The effect of AI-assisted nursing care on digital health literacy, symptom management, and continuity of care among pulmonary outpatients: A quasi-experimental study at Bhayangkara Surabaya Hospital
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Abstract
Background: Pulmonary outpatients often experience recurrent respiratory symptoms requiring continuous support. Limited consultation time, increasing digital health use, and the need for symptom monitoring highlight the importance of AI-assisted nursing care in outpatient pulmonary services.
Purpose: This study analyzed the effect of AI-assisted nursing care on digital health literacy, symptom management, and continuity of care among pulmonary outpatients at Bhayangkara Surabaya Hospital.
Methods: A quasi-experimental study with a two-group pretest-posttest design involved 70 pulmonary outpatients (35 intervention, 35 control). The intervention group received AI-assisted nursing care; the control group received standard care. Data were collected using the Digital Health Literacy Instrument, a symptom management questionnaire, and the Nijmegen Continuity Questionnaire. Analysis used paired t-test, Wilcoxon Signed-Rank Test, independent t-test, and Mann-Whitney U Test.
Results: The intervention group showed significantly greater improvements than the control group. Digital health literacy was significantly higher (t = 9.11, p < 0.001), symptom management improved significantly (Z = −7.84, p < 0.001), and continuity of care differed significantly between groups (t = 8.99, p < 0.001). Change scores were substantially greater in the intervention group, particularly for continuity of care (18.95 vs. 2.26), with small effect sizes across all outcomes.
Conclusion:
AI-assisted nursing care can strengthen digital nursing support for pulmonary outpatients. Integrating structured digital education, chatbot interaction, symptom tracking, reminders, and nurse monitoring improves digital health literacy, symptom management, and continuity of care in outpatient pulmonary services.
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