Purpose: Breast cancer follow-up (surveillance and aftercare) varies from one-size-fits-all to more personalised approaches. A systematic review was performed to get insight in existing evidence on (cost-)efectiveness of personalised follow-up. Methods: PubMed, Scopus and Cochrane were searched between 01–01-2010 and 10–10-2022 (review registered in PROSPERO:CRD42022375770). The inclusion population comprised nonmetastatic breast cancer patients≥18 years, after completing curative treatment. All intervention-control studies studying personalised surveillance and/or aftercare designed for use during the entire follow-up period were included. All review processes including risk of bias assessment were performed by two reviewers. Characteristics of included studies were described. Results: Overall, 3708 publications were identifed, 64 full-text publications were read and 16 were included for data extraction. One study evaluated personalised surveillance. Various personalised aftercare interventions and outcomes were studied. Most common elements included in personalised aftercare plans were treatment summaries (75%), follow-up guidelines (56%), lists of available supportive care resources (38%) and PROs (25%). Control conditions mostly comprised usual care. Four out of seven (57%) studies reported improvements in quality of life following personalisation. Six studies (38%) found no personalisation efect, for multiple outcomes assessed (e.g. distress, satisfaction). One (6.3%) study was judged as low, four (25%) as high risk of bias and 11 (68.8%) as with concerns. Conclusion: The included studies varied in interventions, measurement instruments and outcomes, making it impossible to draw conclusions on the efectiveness of personalised follow-up. There is a need for a definition of both personalised surveillance and aftercare, whereafter outcomes can be measured according to uniform standards.
Pokémon Go, Facebook check-ins, Google Maps, public transport apps and especially smartphone apps are increasingly becoming traceable and locatable. As ‘check-in’, features in social media and games grow in popularity they pinpoint users in relation to everything else in the network, making physical context an essential input for online interactions. But what are the practical consequences of the increased proliferation of devices that can determine our location? Could one say that surveillance is already taken for granted as we passively provide our coordinates to others?
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Background: Follow‑up of curatively treated primary breast cancer patients consists of surveillance and aftercare and is currently mostly the same for all patients. A more personalized approach, based on patients’ individual risk of recurrence and personal needs and preferences, may reduce patient burden and reduce (healthcare) costs. The NABOR study will examine the (cost‑)effectiveness of personalized surveillance (PSP) and personalized aftercare plans (PAP) on patient‑reported cancer worry, self‑rated and overall quality of life and (cost‑)effectiveness. Methods: A prospective multicenter multiple interrupted time series (MITs) design is being used. In this design, 10 participating hospitals will be observed for a period of eighteen months, while they ‑stepwise‑ will transit from care as usual to PSPs and PAPs. The PSP contains decisions on the surveillance trajectory based on individual risks and needs, assessed with the ‘Breast Cancer Surveillance Decision Aid’ including the INFLUENCE prediction tool. The PAP contains decisions on the aftercare trajectory based on individual needs and preferences and available care resources, which decision‑making is supported by a patient decision aid. Patients are non‑metastasized female primary breast cancer patients (N= 1040) who are curatively treated and start follow‑up care. Patient reported outcomes will be measured at five points in time during two years of follow‑up care (starting about one year after treatment and every six months thereafter). In addition, data on diagnostics and hospital visits from patients’ Electronical Health Records (EHR) will be gathered. Primary outcomes are patient‑reported cancer worry (Cancer Worry Scale) and over‑all quality of life (as assessed with EQ‑VAS score). Secondary outcomes include health care costs and resource use, health‑related quality of life (as measured with EQ5D‑5L/SF‑12/EORTC‑QLQ‑C30), risk perception, shared decision‑making, patient satisfaction, societal participation, and cost‑effectiveness. Next, the uptake and appreciation of personalized plans and patients’ experiences of their decision‑making process will be evaluated. Discussion: This study will contribute to insight in the (cost‑)effectiveness of personalized follow‑up care and contributes to development of uniform evidence‑based guidelines, stimulating sustainable implementation of personalized surveillance and aftercare plans. Trial registration: Study sponsor: ZonMw. Retrospectively registered at ClinicalTrials.gov (2023), ID: NCT05975437.
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In veel Afrikaanse landen zien we een inperking van de maatschappelijke ruimte (‘civic space’). Deze ruimte is cruciaal om in democratische staten transparantie, vrijheid van meningsuiting en verantwoording van bestuur te realiseren. In een steeds sterke digitaliserende maatschappij wordt toegang tot digitale middelen een mensenrecht. Daar waar regeringen proberen hun burgers en organisaties dat recht tot digitale informatievoorziening en –uitwisselingen te ontnemen komen de Sustainable Development Goals in het gedrang. Doel African Digital Rights Network (ADRN) wil inzicht verkrijgen in de stakeholders ne technologieën die betrokken zijn net het openen of onderdrukken van de online maatschappelijke ruimte (‘civic space’). Het netwerk beoogt bij te dragen aam empowerment van burgers om hun digitale mensenrechten uit te oefenen. Resultaten ADRN heeft een vergelijkende studie van 10 Afrikaanse landen uitgevoerd naar het gebruik van digitale technologieën voor het openen of onderdrukken van de online maatschappelijke ruimte (‘civic space’). Het project heeft onder andere geleidt tot de volgende publicatie: Mapping the Supply of Surveillance Technologies to Africa: Case Studies from Nigeria, Ghana, Morocco, Malawi, and Zambia Looptijd 01 mei 2020 - 20 april 2021 Aanpak ADRN organiseert een netwerk van onderzoekers, analisten, digitale rechtenorganisaties en activisten om de dynamiek van het openen en onderdrukken van de digitale maatschappelijke ruimte in kaart te brengen. Het netwerk bouwt op een interdisciplinaire onderzoeksaanpak o.l.v. het Institute for Development Studies, een vooraanstaand onderzoeksinstituut. Relevantie van het project Het onderzoek leidt tot aanbevelingen voor o.a. beleidsmakers en maatschappelijke organisaties ter bevordering van de digitale maatschappelijke ruimte. Daarnaast worden digitale tools en trainingsmateriaal gefaciliteerd voor het monitoren van ontwikkelingen en dreigingen van de digitale maatschappelijke ruimte. CofinancieringDit onderzoek wordt gefinancierd door UKRI - GCRF Digital Innovation for Development in Africa (DIDA)Meer weten? UKRI GCRF: African Digital Rights Network Website ADRN
Drones have been verified as the camera of 2024 due to the enormous exponential growth in terms of the relevant technologies and applications such as smart agriculture, transportation, inspection, logistics, surveillance and interaction. Therefore, the commercial solutions to deploy drones in different working places have become a crucial demand for companies. Warehouses are one of the most promising industrial domains to utilize drones to automate different operations such as inventory scanning, goods transportation to the delivery lines, area monitoring on demand and so on. On the other hands, deploying drones (or even mobile robots) in such challenging environment needs to enable accurate state estimation in terms of position and orientation to allow autonomous navigation. This is because GPS signals are not available in warehouses due to the obstruction by the closed-sky areas and the signal deflection by structures. Vision-based positioning systems are the most promising techniques to achieve reliable position estimation in indoor environments. This is because of using low-cost sensors (cameras), the utilization of dense environmental features and the possibilities to operate in indoor/outdoor areas. Therefore, this proposal aims to address a crucial question for industrial applications with our industrial partners to explore limitations and develop solutions towards robust state estimation of drones in challenging environments such as warehouses and greenhouses. The results of this project will be used as the baseline to develop other navigation technologies towards full autonomous deployment of drones such as mapping, localization, docking and maneuvering to safely deploy drones in GPS-denied areas.
The utilization of drones in various industries, such as agriculture, infrastructure inspection, and surveillance, has significantly increased in recent years. However, navigating low-altitude environments poses a challenge due to potential collisions with “unseen” obstacles like power lines and poles, leading to safety concerns and equipment damage. Traditional obstacle avoidance systems often struggle with detecting thin and transparent obstacles, making them ill-suited for scenarios involving power lines, which are essential yet difficult to perceive visually. Together with partners that are active in logistics and safety and security domains, this project proposal aims at conducting feasibility study on advanced obstacle detection and avoidance system for low-flying drones. To that end, the main research question is, “How can AI-enabled, robust and module invisible obstacle avoidance technology can be developed for low-flying drones? During this feasibility study, cutting-edge sensor technologies, such as LiDAR, radar, camera and advanced machine learning algorithms will be investigated to what extent they can be used be to accurately detect “Not easily seen” obstacles in real-time. The successful conclusion of this project will lead to a bigger project that aims to contribute to the advancement of drone safety and operational capabilities in low-altitude environments, opening new possibilities for applications in industries where low-flying drones and obstacle avoidance are critical.
