## 4 Discussion  
The findings from this systematic review suggest that a decrease in pain intensity following mHealth-based exercise therapy is associated with an improvement in physical function in patients with chronic musculoskeletal pain. This association was modulated by several factors, including individual characteristics (BMI), the mHealth intervention dose (frequency of sessions), and the completion rate. On the contrary, we found no association between changes in pain intensity and anxiety symptoms. This contradicts previous findings on the role of mental well-being as a functional outcome predictor in musculoskeletal care [64], but it is line with a recent systematic review concluding that there is not enough evidence to suggest that mental health moderates the effect of exercise on pain and physical function in patients with hip or knee OA [18]. In contrast, a previous study reported how psychosocial factors can moderate the effect of exercise interventions on pain and disability in patients with chronic low back pain [65]. This study raised an important dilemma as to whether psychosocial factors truly function as moderators (where the psychosocial state influences the effect of exercise) or as mediators (where exercise influences the psychosocial state, which subsequently impacts pain), as suggested with the present results [65]. Stratified care entails tailoring treatment to specific subgroups of patients based on key characteristics, such as prognostic factors [66]. Among the observed variables that can modulate the association between pain and physical function, BMI has already been considered, with a strong level of evidence, as a predictor of functional outcomes in musculoskeletal care [64]. Specifically, obesity has been associated with increased pain following exercise in patients with knee OA [67] and, therefore, could influence the effect of exercise on pain and function in people with hip or knee OA [68]. However, a recent systematic review and individual participant data meta-analysis concluded the opposite [18]. Despite the contradictory evidence, clinicians seem to perceive patients with obesity as the most difficult to manage to implement exercise therapy in individuals with OA [68]. In this context, how physiotherapists should discuss obesity with patients and the need for inter-professional collaboration, e.g., with a dietitian, have been reported as the main barriers to overcome in the clinical setting [68]. As opposed to obesity, age did not seem to influence the association between changes in pain and physical function after the intervention. The role of age as a moderator of the effect of exercise is still a matter of debate [16; 18; 69] and could be especially relevant considering mHealth technologies. An older age is often cited as a barrier to the adoption of mHealth [70]. However, this may not be only attributed to age per se but rather to other contextual aspects, such as the device's ease of use and cognitive challenges [70]. Figure 4: Pooled Effect of Pain and Anxiety [43; 44]. mHealth technologies may help to enhance a more personalized treatment [71]. Our findings support the importance of the mHealth intervention dose and completion rate, which reinforces the crucial role of treatment adherence. The loss of motivation and lack of adherence to exercise is a real problem, as it compromises its effectiveness for chronic musculoskeletal pain [72]. The individualization of exercise programs and the use of self-monitoring tools, e.g., mobile devices, could lead to more adherent behavior [21]. However, users' adherence to mHealth programs is also an issue [73]. Although adherence to mHealth should be automatically recorded [73], it is frequently poorly reported, as shown with the mERA checklist. In addition, providing training to clinicians in technical aspects, such as digital literacy, could ensure a more effective use of the technology and, consequently, yield better outcomes [23].