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Findings on the association between smartphone use and cognitive and socioemotional outcomes in middle-aged and older adults are mixed. Given that previous studies have not considered smartphone-use patterns across a variety of applications, we examined the relations between latent smartphone-use profiles and depressive symptoms, life satisfaction, and cognitive failures. We analyzed data from 7,810 healthy middle-aged and older adults (M.sub.age = 61.45, SD = 5.89) who participated in the Singapore Life Panel study. By concurrently considering 10 smartphone activities-calling, messaging, alarms, photography, social networking services, watching videos, playing games, online banking/ shopping, maps/navigation, and voice assistance-we identified five distinct profiles: nonuse, basic and restrained use, social interaction and entertainment, traditional communication, and advanced maximization. We found significant profile differences in depressive symptoms and life satisfaction but not in cognitive failures. Specifically, the traditional communication profile showed significantly fewer depressive symptoms than the social interaction and entertainment, basic and restrained use, and nonuse profiles. Advanced maximization profile also yielded similar results but to a lesser extent. Regarding life satisfaction, the advanced maximization-followed by the social interaction and entertainment-profiles were found to be more beneficial than the other profiles. These results held when multiple covariates were controlled for. Together, our findings demonstrate that individuals with more active use of advanced and wide-ranging functions-particularly communication, social interaction, and entertainment-experience higher life satisfaction and reduced depressive symptoms. Using a person-centered approach, our findings underscore substantial heterogeneity in middle-aged and older adults' smartphone activities and their different psychological implications., Author(s): Hwajin Yang [sup.1] , Germaine Y. Q. Tng [sup.1] , Shuna S. Khoo [sup.1] , Anshu Te [sup.1] Author Affiliations: (1) https://ror.org/050qmg959, grid.412634.6, 0000 0001 0697 8112, School of [...]

The web-based supported collaborative learning is increasingly used to support student social activities in higher institutions. However, little is known about the factors of collaborative learning in a web-based supported learning environment. Therefore, this study examines the use of a web-based supported collaborative platform to enhance project-based student engagement. This research aims to determine the factors that determine collaborative learning and subsequent student satisfaction. Moreover, this research determines students' cognitive load understanding, social influence, and learner's motivation towards collaborative learning and the resultant impact of the web-based supported collaborative platform on student satisfaction. The data was collected from university post-graduate students who used the TRELLO platform. A total of 115 post-graduate students participated in this study, and the resulting data were analyzed based on partial least squares structural equation modelling statistical approach. The study results suggest that students' social influence and motivation positively influence collaborative learning; directly and indirectly, students are satisfied using a web-based supported collaborative learning platform to support project-based student engagement., Author(s): Dokun Oluwajana [sup.1] , Ibrahim Adeshola [sup.2] , Seyefar Clement [sup.3] Author Affiliations: (1) grid.440833.8, 0000 0004 0642 9705, Department of Management Information Systems, Cyprus International University, , Nicosia, [...]

Conversational agents or chatbots are a novel, highly accessible, and low-resource method of psychological intervention delivery. The present research aims to compare two brief chatbot interventions that delivered cognitive restructuring and defiision interventions, respectively. It was hypothesized that a defusion chatbot would lead to reduced cognitive fusion and decreased thought believability relative to cognitive restructuring and a nonactive control. Participants (N- 223; M age of 28.01 [SD = 10.29]; 47 identified as male, 174 as female, and 2 as nonbinary) were randomized into one of three conditions (defiision, restructuring, control), engaged for 5 days completing thought and mood measures pre- and postintervention. Sixty-two participants (M age of 25.98; SD = 8.647 years) completed measures again at time 2 (49 identified as female, 12 as male, and 1 as nonbinary). No statistically significant differences were observed among groups on believability of thoughts (F[2, 25] = .79,p = .47, [eta][p.sup.2] = . 06), negativity of thoughts (F[2,25] = 1.49, p= .25, [[eta].sup.2] = .11), discomfort associated with thoughts (F[2, 25] = .48 ,p = .62, [eta][p.sup.2] = .04), and willingness (F[2, 25] = 3.00, p = .07, r[eta][p.sup.2] = .19) to have negative self-referential thoughts. Moreover, substantial attrition of 72% was observed. Acceptability and usability of the chatbots employed are discussed as contributing toward the limited effectiveness of interventions and elevated attrition. Various recommendations are presented to support researchers and clinicians in developing engaging and effective chatbots. Keywords cognitive defusion * cognitive restructuring * chatbot-delivered interventions * negative self-referential thoughts, Negative self-referential thoughts are those self-relevant thoughts that are critical, derogatory, or self-defeating in nature (Clark & Rhyno, 2005). Cognitive models of psychopathology have long asserted the involvement of negative [...]

This action research study has two aims: (i) to develop a wearable virtual reality language-learning platform for English for specific purposes and (ii) to examine student learning effectiveness and the relationship between self-efficacy and behavioral intention. The participants are 131 university students in Taiwan. A model of wearable virtual reality language-learning based on structural equation modeling is built. A path analysis indicates that self-efficacy directly influences students' perceptions of ease of use of the wearable virtual reality technology and indirectly influences perceived usefulness, attitude, and behavioral intention. Student self-efficacy is slightly above the moderate level. Gender and English proficiency have an effect on student self-efficacy and behavioral intention, whereas students' online and virtual reality learning experiences have no significant effect on these variables. This new environment is shown to facilitate student learning: the pretest and posttest results indicate improvements in lexical and semantic knowledge, reading comprehension, and syntax. The study implies that since self-efficacy is a crucial determinant in student technology use, educators should enhance student self-efficacy in order to encourage them to try innovative technology., Author(s): Chun-Chia Hsu [sup.1] , Yu-Li Chen [sup.2] , Chih-Yung Lin [sup.1] , Wei-chih Lien [sup.2] Author Affiliations: (1) grid.445089.4, 0000 0004 0639 3159, Department of Multimedia and Game Science, [...]