Affective science最新文献_第3页

Mapping Interpersonal Emotion Regulation in Everyday Life 日常生活中的人际情绪调节映射

Affective science Pub Date : 2023-11-13 DOI: 10.1007/s42761-023-00223-z

Anh Tran, Katharine H. Greenaway, Joanne Kostopoulos, Sarah T. O’Brien, Elise K. Kalokerinos

{"title":"Mapping Interpersonal Emotion Regulation in Everyday Life","authors":"Anh Tran, Katharine H. Greenaway, Joanne Kostopoulos, Sarah T. O’Brien, Elise K. Kalokerinos","doi":"10.1007/s42761-023-00223-z","DOIUrl":"https://doi.org/10.1007/s42761-023-00223-z","url":null,"abstract":"Abstract The growing literature on interpersonal emotion regulation has largely focused on the strategies people use to regulate. As such, researchers have little understanding of how often people regulate in the first place, what emotion regulation goals they have when they regulate, and how much effort they invest in regulation. To better characterize features of the regulation process, we conducted two studies using daily diary ( N = 171) and experience sampling methods ( N = 239), exploring interpersonal emotion regulation in the context of everyday social interactions. We found people regulated others’ emotions nearly twice a day, regulated their own emotions through others around once a day, and regulated both their own and others’ emotions in the same interaction roughly every other day. Furthermore, not only did people regulate others’ emotions more often than regulating their own emotions through others, but they also put in more effort to do so. The goals of regulation were primarily to make themselves or others feel better, most often through increasing positive emotions, rather than decreasing negative emotions. Together, these findings provide a foundational picture of the interpersonal emotion regulation landscape, and lay the groundwork for future exploration into this emerging subfield of affective science.","PeriodicalId":72119,"journal":{"name":"Affective science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134992941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Future of Emotion Regulation Research: Broadening Our Field of View 情绪调节研究的未来:拓宽我们的视野

Affective science Pub Date : 2023-10-02 DOI: 10.1007/s42761-023-00222-0

Kate Petrova, James J. Gross

引用次数: 0

Habitual Expressive Suppression of Positive, but not Negative, Emotions Consistently Predicts Lower Well-being across Two Culturally Distinct Regions 在两个文化截然不同的地区，积极而非消极情绪的习惯性表达压抑始终预示着较低的幸福感

Affective science Pub Date : 2023-09-21 DOI: 10.1007/s42761-023-00221-1

Chen-Wei Felix Yu, Claudia M. Haase, Jen-Ho Chang

引用次数: 0

The Future of Affective Science: Introduction to the Special Issue 情感科学的未来：特刊导论。

Affective science Pub Date : 2023-09-12 DOI: 10.1007/s42761-023-00220-2

Michelle N. Shiota, Linda A. Camras, Ralph Adolphs

引用次数: 0

The Future of Immersive Mood Induction in Affective Science: Using Virtual Reality to Test Effects of Mood Context on Task Performance 情感科学中沉浸式情绪诱导的未来：利用虚拟现实测试情绪情境对任务表现的影响。

Affective science Pub Date : 2023-09-12 DOI: 10.1007/s42761-023-00213-1

Nadia Kako, Christian E. Waugh, Kateri McRae

{"title":"The Future of Immersive Mood Induction in Affective Science: Using Virtual Reality to Test Effects of Mood Context on Task Performance","authors":"Nadia Kako, Christian E. Waugh, Kateri McRae","doi":"10.1007/s42761-023-00213-1","DOIUrl":"10.1007/s42761-023-00213-1","url":null,"abstract":"<div><p>A fundamental premise of affective and clinical science is that fluctuations in mood drive meaningful changes in cognition and behavior. These theories are often tested via laboratory mood induction procedures followed by performing an established task. Despite advances in understanding the temporal dynamics of emotions, it is still unclear whether it is the enduring mood that impacts subsequent task performance. Additionally, this design requires task switching, which may limit the impact of mood and affect task performance. We suggest that virtual reality (VR) offers a more powerful, immersive alternative to traditional mood induction methods and effectively addresses these limitations because it can be used to create mood contexts that occur simultaneously with task performance. VR creates an immersive, real-world experience while benefiting from a well-controlled laboratory setting (Diniz Bernardo et al., 2021). We first summarize the literature on mood induction methodologies, including evidence that VR creates a more immersive environment, leading to mood inductions that are greater in magnitude than other methods. We then report a novel empirical study on the feasibility of utilizing VR to create a mood context that occurs simultaneously with a gold-standard emotion regulation task. Our results indicate that VR was a powerful and enduring positive mood induction tool, resulting in immediate changes in mood and greater trial-by-trial positivity ratings during the concurrent task. Portions of this study were pre-registered on August 3, 2020, on the Clinical Trials website (project citation: https://clinicaltrials.gov/ct2/show/NCT04496258).</p></div>","PeriodicalId":72119,"journal":{"name":"Affective science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42761-023-00213-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41173697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Affective Science Research: Perspectives and Priorities from the National Institutes of Health 情感科学研究：美国国立卫生研究院的观点和优先事项。

Affective science Pub Date : 2023-09-06 DOI: 10.1007/s42761-023-00218-w

Janine M. Simmons, Andrew Breeden, Rebecca A. Ferrer, Arielle S. Gillman, Holly Moore, Paige Green, Vani Pariyadath, Erin B. Quinlan, Aleksandra Vicentic

引用次数: 1

We (Still!) Need to Talk About Valence: Contemporary Issues and Recommendations for Affective Science 我们（仍然！）需要谈谈Valence：情感科学的当代问题和建议。

Affective science Pub Date : 2023-09-02 DOI: 10.1007/s42761-023-00217-x

Eric A. Walle, Daniel Dukes

引用次数: 0

Beyond Nature Versus Nurture: the Emergence of Emotion 超越自然与培育：情感的产生。

Affective science Pub Date : 2023-08-30 DOI: 10.1007/s42761-023-00212-2

Adrienne Wood, James A. Coan

{"title":"Beyond Nature Versus Nurture: the Emergence of Emotion","authors":"Adrienne Wood, James A. Coan","doi":"10.1007/s42761-023-00212-2","DOIUrl":"10.1007/s42761-023-00212-2","url":null,"abstract":"<div><p>Affective science is stuck in a version of the nature-versus-nurture debate, with theorists arguing whether emotions are evolved adaptations or psychological constructions. We do not see these as mutually exclusive options. Many adaptive behaviors that humans have evolved to be good at, such as walking, emerge during development – not according to a genetically dictated program, but through interactions between the affordances of the body, brain, and environment. We suggest emotions are the same. As developing humans acquire increasingly complex goals and learn optimal strategies for pursuing those goals, they are inevitably pulled to particular brain-body-behavior states that maximize outcomes and self-reinforce via positive feedback loops. We call these recurring, self-organized states <i>emotions</i>. Emotions display many of the hallmark features of self-organized attractor states, such as hysteresis (prior events influence the current state), degeneracy (many configurations of the underlying variables can produce the same global state), and stability. Because most bodily, neural, and environmental affordances are shared by all humans – we all have cardiovascular systems, cerebral cortices, and caregivers who raised us – similar emotion states emerge in all of us. This perspective helps reconcile ideas that, at first glance, seem contradictory, such as emotion universality and neural degeneracy.</p></div>","PeriodicalId":72119,"journal":{"name":"Affective science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42761-023-00212-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41162747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Synergistic Opportunities for Affective Science and Behavior Change 情感科学与行为改变的协同机遇。

Affective science Pub Date : 2023-08-30 DOI: 10.1007/s42761-023-00216-y

Rebecca A. Ferrer, Arielle S. Gillman

引用次数: 2

Advancing Naturalistic Affective Science with Deep Learning 以深度学习推进自然主义情感科学。

Affective science Pub Date : 2023-08-25 DOI: 10.1007/s42761-023-00215-z

Chujun Lin, Landry S. Bulls, Lindsey J. Tepfer, Amisha D. Vyas, Mark A. Thornton

{"title":"Advancing Naturalistic Affective Science with Deep Learning","authors":"Chujun Lin, Landry S. Bulls, Lindsey J. Tepfer, Amisha D. Vyas, Mark A. Thornton","doi":"10.1007/s42761-023-00215-z","DOIUrl":"10.1007/s42761-023-00215-z","url":null,"abstract":"<div><p>People express their own emotions and perceive others’ emotions via a variety of channels, including facial movements, body gestures, vocal prosody, and language. Studying these channels of affective behavior offers insight into both the experience and perception of emotion. Prior research has predominantly focused on studying individual channels of affective behavior in isolation using tightly controlled, non-naturalistic experiments. This approach limits our understanding of emotion in more naturalistic contexts where different channels of information tend to interact. Traditional methods struggle to address this limitation: manually annotating behavior is time-consuming, making it infeasible to do at large scale; manually selecting and manipulating stimuli based on hypotheses may neglect unanticipated features, potentially generating biased conclusions; and common linear modeling approaches cannot fully capture the complex, nonlinear, and interactive nature of real-life affective processes. In this methodology review, we describe how deep learning can be applied to address these challenges to advance a more naturalistic affective science. First, we describe current practices in affective research and explain why existing methods face challenges in revealing a more naturalistic understanding of emotion. Second, we introduce deep learning approaches and explain how they can be applied to tackle three main challenges: quantifying naturalistic behaviors, selecting and manipulating naturalistic stimuli, and modeling naturalistic affective processes. Finally, we describe the limitations of these deep learning methods, and how these limitations might be avoided or mitigated. By detailing the promise and the peril of deep learning, this review aims to pave the way for a more naturalistic affective science.</p></div>","PeriodicalId":72119,"journal":{"name":"Affective science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42761-023-00215-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41153763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2