Pub Date : 2023-04-12DOI: 10.1038/s44159-023-00171-2
Colleen Ward, Ágnes Szabó
Intercultural contact produces changes in an individual’s culturally grounded beliefs, behaviours and identities, a process known as acculturation. In this Review, we outline the process of acculturation with reference to cultural identity, a type of social identity that includes ethnic, national, and religious identities. We begin by critically reviewing developmental, social, and cross-cultural approaches to the development, negotiation, organization and integration of multiple cultural identities. Next, we highlight microlevel, mesolevel and macrolevel contextual influences on these dynamic processes. Then we review evidence concerning the relationship between cultural identities and well-being and possible explanatory mechanisms for their association. We conclude by summarizing points of agreement across cross-cultural, social and developmental perspectives on cultural identity, noting challenges to advancing the field and making recommendations for future research. Acculturation is the process of individual identity change owing to intercultural contact. In this Review, Ward and Szabó discuss approaches to the study of acculturation, the influence of context on cultural identities, and the relationship between cultural identities and well-being.
跨文化接触会改变一个人基于文化的信仰、行为和身份，这一过程被称为文化适应。在这篇综述中，我们将以文化认同（一种包括种族、民族和宗教认同在内的社会认同）为参照，概述文化适应的过程。首先，我们将批判性地回顾有关多重文化身份的发展、协商、组织和整合的发展、社会和跨文化方法。接着，我们强调了对这些动态过程产生影响的微观层面、中观层面和宏观层面的背景因素。然后，我们回顾了文化认同与福祉之间关系的证据，以及两者之间可能的关联解释机制。最后，我们总结了跨文化、社会和发展视角中关于文化认同的一致观点，指出了推进该领域研究所面临的挑战，并对未来研究提出了建议。文化适应是由于跨文化接触而导致的个人身份改变的过程。在这篇综述中，Ward 和 Szabó 讨论了文化适应的研究方法、背景对文化认同的影响以及文化认同与福祉之间的关系。
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Pub Date : 2023-04-11DOI: 10.1038/s44159-023-00180-1
Philip Cheng
Mentoring is a core part of training the next generation of psychologists. Recognizing how culture and social identities inform mentorship and science is essential for creating a diverse and therefore robust workforce of psychologists.
{"title":"Towards inclusive mentoring in academic psychology","authors":"Philip Cheng","doi":"10.1038/s44159-023-00180-1","DOIUrl":"10.1038/s44159-023-00180-1","url":null,"abstract":"Mentoring is a core part of training the next generation of psychologists. Recognizing how culture and social identities inform mentorship and science is essential for creating a diverse and therefore robust workforce of psychologists.","PeriodicalId":74249,"journal":{"name":"Nature reviews psychology","volume":"2 5","pages":"261-262"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47545902","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}
Pub Date : 2023-04-06DOI: 10.1038/s44159-023-00175-y
Evan M. Kleiman, Catherine R. Glenn, Richard T. Liu
In the past decade, two themes have emerged across suicide research. First, according to meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker than would be expected for the size of the field. Second, review and commentary papers propose that technological and statistical methods (such as smartphones, wearables, digital phenotyping and machine learning) might become solutions to this problem. In this Review, we aim to strike a balance between the pessimistic picture presented by these meta-analyses and the optimistic picture presented by review and commentary papers about the promise of advanced technological and statistical methods to improve the ability to understand, predict and prevent suicide. We divide our discussion into two broad categories. First, we discuss the research aimed at assessment, with the goal of better understanding or more accurately predicting suicidal thoughts and behaviours. Second, we discuss the literature that focuses on prevention of suicidal thoughts and behaviours. Ecological momentary assessment, wearables and other technological and statistical advances hold great promise for predicting and preventing suicide, but there is much yet to do. Despite decades of research, suicide rates remain largely unchanged. In this Review, Kleiman et al. consider the promise and limitations of technology, such as smartphones, and statistical methods, such as machine learning, to predict and prevent suicide and thereby provide a realistic view of what might be possible.
{"title":"The use of advanced technology and statistical methods to predict and prevent suicide","authors":"Evan M. Kleiman, Catherine R. Glenn, Richard T. Liu","doi":"10.1038/s44159-023-00175-y","DOIUrl":"10.1038/s44159-023-00175-y","url":null,"abstract":"In the past decade, two themes have emerged across suicide research. First, according to meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker than would be expected for the size of the field. Second, review and commentary papers propose that technological and statistical methods (such as smartphones, wearables, digital phenotyping and machine learning) might become solutions to this problem. In this Review, we aim to strike a balance between the pessimistic picture presented by these meta-analyses and the optimistic picture presented by review and commentary papers about the promise of advanced technological and statistical methods to improve the ability to understand, predict and prevent suicide. We divide our discussion into two broad categories. First, we discuss the research aimed at assessment, with the goal of better understanding or more accurately predicting suicidal thoughts and behaviours. Second, we discuss the literature that focuses on prevention of suicidal thoughts and behaviours. Ecological momentary assessment, wearables and other technological and statistical advances hold great promise for predicting and preventing suicide, but there is much yet to do. Despite decades of research, suicide rates remain largely unchanged. In this Review, Kleiman et al. consider the promise and limitations of technology, such as smartphones, and statistical methods, such as machine learning, to predict and prevent suicide and thereby provide a realistic view of what might be possible.","PeriodicalId":74249,"journal":{"name":"Nature reviews psychology","volume":"2 6","pages":"347-359"},"PeriodicalIF":0.0,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10040969","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}
Pub Date : 2023-03-29DOI: 10.1038/s44159-023-00176-x
Pat Dudgeon, Abigail Bray, Roz Walker
Indigenous psychology draws on the oldest continuing knowledge systems but remains largely ignored by dominant Western psychological theories and practices. This exclusion results in ongoing negative effects on Indigenous social and emotional wellbeing and requires urgent decolonization efforts.
{"title":"Embracing the emerging Indigenous psychology of flourishing","authors":"Pat Dudgeon, Abigail Bray, Roz Walker","doi":"10.1038/s44159-023-00176-x","DOIUrl":"10.1038/s44159-023-00176-x","url":null,"abstract":"Indigenous psychology draws on the oldest continuing knowledge systems but remains largely ignored by dominant Western psychological theories and practices. This exclusion results in ongoing negative effects on Indigenous social and emotional wellbeing and requires urgent decolonization efforts.","PeriodicalId":74249,"journal":{"name":"Nature reviews psychology","volume":"2 5","pages":"259-260"},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47604617","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}
Pub Date : 2023-03-27DOI: 10.1038/s44159-023-00172-1
Eva G. Krumhuber, Lina I. Skora, Harold C. H. Hill, Karen Lander
Most past research on emotion recognition has used photographs of posed expressions intended to depict the apex of the emotional display. Although these studies have provided important insights into how emotions are perceived in the face, they necessarily leave out any role of dynamic information. In this Review, we synthesize evidence from vision science, affective science and neuroscience to ask when, how and why dynamic information contributes to emotion recognition, beyond the information conveyed in static images. Dynamic displays offer distinctive temporal information such as the direction, quality and speed of movement, which recruit higher-level cognitive processes and support social and emotional inferences that enhance judgements of facial affect. The positive influence of dynamic information on emotion recognition is most evident in suboptimal conditions when observers are impaired and/or facial expressions are degraded or subtle. Dynamic displays further recruit early attentional and motivational resources in the perceiver, facilitating the prompt detection and prediction of others’ emotional states, with benefits for social interaction. Finally, because emotions can be expressed in various modalities, we examine the multimodal integration of dynamic and static cues across different channels, and conclude with suggestions for future research. Most faces that people encounter move, yet most research on emotion recognition uses photographs of posed expressions. In this Review, Krumhuber et al. describe how dynamic information contributes to emotion recognition, beyond the information conveyed in static images.
{"title":"The role of facial movements in emotion recognition","authors":"Eva G. Krumhuber, Lina I. Skora, Harold C. H. Hill, Karen Lander","doi":"10.1038/s44159-023-00172-1","DOIUrl":"10.1038/s44159-023-00172-1","url":null,"abstract":"Most past research on emotion recognition has used photographs of posed expressions intended to depict the apex of the emotional display. Although these studies have provided important insights into how emotions are perceived in the face, they necessarily leave out any role of dynamic information. In this Review, we synthesize evidence from vision science, affective science and neuroscience to ask when, how and why dynamic information contributes to emotion recognition, beyond the information conveyed in static images. Dynamic displays offer distinctive temporal information such as the direction, quality and speed of movement, which recruit higher-level cognitive processes and support social and emotional inferences that enhance judgements of facial affect. The positive influence of dynamic information on emotion recognition is most evident in suboptimal conditions when observers are impaired and/or facial expressions are degraded or subtle. Dynamic displays further recruit early attentional and motivational resources in the perceiver, facilitating the prompt detection and prediction of others’ emotional states, with benefits for social interaction. Finally, because emotions can be expressed in various modalities, we examine the multimodal integration of dynamic and static cues across different channels, and conclude with suggestions for future research. Most faces that people encounter move, yet most research on emotion recognition uses photographs of posed expressions. In this Review, Krumhuber et al. describe how dynamic information contributes to emotion recognition, beyond the information conveyed in static images.","PeriodicalId":74249,"journal":{"name":"Nature reviews psychology","volume":"2 5","pages":"283-296"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48447511","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}
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