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- Bousquet, Jean, et al.
(author)
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Allergic Rhinitis and its Impact on Asthma (ARIA) Phase 4 (2018) : Change management in allergic rhinitis and asthma multimorbidity using mobile technology
- 2019
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In: Journal of Allergy and Clinical Immunology. - : Elsevier. - 0091-6749 .- 1097-6825. ; 143:3, s. 864-879
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Journal article (peer-reviewed)abstract
- Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline by using the best approach to integrated care pathways using mobile technology in patients with allergic rhinitis (AR) and asthma multimorbidity. The proposed next phase of ARIA is change management, with the aim of providing an active and healthy life to patients with rhinitis and to those with asthma multimorbidity across the lifecycle irrespective of their sex or socioeconomic status to reduce health and social inequities incurred by the disease. ARIA has followed the 8-step model of Kotter to assess and implement the effect of rhinitis on asthma multimorbidity and to propose multimorbid guidelines. A second change management strategy is proposed by ARIA Phase 4 to increase self-medication and shared decision making in rhinitis and asthma multimorbidity. An innovation of ARIA has been the development and validation of information technology evidence-based tools (Mobile Airways Sentinel Network [MASK]) that can inform patient decisions on the basis of a self-care plan proposed by the health care professional.
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| 2. |
- Menditto, Enrica, et al.
(author)
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Adherence to treatment in allergic rhinitis using mobile technology : The MASK Study
- 2019
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In: Clinical and Experimental Allergy. - : WILEY. - 0954-7894 .- 1365-2222. ; 49:4, s. 442-460
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Journal article (peer-reviewed)abstract
- Background: Mobile technology may help to better understand the adherence to treatment. MASK-rhinitis (Mobile Airways Sentinel NetworK for allergic rhinitis) is a patient-centred ICT system. A mobile phone app (the Allergy Diary) central to MASK is available in 22 countries. Objectives: To assess the adherence to treatment in allergic rhinitis patients using the Allergy Diary App. Methods: An observational cross-sectional study was carried out on all users who filled in the Allergy Diary from 1 January 2016 to 1 August 2017. Secondary adherence was assessed by using the modified Medication Possession Ratio (MPR) and the Proportion of days covered (PDC) approach. Results: A total of 12143 users were registered. A total of 6949 users reported at least one VAS data recording. Among them, 1887 users reported >= 7 VAS data. About 1195 subjects were included in the analysis of adherence. One hundred and thirty-six (11.28%) users were adherent (MPR >= 70% and PDC <= 1.25), 51 (4.23%) were partly adherent (MPR >= 70% and PDC = 1.50) and 176 (14.60%) were switchers. On the other hand, 832 (69.05%) users were non-adherent to medications (MPR <70%). Of those, the largest group was non-adherent to medications and the time interval was increased in 442 (36.68%) users. Conclusion and clinical relevance: Adherence to treatment is low. The relative efficacy of continuous vs on-demand treatment for allergic rhinitis symptoms is still a matter of debate. This study shows an approach for measuring retrospective adherence based on a mobile app. This also represents a novel approach for analysing medication-taking behaviour in a real-world setting.
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| 8. |
- Meurisch, Christian, et al.
(author)
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SmartGuidance'17 : 2nd Workshop on Intelligent Personal Support of Human Behavior
- 2017
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Conference paper (peer-reviewed)abstract
- In today's fast-paced environment, humans are faced with various problems such as information overload, stress, health and social issues. So-called anticipatory systems promise to approach these issues through personal guidance or support within a user's daily and professional life. The Second Workshop on Intelligent Personal Support of Human Behavior (SmartGuidance'17) aims to build on the success of the previous workshop (namely Smarticipation) organized in conjunction with UbiComp 2016, to continue discussing the latest research outcomes of anticipatory mobile systems. We invite the submission of papers within this emerging, interdisciplinary research field of anticipatory mobile computing that focuses on understanding, design, and development of such ubiquitous systems. We also welcome contributions that investigate human behaviors, underlying recognition and prediction models; conduct field studies; as well as propose novel HCI techniques to provide personal support. All workshop contributions will be published in supplemental proceedings of the UbiComp 2017 conference and included in the ACM Digital Library.
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| 9. |
- Prestia, Annapaola, et al.
(author)
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Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics
- 2015
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In: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 11:10, s. 1191-1201
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Journal article (peer-reviewed)abstract
- Introduction: Proposed diagnostic criteria (international working group and National Institute on Aging and Alzheimer's Association) for Alzheimer's disease (AD) include markers of amyloidosis (abnormal cerebrospinal fluid [CSF] amyloid beta [A beta]42) and neurodegeneration (hippocampal atrophy, temporo-parietal hypometabolism on [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET), and abnormal CSF tau). We aim to compare the accuracy of these biomarkers, individually and in combination, in predicting AD among mild cognitive impairment (MCI) patients. Methods: In 73 MCI patients, followed to ascertain AD progression, markers were measured. Sensitivity and specificity, positive (LR+) and negative (LR-) likelihood ratios, and crude and adjusted hazard ratios were computed. Results: Twenty-nine MCI patients progressed and 44 remained stable. Positivity to any marker achieved the lowest LR- (0.0), whereas the combination A beta 42 plus FDG-PET achieved the highest LR+ (6.45). In a survival analysis, positivity to any marker was associated with 100% conversion rate, whereas negativity to all markers was associated with 100% stability. Discussion: The best criteria combined amyloidosis and neurodegeneration biomarkers, whereas the individual biomarker with the best performance was FDG-PET.
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