Hubungan Romantic Insecure Attachment dengan Perilaku Non-Suicidal Self-Injury (NSSI) pada Emerging Adulthood dengan Alexithymia sebagai Variabel Mediator
Bibliographic record
Abstract
Emerging adulthood merupakan periode yang tepat bagi individu yang ingin mengeksplorasi berbagai pengalaman romantis dan seksual. Individu dengan romantic insecure attachment dalam hubungan dapat menjadi faktor resiko dari NSSI. Penelitian ini bertujuan untuk mengetahui hubungan romantic insecure attachment dengan Non-Suicidal Self-Injury (NSSI) yang dimediasi oleh alexithymia pada emerging adulthood. Alexithymia, yang merujuk pada kesulitan dalam mengidentifikasi, menggambarkan, dan mengungkapkan emosi, diduga memediasi hubungan antara romantic insecure attachment dengan perilaku NSS. Partisipan pada penelitan ini merupakan 177 individu rentan usia 18-25 tahun yang pernah terlibat dengan Non-Suicidal Self-Injury (NSSI) dalam hubungan berpacaran. Pengumpulan data menggunakan metode survei kuisioner dengan instrumen pengukuran translasi The Inventory of Steatment about Self-Injury NSSI (Klonsky & Glenn, 2009), Experiences in Close Relationship-Revised (Fraley dkk. 2000), dan Toronto Alexithymia Scale-20 (TAS-20) (Bagby dkk. 1994). Hubungan positif signifikan ditemukan pada dimensi anxious attachment dengan NSSI baik secara langsung (p=0,029) maupun dimediasi oleh alexithymia (p=0,028) sedangkan dimensi avoidant attachment berhubungan signifikan dengan NSSI hanya dengan mediasi alexithymia (p=0,042).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".