Key result
The selfBACK app improved low back pain outcomes; patients with the greatest depressive symptoms had a relative risk of improvement of 0.8 (95% CI 0.6-1.0) compared to those with no symptoms.
Why the study?
selfBACK provides AI-based self-management support for low back pain, but whether individuals with depressive or stress symptoms benefit from this technology remained to be explored.
Does the selfBACK app improve LBP-related disability in patients with low back pain, including those with high levels of depression or stress?
RCT (n=461)
randomized
Does the selfBACK app improve LBP-related disability in patients with low back pain, including those with high levels of depression or stress?
Relative Risk: 0.8 (95% CI 0.6–1)
The selfBACK app can improve low back pain outcomes even in patients with high levels of baseline depression and stress symptoms, supporting the use of digital health interventions for chronic pain.
Supports selfBACK app use for low back pain even with high depressive symptoms; extends RCT evidence for digital tools in comorbid chronic pain.
BACKGROUND: selfBACK provides individually tailored self-management support for low back pain (LBP) via an artificial intelligence-based smartphone app. We explore whether those with depressive/stress symptoms can benefit from this technology. METHODS: Secondary analysis of the selfBACK randomized controlled trial (n = 461). Participants with LBP were randomized to usual care (n = 229), or usual care plus selfBACK (n = 232). PRIMARY OUTCOME: LBP-related disability (Roland-Morris Disability Questionnaire, RMDQ) over 9 months. SECONDARY OUTCOMES: global perceived effect (GPE)/pain self-efficacy (PSEQ)/satisfaction/app engagement. Baseline depressive symptoms were measured using the patient health questionnaire (PHQ-8) and stress with the perceived stress scale (PSS). Outcomes stratified by baseline PHQ-8/PSS scores to assess associations across the whole cohort, and intervention versus control groups. RESULTS: Participants with higher levels of depressive/stress symptoms reported more baseline LBP-related disability (RMDQ 3.1; 1.6 points higher in most vs least depressed/stressed groups respectively); lower self-efficacy (PSEQ 8.1; 4.6 points lower in most vs least depressive/stressed groups respectively). LBP-related disability improved over time; relative risk of improvement in those with greatest depressive/stress symptoms versus nil symptom comparators at 9 months: 0.8 (95% CI: 0.6 to 1.0) and 0.8 (95% CI: 0.7 to 1.0) respectively. No evidence that different baseline levels of depressive/perceived stress symptoms are associated with different RMDQ/GPE/PSEQ outcomes. Whilst participants with higher PHQ-8/PSS were less likely to be satisfied or engage with the app, there was no consistent association among PHQ-8/PSS level, the intervention and outcomes. CONCLUSIONS: The selfBACK app can improve outcomes even in those with high levels of depressive/stress symptoms and could be recommended for patients with LBP. SIGNIFICANCE: We have demonstrated that an app supporting the self-management of LBP is helpful, even in those with higher levels of baseline depression and stress symptoms. selfBACK offers an opportunity to support people with LBP and provides clinicians with an additional tool for their patients, even those with depression or high levels of stress. This highlights the potential for digital health interventions for chronic pain.
No takes yet. Share an insight, caveat, or question.
Rughani et al. (2023) conducted an RCT in low back pain (LBP) (n=461). selfBACK artificial intelligence-based smartphone app vs. usual care was evaluated on LBP-related disability (Roland-Morris Disability Questionnaire, RMDQ) over 9 months (RR 0.8, 95% CI 0.6 to 1.0). The selfBACK app improved low back pain outcomes; patients with the greatest depressive symptoms had a relative risk of improvement of 0.8 (95% CI 0.6-1.0) compared to those with no symptoms.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: