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Institute
- Department Sport- und Gesundheitswissenschaften (1459) (remove)
In clinical settings, significant resources are spent on data collection and monitoring patients' health parameters to improve decision-making and provide better care. With increased digitization, the healthcare sector is shifting towards implementing digital technologies for data management and in administration. New technologies offer better treatment opportunities and streamline clinical workflow, but the complexity can cause ineffectiveness, frustration, and errors. To address this, we believe digital solutions alone are not sufficient. Therefore, we take a human-centred design approach for AI development, and apply systems engineering methods to identify system leverage points. We demonstrate how automation enables monitoring clinical parameters, using existing non-intrusive sensor technology, resulting in more resources toward patient care. Furthermore, we provide a framework on digitization of clinical data for integration with data management.
Purpose
The objective of the investigation was to determine the concomitant effects of upper arm blood flow restriction (BFR) and inversion on elbow flexors neuromuscular responses.
Methods
Randomly allocated, 13 volunteers performed four conditions in a within-subject design: rest (control, 1-min upright position without BFR), control (1-min upright with BFR), 1-min inverted (without BFR), and 1-min inverted with BFR. Evoked and voluntary contractile properties, before, during and after a 30-s maximum voluntary contraction (MVC) exercise intervention were examined as well as pain scale.
Results
Inversion induced significant pre-exercise intervention decreases in elbow flexors MVC (21.1%, Z2p = 0.48, p = 0.02) and resting evoked twitch forces (29.4%, Z2p = 0.34, p = 0.03). The 30-s MVC induced significantly greater pre- to post-test decreases in potentiated twitch force (Z2p = 0.61, p = 0.0009) during inversion (75%) than upright (65.3%) conditions. Overall, BFR decreased MVC force 4.8% (Z2p = 0.37, p = 0.05). For upright position, BFR induced 21.0% reductions in M-wave amplitude (Z2p = 0.44, p = 0.04). There were no significant differences for electromyographic activity or voluntary activation as measured with the interpolated twitch technique. For all conditions, there was a significant increase in pain scale between the 40-60 s intervals and post-30-s MVC (upright< inversion, and without BFR< BFR).
Conclusion
The concomitant application of inversion with elbow flexors BFR only amplified neuromuscular performance impairments to a small degree. Individuals who execute forceful contractions when inverted or with BFR should be cognizant that force output may be impaired.
Purpose: Ethnic minority groups show elevated suicide attempt rates across Europe. Evidence suggests a similar trend for women of Turkish origin in Germany, yet data on suicidal behaviour in minorities in Germany is scarce. The objective was to examine rates of suicidal behaviour, underlying motives, and to explore the effectiveness of an intervention program.
Methods: From 05/2009-09/2011, data on all suicide attempts among women of Turkish origin who presented at a hospital-based emergency unit in Berlin, Germany, were collected. A multi-modal intervention was conducted in 2010 and the effects of age, generation and the intervention on suicide attempt rates were examined.
Results: At the start, the highest rate was found in women aged 18-24 years with 225.4 (95% CI = 208.8-242.0)/100,000. Adjustment disorder was the most prevalent diagnosis with 49.7% (n = 79), being more common in second-generation women (P = .004). Further analyses suggested an effect of the intervention in the youngest age group (trend change of beta = -1.25; P = .017).
Conclusion: Our findings suggest a particularly high rate of suicide attempts by 18-24-year-old, second-generation women of Turkish origin in Berlin. Furthermore, our results suggest a trend change in suicide attempts in women aged 18-24 years related to a population-based intervention program. (C) 2015 Elsevier Masson SAS. All rights reserved.
Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.
Objective:Common genetic variants in the gene encoding uromodulin (UMOD) have been associated with renal function, blood pressure (BP) and hypertension. We investigated the associations between an important single nucleotide polymorphism (SNP) in UMOD, that is rs12917707-G>T, and estimated glomerular filtration rate (eGFR), BP and cardiac organ damage as determined by echocardiography in patients with arterial hypertension.Methods:A cohort of 1218 treated high-risk patients (mean age 58.5 years, 83% men) with documented cardiovascular disease (81% with coronary heart disease) was analysed.Results:The mean values for 24-h SBP and DBP were 124.714.7 and 73.9 +/- 9.4mmHg; mean eGFR was 77.5 +/- 18.3ml/min per 1.73m(2), mean left ventricular ejection fraction was 59.3 +/- 9.9% and mean left ventricular mass index in men and women was 53.9 +/- 23.2 and 54.9 +/- 23.7g/m(2.7) with 50.4% of patients having left ventricular hypertrophy. A significant association between rs12917707 and eGFR was observed with T-allele carriers showing significantly higher eGFR values (+2.6ml/min per 1.73m(2), P=0.006) than noncarriers. This SNP associated also with left atrial diameter (P=0.007); homozygous carriers of the T-allele had smaller left atrial diameter (-1.5mm) than other genotype groups (P=0.040). No significant associations between rs12917707 and other cardiac or BP phenotypes were observed.Conclusions:These findings extend the previously documented role of UMOD for renal function also to treated high-risk patients with arterial hypertension and reveal a novel association with left atrial remodelling and thus a potential cardiorenal link modulated by UMOD.
Spitzensport, soziale Ungleichheit und soziale Reproduktion im deutsch-französischen Vergleich
(1998)
Changing the perspective sometimes offers completely new insights to an already well-known phenomenon. Exercising behavior, defined as planned, structured and repeated bodily movements with the intention to maintain or increase the physical fitness (Caspersen, Powell, & Christenson, 1985), can be thought of as such a well-known phenomenon that has been in the scientific focus for many decades (Dishman & O’Connor, 2005). Within these decades a perspective that assumes rational and controlled evaluations as the basis for decision making, was predominantly used to understand why some people engage in physical activity and others do not (Ekkekakis & Zenko, 2015).
Dual-process theories (Ekkekakis & Zenko, 2015; Payne & Gawronski, 2010) provide another perspective, that is not exclusively influenced by rational reasoning. These theories differentiate two different processes that guide behavior “depending on whether they operate automatically or in a controlled fashion“ (Gawronski & Creighton, 2012, p. 282). Following this line of thought, exercise behavior is not solely influenced by thoughtful deliberations (e.g. concluding that exercising is healthy) but also by spontaneous affective reactions (e.g. disliking being sweaty while exercising). The theoretical frameworks of dual-process models are not new in psychology (Chaiken & Trope, 1999) and have already been used for the explanation of numerous behaviors (e.g. Hofmann, Friese, & Wiers, 2008; Huijding, de Jong, Wiers, & Verkooijen, 2005). However, they have only rarely been used for the explanation of exercise behavior (e.g. Bluemke, Brand, Schweizer, & Kahlert, 2010; Conroy, Hyde, Doerksen, & Ribeiro, 2010; Hyde, Doerksen, Ribeiro, & Conroy, 2010). The assumption of two dissimilar behavior influencing processes, differs fundamentally from previous theories and thus from the research that has been conducted in the last decades in exercise psychology. Research mainly concentrated on predictors of the controlled processes and addressed the identified predictors in exercise interventions (Ekkekakis & Zenko, 2015; Hagger, Chatzisarantis, & Biddle, 2002).
Predictors arising from the described automatic processes, for example automatic evaluations for exercising (AEE), have been neglected in exercise psychology for many years. Until now, only a few researchers investigated the influence of these AEE for exercising behavior (Bluemke et al., 2010; Brand & Schweizer, 2015; Markland, Hall, Duncan, & Simatovic, 2015). Marginally more researchers focused on the impact of AEE for physical activity behavior (Calitri, Lowe, Eves, & Bennett, 2009; Conroy et al., 2010; Hyde et al., 2010; Hyde, Elavsky, Doerksen, & Conroy, 2012). The extant studies mainly focused on the quality of AEE and the associated quantity of exercise (exercise much or little; Bluemke et al., 2010; Calitri et al., 2009; Conroy et al., 2010; Hyde et al., 2012). In sum, there is still a dramatic lack of empirical knowledge, when applying dual-process theories to exercising behavior, even though these theories have proven to be successful in explaining behavior in many other health-relevant domains like eating, drinking or smoking behavior (e.g. Hofmann et al., 2008).
The main goal of the present dissertation was to collect empirical evidence for the influence of AEE on exercise behavior and to expand the so far exclusively correlational studies by experimentally controlled studies. By doing so, the ongoing debate on a paradigm shift from controlled and deliberative influences of exercise behavior towards approaches that consider automatic and affective influences (Ekkekakis & Zenko, 2015) should be encouraged. All three conducted publications are embedded in dual-process theorizing (Gawronski & Bodenhausen, 2006, 2014; Strack & Deutsch, 2004). These theories offer a theoretical framework that could integrate the established controlled variables of exercise behavior explanation and additionally consider automatic factors for exercise behavior like AEE.
Taken together, the empirical findings collected suggest that AEE play an important and diverse role for exercise behavior. They represent exercise setting preferences, are a cause for short-term exercise decisions and are decisive for long-term exercise adherence. Adding to the few already present studies in this field, the influence of (positive) AEE for exercise behavior was confirmed in all three presented publications. Even though the available set of studies needs to be extended in prospectively studies, first steps towards a more complete picture have been taken. Closing with the beginning of the synopsis: I think that time is right for a change of perspectives! This means a careful extension of the present theories with controlled evaluations explaining exercise behavior. Dual-process theories including controlled and automatic evaluations could provide such a basis for future research endeavors in exercise psychology.
Dropping Out or Keeping Up?
(2016)
The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years ± 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting (η2p = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions.
Dropping Out or Keeping Up?
(2016)
The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years ± 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting (η2p = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions.