Abstract
Objectives
The Self-Evaluation of Negative Symptoms Scale (SNS) is a self-report scale that evaluates a patient’s subjective experience on all five domains of the negative symptoms. This study aimed to present the adaptation and validation study of the Turkish version of SNS(SNS-TR).
Methods
Seventy-five patients and 50 controls were recruited for this study. After the approval of the translation, participants were asked to fill out SNS-TR by themselves. They were interviewed with the Brief Negative Symptoms Scale (BNSS), Positive and Negative Syndrome Scale (PANSS), and Calgary Depression Scale for Schizophrenia (CDSS).
Results
SNS-TR showed good internal consistency in the reliability analysis with Cronbach’s alpha= 0.873. Subscale-total score correlation coefficients were significant (p < 0.01). In the validity analyses, the total and subscale scores of SNS-TR showed positive correlations with the total and subscales of BNSS, with only one exception of BNSS lack of distress subscales. The total score of SNS-TR demonstrated a significant correlation with PANSS-total, PANSS-negative subscale, PANSS-general subscale, and CDSS scores. Confirmatory factor analysis showed acceptable values for the five-factor structure, similar to the original version.
Conclusion
To conclude, our study indicates that SNS-TR is an easily applicable self-evaluation tool with good psychometric properties for assessing negative symptoms.
SNS is a novel and easily applicable self-report scale for examining negative symptoms in schizophrenia patients, allowing them to evaluate their subjective experience on all five domains of the negative symptoms.
It shows good internal consistency (α= 0.873) which is similar to the original version (α = 0.867).
Confirmatory factor analysis scores were found in acceptable ranges and SNS-TR confirm the five-factor structure.
Using this scale in clinical practice would empower both the physician’s examinations and patient participation through treatment and follow-up course.
KEY POINTS
Acknowledgments
The authors thank Vincent Bouvard and Ilona Bouvard for their contributions to the translation and back-translation process.
Disclosure statement
The authors have nothing to disclose related to this study.