Rapid changes in technology are expected to limit the availability of decent work for millions of people worldwide. This particularly disadvantages socially and economically marginalized job seekers who are already being pushed into lower-wage precarious work with increasing levels of job insecurity. While the number of employment support tools that match job seekers to employers has been growing, marginalized job seekers still significantly rely on physical employment centers that have a track record of supporting the specific needs associated with marginalization and economic constraints. We drew from prior HCI and CSCW literature uncovering the employment and technology-related challenges that marginalized job seekers face and from the Psychology of Working Theory to frame our research questions and results. To complement this prior work, we investigated how employment center staff work with marginalized job seekers and moderate factors to securing decent work. We found in an interview of 21 employment center staff\textemdash career advisors and business services coordinators\textemdash that they performed significant work to prepare and encourage marginalized job seekers in applying to positions, while also training employers to be more inclusive and open-minded. Career advisors worked directly with job seekers to connect them with external resources, provide encouragement, strategize long-term goals, and mitigate feelings of stigma. Business services coordinators worked directly with employers to prepare job positions and employee support programs. Drawing from the expertise of employment centers, we contribute a framework for designing employment support tools that better serve the needs of marginalized job seekers, and outline tangible design implications that complement the support these organizations provide.
https://doi.org/10.1145/3476065
The misuse of legal and illegal drugs has grown to such an acute level that it now represents a public health crisis in the United States. To support clinical treatments of substance use disorders (SUDs), formal non-clinical peer recovery support programs pairing coaches with people new to recovery are gaining in popularity. Using a user-centered design approach, we designed a mobile application to support the peer coach recovery program of a health system. The application addresses the needs associated with the coaches’ workflows, encompasses social supports for recoverees, and provides a space for fostering the coach-recoveree relationship. Finally, we then evaluated a prototype with recoverees and program coaches. Through this process, we identified tensions between stakeholder needs and translated these tensions into design features and future design considerations.
For individuals impacted by their own or a family member’s cancer, connecting with other people in similar situations can be an invaluable source of informational and emotional support. Online spaces provide opportunities for peer support that may be more accessible, given the medical and logistical restrictions on face-to-face socialisation associated with cancer and treatment. However, little is known about the impacts of online peer support. This systematic review surveys the literature on psychosocial impacts of online peer support for people impacted by cancer, integrating research from psychology, health, communications, informatics and social computing disciplines. The reviewed papers and interventions vary widely in the type of online peer support provided, who this support was intended for, and how outcomes were evaluated. Quantitative evidence suggests that online peer support may improve psychosocial wellbeing, particularly anxiety and stress, although this appears to depend on how individuals engage and interact with others. Qualitative findings suggest clear value in connecting and sharing experiences with those in similar situations, benefits which may not be well captured quantitatively. Overall, it appears that for individuals who share experiences, express emotions and feel understood and accepted by others, these online peer spaces may be a valuable and viable source of support. However, these benefits require strategic community design and management to build an active and sustainable group dynamic which can effectively and safely support people impacted by cancer.
Native American communities are disproportionately effected by a number of behavioral health disparities, including higher rates of depression, substance abuse, and suicide. As mobile health (mHealth) interventions are increasingly used as methods for addressing these disparities, they continue to lack relevance to Native American youth. In an effort to explore the design of relevant behavioral mHealth intervention for Native American communities, we have developed ARORA, a prototype behavioral mHealth intervention that has been co-designed with Native American youth, a community advisory board, and a clinical psychologist. In this paper, we qualitatively analyze our co-design and focus group sessions using a grounded theory approach and identify the key themes that Native American community members have identified as being critical components of relevant mHealth designs. Notably, we find that the Native American youth who participated in our focus groups desired a greater level of didactic interaction with cultural and behavioral health elements. We conclude with a discussion of the significant challenges that we faced in our efforts to co-design software with Native American stakeholders and we provide recommendations that might guide other HCI researchers and designers through challenges that arise during the process of cross-cultural design.
https://doi.org/10.1145/3449239
Although often ignored, adult gamers, just like the children and adolescents, can suffer from problematic gaming. This study explored the use of a built-in game gradual intervention system (G-GIS), designed to help adult gamers build their wanted game habits in an autonomous and acceptable way. In this study, we interviewed 26 heavy adult gamers (i.e. adult gamers who played the game frequently and for a relatively long time) of an online poker game (with a G-GIS in-built) and triangulated the interview results with their real-world behavioral data collected in eight months, to explore how demographics, attitudes, and contextual factors influence their use of the G-GIS. The results of the study showed that family and occupation demographics play key roles in determining adult gamers’ gaming habits and their self-control under the G-GIS intervention. We also revealed that adult gamers’ attitudes and contextual factors would facilitate or hinder the effectiveness of the G-GIS. The findings of this study extend people’s understanding of heavy adult gamers and reveal how a G-GIS influences the adult gamers from the individual level, which can be applied to design future game intervention systems, especially for the adult gamers.
Automatic emotion recognition (ER)-enabled wellbeing interventions use ER algorithms to infer the emotions of a data subject (i.e., a person about whom data is collected or processed to enable ER) based on data generated from their online interactions, such as social media activity, and intervene accordingly. The potential commercial applications of this technology are widely acknowledged, particularly in the context of social media. Yet, little is known about data subjects' conceptualizations of and attitudes toward automatic ER-enabled wellbeing interventions. To address this gap, we interviewed 13 US adult social media data subjects regarding social media-based automatic ER-enabled wellbeing interventions. We found that participants' attitudes toward automatic ER-enabled wellbeing interventions were predominantly negative. Negative attitudes were largely shaped by how participants compared their conceptualizations of Artificial Intelligence (AI) to the humans that traditionally deliver wellbeing support. Comparisons between AI and human wellbeing interventions were based upon human attributes participants doubted AI could hold: 1) helpfulness and authentic care; 2) personal and professional expertise; 3) morality; and 4) benevolence through shared humanity. In some cases, participants' attitudes toward automatic ER-enabled wellbeing interventions shifted when participants conceptualized automatic ER-enabled wellbeing interventions' impact on others, rather than themselves. Though with reluctance, a minority of participants held more positive attitudes toward their conceptualizations of automatic ER-enabled wellbeing interventions, citing their potential to benefit others: 1) by supporting academic research; 2) by increasing access to wellbeing support; and 3) through egregious harm prevention. However, most participants anticipated harms associated with their conceptualizations of automatic ER-enabled wellbeing interventions for others, such as re-traumatization, the spread of inaccurate health information, inappropriate surveillance, and interventions informed by inaccurate predictions. Lastly, while participants had qualms about automatic ER-enabled wellbeing interventions, we identified three development and delivery qualities of automatic ER-enabled wellbeing interventions upon which their attitudes toward them depended: 1) accuracy; 2) contextual sensitivity; and 3) positive outcome. Our study is not motivated to make normative statements about whether or how automatic ER-enabled wellbeing interventions should exist, but to center voices of the data subjects affected by this technology. We argue for the inclusion of data subjects in the development of requirements for ethical and trustworthy ER applications. To that end, we discuss ethical, social, and policy implications of our findings, suggesting that automatic ER-enabled wellbeing interventions imagined by participants are incompatible with aims to promote trustworthy, socially aware, and responsible AI technologies in the current practical and regulatory landscape in the US.
The post-college transition is a critical period where individuals experience unique challenges and stress before, during, and after graduation. Individuals often use social media to discuss and share information, advice, and support related to post-college challenges in online communities. These communities are important as they fill gaps in institutional support between college and post-college plans. We empirically study the challenges and stress expressed on social media around this transition as students graduate college and move into emerging adulthood. We assembled a dataset of about 299,000 Reddit posts between 2008 and 2020 about the post-college transition from 10 subreddits. We extracted top concerns, challenges, and conversation points using unsupervised Latent Dirichlet Allocation (LDA). Then, we combined the results of LDA with binary transfer learning to identify stress expressions in the dataset (classifier performance at F1=0.94). Finally, we explore temporal patterns in stress expressions and the variance of per-topic stress levels throughout the year. Our work highlights a more deliberate and focused understanding of the post-college transition, as well as useful research and design impacts to study transient cohorts in need of support.
https://doi.org/10.1145/3476039