Phototherapy as an Intervention in Identity Development with Adolescents.

Identity development in adolescence is a period of exploration and experimentation. During this stage of development, adolescents are defining their identity in terms of ethnicity, sexual orientation, and gender. It can be a confusing time and the lack of resources and support influence the ability of the adolescent to form a cohesive identity. This struggle to define an identity may lead to symptoms of depression and difficulties with interpersonal relationships. Identity interventions are limited and primarily involve the adolescent talking to a therapist and attempting to verbalize and define subjective distress. The use of a phototherapy intervention focuses on using an adolescent's subjective experiences. Phototherapy provides a way for the therapist and client to explore the photographs the client takes and opens different avenues in the areas of non-verbal and visual communication. Photographs can also promote increased communication about an adolescent's ethnic, sexual or gender identity. Interpretations made by the adolescent about images in the photographs will get in touch with emotional experiences that may be missed in traditional "talk therapy." This paper reviews literature on identity development, specifically in the areas of ethnicity, sexual orientation, and gender identity. Phototherapy, the use of photography to enhance traditional psychotherapy, is described and a rationale is provided for the utilization of phototherapy in adolescent identity development. Vignettes are provided illustrating how phototherapy can be used when working with adolescents who are questioning and exploring ethnic identity, sexual orientation, and gender identity.

The Impact of Transit Oriented Development on the Travel Behaviors of Workers in Denver, Colorado

To combat unsustainable transportation systems characterized by reliance on petroleum, polluting emissions, traffic congestion and suburban sprawl, planners encourage mixed use, densely populated areas that provide individuals with opportunities to live, work, eat and shop without necessarily having to drive private automobiles to accommodate their needs. Despite these attempts, the frequency and duration of automobile trips has consistently increased in the United States throughout past decades. While many studies have focused on how residential proximity to transit influences travel behavior, the effect of workplace location has largely been ignored. This paper asks, does working near a TOD influence the travel behaviors of workers differently than workers living near a TOD? We examine the non-work travel behaviors of workers based upon their commuting mode and proximity to TODs. The data came from a 2009 travel behavior survey by the Denver Regional Council of Governments, which contains 8,000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-automobile transportation. The results of this study indicate that closer proximity of both households and workplaces to TODs decrease levels of car commuting and that non-car commuting leads to more sustainable personal travel behaviors characterized by more trips made with alternative modes.

The role of the social environment in non-suicidal self-injury among LGBTQ youth: A mixed methods study

Non-suicidal self-injury (NSSI), such as cutting and burning, is a widespread social problem among lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) youth. Extant research indicates that this population is more than twice as likely to engage in NSSI than heterosexual and cisgender (non-transgender) youth. Despite the scope of this social problem, it remains relatively unexamined in the literature. Research on other risk behaviors among LGBTQ youth indicates that experiencing homophobia and transphobia in key social contexts such as families, schools, and peer relationships contributes to health disparities among this group. Consequently, the aims of this study were to examine: (1) the relationship between LGBTQ youth's social environments and their NSSI behavior, and (2) whether/how specific aspects of the social environment contribute to an understanding of NSSI among LGBTQ youth. This study was conducted using an exploratory, sequential mixed methods design with two phases. The first phase of the study involved analysis of transcripts from interviews conducted with 44 LGBTQ youth recruited from a community-based organization. In this phase, five qualitative themes were identified: (1) Violence; (2) Misconceptions, Stigma, and Shame; (3) Negotiating LGBTQ Identity; (4) Invisibility and Isolation; and (5) Peer Relationships. Results from the qualitative phase were used to identify key variables and specify statistical models in the second, quantitative, phase of the study, using secondary data from a survey of 252 LGBTQ youth. The qualitative phase revealed how LGBTQ youth, themselves, described the role of the social environment in their NSSI behavior, while the quantitative phase was used to determine whether the qualitative findings could be used to predict engagement in NSSI among a larger sample of LGBTQ youth. The quantitative analyses found that certain social-environmental factors such as experiencing physical abuse at home, feeling unsafe at school, and greater openness about sexual orientation significantly predicted the likelihood of engaging in NSSI among LGBTQ youth. Furthermore, depression partially mediated the relationships between family physical abuse and NSSI and feeling unsafe at school and NSSI. The qualitative and quantitative results were compared in the interpretation phase to explore areas of convergence and incongruence. Overall, this study's findings indicate that social-environmental factors are salient to understanding NSSI among LGBTQ youth. The particular social contexts in which LGBTQ youth live significantly influence their engagement in this risk behavior. These findings can inform the development of culturally relevant NSSI interventions that address the social realities of LGBTQ youth's lives.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.