AB1570-PARE PROFILING LOW BACK PAIN PATIENTS FOR THE DEVELOPMENT OF A PERSONALIZED COACHING APPLICATION

Abstract

Background: Low back pain is a major public health problem that is increasing with the aging of the population. It is the leading cause of disability in most countries [1]. The recommendations of Inserm (2019) include personalized physical activity programs according to the individual characteristics (motivation, preferences, attitude towards physical activity) and life context of each patient (family and professional load, socioeconomic level, living place) [2]. However, the current management of chronic low back pain includes rehabilitation programs that are costly and/or not always personalized, which reduces their effectiveness. Objectives: The objective of this research is to better understand the characteristics of people with chronic low back pain to identify main motivational profiles that will allow us to offer personalized coaching via a mobile application. Methods: After a review of the literature and following advice from experts in the management of chronic low back pain, we selected 8 scales to characterize patients: General Health Status (MYMOP), Treatment Burden (TBQ), Quality of Life (EQ-5D-5L), Level (IPAQ), Fears and Beliefs (FABQ-AP), and Motivation (EMAPS) for physical activity, Emotional Status (PHQ-9), and Sense of Self-Ef-fcacy (FC-CPSES). These questionnaires were administered online to participants in the ComPaRe (Community of Patients for Research) chronic low back pain cohort. An initial descriptive analysis of the results allowed us to describe our sample. In order to distinguish different motivational profiles of patients towards physical activity, we performed a Agglomerative Hierarchical Clustering (AHC) and a principal component analysis (PCA) of the results of the EMAPS, PHQ-9, FABQ-AP and FC-CPSES scales. Results: A total of 193 patients with chronic low back pain were included (m ≃ 54years, s ≃ 13years; majority women (74%); duration of low back pain: m ≃ 15years, s ≃ 12years; occupational status: 44% employed, 22% on disability, 19% retired). Clustering analysis allowed us to distinguish 4 main profiles that we named as follows: (1) 'Amotivated,' characterized by the lowest motivation and highest amotivation toward physical activity (I.e. they do not understand why it is useful), (2) 'Cautious' with low motivation and having the highest fears and beliefs toward physical activity, (3) 'Depressed' with good intrinsic motivation but also a signifcant level of depressive symptoms, and (4) 'Confdent' also showing good intrinsic motivation and having the highest sense of self-efficacy. Conclusion: The main novelty of this research is a new classifcation of 4 motivational profiles in the low back pain population determined by a clustering method. This typology is in line with the HAPA model of behavior change [3]. It will allow us to make recommendations for the design of a personalized mobile coaching application. Future work will aim to test and evaluate the personalization of e-coaching according to these profiles.