Purpose This study examines the effects of digital health technologies on enhancing children's healthcare utilization in the Kigoma region of Tanzania. It also investigates the factors that influence both the adoption and the extent of usage of digital health technologies among caregivers. Design/methodology/approach A cross-sectional research design was employed, using data collected from 400 respondents selected through a multi-stage sampling technique. A double-hurdle model was applied to analyze the determinants of digital health technology adoption and usage intensity, while a probit model was used to assess the effect of digital health usage on children's healthcare utilization. Findings The results indicate that awareness (ß = 0.643; p = 0.061), ease of use (ß = 0.113; p = 0.000), internet connectivity (ß = 0.512; p = 0.000), and participation in digital health education campaigns (ß = 0.373; p = 0.000) significantly increase the likelihood of adopting digital health technology. In contrast, negative attitudes (ß = −0.738; p = 0.069), low household income (ß = −0.649; p = 0.000), and larger household sizes (ß = −0.217; p = 0.000) reduce the probability of adoption. Among adopters, usage intensity is significantly enhanced by ease of use (ß = 0.747; p = 0.000), better internet connectivity (ß = 0.406; p = 0.001), higher household income (ß = 0.429; p = 0.000), participation in health education programs (ß = 0.607; p = 0.000), and healthcare provider assistance (ß = 0.419; p = 0.001). The double-hurdle model is strongly significant (?2 = 148.61; p = 0.000), confirming the explanatory strength of the selected variables. Regarding children's healthcare utilization specifically on vaccination uptake, mobile health applications (dy/dx = 0.384; p = 0.000) and online appointment/reminder systems (dy/dx = 0.725; p = 0.000) have significant positive effects, while electronic health records show a marginal positive influence (dy/dx = 0.162; p = 0.075). Also, socio-economic factors such as education level of the respondent (dy/dx = 0.118, p 0.01) is positively and significantly associated with timely vaccination, Household income (dy/dx = 0.074, p 0.05) similarly shows a positive and statistically significant effect, Participation in health education campaigns (dy/dx = 0.244, p 0.01) is positively associated with vaccination uptake. Research limitations/implications Although the study provides valuable insights, several limitations should be considered. First, the cross-sectional design restricts causal interpretation of the observed associations. Second, self-reported measures on digital health usage may be influenced by recall or social desirability bias. Third, the study focused on mothers with children under five years, and perspectives from fathers or other caregivers were not captured. Lastly, findings are limited to Kigoma and may not fully represent all regions of Tanzania with different digital health infrastructures. Future studies could adopt longitudinal or mixed-method approaches to strengthen causal inference and generalizability. Practical implications The study recommends expanding digital health training, improving internet access, subsidizing digital health services and strengthening trust-building initiatives to enhance adoption and utilization. Policymakers should focus on integrating digital health into mainstream healthcare services to maximize its impact on healthcare accessibility, particularly for children in resource-constrained settings such as Kigoma. Originality/value This study is among the first to empirically assess both the determinants and effects of digital health technology adoption on children's healthcare utilization in a resource-constrained setting such as Kigoma, Tanzania. By applying a double hurdle model alongside a probit framework, it provides a nuanced understanding of adoption drivers, usage intensity and health outcomes. The findings highlight the distinct impact of mobile health applications and online reminder systems on pediatric healthcare access, offering actionable insights for policymakers and practitioners aiming to integrate digital health into underserved healthcare systems.
Mpfubhusa et al. (Tue,) studied this question.