A latent trajectory analysis of inpatient depression treatment

Patients seeking psychotherapy may progress through treatment in varying ways. Modeling multiple treatment trajectories through growth mixture modeling provides a comprehensive way of understanding a patient population. Multiple trajectories may additionally help researchers describe complexities within a patient population, such as those with severe and persistent disorders and comorbid symptoms, to understand characteristics of patients that may be struggling during treatment. We analyzed the depression symptom outcome measures (PHQ-9) for 246 patients receiving inpatient depression treatment. We constructed a growth mixture model of depression symptom changes, allowing the number of treatment trajectories to emerge through the data, and utilized goodness-of-fit indices to select the superior model. Results indicated three classes was the best fitting model, with patients either (a) patients started above the clinical cutoff score for depression and had significant linear change over time, ending therapy just above the clinical cutoff-"Improvement-leveling off-improvement"; (b) patients started therapy well above the clinical cutoff, showed symptom alleviation at the beginning of therapy before the trajectory started to level off-"High symptom pressure"; or (c) patients started therapy just below the clinical cutoff, had steady change throughout therapy, ending well below the clinical cutoff-"continuous improvement." Implications of the study may include altering the length of treatment based on patient presenting symptoms in order to best serve patients and utilize hospital resources. (PsycInfo Database Record (c) 2022 APA, all rights reserved).