artefacts such as ghosting and occlusion. Conclusion: PolypNextLSTM, integrating pruned ConvNext-Tiny with ConvLSTM for temporal fusion, not only exhibits superior segmentation performance but also maintains the highest frames per speed among evaluated models. Code can be found here: https://github.com/mtec-tuhh/PolypNextLSTM. [ABSTRACT FROM AUTHOR]

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acibadem Saglik Bilimleri Dergisi is the property of Acibadem University Medical School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Induction of labor (IOL) is common with one in four labors being induced in the United States (US). IOL has been associated with lower birth satisfaction. Video education can address gaps in education and promote anticipatory guidance. Prior studies in obstetrics have focused on randomized designs in English-speaking patients, leaving opportunities to explore how these tools perform in a pragmatic fashion with diverse patient populations. Our objective was to evaluate the effects of a video education tool on patient satisfaction and knowledge of IOL experience in English and Spanish-speaking patients scheduled for IOL at a tertiary care hospital. Methods This was a single site pragmatic implementation of a quality improvement measure at an academic hospital. A bilingual survey was developed to evaluate the impact of an educational video on birth satisfaction and knowledge of IOL procedures. The video is freely available in English and Spanish. Baseline postpartum surveys were collected from June to July 2021. The video was subsequently recommended by providers when scheduling IOLs. Post-intervention surveys were collected from September to November 2021 after an implementation period. Groups were compared using t-tests for satisfaction scores and chi-square analyses for categorical variables. Results Thirty-two participants completed the baseline survey and 72 completed the post-implementation survey with response rates of 88.9% and 91.1%, respectively. There were no statistically significant changes between mean total satisfaction scores (26.9 vs 28.0 out of 40.0, p = 0.290). 61 participants were English speaking (58%) and 43 Spanish (42%). Thirty (42%) patients reported watching the video. Correct identification of amniotomy use improved in the post-intervention group (p = 0.002). No changes were seen in anticipated duration of labor nor in whether patients would choose to be induced again. Conclusions Recommendation of video education before scheduled IOL was associated with little improvement in knowledge about IOL, but no significant improvement in patient satisfaction. While video education has improved these measures in randomized trials, our study demonstrated that real-world implementation and patient uptake may be initially difficult. This study may help providers emphasize direct education and counseling and promote optimal implementation of innovative educational media.

Purpose: Mental rehearsal is commonly employed, with positive visualization proposed to enhance complex skill performance. Additionally, video stimulus has been associated with enhanced kinesthetic sensations and rapid hormone fluctuations that may contribute to enhancing mental rehearsal and the conscious and unconscious emotional state for skill execution. Here, we assessed the impact of a 15-minute mental rehearsal intervention on rugby-specific tasks and the associated hormone profile. Methods: Professional rugby players (N = 10) volunteered for a randomized crossover study. They completed three 15-minute preparatory phases (positive or negative video-guided mental rehearsal or self-directed mental rehearsal alone) prior to an exercise stressor and rugby-specific passing task. Salivary testosterone and cortisol were monitored to assess stress responses. Results: Performance during the rugby passing task was improved following the positive video condition (91% [7.4%]) compared to the negative video (79% [6.0%]; ES: 1.22 ± 0.75) and self-visualization (86% [5.8%]; ES: 0.58 ± 0.75), with a significant correlation observed between passing performance and salivary testosterone (r =.47 ±.34, P =.0087). Positive video imagery prior to an exercise stressor also significantly enhanced physiological stress resilience (r =.39 ±.36, P =.0352). Conclusions: This pilot study demonstrates that mental rehearsal was enhanced by appropriate, context-specific video presentation. We propose that the interaction between sex steroids, the adrenal axis, and subsequent conscious and unconscious behaviors may be relevant to competitive rugby. Specifically, we suggest that relatively elevated free testosterone imparts a degree of stress resilience, which may lead to enhanced expression of competitive behaviors and provide an enhanced state for rugby skill execution. [ABSTRACT FROM AUTHOR]

Research focusing on social media usage in sport communication and its related media has made significant strides in the last 2 decades. Researchers have provided key insights into how social media content is created by sport entities and media members, how sport fans and consumers feel about social media content, and how aspects of social media content inform public perception of matters pertaining to race, gender, ethnicity, politics, and other key cultural areas. However, the changing natures of social media technology and user preferences for content have often moved faster than the body of research surrounding them. This commentary highlights a gap in published sport communication studies focusing on dynamic social media content and provides suggestions for addressing a key present, and future, need for scholarly inquiry in the field. [ABSTRACT FROM AUTHOR]

Video has become a widespread tool for capturing naturalistic behavioral data. While mixed methods show great potential in understanding the active nature of children's interaction, only a few studies have developed mixed methods for video-based interaction research. This paper presents a mixed methods embodied interaction model appropriate for studying complex embodied interaction and draws on methodological insights from a mixed methods project to capture changes in children's interaction with touchscreen technologies. The paper details how integrated mixed methods analysis was needed to fully explain the results and how mono-method studies would provide misleading results. The theoretical advancements generated during the project illustrate how mixed methods for video-based studies have valuable properties for understanding complex interactional phenomena, such as learning. [ABSTRACT FROM AUTHOR]

This paper introduces FEMemAE-Jigsaw, a hybrid detection framework that leverages a fusion of reconstruction and jigsaw puzzle detection for video anomaly detection. Initially, we developed a new reconstruction model, FEMemAE, which utilizes an expanded memory module to more effectively retain the original input data’s information. By incorporating a Large Kernel selection module, the model can attend to more feature information. Furthermore, through the integration of a Fast Channel Attention mechanism, the model can more efficiently filter out useful features, thereby producing images with greater discriminability. Under the reconstruction condition, this study employs a further detection method using jigsaw puzzles, which, by training on the spatial information of video frames, can determine whether the input video frames are anomalous. Since the quality of the reconstructed data fundamentally influences the jigsaw puzzle detection, clearer and more discriminative data will be more beneficial for the model to detect normal and abnormal events. Experimental results demonstrate that this method outperforms existing methods on various standard datasets in terms of performance. [ABSTRACT FROM AUTHOR]

Can automatically authored videos of industrial operators help other operators to learn procedural tasks? This question is relevant to the advent of the industrial internet of things (IIoT) and Industry 4.0, where smart machines can help human operators rather than replacing them in order to benefit from the best of humans and machines. This study considers an industrial ecosystem where procedural knowledge (PK) is quickly and effectively transferred from one operator to another. Assembly tasks are procedural in nature and present a certain complexity that still does not allow machines and their sensors to capture all the details of the operations. Especially if the assembly operation is adaptive and not fixed in terms of assembly sequence plan. In order to help the operators, videos of other operators executing the complex procedural tasks can be automatically recorded and authored from machines. This study shows by means of statistical design and analysis of experiments that expert aid can reduce the assembly time of an untrained operator, whereas automatically authored video aids can transfer PK but producing an opposite effect on the assembly time. Therefore, hybrid training methods are still necessary and trade-offs have to be considered. Managerial insights from the results suggest an unneglectable impact of the choice to digitise industrial operations too early. The experimental studies presented can act as guidelines for the correct statistical testing of innovative solutions in industry. [ABSTRACT FROM AUTHOR]

Developing digital learning materials, especially video lectures, is becoming an important issue in education. The emergence of artificial intelligence (AI) has made the creation of videos easier compared to the traditional approach. However, the education sector has yet to benefit from these advanced technologies fully. This research explores the application of Artificial Intelligence (AI) in creating digital learning videos. The study uses 43 selected articles and the PRISMA analysis model to search, classify, and content-filter the results. The findings show a noticeable growth in using AI to create digital learning videos, with 33 topics formed from keywords and articles published in various journals. The most influential works include automatic content extraction from videos and virtual teachers, and there is significant interest in ChatGPT. The main research topics include • developing effective AI models to convert text to video, • integrating personalization and interaction features, and • applying these digital learning videos in education and training. However, many issues remain to be researched, such as enhancing the context-understanding capabilities of AI models and building frameworks to evaluate the effectiveness of videos. AI-generated videos' quality, reliability, and flexibility are significant unresolved challenges, opening up research gaps for future scholars.