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True crime is a highly controversial yet successful entertainment genre that is widely available on streaming, video, and podcast platforms. The content often includes visual depictions of victims and survivors of gender-based violence, as well as depictions of the acts of violence themselves, such as surveillance footage, police or court videos, or photographs. Additionally, producers and account holders on social media platforms frequently use stereotypical, clichéd, and even eroticized representations of violence. True crime formats rarely address neither the structural causes and backgrounds which lead to crimes, nor the impact on victims, survivors, and their relatives. To address these issues, we apply audio-visual content analysis, focusing on the YouTube channel of Bailey Sarian and her content combination of narrating true crime stories while doing her makeup. Drawing on communication and media studies, we explore the dual tenor of subversive-empowering versus voyeuristic-exploitative representations in the context of narratives of gender-based violence. Our analysis highlights that the unreflective and voyeuristic tone of commercialized true crime narratives can lead to the unethical exploitation of real events and the people affected. The Murder, Mystery & Makeup Monday series exemplifies a dual approach, blending affective storytelling, which fosters viewer intimacy, with sensationalistic portrayals that often simplify and stigmatize those involved in criminal cases. Although some empowering and informative voices regarding gender-based violence exist online, they are frequently overshadowed by the sensationalism typical of commercial true crime. The series underscores a tension between intimate engagement and ethical responsibility, shaped by platform-driven pressures that prioritize engagement over quality. Our findings emphasize the need for platforms to actively enable nuanced, balanced portrayals that foster a more informed and empathetic media environment.

Research related to computational modeling for machine-based understanding requires ground truth data for training, content analysis, and evaluation. In this paper, we present a multimodal video database, namely COGNIMUSE, annotated with sensory and semantic saliency, events, cross-media semantics, and emotion. The purpose of this database is manifold; it can be used for training and evaluation of event detection and summarization algorithms, for classification and recognition of audio-visual and cross-media events, as well as for emotion tracking. In order to enable comparisons with other computational models, we propose state-of-the-art algorithms, specifically a unified energy-based audio-visual framework and a method for text saliency computation, for the detection of perceptually salient events from videos. Additionally, a movie summarization system for the automatic production of summaries is presented. Two kinds of evaluation were performed, an objective based on the saliency annotation of the database and an extensive qualitative human evaluation of the automatically produced summaries, where we investigated what composes high-quality movie summaries, where both methods verified the appropriateness of the proposed methods. The annotation of the database and the code for the summarization system can be found at http://cognimuse.cs.ntua.gr/database .

Background Today’s students, who easily lose interest when faced with monotony and repetition, seek convenience and rapid solutions. The PechaKucha presentation method, which emphasizes concise slides enriched with visuals and audio, is increasingly used to enhance engagement in education. This study aimed to evaluate the effect of the PechaKucha method on nursing students’ primary outcome proficiency in deep breathing and coughing (DB&C) exercises and secondary outcome satisfaction with the educational method. Methods A randomized controlled trial was conducted with 96 s-year nursing students. Participants were simple randomly assigned to an experimental group ( n  = 48) and a control group ( n  = 48) using a randomization program. Data were collected through a descriptive information form, a DB&C exercise checklist, and a Visual Analog Scale (VAS) for satisfaction. Results The mean DB&C skill scores were 47.25 ± 10.11 for the experimental group and 36.48 ± 8.62 for the control group. The mean VAS satisfaction scores were 9.04 ± 1.62 and 7.44 ± 2.39, respectively. The intervention group achieved significantly higher scores in both DB&C performance and satisfaction ( p  < 0.05). Conclusion The PechaKucha presentation method may enhance nursing students’ psychomotor learning and satisfaction compared to traditional instruction. Incorporating concise, visual, and dynamic presentation formats could contribute to more engaging and effective nursing education. Future research should explore its applicability across various nursing skills. Trial registiration This study was retrospectively registered as a randomized controlled trial in the ClinicalTrials Registry. Registration Date: 03/02/2025, Registration Number: NCT06862024.

To explore the influencing factors of college students’ learning intention to online teaching videos during the pandemic, this study considered 696 college students from Huangshan University in China. The T-test and ANOVA were utilized to analyze gender, grade, and discipline on college students’ learning intention, and the regression analysis was utilized to explore four aspects including performance expectancy, effort expectancy, social influence, and facilitating conditions on college students’ learning intention. The results indicate the following: first, using descriptive analysis, it is observed that college students did not exhibit a positive learning attitude toward online teaching videos during the pandemic. Second, the t test and one-way analysis of variance indicate that grades between freshmen and seniors significantly influence the learning intention of college students to online teaching videos, whereas genders and disciplines do not. Third, through regression analysis, it is observed that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence college students’ learning intention to online teaching videos. This study stipulates the following research proposals: resource construction, the optimization of the online teaching environment, advanced technology and psychological counseling. It is expected that the findings will provide references for studies on online teaching resources and online learning.

The Internet is a preferred source of health information. This study evaluated the quality, reliability and content of online audio-visual information on the mandibular advancement device (MAD) for the treatment of obstructive sleep apnea (OSA). “Mandibular advancement device” was searched on four online platforms. A total of 63 videos (51% from healthcare professionals, 22% from commercial companies, 21% from laypeople, and 6% from hospitals/universities) were evaluated using metrics, the video information and quality index (VIQI), modified-DISCERN, and the Journal of American Medical Association (JAMA) benchmark criteria and contents. VIQI had significantly lower scores for videos uploaded by laypeople (mean 7.92, 95%CI 5.90–9.95) versus healthcare professionals (12.38, 95%CI 11.28–13.47) and commercial companies (11.21, 95%CI 9.61–12.81). The m-DISCERN scores were significantly lower for laypeople (1.15, 95%CI 0.93–1.40) versus healthcare professionals (2.13, 95%CI 1.73–2.52) and hospitals/universities (3.00, 95%CI 1.70–4.30), as well as for commercial companies (1.43, 95%CI 1.13-1.73) versus hospitals/universities. Contents were significantly less complete for laypeople (1.54, 95%CI 0.60–2.48) versus healthcare professionals (3.25, 95%CI 2.66–3.84). The results of the present study suggest that the quality and completeness of online audio-visual information with respect to the use of MAD for the treatment of OSA are generally poor, and the currently available videos, especially those uploaded by laypeople, may determine misinformation and/or unrealistic treatment expectations.

This action research examines the transition from audio- to video-based tasks in the final Medical Hungarian exam for international medical students, aiming to better align assessment with real-life language needs and enhance student motivation. Conducted at a Hungarian medical university with 61 second-year students, the study uses a mixed-methods approach. Quantitative data from a questionnaire and qualitative insights from focus group interviews reveal students’ experiences with the video-based exam tasks and preparatory materials. The results indicate a positive reception of the Practice Test Book and the new video exam format, with visual cues like body language aiding in comprehension and engagement. Students found that the video-based tasks closely mirrored clinical interactions, strengthening the relevance of language skills in professional contexts. Preparatory materials, including lead-in exercises, were well-received by students and seen as effective in improving readiness for the exam. The study suggests that the shift from audio- to video-based assessment can bridge classroom learning with real-world application, potentially serving as a model for other non-traditional study abroad settings in Languages Other Than English (LOTEs), especially as purely audio-based communication has become less prevalent in today’s world.

The paper analyzes the campaign strategies of the “Prawo i Sprawiedliwość” (PiS) political party during the Polish elections from 2009 to 2020. It examines how the gradual modernization of communication strategies and the adoption of a less aggressive narrative contributed to the party’s revival after a decline in support caused by the political crisis of 2007 and the death of leader Lech Kaczyński in 2010. The research aims to identify the changes in campaigning that contributed to regaining electoral success since the 2015 national elections. The analysis is based on audio-visual materials produced by PiS for the elections during both the “crisis” period (2009-2013) and the “revival” period (2014-2020), allowing for a comparative analysis of the main changes between these two periods. Through content analysis of these materials, the study investigates the topics, genres, formats, national and European dimensions, personalization strategies, and use of negative advertising.

We propose ViComp , an automatic audio-visual camera selection framework for composing uninterrupted recordings from multiple user-generated videos (UGVs) of the same event. We design an automatic audio-based cut-point selection method to segment the UGV. ViComp combines segments of UGVs using a rank-based camera selection strategy by considering audio-visual quality and camera selection history. We analyze the audio to maintain audio continuity. To filter video segments which contain visual degradations, we perform spatial and spatio-temporal quality assessment. We validate the proposed framework with subjective tests and compare it with state-of-the-art methods.

The use of audio-visual media puts bodies literally in focus, but there is as yet surprisingly little in the methodology literature about how to analyze the body in this kind of material. The aim of this article is to illustrate how qualitative audio-visual analysis, focusing on embodiment and materialization, may be used to discern social representations; this is of especial interest when studying materials which have an explicit ambition to achieve \"neutrality\" without reference to certain kinds of bodies. Filmed occupational descriptions—produced by the Swedish Employment Agency (SEA)—are analyzed and discussed. The examples presented in the article illustrate how various forms of audio-visual analysis—content analysis, sequential analysis and narrative analysis—can be used to reveal how social representations of occupations and practitioners are embodied and materialized in these films. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs160139

We present a multimodal method for the automatic synchronization of audio-visual recordings captured with a set of independent cameras. The proposed method jointly processes data from audio and video channels to estimate inter-camera delays that are used to temporally align the recordings. Our approach is composed of three main steps. First we extract from each recording temporally sharp audio-visual events. These audio-visual events are short and characterized by an audio onset happening jointly to a well-localized spatio-temporal change in the video data. Then, we estimate the inter-camera delays by assessing the co-occurrence of the events in the various recordings. Finally, we use a cross-validation procedure that combines the results for all camera pairs and aligns the recordings in a global timeline. An important feature of the proposed method is the estimation of the confidence level on the results that allows us to automatically reject recordings that are not reliable for the alignment. Results show that our method outperforms state-of-the-art approaches based on audio-only or video-only analysis with both fixed and hand-held moving cameras.