App-based multidisciplinary back pain treatment versus combined physiotherapy plus online education: a randomized controlled trial

Abstract

Non-specific low back pain (LBP) is one of the leading causes of global disability. Multidisciplinary pain treatment (MPT) programs comprising educational, physical, and psychological interventions have shown positive treatment effects on LBP. Nonetheless, such programs are costly and treatment opportunities are often limited to specialized medical centers. mHealth and other digital interventions may be a promising method to successfully support patient self-management in LBP. To address these issues, we investigated the clinical effects of a multidisciplinary mHealth back pain App (Kaia App) in a randomized controlled trial (registered at German Clinical Trials Register under DRKS00016329). One-hundred one adult patients with non-specific LBP from 6 weeks to 1 year were randomly assigned to an intervention group or a control group. In the intervention group, the Kaia App was provided for 3 months. Control treatment consisted of six individual physiotherapy sessions over 6 weeks and high-quality online education. The primary outcome, pain intensity, was assessed at 12-week follow-up on an 11-point numeric rating scale (NRS). Our per-protocol analysis showed no significant differences between the groups at baseline (Kaia App group: M = 5.10 (SD = 1.07) vs. control group: M = 5.41 (SD = 1.15). At 12-week follow-up the Kaia App group reported significantly lower pain intensity (M = 2.70 (SD = 1.51)) compared to the control group (M = 3.40 (SD = 1.63)). Our results indicate that the Kaia App as a multidisciplinary back pain app is an effective treatment in LBP patients and is superior to physiotherapy in combination with online education.

Keywords: Computational biology and bioinformatics; Pain management.

Fig. 1

Study flow chart according to CONSORT

Fig. 2

Mean of the pain intensity index over time separately for both groups, error bars represent SEM, Asterisk denotes Bonferroni-corrected p-values < 0.05 (N_{Kaia App} = 42; N_{control group} = 44; a two-factorial split-plot ANOVA was used as omnibus-test; post-hoc t-tests were used for within- and between-group comparisons)

Fig. 3

Responder analysis: Percentage (relative frequency) of patients regarding reduction of pain index from baseline to 12-week follow-up in percent separately for both groups (N_{Kaia App} = 42; N_{control group} = 44). X²-test did not reveal significance

Fig. 4

Overview of the frequency of app use in the app-group (N = 42)

Fig. 5

Examples of app content illustrating the three implemented main therapy modules