Network intervention analysis of a digital intervention for the prevention of depression in patients with chronic back pain

Depression frequently co-occurs with chronic back pain (CBP), complicating treatment outcomes and increasing healthcare utilization. Digital interventions have demonstrated efficacy for the prevention of major depressive disorder (MDD) in individuals with CBP. However, little is known about how these interventions exert the effects at the symptom level. This was a secondary analysis of a RCT for the prevention of depression in patients with subclinical symptoms of depression and co-occurring CBP. N = 295 participants were randomized to a digital intervention lasting approximately 8 weeks or a treatment-as-usual control (TAU) group. Network analysis was used to examine the multimorbid symptom network structure and the symptom-specific treatment effects of the intervention. Depressive symptoms were assessed by the 9-item patient health questionnaire (PHQ-9) and pain-related disability was measured by the 10-item Oswestry Disability Index (ODI). Network analysis of the symptom networks prior to the intervention revealed that the depressive symptom “energy” was the strongest bridge connecting the communities of depression and pain disability symptoms. The largest influence of the intervention post-treatment was also on the “energy” symptom (PHQ4, -0.18). Additionally, the intervention directly improved “concentration” (PHQ7, -0.13), and “pain intensity” (ODI1, -0.09). The current study highlights the role that the symptom of “energy” may play in multimorbid depression and CBP. It also provides a hypothetical mechanism by which in intervention for the prevention of MDD in patients with CBP exerted its effects. Symptom-level approaches using network analysis may facilitate a deeper understanding of multimorbidity, as well as a framework for developing more targeted, effective interventions.