The primary aim of the present research was to examine the effect of training in negating stereotype associations on stereotype activation. Across 3 studies, participants received practice in negating stereotypes related to skinhead and racial categories. The subsequent automatic activation of stereotypes was measured using either a primed Stroop task (Studies I and 2) or a person categorization task (Study 3). The results demonstrate that when receiving no training or training in a nontarget category stereotype, participants exhibited spontaneous stereotype activation. After receiving an extensive amount of training related to a specific category, however, participants demonstrated reduced stereotype activation. The results from the training task provide further evidence for the impact of practice on participants' proficiency in negating stereotypes.

BackgroundA 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.ObjectiveThe 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.MethodsA 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.ResultsThe 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.ConclusionsThis 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.

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Background Adequate self-management skills are of great importance for patients with chronic obstructive pulmonary disease (COPD) to reduce the impact of COPD exacerbations. Using mobile health (mHealth) to support exacerbation-related self-management could be promising in engaging patients in their own health and changing health behaviors. However, there is limited knowledge on how to design mHealth interventions that are effective, meet the needs of end users, and are perceived as useful. By following an iterative user-centered design (UCD) process, an evidence-driven and usable mHealth intervention was developed to enhance exacerbation-related self-management in patients with COPD. Objective This study aimed to describe in detail the full UCD and development process of an evidence-driven and usable mHealth intervention to enhance exacerbation-related self-management in patients with COPD. Methods The UCD process consisted of four iterative phases: (1) background analysis and design conceptualization, (2) alpha usability testing, (3) iterative software development, and (4) field usability testing. Patients with COPD, health care providers, COPD experts, designers, software developers, and a behavioral scientist were involved throughout the design and development process. The intervention was developed using the behavior change wheel (BCW), a theoretically based approach for designing behavior change interventions, and logic modeling was used to map out the potential working mechanism of the intervention. Furthermore, the principles of design thinking were used for the creative design of the intervention. Qualitative and quantitative research methods were used throughout the design and development process. Results The background analysis and design conceptualization phase resulted in final guiding principles for the intervention, a logic model to underpin the working mechanism of the intervention, and design requirements. Usability requirements were obtained from the usability testing phases. The iterative software development resulted in an evidence-driven and usable mHealth intervention—Copilot, a mobile app consisting of a symptom-monitoring module, and a personalized COPD action plan. Conclusions By following a UCD process, an mHealth intervention was developed that meets the needs and preferences of patients with COPD, is likely to be used by patients with COPD, and has a high potential to be effective in reducing exacerbation impact. This extensive report of the intervention development process contributes to more transparency in the development of complex interventions in health care and can be used by researchers and designers as guidance for the development of future mHealth interventions.

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Eating rate is a basic determinant of appetite regulation, as people who eat more slowly feel sated earlier and eat less. Without assistance, eating rate is difficult to modify due to its automatic nature. In the current study, participants used an augmented fork that aimed to decelerate their rate of eating. A total of 114 participants were randomly assigned to the Feedback Condition (FC), in which they received vibrotactile feedback from their fork when eating too fast (i.e., taking more than one bite per 10 s), or a Non-Feedback Condition (NFC). Participants in the FC took fewer bites per minute than did those in the NFC. Participants in the FC also had a higher success ratio, indicating that they had significantly more bites outside the designated time interval of 10 s than did participants in the NFC. A slower eating rate, however, did not lead to a significant reduction in the amount of food consumed or level of satiation. These findings indicate that real-time vibrotactile feedback delivered through an augmented fork is capable of reducing eating rate, but there is no evidence from this study that this reduction in eating rate is translated into an increase in satiation or reduction in food consumption. Overall, this study shows that real-time vibrotactile feedback may be a viable tool in interventions that aim to reduce eating rate. The long-term effectiveness of this form of feedback on satiation and food consumption, however, awaits further investigation.

Recently, there has been an increase in interest for the integration of insights from the behavioural sciences into the design process. The Persuasive by Design model aims to provide an evidence-based framework by which designers gain access to relevant theoretical insights from the behavioural sciences. This paper examines the use of the model in two case studies that dealt with complex behavioural change situations. In both studies, the model proved to be a valuable aid in determining target behaviours and operationalizing intervention concepts, especially in the early stages of the design process. Some shortcomings of the model also transpired. The model was seen as too complex, and its psychological frame does not prevent designers to overlook possible systemic moderators of behaviour. Implications for further development of tools that give access to model insights are discussed.

Background Many intervention development projects fail to bridge the gap from basic research to clinical practice. Instead of theory-based approaches to intervention development, co-design prioritizes the end users’ perspective as well as continuous collaboration between stakeholders, designers, and researchers throughout the project. This alternative approach to the development of interventions is expected to promote the adaptation to existing treatment activities and to be responsive to the requirements of end users. Objective The first objective was to provide an overview of all activities that were employed during the course of a research project to develop a relapse prevention intervention for interdisciplinary pain treatment programs. The second objective was to examine how co-design may contribute to stakeholder involvement, generation of relevant insights and ideas, and incorporation of stakeholder input into the intervention design. Methods We performed an embedded single case study and used the double diamond model to describe the process of intervention development. Using all available data sources, we also performed deductive content analysis to reflect on this process. Results By critically reviewing the value and function of a co-design project with respect to idea generation, stakeholder involvement, and incorporation of stakeholder input into the intervention design, we demonstrated how co-design shaped the transition from ideas, via concepts, to a prototype for a relapse prevention intervention. Conclusions Structural use of co-design throughout the project resulted in many different participating stakeholders and stimulating design activities. As a consequence, the majority of the components of the final prototype can be traced back to the information that stakeholders provided during the project. Although this illustrates how co-design facilitates the integration of contextual information into the intervention design, further experimental testing is required to evaluate to what extent this approach ultimately leads to improved usability as well as patient outcomes in the context of clinical practice.