PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1928
Browse
2 results
Search Results
Article Citation - WoS: 1Citation - Scopus: 1Body Appreciation Matters: The Associations Between Self-Compassion, Body Appreciation, and Disordered Eating Behaviors Among Heterosexual and LGBI+ Emerging Adults in Türkiye(SAGE Publications Inc., 2025-08-06) Deveci, A.N.; Toplu-Demirtaş, E; Bulgan, G.; Toplu Demirtaş, Ezgi; Demirtas, Ezgi TopluObjectives: Self-compassion has been effective in the prevention and treatment of disordered eating behaviors and body image issues, which are significant public health concerns with potential psychosocial and physical consequences. Furthermore, there remains a substantial gap in the existing body of research, particularly in the context of heterosexual, lesbian, gay, and bisexual plus (LGBi+) emerging adults in Türkiye. Therefore, this study aims to explore the mediating role of body appreciation in the relationship between self-compassion and disordered eating behaviors and the moderating role of sexual orientation (heterosexual and LGBi+) in the mediation among emerging adults. Methods: A diverse sample of participants comprising heterosexual (n = 242) and LGBi+ (n = 204) emerging adults (Mage = 22.18; SDage = 3.07; min = 18; max = 30) completed self-report measures of the Self-Compassion Scale, Body Appreciation Scale-2, and Eating Attitude Test-26. Results: The results of moderated meditation revealed that body appreciation mediated the relationship between self-compassion and disordered eating behaviors among both heterosexual and LGBi+ individuals. Conclusions: The findings may inform support strategies and interventions to reduce eating disorder risk and promote mental health and well-being in both heterosexual and LGBi+ populations by emphasizing self-compassion and body appreciation. © The Author(s) 2025Conference Object Citation - WoS: 3Citation - Scopus: 3Detecting Autism From Head Movements Using Kinesics(Assoc Computing Machinery, 2024-11-04) Gokmen, Muhittin; Sariyanidi, Evangelos; Yankowitz, Lisa; Zampella, Casey J.; Schultz, Robert T.; Tunc, BirkanHead movements play a crucial role in social interactions. The quantification of communicative movements such as nodding, shaking, orienting, and backchanneling is significant in behavioral and mental health research. However, automated localization of such head movements within videos remains challenging in computer vision due to their arbitrary start and end times, durations, and frequencies. In this work, we introduce a novel and efficient coding system for head movements, grounded in Birdwhistell's kinesics theory, to automatically identify basic head motion units such as nodding and shaking. Our approach first defines the smallest unit of head movement, termed kine, based on the anatomical constraints of the neck and head. We then quantify the location, magnitude, and duration of kines within each angular component of head movement. Through defining possible combinations of identified kines, we define a higher-level construct, kineme, which corresponds to basic head motion units such as nodding and shaking. We validate the proposed framework by predicting autism spectrum disorder (ASD) diagnosis from video recordings of interacting partners. We show that the multi-scale property of the proposed framework provides a significant advantage, as collapsing behavior across temporal scales reduces performance consistently. Finally, we incorporate another fundamental behavioral modality, namely speech, and show that distinguishing between speaking- and listening-time head movements significantly improves ASD classification performance.