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The Impact of Video-Assisted Debriefing on Fostering Self-Critical Thinking in Mental Health Nursing Students
Full text linkThis study investigated the impact of video recordings from simulated mental health scenarios on the self-critical thinking of undergraduate nursing students. Video-assisted debriefing (VAD) enables students to review their own performance, clarifying memory gaps, applying theory to practice, and fostering self-reflection to identify strengths and areas for improvement. Although widely used, few studies have examined its effect specifically on self-critical capacity in mental health nursing education.
A quasi-experimental exploratory design was used, collecting both quantitative and qualitative data after two debriefing formats: verbal and video-assisted. Quantitative data tracked trends in self-evaluation, while qualitative data explored students' reflections on performance, emotions, strengths, and weaknesses. Data integration provided comprehensive insight.
Quantitative results showed no significant changes between the two evaluation moments. However, qualitative analysis revealed deeper reflections and stronger identification of strengths during VAD sessions. Students felt more self-aware and critical when watching themselves, recognizing specific areas for improvement and reporting enhanced emotional insight.
VAD proved valuable in developing students’ self-perception and reflective thinking in mental health simulations. Some mental health care aspects remained difficult regardless of feedback type, suggesting the need for focused training. Mixed-method approaches offered richer understanding of learning processes.
Implications for Nursing Management: Incorporating VAD into clinical training can enhance studenFunding for open access charge: Universidad de Málaga / CBUA. 2is research was supported in part by the University of Malaga within the framework of the 9nancing program of educational innovation projects under number PIE 19-039. Funding for open access charge: Universidad de Málaga/ CBUA
Las “polémicas apasionadas” de Amando de Miguel en torno al lenguaje inclusivo
No full textPolítica de acceso abierto tomada de: https://www.peterlang.com/repository-policy/El lenguaje inclusivo (no sexista) se gesta en España paralelo a la Constitución
del 78. Es una consecuencia más del Movimiento de Liberación de las Mujeres (Women’s Movement) que, desde los años sesenta, venía promoviendo, a
nivel internacional, la investigación sobre género y lenguaje, sobre todo desde
la Sociolingüística y el Análisis del Discurso (West, Lazar y Kramarae, 2000;
Wodak, 2015, Guerrero Salazar, 2020a). Surge así la lingüística feminista, uno
de cuyos objetivos es buscar alternativas igualitarias a los usos discriminatorios,
alternativas que a partir de los años ochenta son impulsadas por normativas
internacionales y nacionales que recomiendan el uso igualitario del lenguaje a
nivel institucional y que fomentan guías y manuales de uso no sexista del lenguaje. La puesta en marcha de todas estas medidas inicia un debate, de gran
repercusión en los medios de comunicación (Guerrero Salazar, 2019a y 2019b),
que sigue vigente en la actualidad, donde ha cobrado fuerzas gracias a las redes
sociales (Guerrero Salazar, 2019c).DISMUPREM y METAPRE
Real-time unsupervised video object detection on the edge
Full text linkObject detection in video is an essential computer vision task. Consequently, many efforts have been devoted to developing precise and fast deep-learning models for this task. These models are commonly deployed on discrete and powerful GPU devices to meet both frame rate performance and detection accuracy requirements. Furthermore, model training is usually performed in a strongly supervised way so that samples must be previously labelled by humans using a slow and costly process. In this paper, we develop a real-time implementation for unsupervised object detection in video employing a low-power device. We improve typical approaches for object detection using information supplied by optical flow to detect moving objects. Besides, we use an unsupervised clustering algorithm to group similar detections that avoid manual object labelling. Finally, we propose a methodology to optimize the deployment of our resulting framework on an embedded heterogeneous platform. Thus, we illustrate how all the computational resources of a Jetson AGX Xavier (CPU, GPU, and DLAs) can be used to fulfil frame rate, accuracy, and energy consumption requirements. Three different data representations (FP32, FP16 and INT8) are studied for the pipeline networks in order to evaluate the impact of all of them in our pipeline. Obtained results show that our proposed optimizations can improve up to 23.6x
energy consumption and 32.2x
execution time with respect to the non-optimized pipeline without penalizing the original mAP (59.44). This computational complexity reduction is achieved through knowledge distillation, using FP16 data precision, and deploying concurrent tasks in different computing units.Funding for open access charge: Universidad de Málaga / CBU
Data-Driven Marketing Image: Scale Development and Validation
Full text linkhttps://rbgn.fecap.br/RBGN/openaccessPPRO-B3-2023-21Purpose – This study develops and validates a measurement scale for assessing the corporate image of companies that use data-driven marketing in their decision-making and actions in online retailing.
Theoretical framework – The study is grounded in theories of corporate image and consumer behaviour, integrating concepts of data-driven marketing and privacy to develop the DDMI scale.
Design/methodology/approach – A mixed methods approach is employed, beginning with a deductive literature review and qualitative expert interviews to generate scale items, followed by a pilot study and a large-scale survey of 301 consumers via Amazon MTurk. Exploratory and confirmatory factor analyses are conducted to validate the scale.
Findings – DDM strategies significantly affect how customers perceive a company’s image. The DDMI provides a validated scale that measures aspects that are important to customers, such as privacy concerns and personalised customer experience. It reveals that effective communication, efficient payment processes and robust customer support are vital for a positive corporate image.
Practical & social implications – The study offers a novel tool to assess corporate image in environments characterised by high data usage. It enables companies to refine their DDM strategies by identifying how specific practices affect consumer perceptions.
Originality/value – This research introduces the first validated scale to measure consumer perceptions of corporate image in DDM contexts. It advances marketing theory by capturing key dimensions of the digital era, personalisation, privacy and support
The Mediating Role of Psychological Flexibility and Inflexibility Between Impulsivity and Opioid Misuse in People With Chronic Noncancer Pain
Full text linkBackground
The prescription of opioid medication is a frequent therapeutic approach in chronic noncancer pain, as is misuse of prescribed opioids. There is previous evidence for associations between personal variables such as impulsivity and opioid misuse. Psychological flexibility and inflexibility have also been associated with pain-related outcomes and opioid misuse. The aim of this cross-sectional study was to examine the combined role of a dispositional variable (impulsivity) along with psychological factors (Psychological Flexibility and Inflexibility) in pain outcomes and opioid misuse.
Methods
The sample comprised 155 people with chronic noncancer pain. A hypothetical model was tested using correlation and structural equation modelling analyses.
Results
The results show significant associations between impulsivity and Psychological Flexibility, Psychological Inflexibility and opioid misuse. Psychological Flexibility and Inflexibility were related to pain intensity, interference and opioid misuse. Structural equation modelling showed significant associations between impulsivity, Psychological Inflexibility and pain interference, and opioid misuse. Associations between Psychological Flexibility and pain interference and opioid misuse were nonsignificant. These results support the hypothesis that impulsivity and Psychological Inflexibility are factors that contribute to pain interference and opioid misuse, but do not support the hypothesis that Psychological Flexibility reduces opioid misuse.
Conclusions
It is recommended to assess these psychological aspects prior to the prescription of opioid medication, and, if necessary, offering Acceptance and Commitment and Mindfulness Based Therapies could be desirable.Funding for open access charge: Universidad de Málaga / CBU
4D Synchrotron X‑ray Nanoimaging for Early Age Cement Curing: Where Are We and Where Should We Go?
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Inteligencia emocional y probabilidad de intervención en ciberacoso: el papel de la interacción emocional alumno-docente
Full text linkEl presente estudio analiza la relación entre la Inteligencia Emocional (IE) de los docentes y su probabilidad de intervención en casos de ciberacoso, así como el papel mediador de la interacción emocional alumno-docente. Para ello, se realizó un estudio cuantitativo de corte transversal. Se administraron los instrumentos WLEIS, EFI y un ítem para valorar la probabilidad de intervención. La muestra se compone de 105 docentes, de los cuales un 55,2% eran mujeres, con edades comprendidas entre los 29 y 64 años (M = 47; DT = 8,46), de 16 centros educativos de Secundaria. Los resultados mostraron una relación positiva entre la IE y la probabilidad de intervención, además de una mediación total de esta relación por la interacción emocional alumno-docente. De esta manera, la IE se relaciona con una mayor probabilidad de intervención entre víctima y acosador, a través de la interacción centrada en las emociones entre docente y alumno.Parte del proyecto I+D+i PID2020-117006RB-I00, financiado por MCIN/AEI/10.13039/501100011033Grupo de investigación Applied Positive Lab CTS-1048G-FEDER (Junta de Andalucía)Universidad de Málaga (M. T. Chamizo-Nieto bajo un contrato postdoctoral
A semi-implicit exactly fully well-balanced relaxation scheme for the Shallow Water Linearized Moment Equations
Full text linkWhen dealing with shallow water simulations, the velocity profile is often assumed to be constant along the vertical axis. However, since in many applications this is not the case, modeling errors can be significant. Hence, in this work, we deal with the Shallow Water Linearized Moment Equations (SWLME), in which the velocity is no longer constant in the vertical direction, where a polynomial expansion around the mean value is considered. The linearized version implies neglecting the non-linear terms of the basis coefficients in the higher order equations. As a result, the model is always hyperbolic and the stationary solutions can be more easily computed. Then, our objective is to propose an efficient, accurate and robust numerical scheme for the SWLME model, specially adapted for low Froude number situations. Hence, we describe a semi-implicit second order exactly fully well-balanced method. More specifically, a splitting is performed to separate acoustic and material phenomena. The acoustic waves are treated in an implicit manner to gain in efficiency when dealing with subsonic flow regimes, whereas the second order of accuracy is achieved thanks to a polynomial reconstruction and Strang-splitting method. We also exploit a reconstruction operator to achieve the fully well-balanced character of the method. Extensive numerical tests demonstrate the well-balanced properties and large speed-up compared to traditional methods.Funding for open access charge: Universidad de Málaga / CBU