Health data management practices in RDI collaboration

• Head: Kirsi Sipilä, Professor/ Dental Prosthodontics and Stomatognathic Physiology
• Faculty: Faculty of Medicine, Research Unit of Population Health
• Group composition: Professors: 4 (Kirsi Sipilä, Research Unit of Population Health, University of Oulu, and Oulu University Hospital; Minna Isomursu, Digital Health, University of Oulu; Martti T. Tuomisto (emer.), Clinical Psychology, Faculty of Social Sciences (Psychology), Tampere University; Mikko Tulppo, Department of Physiology, Research Unit of Biomedicine, University of Oulu). Associate Professors: 1 (Ritva Näpänkangas, Research Unit of Population Health University of Oulu, and Oulu University Hospital). Postdocs: 3 (Outi Huhtela, Unit of Dentistry, University of Eastern Finland; Rasmus Valtonen, Department of Physiology, Research Unit of Biomedicine, University of Oulu; Juha Markkula, Turku University Hospital Sleep and Breathing Centre and Psychiatry Outpatient Clinic, and University of Turku). Researcher: 1 (Psychologist Vuokko Hägg, Privat Practice, Espoo)
• Website: https://www.oulu.fi/en/university/faculties-and-units/faculty-medicine/research-unit-population-health
• Contact: kirsi.sipila (at) oulu.fi
• Postdoctoral researcher: Marco Antonio Dias da Silva

Chronic pain affects more than 30 % of population world-wide at some stages of life. Temporomandibular disorders (TMD), including pain conditions linked with masticatory muscles and/or temporomandibular joints, are the second most prevalent musculoskeletal pain condition. Applied relaxation (AR) is a scientifically tested and widely used self-control method for treatment of various psychic and somatic conditions, f ex musculoskeletal pains. The patient is guided to control his/her autonomic reactions and sensations with the aid of relaxation of body. Learning of the method includes several stages using a 6-week program. Digitalization could offer an efficient and flexible use of this method, considering the accessibility, timing, cost-effective use of health care resources, and sustainability. The aim of this randomized, controlled multicenter study is to evaluate the effect of a web application of AR training on TMD pain symptoms, psychosocial symptoms and quality of sleep in TMD pain patients. Additionally, the aim is to study the effect of the AR treatment on autonomic function in a subsample of the TMD pain patients.

The sample includes 124 TMD pain patients from four units of the Student Health Service (YTHS) in Finland. Diagnosis of TMD is based on international, validated Diagnostic Criteria for TMD (DC/TMD). Before treatment, the patients fill in a webropol questionnaire inquiring general health and body pain symptoms, psychosocial symptoms (based on DC/TMD Axis II instruments), and quality of sleep (based on Sleep Condition Indicator). The patients are randomly assigned to two groups (n=62 per group). The splint group is treated as traditionally by a stabilization splint. The AR group uses the web application for training of the method. The questionnaire data are collected before treatment, and 6 weeks, 3 months and 1 year after treatment. Autonomic function (heart rate variability, continuous blood pressure and baroreflex sensitivity) is measured for patients in Oulu YTHS unit (n=31). The patients also use a sleep diary mobile application (Oneiros unipäiväkirja, Oneiros Therapies Oy Ltd) starting 2 weeks before and during the treatment, and 2 weeks before 3 month and 1 year follow-up. The permission of the study has been applied from the Ethical Committee of the Wellbeing Services County of North Ostrobothnia. The duration of the project is 7 years. At present, the web application (Relappy.app) has been made in collaboration with Arcode Oy and is ready for testing. Collaboration is also performed with Oneiros Therapies Oy Ltd.

The present study provides much data from sleep diary registrations and AR web application, questionnaires, and autonomic function. The participants evaluate the state of relaxation before and after each exercise, which also provides data. The analyses of data include comparisons of the variables between the treatment groups at different time points, as well as analyzing the associations between sleep diary parameters and pain variables (intensity of pain, pain-related disability). The topic includes in the theme “Health data management in the practices in RDI collaboration”. The project brings together a diverse team of experts, including data scientists, in development of AR web application as practical solution in healthcare.

Key words: pain, relaxation, web application