ReviewThe International journal of eating disorders2019
User-centered design for technology-enabled services for eating disorders.
Review in The International journal of eating disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.
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Who cites it
66 citing papers in PubMed, 1 synthesis or guideline pooled it.
- User Experiences of and Preferences for Self-Guided Digital Interventions for the Treatment of Mild to Moderate Eating Disorders: Systematic Review and Metasynthesis.JMIR mental health · 2025Pooled it
- User Experience and Therapeutic Alliance of Treatment Completers of Clinician-Supported Versus Self-Help Online Intervention for Eating Disorders: A Mixed Methods Approach.European eating disorders review : the journal of the Eating Disorders Association · 2025Trial
- Tailored online eating disorder prevention and health promotion for women: results of a dissemination trial.Frontiers in psychiatry · 2025Trial
- Effects of Chatbot Components to Facilitate Mental Health Services Use in Individuals With Eating Disorders Following Online Screening: An Optimization Randomized Controlled Trial.The International journal of eating disorders · 2024Trial
- Understanding self-monitoring to inform a mobile intervention for binge eating and weight management: A proof-of-concept randomized trial.The International journal of eating disorders · 2022Trial
- Examining the Characteristics of Adolescents Recruited to a Novel Digital Treatment for Eating Disorders: Baseline Assessment in an Open Feasibility Trial.JMIR pediatrics and parenting · 2026Article
- Adult users of a digital binge-eating intervention wanted adaptations for type 2 diabetes: Qualitative study of post-intervention preferences.Research square · 2026Article
- Gamified Assessment of Cognitive Impulsivity in Eating Disorders and Mental Ill-Health: Mixed Methods Study Incorporating Lived Experience Co-Design and Evaluation.JMIR serious games · 2026Article
- Age-Based Left-Digit Bias in the Treatment of Pancreatic Adenocarcinoma.Journal of gastrointestinal cancer · 2026Article
- Exploring expectations for a digital intervention for binge eating among individuals experiencing food insecurity.Eating behaviors · 2026Article
- Leveraging Technology to Enhance Eating Disorder Treatment Outcomes.The Psychiatric clinics of North America · 2026Review
- What does the American public want to know about addiction? A national systematic qualitative investigation.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2026Article
- Health care professionals' postpartum nutritional counselling to women; a mixed-methods approach.BMC health services research · 2026Article
- Supporting Individuals on Eating Disorder Waitlists Through App-Based Motivational Interviewing: A Qualitative Evaluation of a Program-Led Pilot Intervention.The International journal of eating disorders · 2026Article
- Human-Centered Design of a Personalized Digital Health Intervention to Improve Oral Chemotherapy Adherence in Adolescents and Young Adults With Hematologic Cancers.Pediatric blood & cancer · 2025Article
- Open Pilot Trial of a Coached Digital Program for Lower-Income Adults With Eating Disorders.The International journal of eating disorders · 2025Article
- Development of a Bayesian Network-Based Parallel Mechanism for Lower Limb Gait Rehabilitation.Biomimetics (Basel, Switzerland) · 2025Article
- Adaptations of an online cognitive-behavioral therapy intervention for binge type eating disorders in publicly-insured and uninsured adults: a pilot study.BMC public health · 2025Article
- 'Harder to reach' versus reaching harder: Exploring preferred dissemination pathways to a digital binge-eating intervention for adults with or at risk of food insecurity.Eating behaviors · 2025Article
- Optimizing Testimonials for Behavior Change in a Digital Intervention for Binge Eating: Human-Centered Design Study.JMIR formative research · 2025Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
objectiveTechnology-enabled services frequently have limited reach and suboptimal engagement when implemented in real-world settings. One reason for these implementation failures is that technology-enabled services are not designed for the users and contexts in which they will be implemented. User-centered design is an approach to designing technologies and services that is grounded in information from the stakeholders who will be using or impacted by them, and the contexts for implementation. The purpose of this article is to present user-centered design methods that can be applied to technology-enabled services for eating disorders.
methodWe provide an overview of the user-centered design process, which is iterative and involves stakeholders throughout. One model is presented that depicts six phases of a user-centered design process: investigate, ideate, prototype, evaluate, refine and develop, and validate.
resultsWe then review how user-centered design approaches can be applied to designing technology-enabled services for patients with eating disorders, and we integrate a hypothetical case example that demonstrates the application of these techniques to designing a technology-enabled service for binge eating. Most of the user-centered design techniques can be implemented relatively quickly, allowing us to rapidly learn what stakeholders want and to identify problems before devoting time and resources to developing and delivering technologies and services. DISCUSSION: Through this work, we show how designing services that fit into the patterns and routines that stakeholders already are doing can ensure that services are relevant to stakeholders and meet their needs, potentially improving engagement and clinical impact. RESUMEN: Los servicios habilitados tecnológicamente frecuentemente tienen un alcance limitado y un involucramiento subóptimo cuando son implementados en escenarios del mundo real. Una razón para estas fallas de implementación es que los servicios habilitados tecnológicamente no están diseñados para los usuarios y contextos en los que serán implementados. El diseño centrado en el usuario es un abordaje para diseñar tecnologías y servicios que está basado en información de las partes interesadas que estarán haciendo uso o impactados por ellos, y los contextos para implementación. El propósito de este estudio es presentar métodos de diseños centrados en el usuario que pueden ser aplicados a servicios habilitados tecnológicamente para trastornos de la conducta alimentaria. Ofrecemos una visión general del proceso de diseño centrado en el usuario, que es iterative e involucra a las partes interesadas a lo largo de todo el proceso. Hemos presentado un modelo que describe seis fases de un proceso de diseño centrado en el usuario: investigar, idear, crear prototipos, evaluar, refinar y desarrollar, y validar. Luego revisamos cómo estos abordajes de diseño centrado en el usuario pueden ser aplicados para diseñar servicios habilitados tecnológicamente para pacientes con trastornos de la conducta alimentaria, e integramos un ejemplo de caso hipotético que demuestra la aplicación de estas técnicas para diseñar un servicio habilitado tecnológicamente para comer en atracones. Muchas de las técnicas de diseño centrado en el usuario pueden ser implementadas relativamente rápido, lo que nos permite aprender rápidamente lo que las partes interesadas quieren e identificar los problemas antes de dedicarles tiempo y recursos al desarrollo y entrega de tecnologías y servicios. A través de este trabajo, mostramos cómo el diseño de servicios que se ajustan a los patrones y rutinas que las partes interesadas ya están haciendo puede garantizar que los servicios sean relevantes para los interesados y que satisfagan sus necesidades, lo que podría mejorar la participación y el impacto clínico.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.