Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
Mais filtros

Base de dados
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
JMIR Res Protoc ; 11(3): e16430, 2022 Mar 22.
Artigo em Inglês | MEDLINE | ID: mdl-35315784

RESUMO

BACKGROUND: Involving chronically ill patients in the management of their health is widely recognized as a vital component of high-quality health care. However, to assume the role of informed participants, patients need both access to their health information and assistance in interpreting such data. Smartphone technology with SMS text messaging functionality offers a convenient and minimally demanding mechanism for providing such dual capabilities to patients. To date, a number of similar digital tools have been developed for use in various chronic and progressive disease conditions, including rheumatoid arthritis. OBJECTIVE: This paper aims to describe the development of a research protocol that applies a human-centered design (HCD) approach to develop a mobile health (mHealth) intervention to support symptom management and treatment adherence for rheumatoid arthritis. METHODS: To guide the development of the mHealth intervention for use within a commercial biotechnology context, we selected and applied an HCD framework consisting of three phases: understanding, ideation, and implementation. RESULTS: Leveraging the framework, we mapped the key objectives and research questions to each phase and identified the HCD techniques and methods most suitable for addressing them. In addition, we identified the need to include a fourth phase, one that referred to postimplementation assessment, which would enable evaluation of patient engagement and intervention impact on symptom self-management. CONCLUSIONS: This paper presents a research protocol that applied an HCD framework to guide the development of an mHealth intervention within a commercial biotechnology context. This type of guidance is salient because commercial entities are becoming one of the leading producers of this type of intervention. However, the methodologies used and challenges faced from a research and development perspective are not well-represented in the published research literature to date. Our application of the HCD framework yielded important findings. Each phase of the HCD framework provided important guidance for increasing the likelihood that the final product would be understandable, acceptable, feasible, and engaging to use. Consistent with other researchers in the field of mHealth interventions, we identified the need to add a fourth phase to the HCD framework, one that focused on a postimplementation assessment to guide further improvements to support adoption in real-world settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/16430.

2.
JMIR Form Res ; 4(11): e18982, 2020 Nov 17.
Artigo em Inglês | MEDLINE | ID: mdl-33200997

RESUMO

BACKGROUND: Relapsed and refractory multiple myeloma (RRMM) is a bone marrow cancer that requires systemic treatment, which often results in severe symptom burden. Recent studies have found that electronic patient-reported outcome (ePRO) interventions implemented in the clinic setting have had positive outcomes for other oncology populations. Evidence of the efficacy of a similar approach is lacking for patients with RRMM. OBJECTIVE: Recent recommendations for digital health interventions call for the publication of descriptions of iterative development processes in order to improve reproducibility and comparability. This study is an implementation pilot aiming to evaluate the acceptability and appropriateness of an ePRO intervention for patients with RRMM and to explore its impact on clinic workflow. METHODS: A total of 11 patients with RRMM were recruited from the John Theurer Cancer Center in Hackensack, New Jersey. Patients used a mobile app to report on 17 symptoms at 4 sessions, each a week apart. Patients could also report symptoms ad hoc. When reports met predefined thresholds, the clinic was alerted and patients received automated guidance. Study end points were assessed using qualitative and quantitative methods. RESULTS: A total of 9 patients (mean age 69.7 years) completed the study. Overall, 83% (30/36) of weekly sessions were completed. Patients found the frequency and time required to complete reporting acceptable. All patients agreed that the app was easy to use and understand. Providers felt the alerts they received required refinement. Patients and providers agreed it would be beneficial for patients to report for longer than 4 weeks. Patients felt that the training they received was adequate but contained too much information for a single session. All patients found the symptoms tracked to be appropriate; providers suggested shortening the list. All patients understood how to use the app for weekly reporting but had confusion about using it ad hoc. Providers felt the ad hoc feature could be removed. Neither patients nor providers viewed the in-app data reports but agreed on their potential value. Patients reported benefitting from symptom reporting through increased awareness of their symptoms. Clinic staff reported that app alerts were too numerous and redundant. They had difficulty responding to alerts within their existing workflow, partially because the data were not integrated into the electronic medical record system. CONCLUSIONS: Overall, the intervention was found to be acceptable and appropriate for patients with RRMM. Points of friction integrating the intervention into the clinic workflow were identified. Clinic staff provided recommendations for addressing these issues. Once such modifications are implemented, ePRO data from patients with RRMM could be used to inform and improve clinical research and care. This study underlines the importance of an iterative approach to implementation that includes all stakeholders in order to ensure successful adoption.

3.
JMIR Res Protoc ; 5(1): e25, 2016 Feb 16.
Artigo em Inglês | MEDLINE | ID: mdl-26883135

RESUMO

BACKGROUND: Mobile technology offers new capabilities that can help to drive important aspects of chronic disease management at both an individual and population level, including the ability to deliver real-time interventions that can be connected to a health care team. A framework that supports both development and evaluation is needed to understand the aspects of mHealth that work for specific diseases, populations, and in the achievement of specific outcomes in real-world settings. This framework should incorporate design structure and process, which are important to translate clinical and behavioral evidence, user interface, experience design and technical capabilities into scalable, replicable, and evidence-based mobile health (mHealth) solutions to drive outcomes. OBJECTIVE: The purpose of this paper is to discuss the identification and development of an app intervention design framework, and its subsequent refinement through development of various types of mHealth apps for chronic disease. METHODS: The process of developing the framework was conducted between June 2012 and June 2014. Informed by clinical guidelines, standards of care, clinical practice recommendations, evidence-based research, best practices, and translated by subject matter experts, a framework for mobile app design was developed and the refinement of the framework across seven chronic disease states and three different product types is described. RESULTS: The result was the development of the Chronic Disease mHealth App Intervention Design Framework. This framework allowed for the integration of clinical and behavioral evidence for intervention and feature design. The application to different diseases and implementation models guided the design of mHealth solutions for varying levels of chronic disease management. CONCLUSIONS: The framework and its design elements enable replicable product development for mHealth apps and may provide a foundation for the digital health industry to systematically expand mobile health interventions and validate their effectiveness across multiple implementation settings and chronic diseases.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA