Introduction: Diabetes has become a serious disease in the 21^st century, affecting a large number of people around the world. Considering the chronic nature and long-term effects of diabetes, problems such as changes in disease perception and sleep quality may occur. As a result, diabetic patients are exposed to a higher risk of depression, compared to non-diabetic cases. The aim of this study was to evaluate a prediction model of depression based on disease perception and sleep quality, mediated by pain catastrophizing.

Methodology: In this correlational study, the population consisted of all diabetic patients, referred to the diabetes clinic of Ayatollah Taleghani Hospital in Kermanshah, Iran. A total of 150 patients were selected via convenience sampling. The data collection tools included Beck Depression Inventory, brief illness perception questionnaire (IPQ), Pittsburgh sleep quality index, and pain catastrophizing scale. For statistical analysis, path analysis was performed using AMOS software. Also, stepwise regression analysis was carried out using SPSS.

Results: The results showed that disease perception and sleep quality could significantly and directly predict pain catastrophizing and depression. Finally, based on the proposed model, disease perception and sleep quality, mediated by pain catastrophizing, could significantly predict depression.

Conclusion: Based on the present results, use of appropriate treatments, such as cognitive behavioral therapy, acceptance and commitment therapy, and interventions for sleep quality improvement, pain relief, and mediation of catastrophic thoughts could prevent depression in diabetic patients.