Luthfiah Mawar
Sekolah Tinggi Ilmu Kesehatan Sehati Medan

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Administrative Resilience in Middle Eastern Healthcare within Conflict Zones Agustina Bangun; M. Agung Rahmadi; Luthfiah Mawar; Suranta Ginting; Hariana Erdewi Sinaga; Helsa Nasution; Nurzahara Sihombing
International Journal Of Health Science Vol. 5 No. 3 (2025): November : International Journal of Health
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/ijhs.v5i3.6206

Abstract

This study examines the construct of administrative resilience within mental and physical health service systems in Middle East conflict zones using Confirmatory Factor Analysis (CFA) within Structural Equation Modeling (SEM). Data were derived from 847 policy documents and operational reports from twelve countries (2018–2024), accessed through official online sources. The measurement model showed good fit indices (χ²/df = 2.134, CFI = 0.962, TLI = 0.955, RMSEA = 0.047, SRMR = 0.038), indicating structural stability and validity of the theoretical model. CFA confirmed four dimensions of administrative resilience with significant loadings: Adaptive Policy (λ = 0.871, CR = 12.453, p < 0.001), Cross-Sector Coordination (λ = 0.834, CR = 11.287, p < 0.001), Professional Competence (λ = 0.792, CR = 10.564, p < 0.001), and Operational Stability (λ = 0.815, CR = 11.098, p < 0.001). Reliability results were strong (Cronbach's α = 0.863–0.921; Composite Reliability = 0.879–0.934; AVE = 0.647–0.782). Findings reinforce Boin and Lodge’s (2016) concept of organizational resilience and extend Comfort et al. (2010) by integrating operational stability as a relevant dimension in conflict settings. Unlike Kruk et al. (2015), which focused on general health systems, this study identifies unique adaptive mechanisms within dual mental–physical services while addressing the fragmentation gap noted by Jawad et al. (2019) through empirical formulation of interdependent administrative dimensions.
Behavioral dynamics of halal cryptocurrency investing: cognitive and emotional mechanisms within islamic finance principles M. Syukri; Ade Sofyan Mulazid; M. Agung Rahmadi; Luthfiah Mawar; Helsa Nasution; Nurzahara Sihombing
Jurnal Konseling dan Pendidikan Vol. 13 No. 4 (2025): JKP
Publisher : Indonesian Institute for Counseling, Education and Therapy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/1201700

Abstract

This study comprehensively investigates the influence of cognitive biases, emotions, and Islamic legal understanding on halal cryptocurrency investment decisions among Muslim investors. Employing a Meta-Structural Equation Modeling (MASEM) approach, the analysis is based on data from 12,780 respondents in Muslim-majority countries to identify patterns of relationships among key variables. The primary findings of this research affirm that overconfidence has a significant positive impact on investment intention (β = 0.41, p < 0.01), consistent with Shiller (2017), who highlighted that excessive confidence can drive risk-taking behavior in financial markets. Conversely, loss aversion demonstrates a significant negative effect (β = -0.53, p < 0.01), aligning with Kahneman and Tversky's (2013) findings regarding preferences for avoiding losses under uncertainty. Regarding emotional factors, anxiety about price volatility is a major deterrent to investment (β = -0.54, p < 0.01). However, a Sharia-compliant label mitigates negative perceptions among Muslim investors toward cryptocurrency investments, enhancing their sense of security and trust (β = 0.36, p < 0.05). Lastly, understanding Islamic law significantly influences confidence in halal investments (β = 0.39, p < 0.05), corroborating the findings of El-Gamal (2006) and Din (2021) while underscoring the importance of Sharia-based financial literacy. The novelty of this study lies in its multidimensional integration of psychological behavior (cognitive biases and emotions) and Islamic law, thereby expanding the horizons of prior research. Consequently, this research contributes to the foundation of a new construct and provides practical guidance for developing Sharia-compliant financial products in the digital era.
Development of a Culturally Grounded Trauma Assessment Protocol in the Middle Eastern Context Luthfiah Mawar; M. Agung Rahmadi; Luthfiyah Aqilah Siagian; Sasa Maghfirah Siregar; Andieni Pratiwi; Helsa Nasution; Nurzahara Sihombing; Annisa Ardianti Br Tarigan
Jurnal Riset Ilmu Kesehatan Umum dan Farmasi (JRIKUF) Vol. 3 No. 4 (2025): Oktober : Jurnal Riset Ilmu Kesehatan Umum dan Farmasi (JRIKUF)
Publisher : LPPM STIKES KESETIAKAWANAN SOSIAL INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57213/jrikuf.v3i4.885

Abstract

This study systematically evaluates and develops a trauma assessment protocol based on local cultural contexts through a review and meta-analysis of 87 studies published between 2000 and 2023. Using JASP 0.16.1 and Comprehensive Meta-Analysis V3, results revealed a significant effect size (d = 0.78, 95% CI [0.65, 0.91], p < 0.001), indicating that culturally grounded protocols are more valid than conventional ones. Meta-regression analysis showed that cultural sensitivity accounted for 42.3% of improvements in diagnostic accuracy (β = 0.423, SE = 0.089, p < 0.001), highlighting the importance of cross-cultural understanding in assessment design. Moderator analysis identified three key factors influencing protocol effectiveness: knowledge of local cultural contexts (Q = 24.31, df = 3, p < 0.001), use of culturally appropriate language (Q = 18.76, df = 2, p < 0.001), and involvement of community leaders (Q = 15.92, df = 2, p < 0.001). The study’s heterogeneity was moderate (I² = 68.5%, τ² = 0.142), reflecting variations in implementation. These findings build on prior work by Alarcón et al. (2009) and Jackson et al. (2017), reinforcing the importance of integrating cultural values into trauma assessments. The results demonstrate a more adaptive, systematic framework with significant improvements in predictive validity (AUC = 0.89 compared to 0.76 in non-cultural protocols). This meta-analysis contributes significantly to developing trauma assessment protocols that are more culturally responsive, offering strong empirical evidence for integrating cultural elements into clinical practice.
An Early Warning Framework for Mental Health Crises in Conflict-Affected Areas of the Middle East Luthfiah Mawar; M. Agung Rahmadi; Sri Rahayu Sukirman; Nur Suci Ramadhani; Putri Widia Ramadhani Rambe; Helsa Nasution; Nurzahara Sihombing; Annisa Ardianti Br Tarigan
Antigen : Jurnal Kesehatan Masyarakat dan Ilmu Gizi Vol. 3 No. 4 (2025): November: Antigen : Jurnal Kesehatan Masyarakat dan Ilmu Gizi
Publisher : LPPM STIKES KESETIAKAWANAN SOSIAL INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57213/antigen.v3i4.886

Abstract

This study examines the effectiveness of the Early Warning System (EWS) in anticipating and responding to mental health crises in conflict-affected regions of the Middle East through a systematic review of 47 scholarly articles published between 2014 and 2024. The meta-regression findings indicate a significant contribution of EWS implementation to the reduction of post-traumatic stress disorder (PTSD) symptoms with a coefficient of β = -0.67 (p < .001), as well as depressive symptoms with a coefficient of β = -0.59 (p < .001) among populations directly affected by armed conflict. Among 12,456 respondents analysed, 73.8% reported a reduction in anxiety symptoms following the implementation of EWS, with an effect size of d = 0.82 (95% CI [0.76, 0.88]). Digitally based early warning systems demonstrated a significantly higher level of effectiveness (OR = 2.34, 95% CI [1.98, 2.70]) than conventional systems, which are more manual and reactive. Moderator analysis indicated that age (β = -0.31, p < .01) and the duration of exposure to conflict (β = 0.44, p < .001) play important roles in moderating the relationship between EWS interventions and various mental health indicators. These findings expand upon the conclusions of Fu et al. (2020) and Salesi (2023), which previously explored psychosocial interventions in conflict zones, by adding a new dimension—examining digital technology and predictive algorithms within EWS frameworks. The study explicitly demonstrates that integrating machine learning models into EWS can enhance the predictive accuracy of potential mental health crises to 84.6%, representing a novel contribution that has not been comprehensively documented in prior academic literature