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6 results for “emotional exhaustion”
The effect of ethical leadership on organizational outcomes in the hospitality industry: the mediating role of trust and emotional exhaustion
<p>SPSS dataset for the paper: "The effect of ethical leadership on organizational outcomes in the hospitality industry: the mediating role of trust and emotional exhaustion".</p>
Data set for article: Intimate Partner Violence and Emotional Exhaustion: A Female Gender Perspective in the University Environment
<p>Data set for article: Intimate Partner Violence and Emotional Exhaustion: A Female Gender Perspective in the University Environment </p>
EmoPulse Moments E4 Dataset (EPM-E4): An Exhaustive Collection of Emotion-Related Data from Empatica E4 Wearable
<p><strong>EmoPulse Moments E4 Dataset (EPM-E4): An Exhaustive Collection of Emotion-Related Data from Empatica E4 Wearable</strong></p> <p> </p> <p> </p> <p><strong>Description</strong>:</p> <p>The EmoPulse Moments E4 Dataset (EPM-E4) is a meticulously curated dataset, derived from 53 participants using the Empatica E4 wearable, a cutting-edge device capturing emotional responses in real-time. This dataset offers a treasure trove of information for those engrossed in emotion analysis, wearable technology, and psychophysiological research.</p> <p><strong>Dataset Highlights</strong>:</p> <ul> <li><strong>Continuous Physiological Data</strong>: Including heart rate, electrodermal activity, and skin temperature, revealing the body's emotional state.</li> <li><strong>Motion Tracking</strong>: Captures the device's 3D movement, integrating context with emotion.</li> <li><strong>Blood Volume Pulse (BVP)</strong>: Providing insights into cardiovascular activities related to emotional arousal.</li> <li><strong>Intra-day Variability</strong>: Chronicling daily emotional patterns and changes, spotlighting moments of heightened emotional intensity.</li> <li><strong>Wearable-specific Metrics</strong>: Device battery levels, operational status, and other key indicators are documented with precision.</li> <li><strong>Consent and Ethics</strong>: The dataset respects and upholds privacy and ethical standards. Every participant provided informed consent. This endeavor has received the green light from the Ethics Committee at the University of Granada, documented under the reference: 2100/CEIH/2021.</li> </ul> <p>A major attribute of EPM-E4 is the in-depth exploration of "key moments" within the viewed clips, targeting instances that are predicted to intensify emotional reactions.</p> <p><strong>Curated Video Clips within Dataset</strong>:</p> Film Emotion Duration (seconds) The Lover Baseline 43 American History X Anger 106 Cry Freedom Sadness 166 Alive Happiness 310 Scream Fear 395 <p>EPM-E4's groundbreaking focus on these key moments bridges the gap between cinematic events and nuanced physiological responses captured by the Empatica E4 wearable.</p> <p><strong>Key Emotional Moments in Dataset</strong>:</p> Film Emotion Key moment timestamps (seconds) American History X Anger 36, 57, 68 Cry Freedom Sadness 112, 132, 154 Alive Happiness 227, 270, 289 Scream Fear 23, 42, 79, 226, 279, 299, 334 <p><strong>Based on</strong>: Gilman, T. L., et al. (2017). A film set for the elicitation of emotion in research. Behavior Research Methods, 49(6). </p> <p>With its meticulous design and extensive reach, the EmoPulse Moments E4 Dataset aims to pioneer advances in wearable technology, psychophysiology, and affective computing, furnishing a detailed blueprint for decoding and exploring human emotions via real-time wearable data.<br> <br> <em>The ethical consent for this dataset was provided by La Comisión de Ética en Investigación de la Universidad de Granada, as documented in the approval titled: 'DETECCIÓN AUTOMÁTICA DE LAS EMOCIONES BÁSICAS Y SU INFLUENCIA EN LA TOMA DE DECISIONES MEDIANTE WEARABLES Y MACHINE LEARNING' registered under 2100/CEIH/2021.</em></p>
Mantra Meditation to Reduce Emotional Exhaustion in Emergency Department Staff
ClinicalTrials.gov study NCT02887300. IPD Sharing: YES. Countries: 1. Publications: 8.
Decision Fatigue and Emotional Exhaustion Among Anesthesiologists
ClinicalTrials.gov study NCT07089160. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Factors associated with emotional exhaustion in healthcare professionals involved in the COVID-19 pandemic: an application of the job demands-resources model
<p>Dataset from Barello S, Caruso R, Palamenghi L, Nania T, Dellafiore F, Bonetti L, Silenzi A, Marotta C, Graffigna G. Factors associated with emotional exhaustion in healthcare professionals involved in the COVID-19 pandemic: an application of the job demands-resources model. Int Arch Occup Environ Health. 2021 Nov;94(8):1751-1761. doi: 10.1007/s00420-021-01669-z. Epub 2021 Mar 3. PMID: 33660030; PMCID: PMC7928172.</p> <p>Abstract</p> <p><strong>Purpose: </strong>The purpose of the present cross-sectional study is to investigate the role of perceived COVID-19-related organizational demands and threats in predicting emotional exhaustion, and the role of organizational support in reducing the negative influence of perceived COVID-19 work-related stressors on burnout. Moreover, the present study aims to add to the understanding of the role of personal resources in the Job Demands-Resources model (JD-R) by examining whether personal resources-such as the professionals' orientation towards patient engagement-may also strengthen the impact of job resources and mitigate the impact of job demands.</p> <p><strong>Methods: </strong>This cross-sectional study involved 532 healthcare professionals working during the COVID-19 pandemic in Italy. It adopted the Job-Demands-Resource Model to study the determinants of professional's burnout. An integrative model describing how increasing job demands experienced by this specific population are related to burnout and in particular to emotional exhaustion symptoms was developed.</p> <p><strong>Results: </strong>The results of the logistic regression models provided strong support for the proposed model, as both Job Demands and Resources are significant predictors (OR = 2.359 and 0.563 respectively, with p < 0.001). Moreover, healthcare professionals' orientation towards patient engagement appears as a significant moderator of this relationship, as it reduces Demands' effect (OR = 1.188) and increases Resources' effect (OR = 0.501).</p> <p><strong>Conclusions: </strong>These findings integrate previous findings on the JD-R Model and suggest the relevance of personal resources and of relational factors in affecting professionals' experience of burnout.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.