Introduction Patient education is an important part of the management of rheumatic and musculoskeletal diseases. Given that patients with diverse diseases do not have the same needs, it is crucial to assess the educational requirements of targeted groups to provide tailored educational interventions. The aim of our study was to assess educational needs of a large cohort of patients with different rheumatic and musculoskeletal diseases attending a health facility in Austria. Methods We assessed educational needs, via an online survey of patients with fibromyalgia (FMS), rheumatoid arthritis (RA), and ankylosing spondylitis (AS) recruited from an Austrian health‐care facility, using the Austrian version of the Educational Needs Assessment Tool (OENAT). Results For our sample of 603 patients, AS (62%), RA (15%), and FMS (24%), there were no educational need differences for the domains of movements, disease process, and self‐help measures. Patients with FMS had less need for pain management education and greater need for education about feelings, than other disease groups. Patients with RA had a greater need for education related to treatments than other groups, and patients with AS had a greater need for treatment education than patients with FMS. Patients with AS reported greater need for support system education than other patient groups. Conclusion Educational needs vary by disease groups, suggesting that health‐care professionals should assess disease‐specific needs for education to provide optimal assistance in disease management for patients.

In the scientific field, data acquisition using commercial or self-developed sensors is a necessity for many research activities. Data security and data privacy are important requirements in all types of IoT applications, especially in the medical context. IoTree42 is a powerful, OpenSource platform that closes the gap between cost-efficiency, the ease of use and digital sovereignty. The flexible and user-friendly design makes the platform ideal for the originally conceived research context. Nevertheless, it can be used for smaller budget-oriented setups and industrial applications with thousands of sensors and actuators likewise. The platform was developed with security in mind by minimizing interfaces and the use of stable software components and transport protocols. IoTree42 utilizes lightweight OpenSource software cast into a flexible backend, allowing the deployment not only on full-fledged servers but also on single board computers like the Raspberry Pi. Data is transmitted with low overhead via MQTT, a robust protocol optimized for machine to machine communication. The transmission technology between all components is freely selectable. Besides data acquisition, IoTree42 enables control of actuators and automation through interfaces with visual programming tools. This allows for remote interventions without requiring prior programming experience. The incoming data can conveniently be visualized in dashboards or easily be exported for further analysis. The network consists of a central server and satellites (gateways) arranged in a star topology. Sensors and actuators connect to the gateway. The initial setup of the server and the gateways is automated, well documented, and can be done within minutes. Thanks to the increasing usage and the contribution of the community, the pool of code examples for sensors is growing and lowers the entry hurdle for users without programming background. IoTree42 is a fast-growing, multi-user, hardware and cloud agnostic, easy to deploy, privacy compliant and competitive solution compared to commercial IoT alternatives.

The application of virtual reality (VR) as a supportive tool in psychotherapy has gained great popularity in recent years. Especially for addiction therapy, a combination of virtual exposure and learning or training coping skills by using biofeedback has a high potential to improve conventional therapy. To add value, the new therapy system has to meet the needs of patients and practitioners likewise. Added values consistently named by experts included, but were not limited to, new possibilities of creating individual exposition or coping scenarios, enhanced psychoeducation, a shorter duration of treatment, telemedical aspects, the possibility of measuring and predicting craving and finally an improvement in abstinence. Besides literature research, we evaluated existing technical solutions in the field of virtual addiction treatment, surveyed experts and evolved a concept that led to a first prototype. The prototype consists of a wireless VR headset and a wireless multi-sensor system for measuring the physiological reaction to stimuli or the effectiveness of coping strategies by means of biofeedback. For further studies we developed both, a virtual exposure and a coping scenario and tested the hardware and software in a pilot study in order to elaborate factors that could negatively affect the therapy adherence, the effectiveness of exposition (immersion) and possible hurdles in practical use. Cybersickness and the lack of haptic feedback turned out to be the main limiting factors. Concepts for the next iteration of the therapy system will reflect these points for upcoming clinical studies. In our proof of concept, we demonstrated that virtual therapy can be implemented with a reasonable effort of time and costs. The combination of software and hardware, that supplements the traditional therapeutic approach, lays the foundation for upcoming clinical use and trials to prove the better outcome of VR enhanced addiction therapy.

Recording of heart rate variability (HRV) is a noninvasive and continuous measurement method that allows investigating the autonomic nervous system (ANS) and its reaction to environmental influences. For a precise measurement of HRV data, a carefully chosen study design and environment is required to minimize secondary influences. One major influence to be avoided is movement. However, in the daily routine and for some scientific questions, movement can often not be avoided. If so, a manual or automated method to differentiate between artifacts caused by body movement and the actual psychophysiological effect is needed to ensure the data quality. In this approach, a chest-worn sensor was developed, that measures the heart rate using a single lead ECG and filters the measured change of the HRV caused by movement. Data from an integrated accelerometer is used to detect upper body movements that affect the resting heart rate. The movementcorresponding time stamps are then used to filter the Interbeat Intervals (IBI) accordingly. Functionality and effectiveness of the sensor system have been tested against state-of-the art sports- or clinical devices in varying scenarios. As our test series showed, motion filtering has a decisive effect when motion occurs, two-thirds of all cases showed a significant effect of motion filtering, with small to medium effect sizes for the parameters SD2, SD2/SD1, and SDNN. Thereby, automatic filtering of motion artifacts can help to significantly reduce the need for costly post-processing of distorted data sets. The results show a better data quality of HRV measurement, a method that is commonly used for the investigation of physiological processes in the field of chronic pain, psychology, psychiatry, or sports medicine.

The present study examines connections between patient expectations and health-related quality of life. We explore a key distinction between expectations about general health and expectations for functional improvement. Patients were 1444 individuals with multiple conditions experiencing chronic pain who were seeking treatment at the Gastein Healing Gallery in Böckstein, near Bad Gastein, Austria. In addition to measures of expectations, patients completed measures of pain, mental and physical health, life satisfaction, fatigue, and sleep problems. Structural equation models were used to fit a latent variable model where both expectation variables were used to predict health-related quality of life. Results showed that expectations regarding potential functional improvement resulting from treatments at the Gastein Healing Gallery were associated with improved health-related quality of life. Expectations about general health improvements related to treatment were not associated with health-related quality of life. To facilitate optimal healing, clinicians may decide to emphasize expectations about functional recovery when discussing treatment methods similar to those offered at the Gastein Healing Gallery, and in so doing, health-related quality of life may benefit.