Purpose: To study the association between fatigue and participation and QoL after acquired brain injury (ABI) in adolescents and young adults (AYAs). Materials & Methods: Cross-sectional study with AYAs aged 14–25 years, diagnosed with ABI. The PedsQL™ Multidimensional Fatigue Scale, Child & Adolescent Scale of Participation, and PedsQL™4.0 Generic Core Scales were administered. Results: Sixty-four AYAs participated in the study, 47 with traumatic brain injury (TBI). Median age at admission was 17.6 yrs, 0.8 yrs since injury. High levels of fatigue (median 44.4 (IQR 34.7, 59.7)), limited participation (median 82.5 (IQR 68.8, 92.3)), and diminished QoL (median 63.0 (IQR 47.8, 78.3)) were reported. More fatigue was significantly associated with more participation restrictions (β 0.64, 95%CI 0.44, 0.85) and diminished QoL (β 0.87, 95%CI 0.72, 1.02). Conclusions: AYAs with ABI reported high levels of fatigue, limited participation and diminished quality of life with a significant association between fatigue and both participation and QoL. Targeting fatigue in rehabilitation treatment could potentially improve participation and QoL.
PURPOSE: Fatigue is a common and potentially disabling symptom in patients with cancer. It can often be effectively reduced by exercise. Yet, effects of exercise interventions might differ across subgroups. We conducted a meta-analysis using individual patient data of randomized controlled trials (RCTs) to investigate moderators of exercise intervention effects on cancer-related fatigue.METHODS: We used individual patient data from 31 exercise RCTs worldwide, representing 4,366 patients, of whom 3,846 had complete fatigue data. We performed a one-step individual patient data meta-analysis, using linear mixed-effect models to analyze the effects of exercise interventions on fatigue (z-score) and to identify demographic, clinical, intervention- and exercise-related moderators. Models were adjusted for baseline fatigue and included a random intercept on study level to account for clustering of patients within studies. We identified potential moderators by testing their interaction with group allocation, using a likelihood ratio test.RESULTS: Exercise interventions had statistically significant beneficial effects on fatigue (β= -0.17 [95% confidence interval (CI) -0.22;-0.12]). There was no evidence of moderation by demographic or clinical characteristics. Supervised exercise interventions had significantly larger effects on fatigue than unsupervised exercise interventions (βdifference= -0.18 [95%CI -0.28;-0.08]). Supervised interventions with a duration ≤12 weeks showed larger effects on fatigue (β= -0.29 [95% CI -0.39;-0.20]) than supervised interventions with a longer duration. CONCLUSIONS: In this individual patient data meta-analysis, we found statistically significant beneficial effects of exercise interventions on fatigue, irrespective of demographic and clinical characteristics. These findings support a role for exercise, preferably supervised exercise interventions, in clinical practice. Reasons for differential effects in duration require further exploration.
This study investigated the association of fatigue and cognitive complaints among employees post-cancer diagnosis, with work-related outcomes, and moderation by cancer-related anxiety. A survey was carried out among workers 2–10 years after cancer diagnosis. Employees without cancer recurrence or metastases were selected (N = 566). Self-reported fatigue and cognitive complaints were classified into three groups. ANOVA’s and regression analyses were used, controlling for age. Group 1 (cognitive complaints, n = 25, 4.4%), group 2 (fatigue, n = 205, 36.2%), and group 3 (cognitive complaints and fatigue, n = 211, 37.3%) were associated with higher burnout complaints and lower work engagement, and group 2 and 3 with lower work ability. Cancer-related anxiety positively moderated the association of group 3 with higher burnout complaints. Employees with both fatigue and cognitive complaints report less favorable work functioning. Cancer-related anxiety needs attention in the context of burnout complaints.
Automated driving nowadays has become reality with the help of in-vehicle (ADAS) systems. More and more of such systems are being developed by OEMs and service providers. These (partly) automated systems are intended to enhance road and traffic safety (among other benefits) by addressing human limitations such as fatigue, low vigilance/distraction, reaction time, low behavioral adaptation, etc. In other words, (partly) automated driving should relieve the driver from his/her one or more preliminary driving tasks, making the ride enjoyable, safer and more relaxing. The present in-vehicle systems, on the contrary, requires continuous vigilance/alertness and behavioral adaptation from human drivers, and may also subject them to frequent in-and-out-of-the-loop situations and warnings. The tip of the iceberg is the robotic behavior of these in-vehicle systems, contrary to human driving behavior, viz. adaptive according to road, traffic, users, laws, weather, etc. Furthermore, no two human drivers are the same, and thus, do not possess the same driving styles and preferences. So how can one design of robotic behavior of an in-vehicle system be suitable for all human drivers? To emphasize the need for HUBRIS, this project proposes quantifying the behavioral difference between human driver and two in-vehicle systems through naturalistic driving in highway conditions, and subsequently, formulating preliminary design guidelines using the quantified behavioral difference matrix. Partners are V-tron, a service provider and potential developer of in-vehicle systems, Smits Opleidingen, a driving school keen on providing state-of-the-art education and training, Dutch Autonomous Mobility (DAM) B.V., a company active in operations, testing and assessment of self-driving vehicles in the Groningen province, Goudappel Coffeng, consultants in mobility and experts in traffic psychology, and Siemens Industry Software and Services B.V. (Siemens), developers of traffic simulation environments for testing in-vehicle systems.
Jongeren met chronische aandoeningen worden vaak geconfronteerd met problemen in het dagelijks functioneren, waarbij vermoeidheid wordt genoemd als het meest invaliderend. De prevalentie van vermoeidheid onder jongeren met chronische aandoeningen varieert tussen de 51-75%. Vermoeidheid kan onafhankelijk ontstaan van het onderliggende pathologisch mechanisme; uit literatuur blijkt dat ziekte-specifieke benaderingen weinig of nauwelijks effect hebben op vermoeidheid. Vermoeidheid wordt bovendien te laat opgemerkt of blijft onbehandeld. Inzicht in de ziekte-overstijgende mechanismen van vermoeidheid is van belang om vroegtijdig opsporen en de ontwikkeling van passende interventies te faciliteren. Dit postdoc onderzoek richt zich op het ontrafelen van ziekte-overstijgende mechanismen van vermoeidheid vanuit het perspectief van jongeren, het gezin en de fysieke en sociale leefomgeving. Binnen een longitudinale cohortstudie gedurende 12 maanden worden 208 jongeren met verschillende chronische aandoeningen gemonitord. Naast traditionele onderzoeksmethodieken zoals vragenlijsten en fysieke testen, wordt gebruik gemaakt van remote sensoring, linked data en context mapping (=kwalitatieve methode). Studenten die participeren in het onderzoek zullen de mogelijkheden en beperkingen van zulke methoden ervaren. Dit kan o.a. bijdragen aan het integreren van zorgtechnologie in het dagelijks (kinder)fysiotherapeutisch handelen. We ontwikkelen een theoretisch raamwerk dat de basis legt voor betere vroegdetectie (op afstand en non-invasief) van vermoeidheid en voor het identificeren van mogelijke aangrijpingspunten voor behandeling (doelstelling 1 en 2). Verder draagt het postdoc onderzoek bij aan een beter inzicht in de rol van de sociale en fysieke leefomgeving bij de maatschappelijke participatie van jongeren met chronische aandoeningen (doelstelling 3). Studenten zullen in veldwerk ter plaatse metingen doen, de leefsituatie verkennen en samen met zorgprofessionals en docenten hun klinische blik verrijken. Doordat zij daadwerkelijk in de leefomgeving van jongeren zelf aanwezig zijn kan dit bijdragen aan bewustzijn over de rol van verschillende sociale en fysieke factoren op vermoeidheid en op de maatschappelijke participatie van jongeren met uiteenlopende chronische aandoeningen.
Rotating machinery, such as centrifugal pumps, turbines, bearings, and other critical systems, is the backbone of various industrial processes. Their failures can lead to significant maintenance costs and downtime. To ensure their continuous operation, we propose a fault diagnosis and monitoring framework that leverages the innovative use of acoustic sensors for early fault detection, especially in components less accessible for traditional vibration-based monitoring strategies. The main objective of the proposed project is to develop a fault diagnosis and monitoring framework for rotating machinery, including the fusion of acoustic sensors and physics-based models. By combining real-time monitoring data from acoustic sensors with an understanding of first principles, the framework will enable maintenance practitioners to identify and categorize different failure modes such as wear, fatigue, cavitation, reduced flow, bearing damage, impeller damage, misalignment, etc. In the initial phase, the focus will be on centrifugal pumps using the existing test set-up at the University of Twente. Sorama specializes in acoustic sensors to locate noise sources and will provide acoustic cameras to capture sound patterns related to pump deterioration during various operating conditions. These acoustic signals will then be correlated with the different failure modes and mechanisms that will be described by physics-based models, such as wear, fatigue, cavitation, corrosion, etc. Furthermore, a recently published data set by the Dynamics Based Maintenance research group that includes vibration analysis data and motor current analysis data of various fault scenarios, such as mentioned above, will be used as validation. The anticipated outcome of this project is a versatile framework for a physics-informed acoustic monitoring system. This system is designed to enhance early fault detection significantly, reducing maintenance costs and downtime across a broad spectrum of industrial applications, from centrifugal pumps to turbines, bearings, and beyond.
