The purpose of this study was to develop an Android App based on the clinical classification criteria for patients with CMP according to their pain phenotype. This study explores the feasibility and usability of the Algo(s)rithm app in clinical practice.
The study was conducted with 27 physiotherapists to assess the feasibility and usability of the "Algo(s)rithm" app in supporting clinical decision-making for CPM. The uMARS (user version of the Mobile App Rating Scale) tool was used to evaluate the app's usability, acceptance, interactivity, and the quality of information provided. Participants classified a patient scenario, using the app, in the appropriate pain phenotype. Data were gathered on the app’s functionality, aesthetics, and user satisfaction.
The study included 27 physiotherapists, specializing in musculoskeletal conditions, with a mean age of 31.48 years (±7.40). The majority (81.5%) reported that the vignettes had a similar level of difficulty. Participants rated the Algo(s)rithm app positively, with an overall quality score of 4.21 (SD = 0.38) and high scores for engagement (mean = 4.59), appropriateness for the target population (mean = 4.59), and reliability of information (mean = 4.56). While features like personalization and aesthetics received slightly lower ratings (mean = 3.74), all users indicated they would recommend the app, and over half (55.5%) would be willing to pay for it. A significant majority (81.5%) rated the app with 4 or 5 stars, and 88.9% expressed intent to use it more than 10 times in the next year.
The findings of this study suggest that the "Algo(s)rithm" eHealth app is a promising tool for enhancing the clinical decision-making process among physiotherapists managing chronic musculoskeletal pain. The positive ratings in usability, engagement, and the reliability of information indicate that the app is well-received and potentially beneficial in clinical practice.
Given that a significant proportion of participants expressed willingness to recommend the app and consider payment for its use, there is a strong indication of its value within the healthcare community. These results highlight the importance of integrating digital health solutions in clinical practice to improve the assessment and classification of pain phenotypes. Furthermore, the field of pain phenotype-based assessment is constantly evolving, and through this app, continuous updates can be provided to ensure clinicians have access to the latest and most accurate knowledge.
chronic musculoskeletal pain
eHealth
