Objective:

To synthesize diagnostic challenges in adolescent borderline personality disorder (BPD) and evaluate the need for dynamic assessment tools that integrate personality functioning, digital indicators, and AI-enhanced assessment tools.

Approach:

• Assessment Tools: Evaluates existing LPF-based assessment tools like LoPF-Q 12–18 and AIDA, noting their limitations in capturing rapid, context-dependent changes in adolescent behavior.

Key Findings:

• BPD is often underdetected and undertreated in adolescents due to diagnostic uncertainty and stigma.
• Existing assessment tools provide static evaluations that do not capture the dynamic nature of adolescent BPD.
• Digital phenotyping and AI can enhance traditional assessments by providing continuous data on behavioral and physiological signals.

Interpretation:

The review highlights the need for developmentally sensitive assessment approaches that integrate traditional and digital methods.

Limitations:

• The review does not present a validated clinical framework or original data, which limits its applicability.
• It focuses on conceptual integration rather than systematic evidence mapping.

Conclusion:

A hybrid assessment model combining LPF-based tools and digital indicators may improve the understanding and diagnosis of adolescent BPD.