User‐centered design for technology‐enabled services for eating disorders

Graham, Andrea K.; Wildes, Jennifer E.; Reddy, Madhu; Munson, Sean A.; Taylor, C. Barr; Mohr, David C.

doi:10.1002/eat.23130

Cited by 71 publications

(58 citation statements)

References 43 publications

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“…One of the challenges of population-based interventions is that little is actually known about what users may want. A general strategy is to first consider the interests/resources of the users/stakeholders, followed by using user-centered design [ 30 ] approaches to build out interventions designed with ultimate implementation in mind [ 5 ]. In building out the interventions, modern designs would be used (eg, the multiphase optimization strategy and others [ 1 , 2 , 31 , 32 ] to engineer optimized interventions, before evaluation in randomized controlled trials).…”

Section: Outcome Optimization Targetsmentioning

confidence: 99%

Using Digital Technology to Reduce the Prevalence of Mental Health Disorders in Populations: Time for a New Approach

Taylor¹,

Ruzek²,

Fitzsimmons‐Craft³

et al. 2020

J Med Internet Res

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Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach. Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions.

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Section: Outcome Optimization Targetsmentioning

confidence: 99%

Using Digital Technology to Reduce the Prevalence of Mental Health Disorders in Populations: Time for a New Approach

Taylor¹,

Ruzek²,

Fitzsimmons‐Craft³

et al. 2020

J Med Internet Res

Self Cite

View full text Add to dashboard Cite

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“…Parameters can be iterated upon individually or simultaneously, depending on the research goals and study designs chosen. A variety of study designs and methodologies could be used, including traditional studies, descriptive/qualitative research (e.g., determining personalization strategies using user‐centered design methods; Graham et al, ), and information science methodologies (to predict outcomes, e.g., from user search histories or text messages, before obtaining outcome data), examined in a variety of ways (e.g., A/B or adaptive designs). We reiterate the importance of rapidly creating and testing iterations that can be efficiently deployed, allowing for rapid generation of data and feedback to inform future solutions (Graham et al, ).…”

Section: Putting It All Togethermentioning

confidence: 99%

“…In summary, we believe that reach, uptake, engagement, and outcomes can be best studied from a population‐based framework that focuses on optimizing outcomes overall and for subpopulations. To achieve this goal, modern research methods and models can be leveraged, such as statistical, data‐driven scientific frameworks, experimental designs, and user‐centered design methods, to study ways to expand reach while enhancing our understanding of what works for whom and improving outcomes (e.g., Brown et al, ; Collins, ; Collins, Murphy, & Strecher, ; Graham et al, ; Mohr, Lyon, Lattie, Reddy, & Schueller, ). For example, the Multiphase Optimization Strategy (Collins, ) provides a framework for optimizing an intervention based on an optimization criterion.…”

Section: Putting It All Togethermentioning

confidence: 99%

Optimizing eating disorder treatment outcomes for individuals identified via screening: An idea worth researching

Taylor

Graham

Fitzsimmons‐Craft

et al. 2019

Intl J Eating Disorders

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In recent years, online screens have been commonly used to identify individuals who may have eating disorders (EDs), many of whom may be interested in treatment. We describe a new empirical approach that takes advantage of current evidence on empirically supported, effective treatments, while at the same time, uses modern statistical frameworks and experimental designs, data‐driven science, and user‐centered design methods to study ways to expand the reach of programs, enhance our understanding of what works for whom, and improve outcomes, overall and in subpopulations. The research would focus on individuals with EDs identified through screening and would use continuously monitored data, and interactions of interventions/approaches to optimize reach, uptake, engagement, and outcome. Outcome would be assessed at the population, rather than individual level. The idea worth researching is to determine if an optimization outcome model produces significantly higher rates of clinical improvement at a population level than do current approaches, in which traditional interventions are only offered to the few people who are interested in and able to access them.

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“…User‐centered design provides a methodology for engaging with end‐users to understand their needs and preferences by making users the center of the design process. Through collaborative and iterative engagement with end‐users, user‐centered design helps to make technological systems easier to understand, navigate, and evaluate (Graham et al, ; Norman, ). Design approaches are gaining traction for health‐related interventions (e.g., Jacobs, Clawson, & Mynatt, ; Miller & Mynatt, ; Patwardhan et al, ; Tendedez, McNaney, Ferrario, & Whittle, ; Toscos, Faber, An, & Gandhi, ), making this methodology ripe for informing an intervention for obesity and binge eating.…”

Section: Introductionmentioning

confidence: 99%

Past, current, and future willingness to engage with treatment targets: Applying user‐centered design to inform the design of a mobile behavioral intervention

Weinheimer

Chang

Neubert

et al. 2020

Intl J Eating Disorders

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Objective: User-centered design can improve engagement with and the potential efficacy of behavioral interventions, but is underutilized in health care. This work demonstrates how design methodologies can inform the design of a mobile behavioral intervention for binge eating and obesity.Method: A needs assessment was conducted with end-users (N = 22 adults with obesity and recurrent binge eating [≥12 episodes in 3 months] who were interested in losing weight and addressing binge eating), which included assessing participants' past/current and future willingness to engage with 20 treatment targets for managing binge eating and weight. Targets focused on improving dietary intake, increasing physical activity, and reducing overvaluation of weight and/or shape, unhealthy weight control practices, and negative affect. Results:Participants' past and current use of targets varied. For all targets except those addressing unhealthy weight control practices, on average, participants had increasing levels of willingness to try targets. Among participants not currently using a target, at least some were willing to use every target again.Discussion: Findings inform ways to personalize how users begin treatment. Furthermore, this study exemplifies how user-centered design can inform ways to ensure that digital interventions are designed to meet end-users' needs to improve engagement and clinical impact.

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User‐centered design for technology‐enabled services for eating disorders

Cited by 71 publications

References 43 publications

Using Digital Technology to Reduce the Prevalence of Mental Health Disorders in Populations: Time for a New Approach

Using Digital Technology to Reduce the Prevalence of Mental Health Disorders in Populations: Time for a New Approach

Optimizing eating disorder treatment outcomes for individuals identified via screening: An idea worth researching

Past, current, and future willingness to engage with treatment targets: Applying user‐centered design to inform the design of a mobile behavioral intervention

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