TY - JOUR A1 - Schlecht, Sina A1 - Neubert, Sven A1 - Meng, Karin A1 - Rabe, Antonia A1 - Jentschke, Elisabeth T1 - Changes of symptoms of anxiety, depression, and fatigue in cancer patients 3 months after a video-based intervention JF - International journal of environmental research and public health N2 - During the COVID-19 pandemic, social distancing restricted psycho-oncological care. Therefore, this secondary analysis examines the changes in anxiety, fear of progression, fatigue, and depression in cancer patients after a video-based eHealth intervention. We used a prospective observational design with 155 cancer patients with mixed tumor entities. Data were assessed before and after the intervention and at a three-month follow-up using self-reported questionnaires (GAD-7, FOP-Q-SF, PHQ-8, and EORTC QLQ-FA12). The eight videos included psychoeducation, Acceptance and Commitment Therapy elements, and yoga and qigong exercises. The results showed that three months after finishing the video-based intervention, participants showed significantly reduced fear of progression (d = −0.23), depression (d = −0.27), and fatigue (d = −0.24) compared to the baseline. However, there was no change in anxiety (d = −0.09). Findings indicated marginal improvements in mental distress when using video-based intervention for cancer patients for up to three months, but long-term effectiveness must be confirmed using a controlled design. KW - cancer KW - psycho-oncology KW - eHealth KW - supportive care intervention KW - psychoeducation KW - mind–body intervention KW - distress Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-357294 VL - 20 IS - 20 ER - TY - JOUR A1 - Neubert, Sven A1 - Schlecht, Sina A1 - Meng, Karin A1 - Rabe, Antonia A1 - Jentschke, Elisabeth T1 - Effects of a video sequence based intervention on anxiety, fatigue and depression in cancer patients: results of a randomized controlled trial JF - Integrative Cancer Therapies N2 - Background: Cancer patients often suffer from psychological symptoms and need psychological support. Especially during the COVID-19 pandemic, eHealth interventions might be helpful to overcome the obstacles of the pandemic. This study evaluates the effectiveness of a video sequence-based eHealth intervention on anxiety, fatigue, and depression in cancer patients. Methods: Patients (N = 157) with different tumor entities were randomly assigned to the video intervention group (IG) and the waiting control group (CG). Patients in the IG received a video intervention comprising 8 video sequences over 4 weeks. The videos included psychoeducation on distress and psychological symptoms, Acceptance and Commitment Therapy elements, and Yoga and Qigong exercises. Patients’ anxiety and fear of progression (primary outcomes) and secondary outcomes were assessed before randomization (T1) and after the end of the intervention for IG or the waiting period for CG (T2) using self-reported questionnaires (GAD-7, PA-F-KF, EORTC QLQ-FA12, PHQ-8). Results: Patients of the IG showed no significant improvement in anxiety (GAD-7; P = .75), fear of progression (FoP-Q-SF; P = .29), fatigue (EORTC QLQ-FA12; P = .72), and depression (PHQ-8; P = .95) compared to patients in the waiting CG. However, symptoms of anxiety, fatigue, and depression decreased in both groups. Exploratory subgroup analysis regarding sex, therapy status, therapy goal, and tumor entity showed no effects. Overall, the intervention had a high level of acceptance. Conclusions: The video intervention was ineffective in reducing the psychological burden compared to a waiting CG. The findings support prior observations of the value of therapeutic guidance and promoting self-management for improving patients’ psychological burdens. Further studies are required to evaluate the effectiveness of psycho-oncological eHealth delivered through video sequences. KW - eHealth KW - psycho-oncology KW - complementary medicine KW - psychoeducation KW - mind-body-intervention KW - anxiety KW - depression KW - fatigue KW - oncology Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304581 SN - 1552-695X VL - 22 ER - TY - JOUR A1 - Liman, Leon A1 - May, Bernd A1 - Fette, Georg A1 - Krebs, Jonathan A1 - Puppe, Frank T1 - Using a clinical data warehouse to calculate and present key metrics for the radiology department: implementation and performance evaluation JF - JMIR Medical Informatics N2 - Background: Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals. Objective: This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI). Methods: Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics. Results: The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations. Conclusions: A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing. KW - data warehouse KW - eHealth KW - hospital data KW - electronic health records KW - radiology KW - statistics and numerical data KW - medical records Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349411 SN - 2291-9694 VL - 11 ER - TY - JOUR A1 - Düking, Peter A1 - Zinner, Christoph A1 - Reed, Jennifer L. A1 - Holmberg, Hans‐Christer A1 - Sperlich, Billy T1 - Predefined vs data‐guided training prescription based on autonomic nervous system variation: A systematic review JF - Scandinavian Journal of Medicine & Science in Sports N2 - Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre‐ and post‐intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV‐based interventions reduced the amount of moderate‐ and/or high‐intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV‐based training. Peak oxygen uptake (VO\(_{2peak}\)) and submaximal running parameters (eg, LT1, LT2) improved following both HRV‐based and predefined training, with no clear difference in the extent of improvement in VO\(_{2peak}\). Submaximal running parameters tended to improve more following HRV‐based training. Research findings to date have been limited and inconsistent. Both HRV‐based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater. KW - cardiorespiratory fitness KW - eHealth KW - endurance KW - innovation KW - technology KW - training KW - wearable Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-217893 VL - 30 IS - 12 SP - 2291 EP - 2304 ER - TY - JOUR A1 - Düking, Peter A1 - Tafler, Marie A1 - Wallmann-Sperlich, Birgit A1 - Sperlich, Billy A1 - Kleih, Sonja T1 - Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis JF - JMIR Mhealth and Uhealth N2 - Background: Decreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA. Objective: The aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users’ PA behavior. Methods: The BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin Vívoactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature. Results: The most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin Vívoactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA. Conclusions: Wearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations. KW - cardiorespiratory fitness KW - innovation KW - smartwatch KW - technology KW - wearable KW - eHealth KW - mHealth Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-230556 VL - 8 IS - 11 ER - TY - JOUR A1 - Düking, Peter A1 - Achtzehn, Silvia A1 - Holmberg, Hans-Christer A1 - Sperlich, Billy T1 - Integrated framework of load monitoring by a combination of smartphone applications, wearables and point-of-care testing provides feedback that allows individual responsive adjustments to activities of daily living JF - Sensors N2 - Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual’s physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise prescription. Here, we outline 24-h monitoring of selected parameters by these technologies that (i) allows responsive adjustments of exercise programs, (ii) enhances performance and/or (iii) reduces the risk for overuse, injury and/or illness. KW - biofeedback KW - eHealth KW - individualized training KW - injury prevention KW - IoT KW - periodization KW - load management Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-176506 VL - 18 IS - 5 ER -