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Despite significant cultural strengths and knowledge, Indigenous people around the world experience substantial health inequities due to the historic and ongoing impacts of settler colonialism. As information and communication technologies (ICTs) are increasingly used as part of health interventions to help bridge equity gaps, it is important to characterize and critically evaluate how ICT-facilitated health interventions are designed for and used by Indigenous people. This critical literature review queried articles from three archives focused on health and technology with the goal of identifying cross-cutting challenges and opportunities for ICT-facilitated health interventions in Indigenous communities. Importantly, we use the lens of decolonization to understand important issues that impact Indigenous sovereignty, including the incorporation of Indigenous Knowledge and engagement with data sovereignty. 

Despite high incidence of depression, anxiety, and post traumatic stress disorder, stigma and lack of access to culturally responsive behavioral health care resources prevents many Native Americans (NA) from seeking care. However, the rise of culturally-responsive in-person and digital behavioral health resources for NA communities provides new opportunities to address these longstanding health equity issues. The major challenge is helping people in NA communities find these meaningful resources and helping anchor institutions understand how resources are being sought and utilized to support more responsive internal programming. In this context, we have partnered with Hopi Behavioral Health Services (HBHS) to design the Resilience Resource Database to digitally disseminate mental and behavioral health resources. This paper presents initial findings that have resulted from the initial stage of an iterative participatory design process with HBHS. 

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. 

Abstract Background HIV-1 proviruses persist in people on antiretroviral therapy (ART) but most are defective and do not constitute a replication-competent reservoir. The decay of infected cells carrying intact compared with defective HIV-1 proviruses has not been well defined in people on ART. Methods We separately quantified intact and defective proviruses, residual plasma viremia, and markers of inflammation and activation in people on long-term ART. Results Among 40 participants tested longitudinally from a median of 7.1 years to 12 years after ART initiation, intact provirus levels declined significantly over time (median half-life, 7.1 years; 95% confidence interval [CI], 3.9–18), whereas defective provirus levels did not decrease. The median half-life of total HIV-1 DNA was 41.6 years (95% CI, 13.6–75). The proportion of all proviruses that were intact diminished over time on ART, from about 10% at the first on-ART time point to about 5% at the last. Intact provirus levels on ART correlated with total HIV-1 DNA and residual plasma viremia, but there was no evidence for associations between intact provirus levels and inflammation or immune activation. Conclusions Cells containing intact, replication-competent proviruses are selectively lost during suppressive ART. Defining the mechanisms involved should inform strategies to accelerate HIV-1 reservoir depletion.