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All Journal Sriwijaya Journal of Forensic and Medicolegal Sriwijaya Journal of Obstetrics and Gynecology
Taufiq Indera Jayadi
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Biochemistry, Genetics & Molecular Biology Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health

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Knowledge, Attitudes, and Practices Regarding Contraception Among Young Women in Urban Indonesia: A Mixed-Methods Approach Hidayat, Rachmat; Cinthya Callathea; Taufiq Indera Jayadi; Maximillian Wilson
Sriwijaya Journal of Obstetrics and Gynecology Vol. 2 No. 1 (2024): Sriwijaya Journal of Obstetrics and Gynecology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjog.v1i2.95

Abstract

Introduction: Unintended pregnancies and unsafe abortions remain significant public health concerns in Indonesia, particularly among young women in urban areas. This study aimed to explore the knowledge, attitudes, and practices (KAP) regarding contraception among young women residing in urban Indonesia, employing a mixed-methods approach to gain an in-depth understanding of this complex issue. Methods: This study used a sequential explanatory mixed-methods design. The quantitative phase involved a cross-sectional survey of 500 young women aged 18-24 years residing in Jakarta, Indonesia. A structured questionnaire assessed their knowledge about various contraceptive methods, attitudes towards contraception, and current contraceptive practices. The qualitative phase comprised in-depth interviews with 30 participants purposively selected from the survey sample to explore their experiences, beliefs, and perspectives on contraceptive use. Quantitative data were analyzed using descriptive statistics and logistic regression, while thematic analysis was employed for qualitative data. Results: The quantitative findings revealed that while the majority of participants had good knowledge about contraception, misconceptions and gaps existed regarding specific methods, particularly long-acting reversible contraceptives (LARCs). Attitudes towards contraception were generally positive, although concerns about side effects and social stigma were prevalent. The prevalence of current contraceptive use was moderate, with condoms and oral contraceptive pills being the most common methods. Qualitative findings provided deeper insights into the factors influencing contraceptive use, including perceived susceptibility to pregnancy, partner communication, family and social influences, access to healthcare services, and religious beliefs. Conclusion: This study highlights the need for comprehensive sexuality education programs tailored to address misconceptions and promote informed decision-making about contraception among young women in urban Indonesia. Strategies to improve access to youth-friendly contraceptive services and address social and cultural barriers to contraceptive use are also essential.
Decoding Deception: Advanced fMRI and Machine Learning Techniques for Detecting Malingered Psychiatric Symptoms in Forensic Evaluations in Indonesia Taufiq Indera Jayadi; Taryudi Suharyana; Vita Amanda; Brenda Jaleel
Sriwijaya Journal of Forensic and Medicolegal Vol. 2 No. 2 (2024): Sriwijaya Journal of Forensic and Medicolegal
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjfm.v2i2.200

Abstract

Introduction: Detecting malingered psychiatric symptoms presents a significant challenge in Indonesian forensic evaluations, potentially impacting justice and resource allocation. Current methods rely heavily on clinical judgment and psychometric testing, lacking objective biomarkers. This study explored the potential of combining functional magnetic resonance imaging (fMRI) with machine learning (ML) to identify neural patterns differentiating malingered from genuine psychiatric symptoms in an Indonesian forensic context. Methods: This case-control study included 90 Indonesian male participants referred for forensic psychiatric evaluation (visum et repertum psychiatricum): 30 diagnosed genuine psychiatric patients (schizophrenia/psychotic depression), 30 individuals identified as malingerers, and 30 healthy controls. Participants underwent clinical assessment, psychometric testing (including symptom validity tests - SVTs), and an fMRI scan using a symptom-endorsement paradigm designed to probe cognitive control and deception-related neural activity. Preprocessed fMRI data were analyzed using group-level GLM and machine learning (Support Vector Machine - SVM; Random Forest - RF) classifiers trained on extracted features (ROI activation, functional connectivity) to distinguish malingerers. Performance was evaluated using k-fold cross-validation. Results: fMRI results indicated significantly greater activation in the malingering group compared to genuine patients and controls in prefrontal (dlPFC, vlPFC) and anterior cingulate cortex (ACC) regions during feigned symptom endorsement (p<0.001, FWE-corrected). An SVM classifier using combined ROI activation and functional connectivity features achieved the highest accuracy (83%), sensitivity (80%), specificity (86%), and AUC (0.88) in distinguishing malingerers from genuine patients. Conclusion: These findings suggest that integrating fMRI and ML techniques holds promise as an objective, supplementary tool for detecting malingered psychiatric symptoms within Indonesian forensic evaluations. While promising, the moderate accuracy highlights the need for further validation, consideration of ethical implications, and adaptation to the Indonesian context before any potential clinical application.
Co-Authors Brenda Jaleel Cinthya Callathea Maximillian Wilson RACHMAT HIDAYAT Taryudi Suharyana Vita Amanda