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      Development and usability testing of a patient decision aid for newly diagnosed relapsing multiple sclerosis patients

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          Abstract

          Background

          Multiple sclerosis (MS) patients often struggle with treatment decisions, in part due to the increasing number of approved disease modifying therapies, each with different characteristics, and also since physicians can struggle to identify which of these characteristics matter most to each individual patient. Decision uncertainty can contribute to late treatment initiation and treatment non-adherence—causes of ‘undertreatment’ in MS. An interactive online patient decision aid that informs patients of their options, considers their individual preferences and goals, and facilitates conversations with their physicians, could improve how patients with relapsing forms of MS make evidence-based treatment decisions.

          Objective

          To develop and evaluate a prototype patient decision aid (PtDA) for first-line disease modifying therapies for relapsing-remitting multiple sclerosis.

          Methods

          Informed by previous studies and International Patient Decision Aid Standards guidelines, a prototype PtDA was developed for patients with relapsing multiple sclerosis considering first line treatment. Patients with relapsing multiple sclerosis were recruited from the University of British Columbia’s Multiple Sclerosis Clinic to participate in either an online survey or a focus group. Online survey participants completed the PtDA, followed by measures of acceptability, usability, and preparedness for decision-making, and provided general feedback. Focus group participants assessed usability of the revised PtDA. The analysis of qualitative and quantitative data led to improvements of the PtDA prototype.

          Results

          The prototype PtDA received high ratings for acceptability and usability, and after its use, participants reported high-levels of preparedness for decision-making. Analysis of all qualitative data identified three key themes: the need for credible information; the usefulness of the PtDA; and the importance of normalizing and sharing experiences. Nine content areas were identified for revision. Overall, participants found the PtDA to be a valuable tool for facilitating treatment decisions.

          Conclusions

          This mixed methods study has led to the development of a PtDA that can support patients with RRMS as they make treatment decisions. Future studies will assess the feasibility of implementation and the impact of the PtDA on both the timely treatment initiation and longer-term adherence.

          Electronic supplementary material

          The online version of this article (10.1186/s12883-019-1382-7) contains supplementary material, which is available to authorized users.

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          Most cited references 46

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          Three approaches to qualitative content analysis.

          Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
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            Developing a quality criteria framework for patient decision aids: online international Delphi consensus process.

            To develop a set of quality criteria for patient decision support technologies (decision aids). Two stage web based Delphi process using online rating process to enable international collaboration. Individuals from four stakeholder groups (researchers, practitioners, patients, policy makers) representing 14 countries reviewed evidence summaries and rated the importance of 80 criteria in 12 quality domains on a 1 to 9 scale. Second round participants received feedback from the first round and repeated their assessment of the 80 criteria plus three new ones. Aggregate ratings for each criterion calculated using medians weighted to compensate for different numbers in stakeholder groups; criteria rated between 7 and 9 were retained. 212 nominated people were invited to participate. Of those invited, 122 participated in the first round (77 researchers, 21 patients, 10 practitioners, 14 policy makers); 104/122 (85%) participated in the second round. 74 of 83 criteria were retained in the following domains: systematic development process (9/9 criteria); providing information about options (13/13); presenting probabilities (11/13); clarifying and expressing values (3/3); using patient stories (2/5); guiding/coaching (3/5); disclosing conflicts of interest (5/5); providing internet access (6/6); balanced presentation of options (3/3); using plain language (4/6); basing information on up to date evidence (7/7); and establishing effectiveness (8/8). Criteria were given the highest ratings where evidence existed, and these were retained. Gaps in research were highlighted. Developers, users, and purchasers of patient decision aids now have a checklist for appraising quality. An instrument for measuring quality of decision aids is being developed.
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              Physician communication and patient adherence to treatment: a meta-analysis.

              Numerous empirical studies from various populations and settings link patient treatment adherence to physician-patient communication. Meta-analysis allows estimates of the overall effects both in correlational research and in experimental interventions involving the training of physicians' communication skills. Calculation and analysis of "r effect sizes" and moderators of the relationship between physician's communication and patient adherence, and the effects of communication training on adherence to treatment regimens for varying medical conditions. Thorough search of published literature (1949-August 2008) producing separate effects from 106 correlational studies and 21 experimental interventions. Determination of random effects model statistics and the detailed examination of study variability using moderator analyses. Physician communication is significantly positively correlated with patient adherence; there is a 19% higher risk of non-adherence among patients whose physician communicates poorly than among patients whose physician communicates well. Training physicians in communication skills results in substantial and significant improvements in patient adherence such that with physician communication training, the odds of patient adherence are 1.62 times higher than when a physician receives no training. Communication in medical care is highly correlated with better patient adherence, and training physicians to communicate better enhances their patients' adherence. Findings can contribute to medical education and to interventions to improve adherence, supporting arguments that communication is important and resources devoted to improving it are worth investing in. Communication is thus an important factor over which physicians have some control in helping their patients to adhere.
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                Author and article information

                Contributors
                nick.bansback@ubc.ca
                jchiu@cheos.ubc.ca
                robert.carruthers@ubc.ca
                rmetcalfe@alumni.ubc.ca
                emmanuelle.lapointe@usherbrooke.ca
                alice.schabas@vch.ca
                lenzen@telus.net
                larry.lynd@ubc.ca
                t.traboulsee@ubc.ca
                Journal
                BMC Neurol
                BMC Neurol
                BMC Neurology
                BioMed Central (London )
                1471-2377
                20 July 2019
                20 July 2019
                2019
                : 19
                Affiliations
                [1 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, School of Population and Public Health, , University of British Columbia, ; 2206 East Mall, Vancouver, British Columbia V6T 1Z3 Canada
                [2 ]ISNI 0000 0000 8589 2327, GRID grid.416553.0, Centre for Health Evaluation & Outcome Sciences, , St. Paul’s Hospital, ; 1081 Burrard Street, Vancouver, British Columbia V6Z 1Y6 Canada
                [3 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Division of Neurology, , University of British Columbia, Djavad Mowafaghian Center for Brain Health, ; 2215 Wesbrook Mall, Vancouver, British Columbia V6T 1Z3 Canada
                [4 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Faculty of Pharmaceutical Sciences, , University of British Columbia, ; 2405 Wesbrook Mall, Vancouver, British Columbia V6T 1Z3 Canada
                [5 ]Collaboration for Outcomes Research and Evaluation, 2405 Wesbrook Mall, Vancouver, British Columbia V6T 1Z3 Canada
                [6 ]Vancouver, British Columbia Canada
                Article
                1382
                10.1186/s12883-019-1382-7
                6642472
                31325961
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: VGH & UBC Hospital Foundation
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Neurology

                decision making, disease-modifying therapy, decision aid, multiple sclerosis

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