Automated System for Scoring and Interpretation of the Satisfaction with Life Scale: Development and Clinical Applications

When psychological assessments are automated for scoring and interpreting the Satisfaction with Life Scale (SWLS), improvements in efficiency and error reduction are anticipated. We evaluated a Python-based system designed for automatic scoring and interpretation of the SWLS in a simulated environment. Performance metrics included processing time and scoring accuracy compared to traditional manual methods. Automation significantly reduced assessment time and minimized common manual scoring errors, with minimal impact on total score values. Findings suggest the system’s potential utility in clinical and research settings, while highlighting the need for further empirical validation using real participant data. Practical implications for psychological assessment and digital integration in professional workflows are discussed.