Digital Commons Network^™

Symbol-Temporal Consistency Self-Supervised Learning For Robust Time Series Classification, Kevin Garcia, Cassandra Garza, Brooklyn Berry, Yifeng Gao

Computer Science Faculty Publications

The surge in the significance of time series in digital health domains necessitates advanced methodologies for extracting meaningful patterns and representations. Self-supervised contrastive learning has emerged as a promising approach for learning directly from raw data. However, time series data in digital health is known to be highly noisy, inherently involves concept drifting, and poses a challenge for training a generalizable deep learning model. In this paper, we specifically focus on data distribution shift caused by different human behaviors and propose a self-supervised learning framework that is aware of the bag-of-symbol representation. The bag-of-symbol representation is known for its insensitivity …

High Organofluorine Concentrations In Municipal Wastewater Affect Downstream Drinking Water Supplies For Millions Of Americans, Birdger J. Ruyle, Emily H. Pennoyer, Simon Vojta, Jitka Becanova, Minhazul Islam, Thomas F. Webster, Wendy Heiger-Bernays, Rainer Lohmann, Paul Westerhoff, Charles E. Schaefer, Elsie M. Sunderland

Graduate School of Oceanography Faculty Publications

Wastewater receives per- and polyfluoroalkyl substances (PFAS) from diverse consumer and industrial sources, and discharges are known to be a concern for drinking water quality. The PFAS family includes thousands of potential chemical structures containing organofluorine moieties. Exposures to a few well-studied PFAS, mainly perfluoroalkyl acids (PFAA), have been associated with increased risk of many adverse health outcomes, prompting federal drinking water regulations for six compounds in 2024. Here, we find that the six regulated PFAS (mean = 7 to 8%) and 18 measured PFAA (mean = 11 to 21%) make up only a small fraction of the extractable organofluorine …

Scientists’ Statement On The Chemical Definition Of Pfass, Gabriel Sigmund, Marta Venier, Marlene Ågerstrand, Ian T. Cousins, Jamie Dewitt, Miriam L. Diamond, Jennifer Field, Alex T. Ford, Shira Joudan, Stefan Van Leeuwen, Rainer Lohmann, Carla Ng, Martin Scheringer, Anna Soehl, Noriyuki Suzuki, Xenia Trier, Sara Valsecchi, Penny Vlahos, Cora J. Young, Zhanyun Wang

Graduate School of Oceanography Faculty Publications

The undersigned are scientists with expertise in per- and polyfluoroalkyl substances (PFASs) and/or the management of chemicals. We assert that the Organization for Economic Co-operation and Development (OECD) definition of PFASs is scientifically grounded, unambiguous, and well suited to identify these chemicals. We are concerned that some individuals and organizations are seeking a redefinition of PFASs endorsed by the International Union of Pure and Applied Chemistry (IUPAC) to exclude certain fluorinated chemical subgroups from the scope of the existing definition. We are concerned that this effort is politically and/or economically, rather than scientifically, motivated. An IUPAC-endorsed and potentially narrower PFAS …

Spatial And Temporal Trends Of Dissolved Polybrominated Diphenyl Ethers And Non-Bde Flame Retardants In The Aquatic Environment Across Countries, Lian-Jun Bao, Branislav Vrana, Rainer Lohmann, Jaromír Sobotka, Foppe Smedes, Derek Muir, Ian J. Allan, Peleg Astrahan, Terry Bidleman, Denis Crowley, Evgen Dykyi, Nicolas Estoppey, Gilberto Fillmann, Liisa Jantunen, Sarit Kaserzon, Keith A. Maruya, Brendan Mchugh, Brent Newman, Raimon M. Prats, Manolis Tsapakis, Rebecca Sutton, Mats Tysklind, Barend L. Van Drooge, Charles S. Wong, Eddy Y. Zeng

Graduate School of Oceanography Faculty Publications

Measuring dissolved concentrations of polybrominated diphenyl ethers (PBDEs) and non-BDE flame retardants on a global scale provides critical insights into the effectiveness of the Stockholm Convention. In the present study, we deployed passive sampling devices at 43 seawater and freshwater sites covering 21 countries from 2016 to 2020. The detection frequencies were 20–94% for BDE congeners and 33–42% for dechlorane plus, higher than those (0–20%) for other target compounds. The median concentrations of dissolved Σ₉PBDE (sum of BDE-28, -47, -66, -85, -99, -100, -153, -154, and -183) were 0.28 and 0.64 pg L^–1 in seawater and freshwater, …

Achievements And Challenges With Equilibrium And Kinetic Passive Sampling Of Hydrophobic And Hydrophilic Organic Compounds In Surface Waters, Kees Booij, Rachel Mackie, Branislav Vrana, Rainer Lohmann, Sarit L. Kaserzon

Graduate School of Oceanography Faculty Publications

Passive sampling in surface waters is an important method in the monitoring and risk assessment of hydrophobic and hydrophilic organic chemicals. Sampler designs can be optimized for fast equilibrium attainment (equilibrium sampling) or improved time-integrative capability (kinetic sampling). We argue that both equilibrium and kinetic sampling can be applied when aqueous concentrations do not vary with time, whereas kinetic sampling also yields useful results for time-variable concentrations that are often observed with hydrophilic compounds in surface waters. We show that these methods have similar accuracy in principle but that their dominant error sources are different: sampler-water sorption coefficients for equilibrium …

Characterization Of The Potential Long-Term Impact From Sedimentary Pfas At A Historically Contaminated Textile Waste Site, Jarod Snook, Jitka Becanova, Simon Vojta, Rainer Lohmann

Graduate School of Oceanography Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) are pervasive pollutants at historically contaminated sites throughout the United States and beyond. Two such sites in Rhode Island, USA, are textile-mill-associated waste retention ponds known to introduce PFAS contamination to the adjacent river, estuary, and eventually the Atlantic Ocean. Here, we thoroughly investigated the retention ponds as a long-term source of PFAS via water passive sampling, sediment coring, and laboratory-derived partitioning coefficients, K_d, with field sediment and water. Additional studies were performed to assess the mobility and estimate the mass fluxes of PFAS from sediment to water. Retention pond 1 was more …

Multimodal Feature Fusion And Machine Learning For Adhd Detection Using Neuroimaging Data, Isabel Pham

Master's Projects

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopment disorder that can significantly affect a person’s attention, impulse control, and executive function. Currently, the traditional diagnosis method often relies on clinical assessments and observations. However, these methods can be subjective and lead to inconsistencies in diagnosis between individuals. To address this challenge, neuroimaging and machine learning (ML) are promising tools for providing a more objective diagnosis of ADHD. The goal of this project is to apply a multimodal approach in which structural and functional features of specific regions of the brain are used to develop a more accurate and objective …

Social Engineering Scenario Generation For Awareness-Based Attack Resilience, Jade Webb

Master's Projects

Social engineering is found in a strong majority of cyberattacks today, as it is a powerful manipulation tactic that does not require the technical skills of hacking. Calculated social engineers utilize simple communication to deceive and exploit their victims, all by capitalizing on the vulnerabilities of human nature: trust and fear. When successful, this inconspicuous technique can lead to millions of dollars in losses. Social engineering is not a one-dimensional technique; criminals often leverage a combination of strategies to craft a robust yet subtle attack. In addition, offenders are continually evolving their methods in efforts to surpass preventive measures. A …

Cca Analysis Using Computer Vision Techniques, Rahul Thakur

Master's Projects

Coral reefs are an essential part of the marine ecosystem. They perform a wide variety of tasks, some directly and others indirectly. They can produce oxygen, absorb carbon dioxide, along with supporting ocean habitat. Crustose Coralline Algae (“CCA”) plays an important role in helping provide structural support to Coral Reef ecosystems. However, global warming is causing ocean water to become more acidic resulting in coral bleaching. This is leading to changes in coral environments and causing coral deaths at alarming rates. Object detection using computer vision techniques, specifically deep learning, can help to monitor coral reef health and identify CCA …

Coral Vision – Crustose Coralline Algae Detection With Computer Vision, Ryan Tseng

Master's Projects

Crustose coralline algae (CCA) are a group of red algae that are vital contributors to the health of coral reef ecosystems. Monitoring CCA abundance can serve as an indicator for coral reef health and improve reef conservation efforts. Autonomous Reef Monitoring Structures (ARMS) are artificial structures that can be deployed into coral reef ecosystems and retrieved to gather ecological data without harming reef structures. Traditional methods of calculating CCA abundance require manual analysis and are labor-intensive. Recent developments in computer vision and deep learning technology have provided an avenue to fully automate this task. This research aims to train a …

Real-Time Adaptive Framework For Topic Modeling In Social Engineering Attacks, Manav Bhasin

Master's Projects

Detecting social engineering attempts is crucial for security, as these threats are becoming more frequent and increasingly exploit human vulnerabilities. This research focuses on topic modeling using conversational data from Kevin Mitnick’s ”The Art of Deception” with dialogues that illustrate various social engineering strategies. The dataset comprises manually extracted and synthetically augmented conversations to ensure natural dialogue flow. Two methodologies are presented for utterance-level and global topic extraction: prompt engineering leveraging OpenAI’s GPT-4o-mini, characterized by few-shot learning and chain-of-thought prompting, and Quantized Low Rank Adaptation (QLoRA) utilizing Mistral’s 7B instruct model for efficient fine-tuning. Through experimentation and evaluation, this study …

Simple Vs. Complex Human Activity Classification Via Hybrid Machine Learning Models, Anusha Kukreja

Master's Projects

In-depth understanding of the complexity of daily human activities is crucial for building responsive health monitoring and assistive technologies. However, limited research has focused on distinguishing activities based on their involvement level, as most existing work classifies only the type of activity performed. In this thesis, we address this gap by proposing a method to classify human activities as either simple or complex using sensor data from the Opportunity dataset. We define complex activities as those involving object interactions or multiple coordinated movements (e.g., drinking from a cup, cleaning a table), and simple activities as static or low-effort postures (e.g., …

Do Specialized Medical Llms Demand A Radically New Approach Under The Eu's Medical Device Regulation, Hannah Louise Smith, W. Nicholson Price Ii

Articles

We examine the arguments made by Onitiu and colleagues concerning the need to adopt a “backward-walking logic” to manage the risks arising from the use of Large Language Models (LLMs) adapted for a medical purpose. We examine what lessons can be learned from existing multi-use technologies and applied to specialized LLMs, notwithstanding their novelty, and explore the appropriate respective roles of device providers and regulators within the ecosystem of technological oversight.

The Law Of Energy Abundance, Alexandra B. Klass, Matthew Appel

Articles

For the first time in decades, electricity demand in the United States is increasing due to the growth of data centers to power artificial intelligence, new manufacturing hubs, and transportation electrification. At the same time, coalfired power plants have been closing in response to competition from lower cost natural gas and renewable energy. Clean energy is being rapidly deployed to replace fossil fuels but not quickly enough to address concerns about demand growth and grid reliability. Accordingly, there is a growing imbalance between electricity supply and demand in many regions of the country that threatens to increase electricity prices and …

The European Health Data Space As A Compass For Academic/Industry Collaborations, Gabriela Lenarczyk, Hannah Louise Smith, W. Nicholson Price Ii

Articles

Against the backdrop of a deepening funding crisis for academic research in the US, how and when can closer relationships between academia and industry better support the research enterprise? Spector-Bagdady (2025) explores this potential response, bringing insight from genetic data sharing between academia and industry—and the benefits and challenges that arise from that sharing. She calls for a response that aligns academic institutional policy to support the realization of any public good, recognizing the pitfalls and problematic incentives that shape individual responses. It’s a timely call, and an attractive one in a time of urgent uncertainty about funding and support. …

Synthetic Data Generation Of Health And Demographic Surveillance Systems Data: A Case Study In A Low- And Middle-Income Country, Dorcas G. Mwigereri, Nigel T. Kamotho, Akbar K. Waljee, Ryan T. Rego, Eileen M. Weinheimer-Haus, Farhana Alarakhiya, Anthony K. Ngugi, W. Nicholson Price, Ji Zhu, Stephen Peter Wong, Geoffrey H. Siwo

Articles

Objective: To evaluate effectiveness of open-source generative models in producing high-quality tabular synthetic data using a Health and Demographic Surveillance System (HDSS) dataset from rural Kenya, as a proof of concept in a low- and middle-income (LMIC) setting.

Materials and Methods: Three open-source models (CTGAN, TableGAN, and CopulaGAN) were used to generate synthetic data from the Kaloleni/ Rabai HDSS dataset. To assess the quality of the synthetic datasets generated by each model, we performed fidelity, utility, and privacy tests.

Results: CTGAN outperformed the other models, producing synthetic data that closely mirrored the statistical properties of the real dataset while preserving …

Consensus And Conflict Over Context: Select Criminal Law And Procedure Cases From The Supreme Court's 2024-25 Term, Eve Brensike Primus, Elena Schultz

Articles

In its 2024-2025 Term, the Supreme Court emphasized the utility—and necessity—of context-based, fact-sensitive analyses throughout its criminal law and procedure cases. Though the Justices sparred over how to derive meaning from factual, structural, legal, and historical contexts, they tended to agree that courts should not be artificially restricted from considering the breadth of the record before them.

Pathogens And Parasites Of Feral And Managed Honey Bee, Apis Mellifera, Colonies From Oklahoma, Allen Szalanski

Entomology and Plant Pathology Faculty Publications and Presentations

Managed honey bee populations in the United States have been under stress over the past several decades, probably due to the interaction among multiple biotic and abiotic stressors. While most research has focused on national surveys of honey bee pathogens and parasites, state-specific studies that include both managed and feral honey bee populations may offer additional insights into the factors that contribute to the decline of honey bees. We conducted a survey to detect parasites and pathogens from feral and managed honey bees in colonies in Oklahoma. A total of 253 (89 managed and 164 feral) honey bees from these …

Addressing The Unmet Mental Health Crisis Of Youth In West Englewood, Joallyn Porter

Theses and Dissertations from DePaul University

Chicago youth face significant unmet mental health needs driven by systemic inequalities, community violence, poverty and limited access to care. Alarmingly high rates of anxiety, depression, and trauma impact youth across the city, particularly neighborhoods on the south and west sides, yet far too frequently, stigma, lack of culturally responsive services, and insufficient school and community resources prevent early intervention and effective mental health treatments. Schools, often the first point of contact for mental health support; lack the staffing, funding, and infrastructure necessary to meet growing demands—particularly in under-resourced neighborhoods where families encounter economic and logistical barriers to care. Addressing …

Global, Regional, And National Burden Of Cardiovascular Diseases And Risk Factors In 204 Countries And Territories, 1990-2023, Global Burden Of Cardiovascular Diseases And Risks 2023 Collaborators, Benjamin A. Stark, Nicole K. Decleene, Emily C. Desai, Johnathan M. Hsu, Catherine O. Johnson, Laura Lara-Castor, Kate E. Legrand, Prof Bhoomadevi A., Mohammad Amin Aalipour, Nasir Abbas, Madineh Abbasi, Mohammadreza Abbasian, Hedayat Abbastabar, Abdallah H. A. Abd Al Magied, Samar Abd Elhafeez, Gregory A. Roth, Et Al.

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background

Cardiovascular diseases (CVDs) are the leading cause of mortality and are among the foremost causes of disability globally. CVD burden has continued to increase in most countries since 1990, with trends driven by changing exposures to harmful risk factors, population growth, and population aging.

Objectives

We report estimates of global, national, and subnational CVD burden, including 18 subdiseases and 12 associated modifiable risk factors. We analyzed change in CVD burden from 1990 to 2023 and identified drivers of change including population growth, population aging, and risk factor exposure.

Methods

The Global Burden of Disease (GBD) 2023 study, a multinational …

Advances In Conductive Polymer-Based Flexible Electronics For Multifunctional Applications, Md Abdus Shahid, Md Mostafizur Rahman, Md Tanvir Hossain, Imam Hossain, Md Sohan Sheikh, Md Sunjidur Rahman, Nasir Uddin, Scott W. Donne, Md Ikram Ul Hoque

Michigan Tech Publications

The rapid developments in conductive polymers with flexible electronics over the past years have generated noteworthy attention among researchers and entrepreneurs. Conductive polymers have the distinctive capacity to conduct electricity while still maintaining the lightweight, flexible, and versatile characteristics of polymers. They are crucial for the creation of flexible electronics or gadgets that can stretch, bend, and adapt to different surfaces have sparked momentous interest in electronics, energy storage, sensors, smart textiles, and biomedical applications. This review article offers a comprehensive overview of recent advancements in conductive polymers over the last 15 years, including a bibliometric analysis. The properties of …

Fatigue Life Of Pre-Cut Seam Asphalt Mixture Composite Beams: A Combined Study Of Fatigue Damage Evolution And Reflective Cracking Extension, Hongfu Liu, Hong Lu, Xun Zhu, Zhengwei Yi, Xin Yu, Dongzhao Jin, Xinghai Peng, Songtao Lv

Michigan Tech Publications

This study investigated the impact of reflective cracking on the fatigue performance of asphalt pavements after milling and resurfacing under various conditions. Fatigue life was assessed through four-point flexural fatigue tests, while the crack extension pattern of composite beams was analyzed by digital image correlation (DIC) at both macroscopic and microscopic scales. Evaluation parameters such as stress ratios, immersion time, porosity, and types of viscous oils were assessed. A fatigue life prediction model of composite beams was established, accounting for the combined influence of these factors. To enhance the accuracy of determining composite beam failure, the critical fatigue damage was …

Long Oligos: Direct Chemical Synthesis Of Genes With Up To 1728 Nucleotides, Yipeng Yin, Reed Arneson, Yinan Yuan, Shiyue Fang

Michigan Tech Publications

The longest oligos that can be chemically synthesized are considered to be 200-mers. Here, we report direct synthesis of an 800-mer green fluorescent protein gene and a 1728-mer Φ29 DNA polymerase gene on an automated synthesizer. Key innovations that enabled this breakthrough include conducting the synthesis on a smooth surface rather than within the pores of traditional supports, and the use of the powerful catching-by-polymerization (CBP) method for isolating the full-length oligos from a complex mixture. Conducting synthesis on a smooth surface not only eliminated the steric hindrance that would otherwise prevent long oligo assembly, but also, surprisingly, drastically reduced …

Surveillance Report​: Che-Wei Hsu​, Che-Wei Hsu

Theses

Face ID: A Surveil of Che-Wei Hsu is a lens based artistic investigation and experience into the nature of surveillance in modern society. Through performance, photography, and installation, my work explores the dynamics between being watched and watching, questioning how surveillance influences human behavior and identity. In my art practice, I think about the behavior that people would not do in front of other people or violate the social norm and perform in the public as a way to experience how surveillance influences how we act in the public, for example eating a sandwich on the ladder in front of …

Fake News Detection In Arabic Media Using Machine Learning And The Afnd Dataset, Hussain Ali Bahri

Theses

The proliferation of fake news in digital media poses a significant challenge to information credibility, particularly in linguistically diverse regions such as the Arab world. This study addresses the critical problem of detecting fake news in Arabic media by leveraging advanced natural language processing (NLP) techniques and the AFND dataset, which contains over 600,000 news articles categorized into "credible," "not credible," and "undecided" classes. The research focuses on developing a robust system using AraBERT, a transformer-based model specifically pre-trained for Arabic text. Key contributions of this work include a comprehensive preprocessing pipeline tailored to Arabic linguistic complexities, incorporating stopword removal, …

Predicting Biomechanical Risk Factors For Division - I Women’S Basketball Athletes, Aayushi Shah, Vanaja Agarwal, Dhairya Shah, Harman Jani, Sristi Sharma, Kaya Tolga, Christopher Taber, Mehul Raval

School of Computer Science & Engineering Faculty Publications

Collegiate basketball is characterized by high-impact movements such as jump landings, making athletes more susceptible to injuries. Critical biomechanical factors like knee flexion, lateral trunk flexion, and foot landing asymmetry are strongly associated with injury risk. This study aims to predict six biomechanical risk factors in the landing error scoring system (LESS). The dataset comprises 8600 video frames of counter-movement jumps (CMJs) from 17 NCAA Division I female basketball athletes, recorded from frontal and lateral perspectives and annotated using a customized error annotation algorithm. The study uses the You Only Look Once (YOLOv5nu) model to analyze the basketball athletes’ CMJ …

Abolitionism, Artificial Intelligence, And Non-Reformist Reform, Youngjae Lee

Faculty Scholarship

Prison abolitionism has gained significant prominence in criminal law scholarship, while artificial intelligence (AI) has emerged as a transformative force across society. Two schools of thought have arisen regarding their intersection. Some scholars contend abolitionists should welcome AI technologies to reduce the carceral state’s reach. Critics view these tools skeptically, arguing that they lead to biased surveillance and incarceration practices. Using this debate as an example, this article seeks to illuminate the distinction between reformist and non-reformist reforms. The article argues that abolitionists’ criticism of reformists as agents of oppression risks alienating potential allies and discouraging progressive interventions in pivotal, …

The Power Of Presence: Body Image In Disney's The Little Mermaid, Megan Chatelain

University of the Pacific Theses and Dissertations

This study explores how body image is represented in Disney’s The Little Mermaid across its 1989 animated film and the 2019 and 2023 adaptations. Grounded in Gerbner’s Cultivation Theory, the research examines how repeated media exposure shapes audience perceptions of morality, beauty, and identity—particularly through the portrayal of body size. Using a triangulated qualitative approach—reflexive journaling, content analysis, and survey responses—the study reveals consistent patterns: thin characters are depicted as virtuous, desirable, and heroic, while larger-bodied characters are often cast as villainous, comedic, or morally flawed. These associations were recognized by participants across all methods and confirmed through both reflective …

ผลของโปรแกรมการจัดการอาการร่วมกับการบริหารกาย-จิตแบบชี่กงต่ออาการเหนื่อยล้า อาการนอนไม่หลับและอาการ วิตกกังวล ในผู้ที่เป็นมะเร็งเต้านมที่ได้รับยาเคมีบำบัดแบบเสริม, อรุณศรี สารธิมา, นพมาศ พัดทอง

Journal of Nursing Research, Innovation, and Health

วัตถุประสงค์: เพื่อเปรียบศึกษาผลของโปรแกรมการจัดการอาการร่วมกับการบริหารกาย-จิตแบบชี่กงต่ออาการเหนื่อยล้า นอนไม่หลับและอาการวิตกกังวล ในผู้ที่เป็นมะเร็งเต้านมที่ได้รับเคมีบำบัดแบบเสริม

รูปแบบการวิจัย: การวิจัยครั้งนี้เป็นงานวิจัยกึ่งทดลอง (Quasi Experimental Research)

วิธีดำเนินการวิจัย: กลุ่มตัวอย่าง คือ ผู้ที่เป็นมะเร็งเต้านมในระยะที่ 1-3 อายุตั้งแต่ 20 ปีขึ้นไป ได้รับยาเคมีบำบัดเสริม จำนวน 42 คน แบ่งเป็นกลุ่มทดลองและกลุ่มควบคุม กลุ่มละ 21 คน กลุ่มควบคุมได้รับการพยาบาลตามปกติ ในขณะที่กลุ่มทดลองได้รับการพยาบาลตามปกติร่วมกับโปรแกรมการจัดการอาการร่วมกับการบริหารกาย-จิตแบบชี่กง ตามแนวคิดการจัดการอาการของ Dodd และคณะ (2001) และแนวคิดการบริหารกาย-จิตแบบชี่กง ของ เทอดศักดิ์ เดชคง (2545) เครื่องมือที่ใช้ในการเก็บรวบรวมข้อมูล คือ 1.แบบบันทึกข้อมูลส่วนบุคคล 2. แบบบันทึกข้อมูลเกี่ยวกับโรคมะเร็ง 3. แบบประเมินอาการ ได้แก่ แบบประเมินอาการเหนื่อยล้า แบบประเมินอาการนอนไม่หลับ แบบประเมินอาการวิตกกังวล วิเคราะห์หาค่าความเที่ยงของเครื่องมือโดยหาค่าสัมประสิทธิ์อัลฟาครอนบาค ได้ค่าความเที่ยงเท่ากับ .96, .81, และ .80 ตามลำดับ และ วิเคราะห์ข้อมูลโดยหาค่าเฉลี่ย ร้อยละ ส่วนเบี่ยงเบนมาตรฐาน และสถิติทดสอบที

ผลของโปรแกรมสุขภาพจิตศึกษาครอบครัวโดยบูรณาการกับแอปพลิเคชันไลน์ต่อพฤติกรรมการใช้ยาตามเกณฑ์การรักษาของผู้ป่วยจิตเภทในชุมชน, ศิริพร พึ่งตน, สุดาพร สถิตยุทธการ

Journal of Nursing Research, Innovation, and Health

วัตถุประสงค์: เพื่อศึกษาการเปรียบเทียบพฤติกรรมการใช้ยาตามเกณฑ์การรักษาของผู้ป่วยจิตเภทในชุมชนก่อนและหลังได้รับโปรแกรมฯ และเพื่อเปรียบเทียบพฤติกรรมการใช้ยาตามเกณฑ์การรักษาของผู้ป่วยจิตเภทในชุมชนที่เข้าได้รับโปรแกรมฯกับกลุ่มที่ได้รับการพยาบาลตามปกติ

รูปแบบการวิจัย: การวิจัยกึ่งทดลอง

วิธีดำเนินการวิจัย: กลุ่มตัวอย่าง คือ ผู้ป่วยจิตเภทและผู้ดูแลในชุมชนที่มารับบริการแผนกจิตเวชและยาเสพติดของโรงพยาบาลองครักษ์ จำนวน 40 คน จับคู่ให้มีลักษณะคล้ายคลึงกันด้วยอายุและเพศ เครื่องมือวิจัย ประกอบด้วย  1) โปรแกรมสุขภาพจิตศึกษาครอบครัวโดยบูรณาการกับแอปพลิเคชันไลน์  2) แบบวัดพฤติกรรมการใช้ยาตามเกณฑ์การรักษา  3) แบบวัดความรู้ความเข้าใจผู้ป่วยจิตเภทและผู้ดูแล เครื่องมือทุกชุดผ่านการตรวจสอบความตรงเนื้อหาโดยผู้ทรงคุณวุฒิ  5 ท่าน สถิติที่ใช้วิเคราะห์ข้อมูล  ได้แก่  ค่าเฉลี่ย  ส่วนเบี่ยงแบบมาตรฐานและสถิติทดสอบที

ผลการศึกษา: 1) พฤติกรรมการใช้ยาตามเกณฑ์การรักษาของผู้ป่วยจิตเภทในชุมชนที่ได้รับโปรแกรมสุขภาพจิตศึกษาครอบครัวโดยบูรณาการกับแอปพลิเคชันไลน์สูงกว่าก่อนได้รับโปรแกรม อย่างมีนัยสำคัญทางสถิตที่ระดับ  .05

2) พฤติกรรมการใช้ยาตามเกณฑ์การรักษาของผู้ป่วยจิตเภทในชุมชนที่ได้รับโปรแกรมสุขภาพจิตศึกษาครอบครัวโดยบูรณาการกับแอปพลิเคชันไลน์สูงกว่ากลุ่มที่ได้รับการพยาบาลตามปกติ อย่างมีนัยสำคัญทางสถิตที่ระดับ .05

สรุป: โปรแกรมสุขภาพจิตศึกษาครอบครัวโดยบูรณาการกับแอปพลิเคชันไลน์ช่วยให้ผู้ป่วยจิตเภทในชุมชนมีพฤติกรรมการใช้ยาตามเกณฑ์การรักษาสูงขึ้น