Sharing Stress With a Robot: What Would a Robot Say?

With the prevalence of mental health problems today, designing human-robot interaction for mental health intervention is not only possible, but critical. The current experiment examined how three types of robot disclosure (emotional, technical, and by-proxy) affect robot perception and human disclosure behavior during a stress-sharing activity. Emotional robot disclosure resulted in the lowest robot perceived safety. Post-hoc analysis revealed that increased perceived stress predicted reduced human disclosure, user satisfaction, robot likability, and future robot use. Negative attitudes toward robots also predicted reduced intention for future robot use. This work informs on the possible design of robot disclosure, as well as how individual attributes, such as perceived stress, can impact human robot interaction in a mental health context

Anger without Agency: Exploring the Experiences of Stress in Adolescent Girls

Although a great deal of research has measured stressful life events and stress-related symptoms in adolescents, little research has qualitatively examined the experience of stress in teens. The purpose of this study was to utilize thematic analysis to explore how teen girls described their experiences of stress. Thirty-one girls, ages 14–18, were recruited for a study examining stress and stress-related symptoms. As part of this study, they participated in an open-ended, qualitative interview about their personal experiences of stress. Themes included the mind of stress, emotionally shutting out others, and “growing out of it.” The overarching finding was that all teen girls described anger in relation to stress. Most concerning was the predominant theme of a lack of agency in relation to affecting change or management of stress in their lives

Young people's data governance preferences for their mental health data: MindKind Study findings from India, South Africa, and the United Kingdom

Mobile devices offer a scalable opportunity to collect longitudinal data that facilitate advances in mental health treatment to address the burden of mental health conditions in young people. Sharing these data with the research community is critical to gaining maximal value from rich data of this nature. However, the highly personal nature of the data necessitates understanding the conditions under which young people are willing to share them. To answer this question, we developed the MindKind Study, a multinational, mixed methods study that solicits young people's preferences for how their data are governed and quantifies potential participants' willingness to join under different conditions. We employed a community-based participatory approach, involving young people as stakeholders and co-researchers. At sites in India, South Africa, and the UK, we enrolled 3575 participants ages 16-24 in the mobile app-mediated quantitative study and 143 participants in the public deliberation-based qualitative study. We found that while youth participants have strong preferences for data governance, these preferences did not translate into (un)willingness to join the smartphone-based study. Participants grappled with the risks and benefits of participation as well as their desire that the "right people" access their data. Throughout the study, we recognized young people's commitment to finding solutions and co-producing research architectures to allow for more open sharing of mental health data to accelerate and derive maximal benefit from research

Engaging English Language Learners as Cultural Informants in the Design of a Social Robot for Education

Background: There are 4.9 million English Language Learners (ELLs) in the United States. Only 2% of educators are trained to support these vulnerable students. Social robots show promise for language acquisition and may provide valuable support for students, especially as we return to needing smaller classes due to COVID-19. While cultural responsiveness increases gains for ELLs, little is known about the design of culturally responsive child–robot interactions. Method: Therefore, using a participatory design approach, we conducted an exploratory study with 24 Spanish-speaking ELLs at a Pacific Northwest elementary school. As cultural informants, students participated in a 15-min, robot-led, small group story discussion followed by a post-interaction feedback session. We then conducted reflexive critiques with six ELL teachers who reviewed the group interactions to provide further interpretation on design feature possibilities and potential interactions with the robot. Results: Students found the social robot engaging, but many were hesitant to converse with the robot. During post-interaction dialogue students articulated the specific ways in which the social robot appearance and behavior could be modified to help them feel more comfortable. Teachers postulated that the social robot could be designed to engage students in peer-to-peer conversations. Teachers also recognized the ELLs verbosity when discussing their experiences with the robot and suggested such interactions could stimulate responsiveness from students. Conclusion: Cultural responsiveness is a key component to successful education in ELLs. However, integrating appropriate, cultural responsiveness into robot interactions may require participants as cultural informants to ensure the robot behaviors and interactions are situated in that educational community. Utilizing a participatory approach to engage ELLs in design decisions for social robots is a promising way to gather culturally responsive requirements to inform successful child–robot interactions

Participatory Research Principles in Human-Centered Design: Engaging Teens in the Co-Design of a Social Robot

Social robots are emerging as an important intervention for a variety of vulnerable populations. However, engaging participants in the design of social robots in a way that is ethical, meaningful, and rigorous can be challenging. Many current methods in human–robotic interaction rely on laboratory practices, often experimental, and many times involving deception which could erode trust in vulnerable populations. Therefore, in this paper, we share our human-centered design methodology informed by a participatory approach, drawing on three years of data from a project aimed to design and develop a social robot to improve the mental health of teens. We present three method cases from the project that describe creative and age appropriate methods to gather contextually valid data from a teen population. Specific techniques include design research, scenario and script writing, prototyping, and teens as operators and collaborative actors. In each case, we describe the method and its implementation and discuss the potential strengths and limitations. We conclude by situating these methods by presenting a set of recommended participatory research principles that may be appropriate for designing new technologies with vulnerable populations

Changes in Political Astuteness Following Nurse Legislative Day

Political astuteness, including awareness, knowledge, and involvement, is necessary if nurses are to engage in policy advocacy—a vital aspect of the nursing profession. However, little is known about the effects of learning activities, such as legislative days, on political astuteness. The purpose of this research was to determine if political astuteness changed after participants attended a state nurse legislative day. Pre and post data were collected from participants in two studies (N = 80 and N  = 34) using the Political Astuteness Inventory (PAI). Political astuteness scores were significantly higher after participants attended legislative day as compared to before. Age and educational rank were positively correlated with political astuteness. Experiential activities such as attending nurse legislative days that offer opportunities to learn policy advocacy skills can enhance knowledge of and participation in the policy process

Participatory Research Principles in Human-Centered Design: Engaging Teens in the Co-Design of a Social Robot

Social robots are emerging as an important intervention for a variety of vulnerable populations. However, engaging participants in the design of social robots in a way that is ethical, meaningful, and rigorous can be challenging. Many current methods in human⁻robotic interaction rely on laboratory practices, often experimental, and many times involving deception which could erode trust in vulnerable populations. Therefore, in this paper, we share our human-centered design methodology informed by a participatory approach, drawing on three years of data from a project aimed to design and develop a social robot to improve the mental health of teens. We present three method cases from the project that describe creative and age appropriate methods to gather contextually valid data from a teen population. Specific techniques include design research, scenario and script writing, prototyping, and teens as operators and collaborative actors. In each case, we describe the method and its implementation and discuss the potential strengths and limitations. We conclude by situating these methods by presenting a set of recommended participatory research principles that may be appropriate for designing new technologies with vulnerable populations

Participatory Research Principles in Human-Centered Design: Engaging Teens in the Co-Design of a Social Robot

Social robots are emerging as an important intervention for a variety of vulnerable populations. However, engaging participants in the design of social robots in a way that is ethical, meaningful, and rigorous can be challenging. Many current methods in human–robotic interaction rely on laboratory practices, often experimental, and many times involving deception which could erode trust in vulnerable populations. Therefore, in this paper, we share our human-centered design methodology informed by a participatory approach, drawing on three years of data from a project aimed to design and develop a social robot to improve the mental health of teens. We present three method cases from the project that describe creative and age appropriate methods to gather contextually valid data from a teen population. Specific techniques include design research, scenario and script writing, prototyping, and teens as operators and collaborative actors. In each case, we describe the method and its implementation and discuss the potential strengths and limitations. We conclude by situating these methods by presenting a set of recommended participatory research principles that may be appropriate for designing new technologies with vulnerable populations

Participatory Pilot of an Art-Based Mindfulness Intervention for Adolescent Girls With Headache

A participatory pilot study researched mindfulness sessions informed by art therapy for adolescent girls suffering from headaches. Researchers worked closely with 8 participants to customize and implement an appropriate mindfulness-based art intervention. Program evaluation included both quantitative and qualitative outcomes, including pre- and postintervention artwork. The adolescents were engaged in the sessions and they embraced the idea of an art-based, mindfulness approach to help with their headaches. The findings supported a strong, positive impact of the intervention on both reducing stress and headaches. This mixed-method pilot study provides preliminary support for the value of mindfulness interventions based on art therapy principles and practices to reduce stress and headaches in adolescent girls

Teen-Robot Interaction: A Pilot Study of Engagement With a Low-Fidelity Prototype

Today\u27s teens will most likely be the first generation to spend a lifetime living and interacting with both mechanical and social robots. Although human-robot interaction has been explored in children, adults, and seniors, examination of teen-robot interaction has been minimal. Using human-centered design, our team is developing a social robot to gather stress and mood data from teens in a public high school. As part of our preliminary design stage, we conducted a interaction pilot study in the wild to explore and capture teens\u27 initial interactions with a low-fidelity social robot prototype. We observed strong engagement and expressions of empathy from teens during our qualitative, interaction studies