Interoception refers to the process of perceiving and interpreting internal physiological signals and plays a central role in symptom perception. In conditions with a high symptom burden such as chronic obstructive pulmonary disease (COPD), clinical features including dyspnea perception, depression, and sleep quality may be influenced not only by disease severity but also by the interpretation of internal bodily signals.

Recent evidence suggests that respiratory-related internal signals are transmitted to the central nervous system through multiple afferent pathways and integrated within cortical and subcortical networks, contributing to subjective experiences such as dyspnea. In this context, dyspnea perception may arise from the interaction between disease severity and interoceptive processes.

Depressive symptoms and impaired sleep quality are also closely associated with interoceptive processes and may contribute to the perception of respiratory symptoms. However, studies simultaneously examining interoception, disease severity, dyspnea perception, depression, and sleep quality in hospitalized patients with acute COPD exacerbation are limited.

This prospective, observational, cross-sectional study will include 50 individuals aged 40 years and older who are hospitalized with acute COPD exacerbation in a Chest Diseases clinic. Data will be collected at a single time point when patients are clinically stable, without interfering with routine clinical care. Participants will be recruited using a consecutive sampling method.

Sociodemographic and clinical data will be obtained from patient records and a structured data collection form. Disease severity will be assessed using oxygen requirement, respiratory rate, oxygen saturation, and arterial blood gas values when available. Interoception will be evaluated using the Multidimensional Assessment of Interoceptive Awareness (MAIA-2). Symptom burden will be assessed with the COPD Assessment Test (CAT), dyspnea with the Modified Medical Research Council (mMRC) scale, sleep quality with the Richards-Campbell Sleep Questionnaire (RCSQ), and depressive symptoms with the Hospital Anxiety and Depression Scale - Depression subscale (HADS-D).

Statistical analyses will be performed using IBM SPSS Statistics software. Relationships between variables will be analyzed using Pearson or Spearman correlation depending on data distribution, with a significance level of p<0.05.