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Problem Solving as a Predictor of Suicidal Thoughts and Behaviors
No full textSuicide is a major public health concern, particularly on college campuses. A number of risk factors have been identified in the prediction of suicidal thoughts and behaviors, including difficulty with problem solving. However, great variability exists in how problem solving is defined and measured in the literature. While problem solving has traditionally been conceptualized as a major component of executive functioning involving higher order intellectual or cognitive processes, social problem solving (SPS) involves one's beliefs and emotional reactions to stressful problems that are encountered in everyday life. The current study aimed to validate existing research that both neuropsychological measures of problem solving and SPS measures are separately correlated with deliberate self-harm behaviors and suicidal ideation. In addition, this study tested the hypothesis that social problem solving mediates the relationship between the neuropsychological measures of problem solving and the outcome measures of deliberate self-harm and suicidal ideation. The study sample consisted of 191 undergraduate students at Drexel University who were recruited via a participant management software. Graduate student assessors administered a demographics questionnaire, Short Portable Mental Status Questionnaire, Iowa Gambling Task (IGT), Tower of London (ToL), Social Problem-Solving-Revised: Short Form (SPSI-R:S), Deliberate Self-Harm Inventory, and Beck Scale for Suicide Ideation. If a participant reported a current wish to die or any intent to end his/her life, the assessor administered the Suicide Behaviors Questionnaire-Revised and completed an evidence-based suicide risk assessment and safety planning intervention. At completion of the study, each participant received a debriefing statement and list of counseling and emergency services. A bivariate correlation matrix determined that self-harm behaviors and suicidal ideation were significantly correlated with the SPSI-R:S, but not the IGT or ToL. Using individual regression analyses, the IGT and ToL were not found to be significant predictors of deliberate self-harm or suicidal ideation. The data therefore did not fulfill the basic requirements of the proposed mediation models. Exploratory analyses showed that when entered into the same model, the SPSI-R:S was the only problem-solving measure to make a unique statistically significant contribution to the prediction of deliberate self-harm and suicidal ideation. This study is among the first to assess the relative importance of neuropsychological and SPS constructs of problem solving in the prediction of suicide-related outcomes. The findings suggest that clinicians should consider evaluating individuals' social problem solving as part of a comprehensive suicide risk assessment, with a focus on emotional reactions to stress rather than the more intellectual or cognitive aspects of problem solving. Given the relationship between SPS and suicidal thoughts and behaviors, college students may benefit from Emotion-Centered Problem-Solving Therapy with an emphasis on handling real-world stressful problems and regulating negative emotions that interfere with effective problem solving.Ph.D., Psychology -- Drexel University, 201
Cumulative Risk Factors for Socioemotional Problems in Toddlers with Developmental Delays
No full textOffspring who encounter biological and psychosocial adversities early in development are vulnerable to lasting physical, mental, emotional, and social deficits across the lifespan, especially autism spectrum disorders (ASD) and socioemotional problems. Numerous individual risk factors have been linked with these problems separately in children of various ages. However, few studies have analyzed the effects of prenatal, perinatal, and early life exposure to cumulative risk factors in predicting socioemotional problems co-occurring with ASD in toddlers. The current study aimed to determine if ASD was associated with internalizing, externalizing, and dysregulation problems in toddlers, and if a novel measure of cumulative risk explained observed deficits above and beyond an ASD diagnosis. 344 participants from an ongoing multisite longitudinal study evaluating optimal timing for repeat ASD screening were divided into 3 groups based on a diagnosis given at a clinical evaluation by trained research staff: ASD (n = 107), developmental delays (DD; n = 145), and typical development (TD; n = 92). The Cumulative Risk Scale was developed from a developmental history questionnaire. The presence of a risk factor (e.g., prenatal SSRI exposure, prematurity, low birth weight, maternal psychiatric diagnosis) was coded as 1 and the absence as 0, and the sum total created each participant’s Cumulative Risk Score. After handling significant amounts of missing data with five iterations of multiple imputation, three multiple hierarchical regressions were conducted to determine if an ASD diagnosis was significantly associated with the Externalizing, Internalizing, and Dysregulation domain standard scores of the Infant-Toddler Social-Emotional Assessment (ITSEA). A second block of the hierarchical regression containing the novel Cumulative Risk Scale was added to determine if cumulative risk predicted these outcomes and increased the predictive ability of the model. The "segmented" package of R was then utilized to identify a linear or threshold relationship between cumulative risk and ITSEA outcomes. Results show that an ASD diagnosis was significantly associated with Internalizing problems ([beta] = .143, p = .035, 95% CI [.305, 8.430]), partially supporting the first hypothesis that an ASD diagnosis would be associated with internalizing, externalizing, and dysregulation problems. Further analyses show that both an ASD ([beta] = .278, p < .001, 95% CI [.088, .231]) and DD diagnosis ([beta] = .157, p = .010, 95% CI [.020, .149]) predict Depression/Withdrawal symptoms when controlling for child age. The addition of the Cumulative Risk Scale to the regression model improved prediction of Dysregulation problems only ([beta] = .103, p = .039, 95% CI [.027, 1.010], R2 change = .009, p = .039), partially supporting the second hypothesis that Cumulative Risk would significantly predict socioemotional problems. Further hierarchical multiple linear regressions showed cumulative risk significantly predicted Sleep Problems ([beta] = .101, p = .048) and Eating Problems ([beta] = .102, p = .045). Both hierarchical regressions showed a significant R2 change as well, but should also be interpreted with caution, as both increases were small (0.9% increases). An ASD diagnosis was significantly predictive of only the Negative Emotionality Subscale of the Dysregulation domain ([beta] = .151, p = .047). Results from the "segmented" package of R estimate a break point of 10.27 (p = .04171) for predicting Externalizing problems, but not Internalizing or Dysregulation problems. Toddlers ages 12-60 months with ASD are more likely to experience comorbid internalizing problems, which can have numerous clinical implications in the detection and prevention of internalizing problems early in life. Cumulative risk in early developmental periods overall does not explain socioemotional deficits in toddlers with ASD, DD, or with typical development. However, cumulative risk does predict dysregulation problems across children, regardless of diagnosis. A model depicting the relationship between cumulative risk in early developmental periods, dysregulation or non-disorder-specific socioemotional problems, and later psychopathology was proposed and should be investigated further in future research. A significant threshold of 10 risk factors was identified in predicting externalizing problems but may be possible in predicting internalizing and dysregulation problems as well. A more sensitive measure of cumulative biomedical risk early in life may also improve assessment of cumulative risk.M.S., Psychology -- Drexel University, 201
Method for Attaining Object-Side Light Fields and Metric Depth Maps from a Commercial Plenoptic Camera
No full textDetermining object distances and positions is a common computer vision task. This has obvious use in tasks such as autonomous navigation, robotic object retrieval, and surface profiling. Traditional methods for obtaining scene depth information may require active illumination, multiple cameras, or multiple exposures as hardware parameters are incremented. A plenoptic camera can be used to obtain scene depths and has the advantages of being passive and only requiring a single exposure with a single device. Traditional photographic cameras integrate all light arriving at a single detector element or film location, discarding information about the incidence angle of any individual contribution. In a plenoptic camera, an array of microlenses is placed in front of the image sensor, such that light arriving at a given microlens from different directions will arrive at different detector elements. With this, a signal can be attributed to all rays arriving at the microlens array, for which the assemblage is referred to as a "light field." Common light field operations include the creation multiple digital images from one exposure to simulate the effect of changing the camera's focal length ("digital refocus") and the determination of relative distances to scene objects. Existing light field methods are concerned with the light field within the camera (the "image-side light field"), as this is sufficient for most tasks. In contrast, this thesis describes a method for characterization of the light field external to a plenoptic camera (the "object-side light field") by performing experiments that determine the mapping from object-space rays to image-side light field coordinates. Use of an object-side light field allows for the determination of distances to scene objects in absolute terms, rather than the relative depths commonly obtained with image-side light fields. The object-side light field is obtained by observing the appearance of an occluding edge in the image-side light field as it is translated across the plane of the camera's front lens. Perspective images are created for simulated pinhole apertures at the front lens plane and used to view a patterned target, completing the characterization. In this thesis, descriptions of the characterized object-side light field are provided, offering an intuitive understanding of the structure of the light collected by the plenoptic camera. Demonstrations of common light field operations are provided to confirm that there is no loss of functionality through use of an object-side light field rather than an image-side light field. Simulations confirm that the distance to objects near to the camera can be determined to within 1~mm, with accuracy decreasing as the distance to an object increases.Ph.D., Electrical Engineering -- Drexel University, 201
How do we use interactive visualization to facilitate game designers to understand and design with machine learning
No full textMachine learning has recently reached a level of maturity sufficient for being useful to make game design. For example, work exists on automatic analysis of game designs, which could lead to significant reduction of design and production time. The recent successes of implementing machine learning have led to a wave of interest from game designers. Obtaining an understanding of machine learning, however, is difficult. We propose a web-based interactive visualization tool to offer a direct manipulation solution to facilitate game designers to understand and design with machine learning. Evaluation of our application through a panel of experts indicated that the interactive visualization is well-suited for helping designers gaining an intuition of the machine learning process. While a successful initial step towards assisting level design, further research is needed to make machine learning more understandable and useful to game designers.M.S., Digital Media -- Drexel University, 201
The Effect of Simulation on Learner Satisfaction and Self-Confidence Using Simulated CPR Education
No full text“Simulation as a teaching modality is gaining wide acceptance in nursing education in academia and clinical settings” (Nagle, McHale, Alexander, & French, 2009, p. 18). Contemporary research suggests simulation education can improve competence and enhance educational outcomes (McGaghie, Issenberg, Pertrusa, & Scalese, 2010). Many types of simulation devices exist which serve numerous functions. Providing cardiopulmonary resuscitation (CPR) training to employees is an important role of hospital nurse educators. The quality of training, changing cardiopulmonary resuscitation (CPR) guidelines, and a weakened chain of survival post cardiac arrest, all played a role in the decision to implement HeartCode® in one organization (American Heart Association (AHA), 2017). HeartCode® is a computerized self-learning cardiopulmonary resuscitation (CPR) certification course that uses simulation manikins to validate rescue breathing and chest compression skills (AHA, 2017). This project will examine the effect of a high-fidelity simulation on satisfaction, self-confidence and experience level using simulated CPR education.D.N.P., Nursing Practice -- Drexel University, 201
Application of Pattern Recognition Techniques to Aid in Detecting Degradation of a Pulsed Power System
No full textPulsed power is the release of energy over a small interval of time, resulting in a large peak in power at the load. MERCURY is a 2.2 TW pulsed power system used in experiments at the Naval Research Lab. During high power experiments, it was noted that the coating on the inductive cells was damaged. Throughout exploration of the system, researchers determined that when the trigger misfires, the switches can be damaged, which causes ringing and energy dissipation throughout the entire system. It was desired to use the data from the high power experiments to create a tool to automatically examine all of the signals associated with one shot or machine cycle of the pulse power system. A data structure was designed to organize and analyze the data associated with one shot. With this structure in place, it is easy to extract features about the system and explore degradation trends. By exploring these trends, an algorithm was designed to identify and predict when the pulsed power system begins to experience degradation. In this way, damage to the equipment could be prevented. Pattern recognition techniques such as nonlinear unsupervised clustering were applied to data from the MERCURY system, in order to predict and diagnose degradation of equipment.M.S., Electrical Engineering -- Drexel University, 201
The Impact of the NBA-Tencent Exclusive Streaming Agreement on Chinese Basketball Viewers
No full textChinese media company Tencent and the NBA entered into an exclusive streaming contract in 2015, changing the Chinese NBA market. Tencent operates one of the most popular websites in China, and owns Wechat and QQ, which are among the most popular chat applications and software in China. By cooperating with Tencent, the NBA was able to offer a better experience and variety of content to Chinese NBA fans. In addition, the NBA could deliver content to a wide-ranging audience, due to Tencent’s broad user base. However, this exclusive contract had a profound influence among Chinese NBA fans. In the past, viewers could only watch 1-2 live-stream NBA games. After the Tencent-NBA agreement, they could watch almost every NBA game. With a wide variety of choices came also the need to pay for the service. The era of free NBA games was gone, and in its place a new free-premium hybrid business model that offered free and paid content at the same time; if there were 10 basketball games on one day, they would live-stream two free games and the remaining 8 games were charged. This new business model began a new era for NBA viewers in China.M.S., Arts Administration -- Drexel University, 201
Stretch-and-Fold Method for Micro/Nano Fibers Fabrication and Mathematical Analysis of Instability
No full textThe success of the stretch-and-fold method illustrates a more efficient and productive method to manufacture micro/nano-fibers. In the manufacturing process, the theory of Rayleigh-Plateau Instability predicts that surface tension between core and clad interface will overcome the viscosity of the core/clad liquids. This leads to the break of the core into segments. By using a thermoplastic clad (Polycaprolactone, PCL), the dissociation motion of the core's fluid was delayed due to the high viscosity of the melted clad and was finally arrested by to the solidification of the clad at the room temperature. Meanwhile, operating temperature and stretch-and-fold cycle speed are also important factors in the fabrication. To explore the relationship among all these operational factors, experiments were conducted by producing 15/20/25 folds fibers. The manual stretch-and-fold process, weight ratio calculation, scanning electron microscope imaging, and mathematical model approach were the main tasks performed during the entire experiment. Finally, an analysis based on the collected data and mathematical approximation. A prediction is made between stability and related experimental factors.M.S., Mechanical Engineering and Mechanics -- Drexel University, 201
Evaluation of a Reminder System for Perinatal Psychiatric Appointments
No full textAbstract Background: Rates for missed appointments (no-shows) are especially high in psychiatry. Perinatal women are particularly at risk for missing appointments due to logistics such as childcare and transportation. Though rates of depression are higher for perinatal women than the general population, perinatal women often remain untreated. Appointment reminder systems are an effective method for increasing appointment attendance and cancellations. Literature suggests providing two reminders within seven days of the appointment. Maintaining accurate patient contact information is a challenge to delivering reminders. Purpose: Compare the appointment reminder system of a large, urban hospital to evidence-based practice in an effort to reduce the 60% no-show rate within its perinatal psychiatry service. Methods: A two-hour work-group meeting with five identified key experts evaluated the appointment reminder system within the perinatal psychiatry service. A semi-structured interview compared the intended appointment reminder process to its actual delivery. Strengths and challenges were identified. Results: The institution’s appointment reminder system consists of one automated reminder 48 hours prior to the appointment. The scheduling database is not updated to reflect patients who cancel appointments, causing available appoint times to remain unfilled. Depending on the referral source, some patients receive additional personal reminders from clinicians. Conclusions: The current appointment reminder system may benefit from adding an additional reminder based on evidence-based practice which suggests two reminders are preferred. Attention should be given to appointment cancelations to optimize provider time and increase patient access. Keywords: appointment reminders, SMS reminders, appointment no-show.D.N.P., Nursing Practice -- Drexel University, 201
Health Needs Assessment of the Theravada Buddhist Monastic Community in the Northeast USA
No full textThe Theravada Buddhist monastics community living in the northeastern United States of America is a vulnerable population that is not given much attention in the sphere of public health. This needs assessment sought to start laying the foundation for future research and projects to help this population. Information collected through this study has shown that there are some issues within the monastic community, such as a lack of knowledge regarding having regular wellness and care visits and lack of awareness of available community health care services. Additionally, the relationship between the monastic code of conduct and health outcomes was apparent. The results of this needs assessment and potential further areas of study on this population are discussed.M.P.H., Community Health and Prevention -- Drexel University, 201