Systematic Review of Self-Assessment Scales for Specific Negative Symptom Domains in Psychotic Disorders

Background and Hypothesis Negative symptoms (NS) impair outcomes in schizophrenia, affecting quality of life, and resisting pharmacological treatments. Scales targeting specific NS domains—eg, anhedonia, avolition, alogia, social withdrawal, and blunted affect—allow clinicians to assess how treatments affect individual symptoms, and deepen understanding of NS pathophysiology. While observer-rated scales are most widely used, self-assessment tools can provide insight into individuals’ personal experiences. Here we evaluated the psychometric properties of NS self-assessment scales, focusing on tools for specific domains, to guide tailored treatments in clinical and research settings. Study Design We conducted a comprehensive literature review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, searching MEDLINE, and Web of Science for self-assessment scales evaluating specific NS domains. Each tool’s methodological quality was assessed using the COnsensus-based Standards for the selection of health Measurement INstruments checklist. Study Results We identified 15 self-assessment scales: 7 for anhedonia, 7 for avolition, 1 for social withdrawal, and none for alogia or blunted affect. The Temporal Experience of Pleasure Scale was the most valuable tool for anhedonia, with a grade B recommendation. All instruments assessing avolition were assigned a grade C recommendation, due to the limited numbers of validation studies. The University of California Los Angeles Loneliness Scale Version 3 (UCLALS-V3) was the only self-report measure targeting social withdrawal, but its emphasis on depressive symptomatology weakened its recommendation for NS assessment. Conclusion We identified 15 promising self-assessment scales on specific NS domains. Although they require further validation notably on their sensitivity to change, they provide detailed insights into symptomatology and facilitate precise monitoring.