Lifestyle and psychosocial predictors of health resilience among Indonesian disaster preparedness cadres (Tagana)

A machine learning approach

Bibliographic Data

ID22073115
AuthorsMu’man Nuryana (0000-0001-9997-4750, Indonesian Agency for Agricultural Research and Development), Istiana Hermawati (Islamic University of Indonesia), Sugiyanto Sugiyanto (0000-0002-7864-6704, Islamic University of Indonesia), Asmadi Adnan (Indonesian Agency for Agricultural Research and Development), Dayat Hidayat (0000-0003-4329-809X, Indonesian Agency for Agricultural Research and Development), Togiaratua Nainggolan (0000-0002-9573-0860, Social Welfare Department), Setyo Sumarno (0000-0001-6057-133X, Social Welfare Department), Ruaida Murni (Social Welfare Department), Chatarina Rusmiyati (Social Welfare Department), Achmadi Jayaputra (Social Welfare Department), Suryani Suryani (0000-0001-8857-5359, Indonesian Agency for Agricultural Research and Development), Sri Setyati (Universitas Islam Kalimantan Muhammad Arsyad Al Banjary), Andjar Prasetyo (0000-0001-5275-0223, Regional Development Agency, corresponding author), Alhadi Saputra (Indonesian Agency for Agricultural Research and Development), Hadi Supratikta (0000-0003-1876-6461, National Research and Innovation Agency, corresponding author)
Year2025
Volume13
Pages1673734-1673734
Publication date2025-11-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1673734
PMID41268397
OpenAlexW4415902557
LanguageEN
References cited50

This study investigates the determinants of health resilience among TAGANA volunteers in Indonesia using Decision Tree Regression (DTR) and Random Forest Regression (RFR). Data from 200 respondents show that life risk is the most dominant negative factor, while hope healthy acts as a strong protective factor; other variables such as disease history, dynamic experience, and physical-mental balance contribute moderately. RFR outperformed DTR in stability, confirming the robustness of the findings. The results emphasize the need for risk mitigation, psychosocial support, and lifestyle-based interventions, while international best practices provide models for strengthening volunteer resilience. This study contributes evidence-based insights for policy and training frameworks to improve TAGANA’s long-term sustainability in disaster response

Decision tree · Indonesian · Preparedness · Psychological resilience · Psychosocial · Random forest · Regression · Regression analysis · Disaster Management and Resilience · Posttraumatic Stress Disorder Research · Resilience and Mental Health