Research and technological advancements have driven the development of wearable technology for stress management. Previous reviews primarily focused on its performance and effectiveness in health contexts. In contrast, this review takes a human-centric approach and reviews studies on users’ attitudes and experiences. We conducted a narrative review to identify (1) the facilitators and barriers of wearable stress management technology (WSMT) and (2) design considerations for human-centered WSMT. We identified 28 articles reporting user perspectives on stress management technology, primarily based on evaluation studies in which user perspectives were gathered through qualitative methods. We found five facilitators and barriers of WSMT (i.e., usefulness, functionality/interactivity, seamlessness, user privacy, and technology's image). Additionally, we synthesized 18 design considerations, highlighted two main design challenges, and proposed a value-sensitive approach for future research. This review adds to the HCI literature by demonstrating the complexity of designing human-centered WSMT and the need for actionable recommendations.

Abstract Stress-tracking technology is becoming widely available and accessible, offering non-invasive ways to monitor and regulate stress. Yet, current stress-tracking technology presents stress scores that lack transparency, informativeness, and nuance. This provocation paper discusses five key issues that the current stress-tracking technology should overcome, involving conceptualization, measurements, transparency, interpretation, and responsibility. Next, we provide three directions to overcome these issues and inform better stress-tracking practices and future research. Future stress technology should improve stress response measurements, use better terminology and data visualizations, and increase user involvement and transparency. We conclude that there is a pressing need for designers and researchers to take greater responsibility in creating stress-tracking technologies that are useful, fair and just, and centered around individuals’ needs.

Smartphones are powerful tools for reaching the user when it is most needed, i.e. Just-In-Time (JIT). In the context of stress management in professionals, self-tracking can create awareness about stress and eCoaching can provide personalised JIT coping suggestions. Employees should also be receptive to take in or act upon the JIT-messages. Therefore, this study aims to explore what factors (emotional state, events or conditions, and content of the message) affect the employees’ receptivity to JIT-messages. 17 participants were invited to use a prototype of the Resilience Navigator app for two weeks. The mixed-methods approach consisted of mixed effects models analysis on data collected via the app (receptivity and the factors of interest) and qualitative analysis on semi-structured interview data collected after the study period. The overall finding was that the participants’ receptivity in the context of stress management often mismatches with the most relevant moments for JIT-messages. For example, emotions with a negative valence seemed to influence the receptivity towards JIT-messages negatively, although the perceived relevance was high. As technology can pinpoint the most receptive and relevant moment for sending JIT-messages, we advocate to further study this topic with more robust quantitative data.

Previous studies have found that basic movement characteristics of a robot influence the emotional attributes people perceive independent of the embodiment of the motion (e.g. iCat vs. Roomba). Here, with a very simple LEGO robot, we replicate these associations between levels of acceleration and curvature and the extent to which positive and negative emotions are attributed. Importantly, we also show that these associations might not be valid. Prior to the emotional questionnaires participants were asked neutral questions on what they deemed relevant observations pertaining to the different robot motions. Only 3% of the remarks coincided with the emotional terms found in the questionnaires. HRI researchers interested in what people attribute to robot motion should be mindful of participant heuristics and experimenter biases. We provide some suggestions how to create experiments that are robust against these biases.

With the rise of user‐generated content, evaluating the credibility of information has become increasingly important. It is already known that various user characteristics influence the way credibility evaluation is performed. Domain experts on the topic at hand primarily focus on semantic features of information (e.g., factual accuracy), whereas novices focus more on surface features (e.g., length of a text). In this study, we further explore two key influences on credibility evaluation: topic familiarity and information skills. Participants with varying expected levels of information skills (i.e., high school students, undergraduates, and postgraduates) evaluated Wikipedia articles of varying quality on familiar and unfamiliar topics while thinking aloud. When familiar with the topic, participants indeed focused primarily on semantic features of the information, whereas participants unfamiliar with the topic paid more attention to surface features. The utilization of surface features increased with information skills. Moreover, participants with better information skills calibrated their trust against the quality of the information, whereas trust of participants with poorer information skills did not. This study confirms the enabling character of domain expertise and information skills in credibility evaluation as predicted by the updated 3 S ‐model of credibility evaluation.