Assessment of Psychological Distress in Surgical Patients: A Comparison Between Day Care and Long-Term Hospitalization in an Oncology Hospital

<b>Introduction:</b> Patients undergoing surgery are exposed to various stressors that may increase psychological distress during the perioperative period. These repercussions may be substantial, affecting both physical and mental health, as well as the ability to resume regular activities and overall quality of life. Aim: This study aimed to compare the preoperative psychological distress levels of patients admitted to long-term preoperative hospitalization (LONG) to those of patients admitted to day care (DC) facilities for ambulatory surgery within an oncology hospital and to examine potential sociodemographic predictors. <b>Methods:</b> This was a prospective observational study that included 176 individuals who underwent surgery in two cohorts. Patients in the DC cohort (<i>n</i> = 88) were treated in a day care surgery clinic, whereas patients in the LONG cohort (<i>n</i> = 88) were treated in a long-term oncology hospital. Demographic and clinical data were collected. Patients' psychological distress (depression, anxiety, and stress) was preoperatively evaluated using the DASS-42. Univariate and multivariate logistic regression analyses were performed. <b>Results:</b> The DASS-42 scale's Cronbach's alpha was 0.923. There was no significant difference between the cohorts in terms of age; however, waiting time before surgery differed significantly (U = 2884, <i>p</i> = 0.002). Stress levels differed significantly between the two cohorts (<i>p</i> = 0.05). <b>Conclusions:</b> Health managers and health care providers should consider gender, surgical severity, and rural/urban residence as factors associated with preoperative psychological distress. Studies assessing gender-specific dynamics, as well as mixed-methods approaches, could provide deeper insights into patients' experiences and the correlations of distress and highlight implications for oncology nursing practice across different hospitalization models.