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Underserved communities face persistent challenges due to limited access to healthcare services. Digital volunteering offers opportunities for healthcare professionals to support these populations remotely. This study examined factors associated with healthcare workers’ intentions to participate in digital healthcare volunteering in Algeria. An extended technology acceptance model was used, incorporating perceived organizational support (OS), altruism, and social responsibility. A convenience sample of 142 healthcare workers completed a survey, and hierarchical regression analysis was conducted. Results indicated that perceived ease of use, social responsibility, altruism, perceived OS, and perceived usefulness were each significantly associated with intentions to engage in digital volunteering. The extended model explained 75.6% of the variance in intention, highlighting the relevance of psychological, organizational, and ethical factors. These findings provide insights for policymakers, healthcare organizations, and developers seeking to support digital volunteering initiatives. Limitations include the cross-sectional design and the use of convenience sampling, which may affect generalizability. Future research should consider longitudinal designs, larger and more diverse samples, and cross-cultural comparisons to validate and extend these findings.
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Background/Objectives: Telemedicine offers significant potential to improve the quality and accessibility of geriatric care, particularly in resource-constrained settings. However, its effective implementation depends largely on healthcare professionals’ acceptance and willingness to use such systems. Drawing on an extended Technology Acceptance Model (TAM), this study examines the determinants of doctors’ and nurses’ intentions to adopt telemedicine for elderly care in Algeria, with particular emphasis on self-efficacy and institutional support. Methods: This cross-sectional study employed a structured questionnaire administered to 130 healthcare professionals, including physicians and nurses, in Algeria. Hierarchical multiple regression analysis was conducted to test the proposed hypotheses and assess the incremental explanatory power of the extended model. Results: The extended TAM accounted for 48.7% of the variance in intention to use telemedicine. Institutional support (β = 0.432, p < 0.001) and self-efficacy (β = 0.264, p = 0.001) emerged as the strongest predictors. Perceived ease of use (β = 0.178, p = 0.038) and perceived usefulness (β = 0.139, p = 0.021) also had significant positive effects. The inclusion of self-efficacy and institutional support increased the model’s explanatory power by 23.5%. Conclusions: The findings highlight the critical role of organizational support mechanisms, digital competencies, and system usability in fostering telemedicine adoption among healthcare professionals. The study provides practical implications for policymakers and healthcare institutions, emphasizing the need for targeted training programs, supportive infrastructure, and institutional policies that enhance confidence and facilitate the integration of telemedicine into clinical workflows.
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- Public Health (2)
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- Journal Article (2)
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- English (1)