Digital Transformation and Accessibility of Social Protection Services for Persons with Severe Disabilities in Bungoma County, Kenya

Abstract

Persons with Severe Disabilities (PwSD) in rural Kenya, particularly in Bungoma County, face persistent barriers in accessing digitally transformed social protection services due to poor infrastructure, limited digital literacy and inaccessible systems. This study examines the relationship between digital transformation and accessibility of social protection services, focusing on Persons with Severe Disabilities in Bungoma County. The specific objectives of the study included to examine the relationship between digital data management, digital monitoring and evaluation, digital automation, and digital payment systems and accessibility of social protection services and the moderating role of user adoption on the relationship between digital transformation and accessibility of social protection services for PwSD in Bungoma County. The study was anchored on diffusion of innovations theory, technology acceptance model and institutional theory. A correlational research design was employed, using quantitative data collection techniques. This research employed 1,250 implementers of PwSD CTP in Bungoma County as its main target group. The sample size for this study was 375 implementers of the PwSD CT. The study used simple random sampling to select participants. The study attained a sample size of 84%, 315 respondents. The study utilized a structured questionnaire, which was pre-tested for reliability and validity. Cronbach’s Alpha was used to assess the internal consistency of the instrument, with all variables having a Cronbach Alpha coefficient of >0.7, which was deemed acceptable for reliability. The Content Validity Index was calculated to ensure the relevance and clarity of the questionnaire items, with all scores >0.8 and considered satisfactory for content validity. Descriptive statistics (such as frequencies, percentages, means and standard deviations) summarized the demographic characteristics and key variables. Inferential statistics, including correlation analysis and regression analysis, were used to explore relationships between digital transformation variables (such as digital data management, payment systems) and social protection outcomes. The moderating role of user adoption was tested using Baron and Kenny moderation analysis. Data was managed using statistical software SPSS version 27. The study revealed strong support for digital tools in enhancing social protection services for persons with social disadvantages (PwSD). Respondents widely endorsed the use of digital systems for collecting, storing, and retrieving data, noting improved accuracy and efficiency in reducing paperwork. The regression analysis showed that Digital Data Management (β = .159, t = 2.355, p < .05), Digital Monitoring and Evaluation (β = .181, t = 2.660, p < .01) and Digital Automation (β = .401, t = 5.262, p < .001) significantly predicted Accessibility of Social Protection Services (R² = .599), with Digital Automation having the strongest impact, while Digital Payment Systems was non-significant (β = .102, t = 1.487, p = .138). The study concluded that digital M&E tools greatly improved service accessibility. In addition, the study concluded that there was strong willingness among staff and PwSD to embrace digital solutions. The research recommends that organizations should prioritize comprehensive staff training programs to address capacity gaps. Future research should also examine the cost-effectiveness of digital interventions to inform scalable, inclusive policy frameworks for social protection services as well as expanding geographic scope of the research so as to feature the rest of 47 counties in Kenya. This study was significant to policymakers, service providers, and development partners in digital social protection services for PwSD.