Sander Hermsen

Using feedback through digital technology to disrupt and change habitual behavior: A critical review of current literature

Abstract Habitual behavior is often hard to change because of a lack of self-monitoring skills. Digital technologies offer an unprecedented chance to facilitate self-monitoring by delivering feedback on undesired habitual behavior. This review analyzed the results of 72 studies in which feedback from digital technology attempted to disrupt and change undesired habits. A vast majority of these studies found that feedback through digital technology is an effective way to disrupt habits, regardless of target behavior or feedback technology used. Unfortunately, methodological issues limit our confidence in the findings of all but 14 of the 50 studies with quantitative measurements in this review. Furthermore, only 4 studies tested for (and only 3 of those 4 found) sustained habit change, and it remains unclear how feedback from digital technology is moderated by receiver states and traits, as well as feedback characteristics such as feedback sign, comparison, tailoring, modality, frequency, timing and duration. We conclude with recommendations for new research directions.

Evaluation of a Smart Fork to Decelerate Eating Rate.

Overweight is associated with a range of negative health consequences, such as type 2 diabetes, cardiovascular disease, gastrointestinal disorders, and premature mortality. One means to combat overweight is through encouraging people to eat more slowly. People who eat quickly tend to consume more and have a higher body mass index, whereas people who eat more slowly feel satiated sooner and eat less. Unfortunately, eating rate is difficult to modify, because of its highly automatic nature. In clinical settings, researchers have had some success changing behavior by using devices that deliver feedback in real time. However, existing technologies are either too cumbersome or not engaging enough for use in daily life contexts. Training people to eat more slowly in everyday eating contexts, therefore, requires creative and engaging solutions. This article presents a qualitative evaluation of the feasibility of a smart fork to decelerate eating rate in daily life contexts. Furthermore, we outline the planned research to test the efficacy of this device in both laboratory and community settings.

Determinants for Sustained Use of an Activity Tracker: Observational Study

Background A lack of physical activity is considered to cause 6% of deaths globally. Feedback from wearables such as activity trackers has the potential to encourage daily physical activity. To date, little research is available on the natural development of adherence to activity trackers or on potential factors that predict which users manage to keep using their activity tracker during the first year (and thereby increasing the chance of healthy behavior change) and which users discontinue using their trackers after a short time. Objective The aim of this study was to identify the determinants for sustained use in the first year after purchase. Specifically, we look at the relative importance of demographic and socioeconomic, psychological, health-related, goal-related, technological, user experience–related, and social predictors of feedback device use. Furthermore, this study tests the effect of these predictors on physical activity. Methods A total of 711 participants from four urban areas in France received an activity tracker (Fitbit Zip) and gave permission to use their logged data. Participants filled out three Web-based questionnaires: at start, after 98 days, and after 232 days to measure the aforementioned determinants. Furthermore, for each participant, we collected activity data tracked by their Fitbit tracker for 320 days. We determined the relative importance of all included predictors by using Random Forest, a machine learning analysis technique. Results The data showed a slow exponential decay in Fitbit use, with 73.9% (526/711) of participants still tracking after 100 days and 16.0% (114/711) of participants tracking after 320 days. On average, participants used the tracker for 129 days. Most important reasons to quit tracking were technical issues such as empty batteries and broken trackers or lost trackers (21.5% of all Q3 respondents, 130/601). Random Forest analysis of predictors revealed that the most influential determinants were age, user experience–related factors, mobile phone type, household type, perceived effect of the Fitbit tracker, and goal-related factors. We explore the role of those predictors that show meaningful differences in the number of days the tracker was worn. Conclusions This study offers an overview of the natural development of the use of an activity tracker, as well as the relative importance of a range of determinants from literature. Decay is exponential but slower than may be expected from existing literature. Many factors have a small contribution to sustained use. The most important determinants are technical condition, age, user experience, and goal-related factors. This finding suggests that activity tracking is potentially beneficial for a broad range of target groups, but more attention should be paid to technical and user experience–related aspects of activity trackers.

The Value of Agile Methods in Designing for Behavioural Change: A Case Study

Abstract Past research on designing for behavioural change mostly concerned linear design processes, whereas in practice, Agile design methods are increasingly popular. This paper evaluates the possibilities and limitations of using Agile design methods in theory-driven design for behavioural change. We performed a design case study, consisting of a student design team working on improving waiting experiences at Schiphol Airport security and check-in. Our study showed that Agile design methods are usable when designing for behavioural change. Moreover, the Behavioural Lenses toolkit used in the design process is beneficial in facilitating theory-driven Agile design. The combination of an Agile design process and tools to evidentially inform the design enabled the design team to formulate viable and interesting concepts for improving waiting-line experiences. However, limitations also occurred: a mismatch between the rate at which the Scream method proceeded and the time and momentum needed to conduct in-depth research.

Using feedback through digital technology to disrupt and change habitual behavior

Abstract Habitual behavior is often hard to change because of a lack of self-monitoring skills. Digital technologies offer an unprecedented chance to facilitate self-monitoring by delivering feedback on undesired habitual behavior. This review analyzed the results of 72 studies in which feedback from digital technology attempted to disrupt and change undesired habits. A vast majority of these studies found that feedback through digital technology is an effective way to disrupt habits, regardless of target behavior or feedback technology used. Unfortunately, methodological issues limit our confidence in the findings of all but 14 of the 50 studies with quantitative measurements in this review. Furthermore, only 4 studies tested for (and only 3 of those 4 found) sustained habit change, and it remains unclear how feedback from digital technology is moderated by receiver states and traits, as well as feedback characteristics such as feedback sign, comparison, tailoring, modality, frequency, timing and duration. We conclude with recommendations for new research directions.

Using feedback from persuasive technologies to disrupt and change habitual behavior: a review of current literature.

Abstract Habitual behavior is often hard to change because of a lack of self-monitoring skills. Digital technologies offer an unprecedented chance to facilitate self-monitoring by delivering feedback on undesired habitual behavior. This review analyzed the results of 72 studies in which feedback from digital technology attempted to disrupt and change undesired habits. A vast majority of these studies found that feedback through digital technology is an effective way to disrupt habits, regardless of target behavior or feedback technology used. Unfortunately, methodological issues limit our confidence in the findings of all but 14 of the 50 studies with quantitative measurements in this review. Furthermore, only 4 studies tested for (and only 3 of those 4 found) sustained habit change, and it remains unclear how feedback from digital technology is moderated by receiver states and traits, as well as feedback characteristics such as feedback sign, comparison, tailoring, modality, frequency, timing and duration. We conclude with recommendations for new research directions.