Emotional distress is rising globally. Widely-used music streaming apps, if suitably configured, may offer a scalable intervention to help millions of people manage their emotions more effectively. Services like Spotify already offer mood-based playlists. However, such features are not tailored to individual users’ emotional needs, reducing their effectiveness. We introduce MoodDJ, a Spotify plugin that creates playlists that take users on personalised emotion journeys from current to desired emotion. In a 14-day in-the-wild user study, we explored 22 participants' experiences of using MoodDJ through usage logs, surveys, and interviews. Findings reveal diverse patterns of use in a range of contexts, with participants often using MoodDJ to up- or down-regulate arousal or to feel more pleasant. Qualitative data suggest improvements in emotional awareness. We contribute evidence for the feasibility of embedding emotion-regulation interventions within popular music apps, and present design implications for tools of this kind.

Current AI-powered creativity support tools (AI-CSTs) primarily use text prompting to generate solution-oriented outputs. However, the potential value of multimodal prompting in designer-AI interaction, specifically the introduction of productive friction to encourage iteration and reflection, has not been fully explored. To address this, we developed SketchifAI, a prototype AI-CST, and evaluated it with design students. In a mixed-methods, within-participants study, we examined how different input modalities (text, sketch, and sketch-plus-tags) affected design students’ perceived ability to express their intent, their perception of creativity support, and their divergent thinking performance. Our preliminary findings suggest that the sketch modality tended to enhance fluency, with inconclusive evidence for differences in variety, originality, or quality compared to text modality. Yet, paradoxically, participants showed a strong preference for text prompting. We discuss how AI tools might be designed to reintroduce reflection-through-sketching, ensuring that designer-AI interaction supports, rather than erodes, essential design skills in students.

The rise of generative AI presents new opportunities for the understanding and practice of self-care through its capability to generate varied content, including self-care suggestions via text and images, and engage in dialogue with users over time. However, there are also concerns about accuracy and trustworthiness of self-care advice provided via AI. This paper reports our findings from workshops, diaries, and interviews with five researchers and 24 participants to explore their experiences and use of generative AI for self-care. We analyze our findings to present a framework for the use of generative AI to support five types of self-care, – advice seeking, mentorship, resource creation, social simulation, and therapeutic self-expression – mapped across two dimensions – expertise and modality. We discuss how these practices shift the role of technologies for self-care from merely offering information to offering personalized advice and supporting creativity for reflection, and we offer suggestions for using the framework to investigate new self-care designs.

Social media (SM) breaks from studying can either support students' wellbeing and performance by acting as a recovery behaviour or subvert it by acting as a procrastination behaviour. It is currently unclear which influences lead an SM break to be a positive recovery vs. negative procrastination behaviour. A behavioural and emotion regulation (ER) perspective may help to elucidate these influences. In this paper, we report a semi-structured interview study with 20 undergraduates to explore their experiences of SM breaks when studying. Our analysis describes how motivational and environmental factors can influence a break's propensity for recovery or procrastination during the break initiation and execution phases. We apply an ER perspective to these reports and demonstrate how it helps to explain further in which circumstances SM breaks are likely to support recovery or procrastination. Based on this analysis, we present recommendations for designing interventions to support healthy breaks and reduce unhealthy ones.

Technological progress has often been measured by the extent to which it shields and protects us from the harshness of nature. At the same time, it has long been recognised that our resulting disengagement from nature negatively affects our wellbeing and impedes awareness of our vital dependence on natural environments. To understand how HCI has considered the possibilities that digital technology offers for engaging with nature, we conducted a scoping review encompassing more than 20 years of HCI research on nature engagement. We compare the orientations, motivations, and methodologies of different threads within this growing body of work. We show how HCI research has enabled varied forms of direct and indirect engagement with nature, and we develop a typology of the roles proposed for technology in this work. We highlight promising and under-utilised approaches to designing for nature engagement and discuss directions for future research.

The rapid development and ubiquity of mobile and wearable devices promises to enable researchers to monitor users’ granular emotional data in a less intrusive manner. Researchers have used a wide variety of mobile and wearable devices for this purpose, and have proposed various approaches to sense users’ emotional states. In this survey, we utilise three established digital libraries (ACM Digital Library,IEEE Xplore Digital Library, andSpringer Nature). We analysed and critically assessed the different approaches used in the three stages (perception, learning, inference) of a typical mobile emotion sensing framework, following a structured paper selection process. The contribution of this survey is three-fold; first, we document all the latest relevant literature on mobile emotion sensing research; second, we describe how mobile and wearable devices use their sensing and computing capabilities to monitor human emotions; third, we discuss challenges and opportunities of mobile emotion sensing to demonstrate the potential of this thriving field of research.

With the rapid development of mobile and wearable devices, it is increasingly possible to access users’ affective data in a more unobtrusive manner. On this basis, researchers have proposed various systems to recognize user’s emotional states. However, most of these studies rely on traditional machine learning techniques and a limited number of signals, leading to systems that either do not generalize well or would frequently lack sufficient information for emotion detection in realistic scenarios. In this paper, we propose a novel attention-based LSTM system that uses a combination of sensors from a smartphone (front camera, microphone, touch panel) and a wristband (photoplethysmography, electrodermal activity, and infrared thermopile sensor) to accurately determine user’s emotional states. We evaluated the proposed system by conducting a user study with 45 participants. Using collected behavioral (facial expression, speech, keystroke) and physiological (blood volume, electrodermal activity, skin temperature) affective responses induced by visual stimuli, our system was able to achieve an average accuracy of 89.2 percent for binary positive and negative emotion classification under leave-one-participant-out cross-validation. Furthermore, we investigated the effectiveness of different combinations of data signals to cover different scenarios of signal availability.

Two decades of focus on User Experience has yielded an array of digital technologies that help people experience, understand and share emotions. Although the effects of specific technologies upon emotion have been well studied, less is known about how people actively appropriate and combine the full range of devices, apps and services at their disposal to deliberately manage emotions in everyday life. We conducted a one-week diary study in which 23 adults recorded interactions between their emotions and technology use. They reported using a diverse range of emotion-shaping tools and strategies as part of coping with daily challenges, managing routines, and pursuing work and social goals. We analyse these data in the light of psychological theories of emotion. Our findings point to the significance of digital emotion regulation as a powerful perspective to inform wider debates about the impacts of technology on social and emotional well-being.

Recognising and monitoring emotional states play a crucial role in mental health and well-being management. Importantly, with the widespread adoption of smart mobile and wearable devices, it has become easier to collect long-term and granular emotion-related physiological data passively, continuously, and remotely. This creates new opportunities to help individuals manage their emotions and well-being in a less intrusive manner using off-the-shelf low-cost devices. Pervasive emotion recognition based on physiological signals is, however, still challenging due to the difficulty to efficiently extract high-order correlations between physiological signals and users' emotional states. In this paper, we propose a novel end-to-end emotion recognition system based on a convolution-augmented transformer architecture. Specifically, it can recognise users' emotions on the dimensions of arousal and valence by learning both the global and local fine-grained associations and dependencies within and across multimodal physiological data (including blood volume pulse, electrodermal activity, heart rate, and skin temperature). We extensively evaluated the performance of our model using the K-EmoCon dataset, which is acquired in naturalistic conversations using off-the-shelf devices and contains spontaneous emotion data. Our results demonstrate that our approach outperforms the baselines and achieves state-of-the-art or competitive performance. We also demonstrate the effectiveness and generalizability of our system on another affective dataset which used affect inducement and commercial physiological sensors.

Homesickness, which refers to feelings of distress caused by separation from home, is prevalent among university-aged students. Chronic homesickness can exacerbate mood problems, erode academic performance and lead to dropout from school. The present research examines how students use digital technologies to resolve the experience of missing home. Qualitative interviews and diaries with 50 students at major Australian universities revealed that technologies play a significant role in alleviating homesickness. Specifically, students use technologies to acquire social contact, find help and support, build co-presence to recreate their home, connect with culture, experience distant places, and regulate emotions. However, the use of technology sometimes led to increased emotional labour, frequent exposure to homesickness triggers, and heightened perceptions of distance. We conclude by discussing possible design implications for new technologies that allow students to alleviate homesickness by experiencing their home from afar.

Iteration is a central feature of most HCI design methods, creating as it does opportunities for engagements with stakeholder groups. But what does iteration demand of those groups? Under what conditions do iterative engagements arise, and with what stakes? Building on experiences with Aboriginal Australian communities, and drawing on feminist and decolonial thinking, we examine the nature of iteration for HCI and how it frames encounters between design and use, with a focus on the affective dimension of engagement in iterative design processes.

In this paper, we demonstrate the existence of a bidirectional causal relationship between smartphone application use and user emotions. In a two-week long in-the-wild study with 30 participants we captured 502,851 instances of smartphone application use in tandem with corresponding emotional data from facial expressions. Our analysis shows that while in most cases application use drives user emotions, multiple application categories exist for which the causal effect is in the opposite direction. Our findings shed light on the relationship between smartphone use and emotional states. We furthermore discuss the opportunities for research and practice that arise from our findings and their potential to support emotional well-being.

In this article, we show how a technology-mediated mental health therapy involving psycho-education, therapist moderators, and social networking can provide support for carers of young people with mental illness. This multi-faceted tool provides opportunities for users to adapt the system to their needs, leading us to refocus the goal of treatment adherence toward a relatively new phenomenon in HCI, concordance, which has not previously been examined in the HCI literature in relation to online mental-health tools. Concordance shares important links with the development of therapeutic alliance, which is centrally important to mental health therapy, and to Self-Determination Theory (SDT), which informed our approach to design. We present a three-month user study, which provides initial encouraging support for both the suitability of concordance as a lens for viewing user engagement and the idea that users can develop a therapeutic alliance with an online support system. This latter result is surprising as the phenomenon of therapeutic alliance generally describes a relationship between client and (human) clinician. Therapeutic alliance has previously been explored for face-to-face groups, and between individuals and online systems, but not for online groups. We show how even automated system behavior can encourage engagement from users and contribute to alliance formation, if the non-human parts of an online system are interactive. We argue that a design approach involving peer/moderator support as well as automated feedback, and which takes account of SDT, can provide support for therapeutic alliance.

Strong user engagement with digital technologies for behaviour change is often taken as a precursor to their longer-term efficacy. We critically examine this assumption through a qualitative study of a smoking cessation app, called NewLeaf, which allows quitters to swap personal stories. The study examined what influenced people to engage or disengage with NewLeaf, and how the app was deployed in quit attempts during a four week trial. Several properties of swapped stories were reported to promote engagement, including: authenticity, currency, contextualization of advice, and evoking a sense of community. But while the resulting engagement was sometimes productive in supporting quitting, other trajectories of use were observed involving counterproductive engagement, and a surprising pattern of productive disengagement especially among stronger quitters. We discuss how this analysis of different trajectories problematizes any simple interpretation of user engagement as an early indicator of success for behaviour change technologies.

Communication is a critical aspect of any collaborative system. In online multiplayer games and virtual worlds it is especially complex. Users are present over long periods, require both synchronous and asynchronous communication, and may prefer to be pseudonymous or engage in identity-play while managing virtual and physical use contexts. Initially the only medium for player-to-player communication in virtual worlds was text, a medium well suited to identity-play and asynchronous communication, less so to fast-paced coordination and sociability among friends. During the past decade vendors have introduced facilities for gamers to communicate by voice. Yet little research has been conducted to help us understand the influence of voice on the experience of using virtual space: Where, when, and for whom voice is beneficial, and how it might be configured. To address this gap we examined a range of online gaming environments. We analyzed our observations in the light of theory from Human–Computer Interaction, Computer-Supported Cooperative Work, and Computer-Mediated Communication. We conclude that voice radically transforms the experience of online gaming, making virtual spaces more intensely social but removing some of the opportunity for identity play, multitasking, and multigaming while introducing ambiguity over what is being transmitted to whom.

Although the use and prevalence of Web-based mental health applications have grown over the past decade, many of these services suffer high rates of attrition. This is problematic, as face-to-face support for mental health is limited. To determine appropriate design guidelines for increasing engagement, we conducted a study of First-Episode Psychosis (FEP) patients and reviewed theories on the use of existing online services. We produced a set of design goals, developed an online application that combined social networking and online therapy within a clinician-moderated site, and conducted a 6-week trial with a group of young FEP patients. The design goals, based on existing theory including Supportive Accountability and Positive Psychology, are operationlised through a model we call Moderated Online Social Therapy (MOST). The trial results indicate that our implementation achieved the design goals and that the MOST model can inform the development of more effective and engaging online therapies.

An increasingly large number of users connect to virtual worlds on a regular basis to conduct activities ranging from gaming to business meetings. In all these worlds, users project themselves into the environment via an avatar: a 3D body which they control and whose appearance is often customizable. However, considering the prevalence of this form of embodiment, there is a surprising lack of data about how and why users customize their avatar, as well as how easy and satisfying the existing avatar creation tools are. In this paper, we report on a study investigating these issues through a questionnaire administered to more than a hundred users of three virtual worlds offering widely different avatar creation and customization systems (Maple Story, World of Warcraft, and Second Life). We illustrate the often-surprising choices users make when creating their digital representation and discuss the impact of our findings for the design of future avatar creation systems.