DOI: https://doi.org/10.14710/empati.2024.47903

CHATBOT AI DALAM IDENTIFIKASI AWAL GANGGUAN KESEHATAN MENTAL DI INDONESIA: TANTANGAN DAN PROSPEK

Fakultas Psikologi, Universitas Islam Negeri Syarif Hidayatullah Jakarta, Indonesia

Received: 25 Oct 2024; Published: 20 Jan 2025.
Open Access Copyright 2025 Jurnal EMPATI
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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Abstract

Kesehatan mental adalah aspek penting dari kesejahteraan yang seringkali diabaikan. Di Indonesia, prevalensi gangguan kesehatan mental pada usia 15 tahun ke atas mencapai 2%, dengan tantangan akses layanan yang terbatas (Kementerian Kesehatan RI, 2023). Teknologi AI, khususnya chatbot AI, menawarkan solusi potensial untuk deteksi awal gangguan kesehatan mental dengan menyediakan dukungan 24/7 dan skrining gejala awal (Fitzpatrick et al., 2017). Penelitian ini menggunakan metode tinjauan naratif untuk mengevaluasi potensi dan tantangan penerapan chatbot AI dalam konteks Indonesia. Pencarian sistematis dilakukan pada database elektronik utama seperti PubMed, Scopus, ScienceDirect, dan Google Scholar dengan kata kunci “Chatbot AI trends in mental health.” Pencarian dibatasi pada artikel berbahasa Inggris yang diterbitkan antara 2014 hingga 2024 untuk memastikan relevansi. Sebanyak 55 jurnal yang membahas penggunaan chatbot AI dalam kesehatan mental direview. Analisis data dilakukan secara tematik mengikuti prosedur Braun dan Clarke (2006), yang mencakup familiarisasi dengan data, pengkodean awal, pencarian tema, peninjauan tema, dan penamaan tema. Temuan menunjukkan bahwa chatbot AI dapat meningkatkan akses layanan kesehatan mental, mengurangi stigma, dan memberikan dukungan yang dipersonalisasi. Namun, tantangan seperti privasi data, keterbatasan empati, dan sensitivitas budaya harus diatasi. Studi ini merekomendasikan integrasi chatbot AI dalam sistem kesehatan mental Indonesia dan menekankan perlunya penelitian lebih lanjut untuk menilai efektivitas dan keamanan dalam konteks lokal.

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Keywords: akses layanan; Chatbot AI; deteksi awal; kesehatan mental; stigma

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