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1.
BMJ Open ; 11(11): e050256, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1501714

ABSTRACT

INTRODUCTION: The systematic collection of electronic patient-reported outcome (ePRO) in the routine care of patients with chronic haematological malignancies such as chronic lymphocytic leukaemia (CLL) and myelodysplasia syndromes (MDS) can constitute a very ambitious but worthwhile challenge. MyPal is a Horizon 2020 Research & Innovation Action aiming to meet this challenge and foster palliative care for patients with CLL or MDS by leveraging ePRO systems to adapt to the personal needs of patients and caregiver(s). METHODS AND ANALYSIS: In this interventional randomised trial, 300 patients with CLL or MDS will be recruited across Europe. Patients will be randomly allocated to early palliative care using the MyPal system (n=150) versus standard care including general palliative care if needed (n=150). Patients in the experimental arm will be given access to the MyPal digital health platform which consists of purposely designed software available on smartphones and/or tablets. The platform entails different functionalities including physical and psychoemotional symptom reporting via regular questionnaire completion, spontaneous self-reporting, motivational messages, medication management and a personalised search engine for health information. Data on patients' activity (daily steps and sleep quality) will be automatically collected via wearable devices. ETHICS AND DISSEMINATION: The integration of ePROs via mobile applications has raised ethical concerns regarding inclusion criteria, information provided to participants, free and voluntary consent, and respect for their autonomy. These have been carefully addressed by a multidisciplinary team. Data processing, dissemination and exploitation of the study findings will take place in full compliance with European Union data protection law. A participatory design was adopted in the development of the digital platform involving focus groups and discussions with patients to identify needs and preferences. The protocol was approved by the ethics committees of San Raffaele (8/2020), Thessaloniki 'George Papanikolaou' Hospital (849), Karolinska Institutet (20.10.2020), University General Hospital of Heraklion (07/15.4.2020) and University of Brno (01-120220/EK). TRIAL REGISTRATION NUMBER: NCT04370457.


Subject(s)
Hematologic Neoplasms , Palliative Care , Adult , Focus Groups , Hematologic Neoplasms/therapy , Humans , Randomized Controlled Trials as Topic , Sleep Quality , Software
2.
BMC Infect Dis ; 21(Suppl 2): 866, 2021 Sep 13.
Article in English | MEDLINE | ID: covidwho-1477272

ABSTRACT

BACKGROUND: The HIV pandemic impacts the lives of millions and despite the global coordinated response, innovative actions are still needed to end it. A major challenge is the added burden of coinfections such as viral hepatitis, tuberculosis and various sexually transmitted infections in terms of prevention, treatment and increased morbidity in individuals with HIV infection. A need for combination prevention strategies, tailored to high-risk key populations arises and technology-based interventions can be a valuable asset. The COVID-19 pandemic challenged the delivery of existing services and added stress to existing public health and clinical structures but also highlighted the potential of exploiting technical solutions for interventions regarding infectious diseases. In this paper we report the design process, results and evaluation findings from the pilots of 'RiskRadar'-a web and mobile application aiming to support combination prevention, testing and linkage to care for HIV, viral hepatitis, various sexually transmitted infections and tuberculosis. METHODS: RiskRadar was developed for the INTEGRATE Joint Action's aim to improve, adapt and pilot innovative digital tools for combination prevention. RiskRadar was designed iteratively using informed end-user-oriented approaches. Emphasis was placed on the Risk Calculator that enables users to assess their risk of exposure to one or more of the four disease areas, make informed decisions to seek testing or care and adjust their behaviours ultimately aiming to harm/risk reduction. RiskRadar has been piloted in three countries, namely Croatia, Italy and Lithuania. RESULTS: RiskRadar has been used 1347 times across all platforms so far. More than 90% of users have found RiskRadar useful and would use it again, especially the Risk Calculator component. Almost 49.25% are men and 29.85% are in the age group of 25-34. The application has scored 5.2/7 in the User Experience Questionnaire, where it is mainly described as "supportive" and "easy-to-use". The qualitative evaluation of RiskRadar also yielded positive feedback. CONCLUSIONS: Pilot results demonstrate above average satisfaction with RiskRadar and high user-reported usability scores, supporting the idea that technical interventions could significantly support combination prevention actions on Sexually Transmitted Infections.


Subject(s)
COVID-19 , HIV Infections , Hepatitis, Viral, Human , Sexually Transmitted Diseases , Tuberculosis , Adult , HIV Infections/epidemiology , HIV Infections/prevention & control , Hepatitis, Viral, Human/epidemiology , Hepatitis, Viral, Human/prevention & control , Humans , Male , Pandemics , SARS-CoV-2 , Sexually Transmitted Diseases/epidemiology , Sexually Transmitted Diseases/prevention & control , Tuberculosis/prevention & control
3.
JMIR Mhealth Uhealth ; 9(7): e26290, 2021 07 09.
Article in English | MEDLINE | ID: covidwho-1311339

ABSTRACT

BACKGROUND: Obesity is a major public health problem globally and in Europe. The prevalence of childhood obesity is also soaring. Several parameters of the living environment are contributing to this increase, such as the density of fast food retailers, and thus, preventive health policies against childhood obesity must focus on the environment to which children are exposed. Currently, there are no systems in place to objectively measure the effect of living environment parameters on obesogenic behaviors and obesity. The H2020 project "BigO: Big Data Against Childhood Obesity" aims to tackle childhood obesity by creating new sources of evidence based on big data. OBJECTIVE: This paper introduces the Obesity Prevention dashboard (OPdashboard), implemented in the context of BigO, which offers an interactive data platform for the exploration of objective obesity-related behaviors and local environments based on the data recorded using the BigO mHealth (mobile health) app. METHODS: The OPdashboard, which can be accessed on the web, allows for (1) the real-time monitoring of children's obesogenic behaviors in a city area, (2) the extraction of associations between these behaviors and the local environment, and (3) the evaluation of interventions over time. More than 3700 children from 33 schools and 2 clinics in 5 European cities have been monitored using a custom-made mobile app created to extract behavioral patterns by capturing accelerometer and geolocation data. Online databases were assessed in order to obtain a description of the environment. The dashboard's functionality was evaluated during a focus group discussion with public health experts. RESULTS: The preliminary association outcomes in 2 European cities, namely Thessaloniki, Greece, and Stockholm, Sweden, indicated a correlation between children's eating and physical activity behaviors and the availability of food-related places or sports facilities close to schools. In addition, the OPdashboard was used to assess changes to children's physical activity levels as a result of the health policies implemented to decelerate the COVID-19 outbreak. The preliminary outcomes of the analysis revealed that in urban areas the decrease in physical activity was statistically significant, while a slight increase was observed in the suburbs. These findings indicate the importance of the availability of open spaces for behavioral change in children. Discussions with public health experts outlined the dashboard's potential to aid in a better understanding of the interplay between children's obesogenic behaviors and the environment, and improvements were suggested. CONCLUSIONS: Our analyses serve as an initial investigation using the OPdashboard. Additional factors must be incorporated in order to optimize its use and obtain a clearer understanding of the results. The unique big data that are available through the OPdashboard can lead to the implementation of models that are able to predict population behavior. The OPdashboard can be considered as a tool that will increase our understanding of the underlying factors in childhood obesity and inform the design of regional interventions both for prevention and treatment.


Subject(s)
COVID-19 , Child , Europe , Greece , Humans , SARS-CoV-2 , Sweden
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