Journal Article Epublish
PubMed: 42306093 DOI: 10.2147/JMDH.S588471
From Hospital to Home: Enhancing Family Support with MIGYN (Mitra Interaktif Ginekologi), an AI-Based Discharge Planning Chatbot.
J Multidiscip Healthc 19:588471
Authors: Ida Maryati, Ermiati Ermiati, Windy Natasya, Anisa Hasanah, Novi Irmala, Santi Susanti, Atikah Atikah, Dyana Eka Fuzi Yulianti, Khatijah Lim Abdullah
Affiliations
- Department of Maternity and Pediatric Nursing, Faculty of Nursing, Universitas Padjadjaran, Sumedang, West Java, Indonesia.
- Department of Nursing, Dr. Hasan Sadikin General Hospital, Bandung, Indonesia.
- Master of Nursing Program, Faculty of Nursing, Universitas Padjadjaran, Sumedang, West Java, Indonesia.
- School of Nursing, Faculty of Medical and Life Sciences, Sunway University, Petaling Jaya, Selangor, Malaysia.
Abstract
BACKGROUND
Postoperative gynecological patients often experience challenges during the transition from hospital to home due to suboptimal discharge planning. Family involvement plays an important role in supporting postoperative recovery; however, caregiver support and education are frequently unstructured and inconsistent.
OBJECTIVE
To evaluate the effectiveness of MIGYN (Mitra Interaktif Ginekologi), a family-based interactive chatbot, in improving family support and caregiver knowledge among postoperative gynecological patients.
METHODS
A quasi-experimental pre-post test study was conducted involving 34 caregivers of postoperative gynecological patients at Dr. Hasan Sadikin General Hospital, Bandung. Participants were divided into intervention and control groups (n = 17 each). Family support was measured using the Family Support Scale (FSS), while caregiver knowledge was assessed using a structured questionnaire. Data were analyzed using the Wilcoxon signed-rank test and Mann-Whitney U-test.
RESULTS
Both groups demonstrated improvements in family support and caregiver knowledge following the intervention period. Within-group analysis showed significant increases in family support and caregiver knowledge scores in both groups (p < 0.05). However, between-group analysis demonstrated a statistically significant difference only in caregiver knowledge (p = 0.003), with the intervention group showing greater improvement and a moderate effect size (r = 0.51). In contrast, family support did not differ significantly between groups (p = 0.447), with a small effect size (r = 0.13).
CONCLUSION
MIGYN was associated with significant improvements in caregiver knowledge among postoperative gynecological patients, while improvements in family support were relatively comparable between groups. These findings suggest that MIGYN may serve as a digital discharge planning approach to support caregiver education and family involvement during postoperative recovery.
MeSH
Caregivers, Recycling, Gynecology, Artificial Intelligence, Education, Family Support