Daystar University Repository

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Class Projects and Student Articles 3
A collection of Class Projects and Student articles showcasing innovative ideas and diverse perspectives from our talented student community at Daystar University
Conference/ Workshop/ Seminar/ Proceedings/ Lecture Series 94
A collection of conference, workshop, seminar, proceedings, and lecture series showcasing diverse topics and cutting-edge research from faculty and staff of Daystar University.
Daystar Archives 42
An archival collection chronicling the institutional history, academic achievements, and diverse heritage of Daystar University.
Daystar University Publications 1463
A collection of Publications by faculty and staff showcasing research, academic achievements, and institutional insights of Daystar University.
Lectures and Speeches 6
A collection of Lectures and Speeches from distinguished speakers across various disciplines of Daystar University.

Recent Submissions

The Burdens of Care on Informal Caregivers of Patients with Mental Disorders Attending Clinics at Mathari Teaching and Referral Hospital
(African Journal of Emerging Issues, 2025-03) Onyango, Peter; James, Naomi; Walioli,Ruth; Menecha, Jared Bravin; Ongaro, Kennedy
Caregiving for patients with mental disorders places significant burdens on informal caregivers, manifesting as physical and psychological strain over extended periods. Most research examining caregiving burden variations has been conducted in Western countries, creating a knowledge gap regarding the specific nature and intensity of these burdens in the Kenyan context, particularly at Mathari National Teaching and Referral Hospital. Purpose of the Study:This study aimed to investigate the burdens of care experienced by informal caregivers of patients with mental disorders attending clinics at Mathari National Teaching and Referral Hospital. Methodology:A descriptive survey design was employed, targeting informal caregivers who accompanied patients with mental disorders to Mathari Hospital. Using purposive sampling, 92 caregivers were selected based on the Krejce and Morgan table, with 80 completed questionnaires included in the final analysis. Data collection utilized the Zarit Burden Interview (ZBI), a validated 22-item tool with strong psychometric properties (Cronbach alpha 0.93, test-retest reliability 0.89), alongside a researcher-designed sociodemographic questionnaire. Data analysis employed SPSS version 25, using descriptive and inferential statistics.Findings:The findings revealed that caregiver burden scores ranged from 8 to 68 on the ZBI scale. A large number of caregivers scored between 31-36 (mild to moderate burden) and 52-58 (moderate to severe burden). This diversity in scores indicated a wide range of experiences among caregivers, with a significant proportion experiencing moderate to severe burdens that potentially put them at risk for developing physical and mental health issues. Conclusion and Recommendations:Caregivers at Mathari Hospital experience considerable levels of burden that require comprehensive support mechanisms. The study recommended that healthcare systems incorporate caregiver well-being into treatment plans through psychological support, financial aid, and educational programs that help caregivers manage stress and provide bet
Infopreneurship
(Catholic University of Eastern of Eastern Africa (CUEA) Press, 2025) Kimote, Zipporah
The digital age has ushered in unprecedented opportunities for knowledge sharing, entrepreneurship, and innovation. At the intersection of these dynamics lies Infopreneurship—a transformative field that empowers individuals to turn information into impactful products, services, and revenue streams. This book serves as a comprehensive guide for aspiring and seasoned infopreneurs, equipping them with the tools, strategies, and insights needed to thrive in today’s knowledge-driven economy. The chapters within provide a structured exploration of Infopreneurship, starting with foundational concepts in Introduction to Infopreneurship and progressing to advanced topics such as Data Visualization and Analysis and Future Trends and Innovations. Readers will gain a deep understanding of critical domains like Digital Content Creation, User Experience, Information Security, and Market Identification, all tailored to the unique challenges of the information economy. In addition, practical aspects such as Content Marketing and Monetization Strategies and Information Revenue Products and Streams are covered in detail, bridging theory with actionable insights. The inclusion of Case Studies offers real-world examples that illustrate the application of concepts, while chapters on Legal and Ethical Considerations and Monitoring, Evaluation, and Review ensure that readers approach Infopreneurship with integrity and professionalism. This book is not only a roadmap for building a successful infopreneurial venture but also a call to embrace innovation and ethical responsibility in the dissemination of knowledge. It invites readers to reimagine the value of information in a connected world and challenges them to harness its potential for personal and societal growth. Whether you are an entrepreneur, educator, or innovator, this book is your gateway to mastering the art and science of Infopreneurship.
HIV and Sustainable Development: Integrating Religion, Culture, and Science Infrastructure for a Holistic Treatment Acceptance and Adherence in Kenya
(Journal of Infrastructure, Policy and Development, 2025) Otieno, Pamela Mbuya; Niyitunga, Eric Blanco
The achievement of sustainable development in Kenya has been hindered by the prevalence of HIV. The effects of HIV on sustainable development have been given less academic attention. HIV prevalence prevents people from achieving good health and wellbeing, which then makes them unable to conduct activities that lead to sustainable economic growth. The paper found that the prevalence of HIV causes economic hardship, destroys human capital development and human resources by reducing life expectancy and increasing mortality rates. It was equally found that the prevalence of HIV undermines social stability and mobility, reduces economic investments, influences food insecurity and makes people vulnerable. The paper found that the prevalence of HIV reduces labor supply and productivity, increases the cost of health services, promote inequality and poverty. The paper found that the prevalence of HIV was caused by the failure to integrate religion, culture and science infrastructure to achieve a holistic treatment acceptance and adherence that would overcome all misconceptions people have towards the disease. The paper found that while science provides effective HIV treatments, religious and cultural perspectives often shape community attitudes toward the disease. It was found that engaging religious and cultural as well as health workers or health advocates can help reduce stigma and promote ART adherence by aligning treatment messages with faith-based principles. The paper found that the integration that incorporates religion, culture, and science into HIV interventions would promote a more inclusive healthcare system that respects diverse beliefs while ensuring evidence-based treatment is accessible and widely accepted. The study was conducted through a qualitative methodology. Data was collected from secondary sources that included published articles, books and occasional papers as well as reports. Collected data was interpreted and analyzed through document analysis techniques
Exploring the Influence of Pre-Processing techniques in Obtaining Labelled Data from Twitter Data
(IEEE Africon, 2023) Mursi, Japheth Kiplang’at; Subramaniam, Prabhakar Rontala; Govender, Irene
Pre-processing input text play a crucial role in text classification by reducing dimensionality and removing unnecessary content. Different text pre-processing techniques affect prediction models' input vocabulary and documents. Many of the decisions that affect model performance are made during data pre-processing. The notion of data pre-processing affecting the outcome of a prediction task is widely accepted, yet not much work has been done on measuring this impact. In this study, six different text pre-processing techniques were applied, resulting in five types of labelled datasets used in classification. Three machine learning classifiers, Naïve Bayes (NB), Random Forest and Logistic Regression (LG), were used. The accuracy of the classifiers after applying to the different datasets were calculated. Results showed that Naïve Bayes, Random Forest and Logistic regression accuracy significantly improved after using only stemming and removing Stop Words. Naïve Bayes achieved the highest accuracy of 90.71% when the dataset was stemmed and Stop Words removed. Similarly, Random Forest and Logistic Regression gained a higher accuracy of 94.5% and 93.5% when the dataset was stemmed, and Stop Words removed. In addition, accuracy of classifiers on labelled dataset which was tokenized and lemmatized reduced to 88.44% forNaïve Bayes, 92.94% for Random Forest and 92.23% for Logistic Regression. The study concludes that the removal of Stop Words, stemming and lemmatization affect data labelling and prediction model accuracy.
Customer Profiling from Social Media Engagement using LDA and Sentiment Analysis Approach
(Proceedings of the Kabarak University International Research Conference on Computing and Information Systems., 2020) Mursi, Japheth Kiplang'at; Wamuyu, Patrick Kanyi
Social media is now an essential component of the daily life of consumers. People usually share their interest, thoughts on brands and companies through discussions, tweets and status. At present, companies are competing to attract and meet customer needs. For companies, managing customer relationship through social media engagement has become a significant part of digital marketing strategies. The modern customer has different needs, expectations and behaviours which ought to be managed differently by companies., Customer engagement on social networks helps to create relationship with customers, and also acts as quick and cost-effective marketing tool. Social Customer Relationships Management (SCRM) provides a two-way communication channel between customers and businesses through social media sites. SCRM is based on a model of customer engagement which requires strong partnerships and interactions. The purpose of this research study was tounderstand customer interactions with business using topic modelling. The study analysed customer engagement on Twitter of Four selected banks in Kenya. We apply unsupervised topic modelling of LDA and sentiment analysis to create a profile of different customers of selected banks in Kenya. We focus on interactions from a consumer-centric perspective, not focusing on specific firm channels. We conclude that the extracted latent models not only provide insight to the consumer behaviour but also can also improve any company’s Social Customer relationshipmanagement(sCRM) focused on different customer profiles.