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Understanding South Asian American Adolescent Suicidality from an Interpersonal Theory of Suicide: A Case Study
No full textThrough an interpersonal lens of suicide, South Asian youth are navigating complex acculturative factors, familial dynamics, and identity formation which can increase the risk of suicidal ideation and suicide attempts. This paper discusses the cultural, contextual, and societal factors salient to an interpersonal theory of suicide for South Asian youth. This paper also discusses the value and limitations of working with intrapsychic and interpersonal dynamics related to suicidality from a psychodynamic perspective. It ends with clinician considerations and suggestions for future research
Sport and Performance Psychology Service Provision Needs and Preferences of Division-I Student-Athletes, Coaches, and Program Stakeholders at a Private University
No full textIn response to increased reports of mental health concerns among NCAA Division I collegiate student-athletes (Wong, 2017), investigators examined the Sport and Performance Psychology (SPP) service provision needs and preferences of Division I student-athletes, coaches, and program stakeholders within a Division I athletic program. A survey-based needs analysis was employed to provide a comprehensive analysis of: (a) the needs of student-athletes receiving SPP services; (b) help-seeking attitudes of student-athletes receiving SPP services; (c) key stakeholder (i.e., athletic administrators, coaches, athletic trainers, and strength and conditioning coaches) attitudes toward SPP services; (d) key stakeholder perceptions of the SPP needs of their student-athletes; (e) gaps in SPP service care; and (f) barriers to accessing SPP services. The findings revealed significant gaps in accessibility and visibility of SPP services, alongside a notable stigma amongst student-athletes associated with utilizing these services. Moreover, scheduling conflicts emerged as a predominant barrier. These results are discussed in relation to strengthening the effectiveness of service provision through strategic enhancements in visibility, accessibility, and comprehensive education about the benefits of SPP services
Connecting Through Stories: Analyzing Cultural Representation and Emotions in Children\u27s Literature to Inform the Development of a Dialogic Reading Intervention for Latine Fathers and Children
No full textThis study employed a mixed-methods content analysis, involving the random sampling of children\u27s books, which were each read four times to ensure thorough coding. A detailed codebook was developed, encompassing subthemes and overarching themes, to systematically examine the representation of Latine families, emotional expressions, gender roles, and socio-emotional dialogues contained in a sample of 57 children’s books. Findings showed significant gaps in the representation of Latine characters, with Latine protagonists being notably underrepresented despite their demographic prominence in the U.S. The analysis highlighted a predominance of White and non-human protagonists, limited emotional expression beyond joy, and majority reinforcement of traditional gender roles. Additionally, socio-emotional dialogues were scarce, emphasizing the need for more diverse and inclusive portrayals of characters. These findings highlight a potential developmental and/or clinical application, a dialogic reading intervention in the form of a children’s book which features diverse Latine protagonists who experience a dynamic range of emotions. An outline of a book which could be the basis of a fun and engaging intervention for socio-emotional dialogues between fathers and children, which simultaneously promotes emotional literacy, cultural pride, and healthy masculinity is provided
Extending the Utility of Ant Colony Optimization Through the Incorporation of an Intraclass Correlation Coefficient to Assess for Rater Consistency
Get PDFAnt Colony Optimization (ACO) is a flexible algorithm designed to solve complex combinatorial problems. While the method was derived from the behavior of ants by researchers in the field of computer science, its application to solving complex combinatorial problems is widespread in a growing number of fields in behavioral science, including psychometrics. Over the last two decades, psychometricians have adapted ACO to measurement model specification problems with the intention of generating measurement models that express measurement model fit and reliability within the standards of what is considered acceptable. Additionally, psychometricians have used ACO to generate shortened versions of existing measures while preserving the integrity of other psychometric properties (e.g., model fit, validity, and reliability). The current study sought to extend the utility of ACO by incorporating the intra-class correlation coefficient (ICC) as an optimization criterion in seeking an optimal (or near-optimal) measurement model solution. The introduction of ICC to ACO procedures is intended to address data that features multiple observations of the same targets from multiple raters and was the first of its kind. The study featured a new measure designed to capture the quality of telephonically delivery crisis intervention services, the Multidimensional Crisis Monitoring Form (MCMF-3). Scores from the ACO-derived measurement models were further tested to examine the relationship between the quality of universal screening questions asked by crisis workers, and the subsequent quality of their approach to the crisis management process as captured by the MCMF-3. Implications for future research and use of AI-driven techniques in behavioral health measurement practices are discussed in response to the study results
Data as Likeness
No full textArtificial intelligence (AI) and data collection practices pose an ongoing threat to consumers’ privacy. But plaintiffs have struggled to articulate privacy harms associated with data collection in a way that would give them standing to sue. This is a particularly pressing issue given the advances in generative AI and the unauthorized uses of individuals’ personal and biometric data.
This Article revisits the privacy tort of appropriation of likeness and argues that when data are conceptualized as likeness, this tort offers a unique opportunity to protect against the unauthorized collection and use of personal data. Grounding its argument in the historical evolution of the tort of appropriation, this Article contends that an individual’s personal data are an aspect of a person’s unique digital identity, mostly used by third parties in a data-driven world, which should be covered by this tort.
Conceptualizing unauthorized personal data collection in this manner underscores the evolving nature of the common law of torts in recognizing new forms of harms. It offers a solution for the current gridlock on data protection measures and the unauthorized use of one’s data in emerging generative AI technologies such as deep voice. Recent Supreme Court decisions have insisted that privacy victims must show some form of concrete harm to achieve constitutional standing.
Accordingly, employing the privacy tort of appropriation of likeness and recognizing the concept of digital persona allow plaintiffs to establish standing by identifying a close historical or common law analogue for their asserted privacy injury. Lastly, similar to other privacy torts, this approach can survive First Amendment objections
Applications of Computer Vision in Biomechanics and Orthopaedics
Get PDFMachine learning has emerged as a key technology for enabling advanced computer vision systems. These systems now permeate many industries, and have enhanced traditional processes through autonomous interpretation of visual data. In the field of orthopaedics, the increasing prevalence of imaging highlights a need for similar tools. In many cases, however, direct translation of available frameworks fails to resolve the complex problems currently facing this field. Stringent performance requirements, complex visual environments, data scarcity, and implications for patient safety represent domain-specific factors which pose unique challenges to proven techniques. Novel approaches are needed to realize the full benefits of visual understanding from orthopaedic modalities.
This dissertation contributes to expanding the role of computer vision in the field of orthopaedics. Progress is made along two distinct axes spanning both research and industry settings. The first part of this work concerns 6 degree-of-freedom pose estimation of native anatomy in dynamic stereo-radiography. Frameworks are introduced which can localize skeletal structures of the knee and shoulder with a high degree of accuracy, and with no required manual interaction. The resulting systems may catalyze large-scale investigative efforts or clinical use cases through efficient measurement of in vivo movement. The second part of this work focuses on the role of computer vision in orthopaedic procedures. It is contended that markerless computer vision algorithms based on machine learning may benefit intraoperative monitoring and navigation by alleviating limitations of existing technical approaches. Two applications are then investigated: pose estimation of a surgical instrument, and image-guided surgical navigation for robot-assisted drilling. In the first application, the accuracies of pose estimates fail to meet requirements associated with navigation systems. Recommendations for future improvements are thus presented. In the second project, the realized navigation framework is shown to replicate preoperative plans with precision that is on par with commercial robotic systems. The experiments and methods described in this work represent small but significant steps towards harnessing computer vision to improve patient outcomes in orthopaedics
Harmonic Data: AI Music, EDM Transcription, & Minimalist Jazz
Get PDFThis thesis presents research in the domains of music theory and music technology. The topics of the three chapters are as follows: (1) the technical and artistic limitations of artificial intelligence when generating music, (2) the transcription of electronic dance music (EDM) using a hybrid notation system, and (3) the effective convergence of jazz and minimalism in the music of Joe Hisaishi from Studio Ghibli. Each topic investigates a different aspect of harmony and the modern ways in which humans communicate in terms of harmony. The first chapter surveys the latest research projects in AI-generated music and proposes ideas for future applications of music generation using machine learning. The second chapter presents a hybrid notation system for the transcription of electronic dance music. The final chapter identifies progressive composition techniques embodied in the works of Japanese composer Joe Hisaishi, who borrows musical influence from around the world
Flower Study
No full textThis project is a study into extinct flowers, their histories, environments, biology, colors, and assigned personalities then manifested in 3D models and a digital book. The goal was to select six flowers with interesting histories and or cultural connections. Since the flowers can, for the most part, not be seen or kept they were created in Blender as accurately as possible. To give people a means of connection with the flowers, each was assigned a personality based on different factors. These factors could be the colors they possess, where geographically they thrived, parts of their history, and biological factors. To allow these personalities to further flourish color spaces were created in Affinity Designer to be applied not only as the background of the models but the background of half of the book’s pages. The digital bool was created in Affinity Designer, and it sports rendered images of the 3D modeled flowers, information on the flowers, and a designed page with the flowers, their name in chrome lettering created in Adobe Illustrator and Blender, and the aura color spaces. Each person who interacts with the book is encouraged to pick out flowers they connect to and create their own garden of these now-gone flowers