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AUTISM SPECTRUM DISORDER AND ITS EFFECTS ON PARENT RELATIONSHIPS
Get PDFABSTRACT
This proposed study aims to explore the impact of Autism Spectrum Disorder (ASD) on parental relationships. ASD is defined as a neurological developmental disorder that significantly affects individuals\u27 social communication, behavior, and interests. The study will focus on the Parents of children with (ASD) and the heightened stress due to financial strain, increased caregiving responsibilities, and disagreements over parenting strategies. This can lead to lower marital satisfaction and overall relationship strain, as parents struggle to balance their personal relationship with the challenges of raising a child with complex needs.
Without proper support and resources, these issues may worsen over time, potentially resulting in emotional burnout, decreased couple intimacy, and long-term damage to the stability of the family unit. The proposed study will use a qualitative research approach, gathering firsthand accounts from 17 to 40 parents of children with ASD. This approach will provide deep insights into the personal experiences and challenges these parents face in their relationships. Ethical guidelines will be strictly followed throughout the research. Informed consent will be obtained from all participants, and measures will be implemented to ensure confidentiality and data security. The primary goal of this study is to better understand the unique challenges faced by parents of children with ASD. By shedding light on these difficulties, the research seeks to emphasize the need for tailored support and resources to improve the well-being of parental relationships
ISLAMS’ INFLUENCE ON MENTAL HEALTH
Get PDFThis proposed study explores the intricate relationship between Islam and mental health among Muslims in the United States. The study employs a mixed methods approach to provide a comprehensive understanding of this dynamic. Given the significant role spirituality plays in mental health, this research integrates qualitative interviews and quantitative surveys to capture these perspectives, specifically in the Muslim community. The qualitative portion will consist of in-depth interviews to cover personal experiences and beliefs about Islam and mental well-being. Concurrently, quantitative surveys will be conducted to collect broader data on religious practices and their mental health outcomes. Significant gaps and barriers to accessing mental health services will be assessed. The study aims to include a sample across different ages, ethnicities, and levels of religiosity. Data collection will be conducted through secure and ethical means, ensuring confidentiality and informed consent. This study addresses the significant gaps in the literature, including the need for more culturally sensitive approaches and mental health interventions, which consist of a deeper understanding of the true influence of Islamic practices on mental health. The ultimate goal of this paper is to bridge the gap between spirituality and psychology, contributing valuable insight for mental health professionals to consider
From Barriers to Bridges: Counseling for Inlcusion and Student Empowerment
No full textThis project outlines my approach to counseling, which is all about empathy, empowerment, and advocating for change within systems that need it. I use a combination of Narrative Therapy and Solution-Focused Therapy to guide students in identifying their strengths and tackling the challenges they face, both personally and academically. I believe each client is the expert of their own life, and my job is to create a space where they feel safe, understood, and supported as they explore their experiences and make decisions. A big part of my practice is acknowledging and addressing systemic issues like racism and sexism, ensuring that everyone feels heard and valued. I want to create an environment where all students, no matter their background, have the opportunity to thrive. As a change agent, I help students build resilience, advocate for themselves, and challenge the systems that hold them back. I also focus on promoting a culture of respect and allyship in educational settings. My approach is rooted in cultural humility, professional ethics, and always putting the client’s needs first. My goal is to help students grow into their fullest potential while also addressing the systems that create inequality and exclusion. I’m committed to lifelong learning and reflection, ensuring that my practice evolves in ways that best serve each student I work with. By focusing on individual growth and systemic change, I aim to make a real difference in the lives of my clients and the communities they belong to
COMPARISON ON FAMILY-BASED REHABILITATION AND INDIVIDUAL BASED: EFFECT ON CHILDREN AND FAMILIES
Get PDFThis proposed research aims to discover the success of sobriety with rehabilitation programs, specifically those that are family based as compared to individual based. This research will also investigate the measures taken within these rehabilitation programs to prevent generational substance abuse problems. Social workers will benefit from this research by discovering how these programs are successful and if any changes could be made to increase the success rates for those struggling with substance abuse. This research will also allow social workers to develop new strategies to assist in preventing generational substance abuse within families. This study will include interviewing individuals that have completed or partially completed a rehabilitation program that was family based and individuals that completed or partially completed a rehabilitation program that was individual based. The data will be interpreted from focus groups conducted via Zoom meetings
ONE, TWO, THREE, PLAY WITH ME!: A WORKSHOP ON CULTIVATING PLAY EXPERIENCES FOR INFANTS AND TODDLERS
No full textThough infants and toddlers are sometimes underestimated, extensive research documents how rapid brain development is occurring within these early years. Brain development depends on early experiences. That is why it is crucial for these experiences to occur during this critical time of heightened sensitivity to stimulation. Learning experiences for infant and toddlers takes place with play. Establishing environments that cultivate play and offer ample opportunities to engage in play are crucial for development and growth. However, for some children and families, they may encounter barriers to play. Children with disabilities encounter unique barriers such as inaccessibility to adequate environments and social exclusion (Barron et al., 2016; Centers for Disease Control and Prevention, 2022). In addition, Mexican American families encounter barriers to play such as lack of knowledge and materials to optimize play experiences (Aikens & Barbarin, 2008; Fletcher, 2020).
The purpose of this project was to create an evidence based educational workshop for parents and caregivers to learn about the importance of play and how to provide optimal play experiences. The contents of the proposed workshop include the following topics: Why the Early Years Matter, The Power of Play for Development, Provision of Optimal Play Experiences, and Becoming Play Experts. Ultimately, this workshop has the potential to provide valuable information for parents and caregivers, and anyone who works with young children and families
HOW PERSONALITY AND WORK CONTEXT CONTRIBUTE TO THE EMERGENCE OF STAR EMPLOYEES: THE CRITICAL ROLE OF GRIT, EXTRAVERSION, AND POLITICAL SKILL
Get PDFAlthough research on star employees has been around for a while, only a few studies have examined star employees\u27 emergence. Star employees are responsible for a significant amount of organizational success. Their contribution can be seen in various areas such as organizational reputation and the attraction of talent and customers, peers’ influence in the shape of motivation, commitment, and productivity, and revenue. The positive outcomes associated with stars have driven the increased need for such employees. This research investigates the personality traits and the work context that predict stardom. Specifically, the research has three aims: a) understanding who star employees are, b) identifying characteristics of star employees, and c) examining the influence of the organizational environment and work design on star formation. A multivariate path analysis was conducted to examine the relationship between the predictors (i.e., grit, conscientiousness, extraversion, and political skill) and the four dimensions of stardom (e.g., performance, status, visibility, and social capital). Results supported hypotheses 1- 4, confirming the relatedness of grit, conscientiousness, extraversion, and political skill to stardom. In addition, the SMART work design model was used to investigate the moderation effect of mastery, autonomy, and relational job characteristics on the above directional relationships. Results indicated that work characteristics have little meaningful impact on star emergence, as only hypothesis 7a3 was supported, such that mastery strengthened the relationship between grit and stardom visibility. Furthermore, relative weights analysis was conducted to examine the weight each predictor (e.g., grit, political skill) accounts for in stardom. Results for research question 1 revealed that political skill accounted for the most variance in stardom compared to the other predictors
Law Enforcement Perspectives Towards Mental Health Crisis Interventions
Get PDFMental health crisis calls create significant challenges for law enforcement officers, who often serve as the first responders to individuals experiencing psychological distress. Research indicates that 50% of fatal encounters with law enforcement involve individuals with a mental health disorder (Fuller et al., 2015; Kindy & Elliott, 2015). Although the increasing prevalence of mental health- related calls, law enforcement officers frequently lack the specialized training and resources necessary to effectively de-escalate these situations (Cohen & Bagwell, 2023). As a result, interactions between police officers and individuals with mental illness tend to lead to criminalization, unnecessary incarceration, and even fatal outcomes. The introduction of interdisciplinary crisis response models, such as Crisis Intervention Teams (CITs) and police-social worker or mental health professionals\u27 collaborations- has gained attention as potential solutions to bridge the gap between public safety and mental health intervention (Wills et al., 2013). However, limited research has explored law enforcement officers’ perceptions of their preparedness to handle mental health crisis calls, as well as their perspectives on alternative response strategies.
This study seeks to examine the attitudes, perceptions, and experiences of law enforcement officers in responding to mental health crisis calls, with a specific focus on their views regarding training adequacy, barriers to effective interventions, and the integration of mental health professionals into crisis response teams. A qualitative research approach will be employed, utilizing semi-structured interviews with law enforcement officers across agencies in Riverside County. This study will explore officers\u27 self-perceived preparedness, preferred intervention strategies, and recommendations for improving crisis response protocols. This study does not aim to assume that expanded training or interdisciplinary collaborations are the most effective solutions, their research will remain open-ended, allowing officers to articulate their own insights into what would improve outcomes for both law enforcement and individuals in crisis
CONSTRUCTING BINARY ENCODING MATRICES FROM JOINED GRAPHS
Get PDFCodes and technology are part of our daily lives and allow the modern world to function, and for us to have conveniences in our lives such as smartphones that can be used to privately call people on the other side of the planet, and for secure access to the internet. In this thesis we will explore the construction of binary codes created by vertex-edge incidence matrices of planar graphs. The Hamming (7,4) code was an incredible code that allowed the detection and correction of errors after receiving them through a transmission. We will explore the possibility of the creation of generator matrices that can detect and possibly correct errors that occur due to interference caused between the message being sent and it being received. Here, we will provide a proof for tree and cycle graphs, as well as a basis for other graphs and future work
EXPLAINABLE AI (XAI) FOR A MACHINE LEARNING HEART DISEASE PREDICTION MODEL
Get PDFCardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, necessitating the development of accurate and interpretable machine learning (ML) models for early diagnosis and risk assessment (World Health Organization, 2021). While ML algorithms such as logistic regression, decision trees, support vector machines (SVM) (Cortes & Vapnik, 1995), and deep learning models (LeCun et al., 2015) have demonstrated high predictive accuracy, their adoption in clinical practice is hindered by their black-box nature (Rudin, 2019). Explainable AI (XAI) techniques, including SHapley Additive Explanations (SHAP) (Lundberg & Lee, 2017), Local Interpretable Model-agnostic Explanations (LIME) (Ribeiro et al., 2016), and feature importance analysis aim to bridge this gap by improving model transparency and interpretability (Doshi-Velez & Kim, 2017). This study explores the effectiveness of various ML algorithms for heart disease prediction and examines how XAI techniques enhance their interpretability. Furthermore, it investigates the role of model transparency in influencing clinician trust and adoption of AI-based diagnostics. Research indicates that interpretable AI models foster greater trust among healthcare professionals, as they align with established medical knowledge and facilitate informed decision-making. Despite these benefits, challenges such as computational complexity, trade-offs between accuracy and interpretability, and ethical concerns regarding patient data privacy persist. The findings highlight the necessity of integrating XAI techniques into ML models to ensure high accuracy and transparency in heart disease prediction. By addressing existing challenges, AI-driven diagnostics can be effectively incorporated into clinical workflows, ultimately improving patient outcomes and supporting evidence-based medical decision-making
TIME SERIES DEEP LEARNING APPROACH FOR THE INTERMITTENT OPERATIONAL PERFORMANCE OF A WELLHEAD WATER TREATMENT AND DESALINATION SYSTEM
Get PDFDistributed water treatment and desalination (DWTD) systems are becoming significant for serving disadvantaged communities that are geographically segregated from centralized water distribution networks. However, given the remote nature of the communities, these systems must operate autonomously adapting to intermittent operations due to varying water use patterns and unavailability of continuous manual labor support. Machine Learning models describing and forecasting system performance are critical, allowing for model-based control, performance forecasting, fault detection, and determination of causal relationships among process attributes. Accordingly, graph convolutional neural networks with an attention mechanism (GATConv) were developed to describe the intermittent operational profiles of a wellhead water treatment system deployed in a small remote disadvantaged community in California. Time-series data from 22 system sensors was compiled for the four operational modes (startup, permeate production, shutdown, flushing) and three outcomes (nitrate passage (%), salt passage (%), and permeate flux (LMH)). GATConv models with 3 hidden layers, 16 hidden nodes and 8 attention heads in each layer were developed based on 4 months of operational data, consisting of over 6 million samples, each containing 22 sensor data points. GATConv models demonstrated excellent accuracy with R2 \u3e 0.95 for prediction of permeate flux for up to 1 month of operational data forward in time. Causal relationships were extracted by aggregating and visualizing the learned weights within the network structure. For production mode, connections from {feed flow rate to RO system, permeate flow rate, flow rate feed to pressure tank, permeate temperature} were with higher weight for permeate flux, and {raw well feedwater flow rate, recycle stream flow rate, inlet feed pressure for RO elements} showed high weights for feed flow rate. For nitrate passage, permeate conductivity, recycle stream flow rate, raw well feedwater flow rate, and inlet feed pressure for RO element were with higher weight to feed flow rate. Analysis of significant model attributes (normalized weights accumulated over GATConv layers) demonstrated higher weights for {inlet feed pressure, feed flow rate, permeate temperature, permeate flow rate, concentrate pressure}