DOI 10.1186/s12911-026-03432-1
Effectiveness of artificial intelligence mobile app-guided prevention and treatment protocols on cancer patients and their impact on healthcare workers' competence.
Аннотация
BACKGROUND
Artificial intelligence-based mobile health applications are increasingly used in oncology care, mainly to support symptom monitoring and clinical workflows. However, there is limited evidence on applications that simultaneously support cancer patients through structured prevention and treatment guidance while enhancing healthcare workers’ competencies. This study aimed to assess the outcomes of an AI-based mobile application as a supportive tool for cancer patients and examine its impact on healthcare workers’ competence in routine oncology care.
METHODS
A quasi-experimental pre-post design was conducted with 60 cancer patients and 60 healthcare workers. The AI-based mobile application provided content on education, symptom management, and protocol-based support. Data was collected through structured online questionnaires before and after a 12-week intervention using five tools to assess usability, perceived benefits, efficiency of healthcare workers, health awareness, and selected chemotherapy-related symptoms. The same instruments were used for pre- and post-measurements without a control group.
RESULTS
Post-intervention findings indicated improved patient-reported usability of the mobile application, with most participants reporting clarity and perceived usefulness, although some reported occasional confusion or irrelevant responses. Healthcare workers demonstrated statistically significant improvements in perceived efficiency and benefits related to application use (p < 0.01). An increase in reported health awareness among nurses was observed. Patients also reported reductions in the severity of chemotherapy-related symptoms.
CONCLUSION
The findings suggest that the AI-based mobile application may serve as a supportive digital tool in oncology settings by assisting patients in following prevention and treatment guidance and supporting healthcare workers’ perceived efficiency and awareness. CLINICAL TRIAL NUMBER: Not applicable.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.