Factors influencing the use of an artificial intelligence-based app (selfBACK) for tailored self-management support among adults with neck and/or low back pain

Purpose: Tailored self-management support is recommended as first-line treatment for neck and low back pain, for which mHealth applications could be promising. However, there is limited knowledge about factors influencing the engagement with such apps. The aim of this study was to assess barriers and facilitators for engaging with a self-management mHealth app among adults suffering from neck and/or low back pain.

Materials and methods: We carried out a qualitative descriptive study among adults with neck and/or low back pain. The artificial intelligence-based selfBACK app supports tailored self-management of neck and low back pain and was used for 6 weeks. After these 6 weeks, participants were interviewed by phone.

Results: Thirty-two adults (17 males) with neck and/or low back pain participated (mean age = 54.9 (SD = 15.8)). Our results show that the mode of delivery and the novelty of the selfBACK app were perceived most often as a barrier to use the app. The action plans of the app and health-related factors were perceived most often as facilitating factors.

Conclusions: This study provides insight into possible strategies to improve an mHealth service. Furthermore, it shows that adults with neck and/or low back pain are willing and ready to receive blended treatment.