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Background Adherence and motivation are key factors for successful treatment of patients with chronic diseases, especially in long-term care processes like rehabilitation. However, only a few patients achieve good treatment adherence. The causes are manifold. Adherence-influencing factors vary depending on indications, therapies, and individuals. Positive and negative effects are rarely confirmed or even contradictory. An ontology seems to be convenient to represent existing knowledge in this domain and to make it available for information retrieval. Methods First, a manual data extraction of current knowledge in the domain of treatment adherence in rehabilitation was conducted. Data was retrieved from various sources, including basic literature, scientific publications, and health behavior models. Second, all adherence and motivation factors identified were formalized according to the ontology development methodology METHONTOLOGY. This comprises the specification, conceptualization, formalization, and implementation of the ontology “Ontology for factors influencing therapy adherence to rehabilitation” (OnTARi) in Protégé. A taxonomy-oriented evaluation was conducted by two domain experts. Results OnTARi includes 281 classes implemented in ontology web language, ten object properties, 22 data properties, 1440 logical axioms, 244 individuals, and 1023 annotations. Six higher-level classes are differentiated: (1) Adherence, (2) AdherenceFactors, (3) AdherenceFactorCategory, (4) Rehabilitation, (5) RehabilitationForm, and (6) RehabilitationType. By means of the class AdherenceFactors 227 adherence factors, thereof 49 hard factors, are represented. Each factor involves a proper description, synonyms, possibly existing acronyms, and a German translation. OnTARi illustrates links between adherence factors through 160 influences-relations. Description logic queries implemented in Protégé allow multiple targeted requests, e.g., for the extraction of adherence factors in a specific rehabilitation area. Conclusions With OnTARi, a generic reference model was built to represent potential adherence and motivation factors and their interrelations in rehabilitation of patients with chronic diseases. In terms of information retrieval, this formalization can serve as a basis for implementation and adaptation of conventional rehabilitative measures, taking into account (patient-specific) adherence factors. OnTARi also enables the development of medical assistance systems to increase motivation and adherence in rehabilitation processes.

Background When older adults fall below the thresholds of functional geriatric assessment (FGA), they may already be at risk of mobility impairment. A reduction in (jumping) power could be an indication of functional decline, one of the main risk factors for falls. Objective This paper explores whether six-month delta (∆) values of muscle power can predict 24-month follow-up FGA in older adults. Methods This observational study of independent, healthy, high-performing community-dwelling adults aged 70 + years involved FGA (mobility, balance, and endurance tests) at baseline (t0), after 6 months (t1), and after 24 months (t2); maximum jumping power (max JP) was determined at t0 and t1. A predictive linear model was developed in which the percentage change of Δmax JP0,1 was transferred to all FGA (t0) values. The results were compared with measured FGA values at t2 via sensitivity and specificity in terms of the clinically meaningful change (CMC) or the minimal detectable change (MDC). Results In 176 individuals (60% female, mean age 75.3 years) the mean percentage (SD) between predicted and measured FGA ranged between 0.4 (51.3) and 18.11 (51.9). Sensitivity to identify the CMC or MDC of predicted FGA tests at t2 ranged between 17.6% (Timed up and go) and 75.0% (5-times-chair-rise) in a test-to-test comparison and increased to 97.6% considering clinically conspicuousness on global FGA. Conclusion The potential of jumping power to predict single tests of FGA was low regarding sensitivity and specificity of CMC (or MDC). 6 months Δmax JP seem to be suitable for predicting physical function, if the measured and predicted tests were not compared at the test level, but globally, in the target group in the long term.

Health-enabling technologies (HET) have high potential in rehabilitation to support patients performing their home exercises. The modeling of human movements as well as the modelling of quality criteria of an exercise performance remains challenging when implementing HETs. A combination of data-driven approaches and knowledge-based methods may deliver new insights. This requires structured quality assessments of concrete exercise performances from a therapists' point of view. Therefore, a structured, easy to use questionnaire to assess home exercise performances is developed and implemented. The questionnaire consists of eight items in three categories: (1-4) overall assessment of quality and quantity, (5-7) need for correction, and (8) correction hints. The collected data will be the basis for mathematical modeling of home exercise performance assessment as foundation for the development of patient supporting HETs.

Designing health-enabling technologies (HETs) to support individualized physiotherapeutic exercises requires comprehensive knowledge of bio-psycho-social factors to be considered. Therefore, this review identified factors for individualization of therapeutic exercises in patients with musculoskeletal shoulder disorders in peer-reviewed articles searched in MEDLINE. The final full-text analysis included 16 of 335 search results and extracted nineteen main categories of individualization factors. The most frequently identified main categories include progression of exercises, exercise framework, and assessment. An iterative approach with constant reassessments represents the key principle for the process of individualization. Categories that are difficult to standardize were rarely mentioned, but should also be considered. The identified factors can improve the design-process of HETs by sensitizing developers, enable further formal modelling, and support communication between developers, physiotherapists, and patients.

Rehabilitation of musculoskeletal diseases (MSD) of the shoulder is a multifaceted long-term process, which is often not transparent to affected patients. Mobile health applications (apps) have the potential to support this complex process by improving patients' self-management skills. However, there seems to be a lack of apps providing a holistic approach to motivate and guide patients during the whole rehabilitation process. Therefore, a systematic analysis of apps on Google Play Store was conducted by two independent reviewers. A total of 3227 apps were identified, of which 64 met the eligibility criteria for the qualitative analysis. The majority of analyzed apps were developed generally for patients with MSD of the shoulder, rarely for specific diseases (individual needs of patients). The majority of apps focus on the provision of information, exercise training, and alternative medicine. Apps for diagnostics, inpatient treatment, and self-management, especially for multiple rehabilitation phases, are rare or even not existent. Game design elements are seldom used. If there are any, then simple to implement ones, e.g. messages and progress bars. The (psychological) effects of individual game design elements on patients seem to be neglected, when selecting and implementing game-components.

Exercise therapy aims to restore normal musculoskeletal function or to reduce pain in patients with musculoskeletal shoulder disorders. Especially during long-term treatments, patients perform unsupervised exercises at home. Harmful movement deviations should be identified and avoided. Assistive technologies based on physical therapists' knowledge can support patients. In this paper, we present our approach to minimize the complexity of a physical therapists' quality assessment of a shoulder exercise performance. Four experienced physical therapists assessed the quality of 13 exercise performances shown as video recordings with a visual analogue scale and explained their ratings as free text. In some cases, the resulting assessments differed widely depending on the respective therapeutic goals. The therapists had difficulties to reduce the performances quality to a single value. Despite the existing consensus on exercises' descriptions, a more than one-dimensional scale is needed to evaluate exercises. Therefore, rating categories have to be identified for more detailed assessments.

IntroductionShoulder lesions rank among the top 15 diagnoses accounting for days of incapacity to work. Inpatient or full-day outpatient rehabilitation are some of the standard therapies. For sustainable rehabilitation, continuation of rehabilitation after discharge from a rehabilitation centre is vital. Besides medical exercise therapy (MET), home-based physical exercise programmes are used. To monitor exercise quantity and quality, AGT-Reha, a health-enabling technology for home rehabilitation, has been developed and evaluated in a pilot study for technical feasibility and acceptance. To integrate the digital therapeutic AGT-Reha into regular healthcare processes, an efficacy evaluation is required.Methods and analysisAGT-Reha-WK is a prospective, monocentric, non-randomised, unblinded non-inferiority trial. Primary objective is to investigate whether AGT-Reha enhanced home-based exercise training is non-inferior to MET as standard aftercare. Secondary objective is to compare the costs of both therapies. Efficacy as medical success (primary outcome) is examined with regard to ability to work, return to work and sustainability of training (secondary outcomes). The outcome measure for non-inferiority is shoulder function (pain and disability) assessed by the standardised Shoulder Pain and Disability Index (SPADI). The non-inferiority margin is set to 10 points on SPADI score using a 95% CI. Subjects will be recruited at the Rehabilitation Center Bad Pyrmont, Germany. The total number of subjects should be 84 (42 per group). Treatment takes 6 months per patient. Subjects will be assessed at four time points: pre-baseline (admission to rehabilitation centre), baseline (discharge from rehabilitation centre), post-therapy and follow-up (3 months post-therapy).Ethics and disseminationEthics approval was granted by the Ethics Committee of Hannover Medical School (ethics approval no: 7313). Results of the trial are planned to be published in a peer-reviewed journal.Trial registration numberGerman Clinical Trials Register DRKS00011596. Registered 2 June 2017. Recruitment started on 3 March 2017, and it is expected to continue until December 2020.Protocol versionV2.0, 23 May 2018, Amendment 01: improved risk analysis, clarification of exclusion criteria to increase reproducibility, additional documentation with OpenClinica; these changes have no effect on structural equality.