<![CDATA[The increasing intensity of reports of emotional disorders and high individual resistance in accessing professional psychological services due to social stigma are the background to this research. These operational issues have triggered a shift in the preferences of the younger generation to seek alternative, non-traditional support spaces through the interaction of artificial intelligence technology. The main focus of this scientific study is to adapt and validate the psychometric structure of the Online Self-Disclosure Scale instrument in the context of subject self-disclosure to conversational artificial intelligence. The steps for developing this measurement tool (scale development) were operated through a Google Forms digital survey reaching 432 respondents from the Generation Z group in the Greater Jakarta area. Sampling was carried out using a non-probability sampling method with the criteria for subjects aged 18 to 25 years, executed through a purposive sampling technique. Statistical parameter analysis was processed interactively using content validity requirements tests, internal reliability, and Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) modeling. Quantitative data from the empirical evaluation showed that this 17-item instrument met the four-dimensional model's structural suitability (Goodness of Fit) very well, as indicated by the CFI index achievement of 0.957, TLI of 0.948, and GFI of 0.994. The estimated McDonald's omega reliability index was at 0.941 and Cronbach's alpha of 0.939. The main conclusion confirms that this adapted scale draft has proven valid, reliable, and stable for measuring digital psychology phenomena on an ongoing basis. ABSTRAK Meningkatnya intensitas pelaporan gangguan emosional serta tingginya resistensi individu dalam mengakses layanan psikologis profesional akibat stigma sosial melatarbelakangi penelitian ini. Masalah operasional tersebut memicu pergeseran preferensi generasi muda untuk mencari ruang dukungan alternatif nontradisional melalui interaksi teknologi kecerdasan buatan. Fokus utama kajian ilmiah ini adalah mengadaptasi serta memvalidasi struktur psikometrik instrumen Online Self-Disclosure Scale dalam konteks keterbukaan diri subjek terhadap conversational artificial intelligence. Langkah-langkah pengembangan alat ukur (scale development) ini dioperasikan melalui survei digital Google Forms dengan menjangkau 432 responden dari kelompok Generasi Z di wilayah Jabodetabek. Penarikan sampel dijalankan menggunakan metode non-probability sampling dengan kriteria subjek berusia 18 hingga 25 tahun yang dieksekusi melalui teknik purposive sampling. Analisis parameter statistik diproses secara interaktif menggunakan uji persyaratan validitas isi, reliabilitas internal, serta pemodelan Exploratory Factor Analysis (EFA) dan Confirmatory Factor Analysis (CFA). Data kuantitatif hasil evaluasi empiris menunjukkan instrumen 17 butir ini memenuhi kesesuaian struktur model empat dimensi (Goodness of Fit) yang sangat baik, ditunjukkan oleh capaian indeks CFI sebesar 0,957, TLI sebesar 0,948, dan GFI sebesar 0,994. Estimasi indeks reliabilitas McDonald’s omega berada pada parameter 0,941 serta Cronbach’s alpha sebesar 0,939. Simpulan utama menegaskan bahwa draf skala adaptasi ini terbukti sahih, andal, dan stabil untuk mengukur fenomena psikologi digital secara berkelanjutan. ]]>
