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      Development and Usability of ADappt: Web-Based Tool to Support Clinicians, Patients, and Caregivers in the Diagnosis of Mild Cognitive Impairment and Alzheimer Disease

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          Abstract

          Background

          As a result of advances in diagnostic testing in the field of Alzheimer disease (AD), patients are diagnosed in earlier stages of the disease, for example, in the stage of mild cognitive impairment (MCI). This poses novel challenges for a clinician during the diagnostic workup with regard to diagnostic testing itself, namely, which tests are to be performed, but also on how to engage patients in this decision and how to communicate test results. As a result, tools to support decision making and improve risk communication could be valuable for clinicians and patients.

          Objective

          The aim of this study was to present the design, development, and testing of a Web-based tool for clinicians in a memory clinic setting and to ascertain whether this tool can (1) facilitate the interpretation of biomarker results in individual patients with MCI regarding their risk of progression to dementia, (2) support clinicians in communicating biomarker test results and risks to MCI patients and their caregivers, and (3) support clinicians in a process of shared decision making regarding the diagnostic workup of AD.

          Methods

          A multiphase mixed-methods approach was used. Phase 1 consisted of a qualitative needs assessment among professionals, patients, and caregivers; phase 2, consisted of an iterative process of development and the design of the tool (ADappt); and phase 3 consisted of a quantitative and qualitative assessment of usability and acceptability of ADappt. Across these phases, co-creation was realized via a user-centered qualitative approach with clinicians, patients, and caregivers.

          Results

          In phase 1, clinicians indicated the need for risk calculation tools and visual aids to communicate test results to patients. Patients and caregivers expressed their needs for more specific information on their risk for developing AD and related consequences. In phase 2, we developed the content and graphical design of ADappt encompassing 3 modules: a risk calculation tool, a risk communication tool including a summary sheet for patients and caregivers, and a conversation starter to support shared decision making regarding the diagnostic workup. In phase 3, ADappt was considered to be clear and user-friendly.

          Conclusions

          Clinicians in a memory clinic setting can use ADappt, a Web-based tool, developed using multiphase design and co-creation, for support that includes an individually tailored interpretation of biomarker test results, communication of test results and risks to patients and their caregivers, and shared decision making on diagnostic testing.

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          Most cited references20

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          Alzheimer's disease: strategies for disease modification.

          Alzheimer's disease is the largest unmet medical need in neurology. Current drugs improve symptoms, but do not have profound disease-modifying effects. However, in recent years, several approaches aimed at inhibiting disease progression have advanced to clinical trials. Among these, strategies targeting the production and clearance of the amyloid-beta peptide - a cardinal feature of Alzheimer's disease that is thought to be important in disease pathogenesis - are the most advanced. Approaches aimed at modulating the abnormal aggregation of tau filaments (another key feature of the disease), and those targeting metabolic dysfunction, are also being evaluated in the clinic. This article discusses recent progress with each of these strategies, with a focus on anti-amyloid strategies, highlighting the lessons learned and the challenges that remain.
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            Shared decision making: Concepts, evidence, and practice

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              Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations.

              Perception of health risk can affect medical decisions and health behavior change. Yet the concept of risk is a difficult one for the public to grasp. Whether perceptions of risk affect decisions and behaviors often relies on how messages of risk magnitudes (i.e., likelihood) are conveyed. Based on expert opinion, this article offers, when possible, best practices for conveying magnitude of health risks using numeric, verbal, and visual formats. This expert opinion is based on existing empirical evidence, review of papers and books, and consultations with experts in risk communication. This article also discusses formats to use pertaining to unique risk communication challenges (e.g., conveying small-probability events, interactions). Several recommendations are suggested for enhancing precision in perception of risk by presenting risk magnitudes numerically and visually. Overall, there are little data to suggest best practices for verbal communication of risk magnitudes. Across the 3 formats, few overall recommendations could be suggested because of 1) lack of consistency in testing formats using the same outcomes in the domain of interest, 2) lack of critical tests using randomized controlled studies pitting formats against one another, and 3) lack of theoretical progress detailing and testing mechanisms why one format should be more efficacious in a specific context to affect risk magnitudes than others. Areas of future research are provided that it is hoped will help illuminate future best practices.
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                Author and article information

                Contributors
                Journal
                JMIR Form Res
                JMIR Form Res
                JFR
                JMIR Formative Research
                JMIR Publications (Toronto, Canada )
                2561-326X
                Jul-Sep 2019
                08 July 2019
                : 3
                : 3
                : e13417
                Affiliations
                [1 ] Alzheimer Center Amsterdam, Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam Netherlands
                [2 ] Department of Epidemiology and Biostatistics Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam Netherlands
                [3 ] Department of Medical Psychology Amsterdam Public Health Research Insitute University of Amsterdam, Amsterdam UMC Amsterdam Netherlands
                [4 ] Vilans Center of Expertise for Long Term Care Utrecht Netherlands
                [5 ] Medical Decision Making Department of Biomedical Data Sciences Leiden University Medical Center Leiden Netherlands
                [6 ] Tilburg University TIAS School for Business and Society Tilburg Netherlands
                [7 ] Department of Neurology Spaarne Gasthuis Haarlem Netherlands
                Author notes
                Corresponding Author: Ingrid S van Maurik i.vanmaurik@ 123456vumc.nl
                Author information
                http://orcid.org/0000-0001-6919-8340
                http://orcid.org/0000-0003-3487-7938
                http://orcid.org/0000-0003-4618-3837
                http://orcid.org/0000-0002-2917-0842
                http://orcid.org/0000-0003-0879-2164
                http://orcid.org/0000-0001-5334-1085
                http://orcid.org/0000-0002-6708-5374
                http://orcid.org/0000-0002-0527-2270
                http://orcid.org/0000-0003-4922-5983
                http://orcid.org/0000-0001-7158-6449
                http://orcid.org/0000-0002-1046-6408
                http://orcid.org/0000-0002-8145-8595
                http://orcid.org/0000-0001-8766-6224
                Article
                v3i3e13417
                10.2196/13417
                6643768
                31287061
                09ac058a-f1cc-43a3-b478-81b1d294f32d
                ©Ingrid S van Maurik, Leonie NC Visser, Ruth E Pel-Littel, Marieke M van Buchem, Marissa D Zwan, Marleen Kunneman, Wiesje Pelkmans, Femke H Bouwman, Mirella Minkman, Niki Schoonenboom, Philip Scheltens, Ellen MA Smets, Wiesje M van der Flier. Originally published in JMIR Formative Research (http://formative.jmir.org), 08.07.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on http://formative.jmir.org.as well as this copyright and license information must be included.

                History
                : 16 January 2019
                : 28 March 2019
                : 30 April 2019
                : 30 April 2019
                Categories
                Original Paper
                Original Paper

                alzheimer’s disease,biomarkers,decision aids,mild cognitive impairment,precision medicine,risk,shared decision making

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