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Evaluating Technologies for Health Behavior Change in HCI Research

Evaluating Technologies for Health Behavior Change in HCI Research


Today, we're going to delve into the world of evaluating technologies for health behavior change in the realm of Human-Computer Interaction (HCI) research. It's a fascinating area that holds great potential for impacting society in a meaningful way. So, let's break it down in a casual and easy-to-understand manner.

The Rise of HCI Research in Health Behavior Change

In recent years, HCI research has experienced a surge in the development of systems aimed at promoting health behavior change. These systems cover a wide range of health aspects, from encouraging physical activity and healthy diets to managing chronic conditions like diabetes and emotional self-regulation.

The prevalence of chronic diseases and the significant impact of behavioral factors on these conditions have spurred the need for innovative tools to support individuals in adopting and sustaining health-promoting behaviors. Technologies such as mobile apps, web platforms, and social networking tools have emerged as promising avenues for aiding people in their health endeavors.

The Big Question: How Should We Evaluate These Technologies?

As HCI researchers increasingly engage in designing systems for health behavior change, a crucial question arises: How should we evaluate these interventions within the context of HCI research? This question encompasses two key aspects: the types of evaluations suitable for these systems and how the research output should be assessed.

The traditional approach to evaluation often revolves around demonstrating whether a technology brought about the intended change in behavior. However, this approach may be too limited, especially for early-stage technologies developed in the context of HCI research.

Rethinking Evaluation: A Broader Perspective

The traditional clinical notion of behavior change may not always be the most suitable metric for evaluating early-stage technologies. Behavior change is a complex and long-term process, often requiring extensive, large-scale studies that may not align with the early stages of technology development in HCI.

Instead, a narrower notion of efficacy, tailored to the specific intervention strategies employed by a technology, can provide valuable insights into whether the systems are fulfilling their intended purposes, even in their early stages of development. Additionally, studies focusing on people's experiences with the technology can offer crucial insights into the workings of these systems.

The Challenge of Demonstrating Behavior Change

Naturally, the desire to demonstrate behavior change is understandable, given the potential impact on people's lives. However, it's often not feasible, especially in the early stages of technology development. Behavior change is a complex, long-term process with high relapse rates, making it challenging to convincingly attribute changes solely to a specific technology.

For instance, studies have shown that for behaviors like smoking cessation, maintaining the target behavior for several years is crucial for long-term success. This highlights the complexities involved in evaluating behavior change and the limitations of solely relying on traditional clinical metrics in the context of HCI research.

The Importance of Tailored Outcome Measures

In the realm of HCI research, tailoring outcome measures to the specific intervention strategies employed by a technology can offer valuable insights into its efficacy. For example, if a system focuses on self-monitoring as a behavior-change intervention strategy, evaluating its efficacy would involve assessing how well it facilitates self-monitoring practices, rather than solely focusing on the direct impact on behavior change.

This tailored approach to evaluation aligns with the iterative nature of HCI research, allowing for meaningful insights into the effectiveness of technologies, even early in their developmental stages.

Embracing Qualitative Studies

In addition to efficacy evaluations, qualitative studies play a pivotal role in understanding the human experiences with these technologies. These studies provide rich insights into why and how a system is effective, shedding light on the user's perspectives and interactions with the technology.

Understanding the user experience is a central contribution of HCI research in the domain of health behavior change, as it goes beyond mere quantitative assessments and delves into the intricacies of human interactions with these technologies.


In conclusion, evaluating technologies for health behavior change in HCI research requires a nuanced approach that goes beyond traditional clinical metrics. By tailoring outcome measures to specific intervention strategies and embracing qualitative studies, HCI researchers can gain valuable insights into the efficacy and user experiences of these technologies, even in their early stages of development.

This approach not only aligns with the iterative nature of HCI research but also acknowledges the complexities of behavior change, paving the way for meaningful contributions to the design of innovative and effective tools for promoting health behavior change.

So, there you have it – a glimpse into the world of evaluating technologies for health behavior change in HCI research. It's a fascinating intersection of technology, behavior, and human experiences, and the potential for impact is truly exciting.

Hope you found this journey through HCI research insightful!

Citation: Predrag Klasnja, Sunny Consolvo, and Wanda Pratt, “How to Evaluate Technologies for Health Behavior Change in HCI Research,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’11: CHI Conference on Human Factors in Computing Systems, Vancouver BC Canada: ACM, 2011), 3063–72,


  • Health Behavior Change: The process of adopting and maintaining health-promoting behaviors, such as engaging in physical activity, following a healthy diet, managing chronic conditions, and emotional self-regulation.

  • Evaluation: Systematic, objective appraisal of the significance, effectiveness, and impact of activities or condition according to specified objectives and criteria. NCI Thesaurus (

  • Chronic Diseases: A disease condition that persists over a significant span of time. (

  • Intervention Strategies: (intervention) In medicine, a treatment or action taken to prevent or treat disease, or improve health in other ways. (

  • Efficacy: (efficacy) Effectiveness. In medicine, the ability of an intervention (for example, a drug or surgery) to produce the desired beneficial effect. (

  • Qualitative Studies: Research methods that focus on exploring and understanding people's experiences, perspectives, and interactions through non-numerical data, such as interviews, observations, and open-ended survey responses.

  • Outcome Measures: The specific metrics or criteria used to assess the effectiveness or success of an intervention or technology, often tailored to the strategies employed by the technology.

  • Iterative: A process that involves repeating and refining a series of steps, often with the aim of improving and evolving a product or solution over time. In the context of HCI research, it refers to the cyclical nature of design, evaluation, and refinement.

  • User Experience: The overall experience and satisfaction a person has when interacting with a product, system, or service, often encompassing aspects such as usability, accessibility, and emotional response.