Human-to-Computer Interactivity Features Incorporated Into Behavioral Health mHealth Apps: Systematic Search.

BACKGROUND: While there are thousands of behavioral health apps available to consumers, users often quickly discontinue their use, which limits their therapeutic value. By varying the types and number of ways that users can interact with behavioral health mobile health apps, developers may be able to support greater therapeutic engagement and increase app stickiness. OBJECTIVE: The main objective of this analysis was to systematically characterize the types of user interactions that are available in behavioral health apps and then examine if greater interactivity was associated with greater user satisfaction, as measured by app metrics. METHODS: Using a modified PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) methodology, we searched several different app clearinghouse websites and identified 76 behavioral health apps that included some type of interactivity. We then filtered the results to ensure we were examining behavioral health apps and further refined our search to include apps that identified one or more of the following terms: peer or therapist forum, discussion, feedback, professional, licensed, buddy, friend, artificial intelligence, chatbot, counselor, therapist, provider, mentor, bot, coach, message, comment, chat room, community, games, care team, connect, share, and support in the app descriptions. In the final group of 34 apps, we examined the presence of 6 types of human-machine interactivities: human-to-human with peers, human-to-human with providers, human-to-artificial intelligence, human-to-algorithms, human-to-data, and novel interactive smartphone modalities. We also downloaded information on app user ratings and visibility, as well as reviewed other key app features. RESULTS: We found that on average, the 34 apps reviewed included 2.53 (SD 1.05; range 1-5) features of interactivity. The most common types of interactivities were human-to-data (n=34, 100%), followed by human-to-algorithm (n=15, 44.2%). The least common type of interactivity was human-artificial intelligence (n=7, 20.5%). There were no significant associations between the total number of app interactivity features and user ratings or app visibility. We found that a full range of therapeutic interactivity features were not used in behavioral health apps. CONCLUSIONS: Ideally, app developers would do well to include more interactivity features in behavioral health apps in order to fully use the capabilities of smartphone technologies and increase app stickiness. Theoretically, increased user engagement would occur by using multiple types of user interactivity, thereby maximizing the benefits that a person would receive when using a mobile health app.

Pandemic-influenced human mobility on tribal lands in California: Data sparsity and analytical precision.

Human mobility datasets collected from personal mobile device locations are integral to understanding how states, counties, and cities have collectively adapted to pervasive social disruption stemming from the COVID-19 pandemic. However, while indigenous tribal communities in the United States have been disproportionately devastated by the pandemic, the relatively sparse populations and data available in these hard-hit tribal areas often exclude them from mobility studies. We explore the effects of sparse mobility data in untangling the often inter-correlated relationship between human mobility, distancing orders, and case growth throughout 2020 in tribal and rural areas of California. Our findings account for data sparsity imprecision to show: 1) Mobility through legal tribal boundaries was unusually low but still correlated highly with case growth; 2) Case growth correlated less strongly with mobility later in the the year in all areas; and 3) State-mandated distancing orders later in the year did not necessarily precede lower mobility medians, especially in tribal areas. It is our hope that with more timely feedback offered by mobile device datasets even in sparse areas, health policy makers can better plan health emergency responses that still keep the economy vibrant across all sectors.

Integrating Cultural Relevance into a Behavioral mHealth Intervention for Native American Youth.

Native American communities are disproportionately affected by a number of behavioral health disparities, including higher rates of depression, substance abuse, and suicide. As mobile health (mHealth) interventions gain traction 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 (Amplifying Resilience Over Restricted Internet Access), 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 we faced in our efforts to co-design software with Native American stakeholders and provide recommendations that might guide other HCI researchers and designers through challenges that arise during the process of cross-cultural design.

"Of Course, Data Can Never Fully Represent Reality": Assessing the Relationship between "Indigenous Data" and "Indigenous Knowledge," "Traditional Ecological Knowledge," and "Traditional Knowledge".

Multiple terms describe Indigenous peoples' creative expressions, including "Indigenous knowledge" (IK), "traditional ecological knowledge" (TEK), "traditional knowledge" (TK), and increasingly, "Indigenous data" (ID). Variation in terms contributes to disciplinary divides, challenges in organizing and finding prior studies about Indigenous peoples' creative expressions, and intellectually divergent chains of reference. The authors applied a decolonial, digital, feminist, ethics-of-care approach to citation analysis of records about Indigenous peoples knowledge and data, including network analyses of author-generated keywords and research areas, and content analysis of peer-reviewed studies about ID. Results reveal ambiguous uses of the term "Indigenous data"; the influence of ecology and environmental studies in research areas and topics associated with IK, TEK, and TK; and the influence of public administration and governance studies in research areas and topics associated with ID studies. Researchers of ID would benefit from applying a more nuanced and robust vocabulary, one informed by studies of IK, TEK, and TK. Researchers of TEK and TK would benefit from the more people-centered approaches of IK. Researchers and systems designers who work with data sets can practice relational accountability by centering the Indigenous peoples from whom observations are sourced, combining narrative methodologies with computational methods to sustain the holism favored by Indigenous science and the relationality of Indigenous peoples.

Designing a Mobile Game That Develops Emotional Resiliency in Indian Country.

Communities in Indian Country experience severe behavioral health inequities [11, 12]. Based on recent research investigating scalable behavioral health interventions and therapeutic best practices for Native American (NA) communities, we propose ARORA, a social and emotional learning intervention delivered over a networked mobile game that uses geosocial gaming mechanisms enhanced with augmented reality technology. Focusing on the Navajo community, we take a community-based participatory research approach to include NA psychologists, community health workers, and educators as co-designers of the intervention activities and gaming mechanisms. Critical questions involve operation of the application across low-infrastructure landscapes as well scalability of design practices to be inclusive of the many diverse NA cultural communities in Indian Country.