Chronic pain impacts individuals, their families, and society significantly, yet specialist care resources are limited, with most patients managed in primary care. There is a need for tools that support self-management and improve resource allocation. This feasibility study evaluates the implementation of Paindrainer®, a CE-marked Class I digital tool, in primary care. Paindrainer® combines patient self-monitoring via an app with a healthcare provider portal (CARE) for remote monitoring. Using advanced neural networks, it offers personalized feedback to help patients plan and monitor daily activities and their impact on pain. The study aims to assess whether integrating this tool can enhance chronic pain management and patient quality of life.

Long-term pain causes significant suffering to the individual, their loved ones and also entails high societal costs. In specialist care, constant development is underway through the implementation of new research and clinical findings. Patients' own efforts, decisions and strategies are a central and effective part of today's pain management. The importance of strengthening communication between patient and healthcare professionals is increasingly emphasised, as well as promoting the patient's ability to self-manage their situation.

More recently, behavior-modifying techniques have been integrated as complementary measures in the treatment of chronic pain. Despite this, a challenge remains for the healthcare system to create long-term sustainable outcomes for people with chronic pain.

The proportion of people with long-term pain who currently receive treatment in specialist care is very small, and the majority are treated in primary care instead. Resources for this patient group are insufficient and there is a great need for new tools for self- and remote monitoring that could improve the allocation of resources for this group.

This feasibility study aims to investigate whether a digital remote monitoring tool, Paindrainer®, can be implemented in primary care. The tool contains two parts, an app for the patient to use for their own monitoring of activity levels and symptoms, and the CARE portal, which is a remote monitoring tool for healthcare. The study will further explore how the implementation of this digital app in the existing treatment strategy can help address these challenges and improve care for people with chronic pain.

Paindrainer® is a CE marked class 1 product according to MDR and is based on advanced neural networks, which enables sophisticated calculations and takes into account more variables that affect the individual's pain experience and function than the human brain can handle. By using advanced calculations, Paindrainer provides continuous feedback to the patient, giving them a tool to plan and monitor their activities and understand how they affect each other.

This study will further investigate how Paindrainer® can support the individual to plan their activities in both "necessary" areas (such as daily chores, work, sleep) and other areas that are valuable to the individual (e.g. extracurricular activities, social and physical activities). By strengthening the patient's own role, Paindrainer is expected to increase the individual's quality of life and perceived health in both the short and long term.

Inclusion Criteria:

Has pain that affects daily life and has lasted for more than 3 months

Is over 18 years old

Understands Swedish or English

Is motivated and willing to use a digital tool for self-monitoring of activity level and symptoms

Has no planned surgeries during the study period

Has knowledge of and access to using a smartphone or tablet

Exclusion Criteria:

Severe or acute mental illness, severe anxiety, or depression

Ongoing history of substance use disorder

Serious illness under active treatment

Pain related to malignancy

Currently involved in legal proceedings or ongoing litigation related to low back or neck pain

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De-identified individual participant data (demographic information, primary and secondary outcomes) will be shared.

Data will be available starting 6 months after publication of primary results and will be accessible for 5 years thereafter.

Qualified researchers with an approved proposal can request access via the study sponsor. Data will be shared through a secure data sharing platform.