Importantly digital therapeutics do not need to have a siloed focus on SUD treatment . Indeed, we have the opportunity to maximally benefit from what digital technology offers to embrace the co-occurring needs of patients. Digital therapeutics can arguably embrace whatever combination of needs a patient may have. They may focus on, for example, SUD and mental health care, SUD and chronic pain management, SUD and infectious diseases such as HIV and hepatitis, and/or SUD care and care for chronic physical health conditions. Because patients typically do not experience SUD in isolation but often have many care needs and because various comorbidities interact in clinically meaningful ways , digital technologies can transcend the artificial constraints of siloed care models to provide therapeutic resources across many health domains and disease states. Digital health offers great promise for increasing the breadth and potency of models of SUD healthcare delivery. Although applying digital health to the assessment and treatment of SUDs offers great promise, many challenges remain in this work. Indeed, there is tremendous opportunity for expanding research focused on how to best balance the promise of digital health with its potential limitations. For example, we can examine ethical questions such as “how do we best ensure that the benefit of digital tools outweighs potential risks?” And “how do we best ensure protections of patient privacy and sensitive information while still allow for data to be shared in accordance with patient preferences and treatment goals?” Additionally, some sources of digitally-derived data,dry racks for weed although rich and often voluminous, may contain biases and/or methodological challenges .
For example, data collected via EMA questions on mobile devices or via computerized SUD screeners are based on individuals’ self-report and may be subject to reporting bias. Additionally, identifying the optimal source of “ground truth” when making inferences about behavior using mobile sensing data remains a challenge . And best practices in preserving privacy when capturing and analyzing sensitive data need to prioritized . Further, although many populations across the world are increasingly getting access to mobile devices, some populations may have inconsistent access to mobile technology and/or live in communities with limited connectivity . And, patient engagement with digital therapeutic tools is an ongoing challenge . Further, although interest in digital therapeutics among providers and healthcare systems has markedly increased in recent years, challenges remain with implementation and sustainability as well as payment models of digital health tools in many health care contexts . Indeed, as the application of digital health to SUDs continues to expand, it is important that we have a parallel examination of ways in which to support the optimal and pragmatic measurement of patient privacy and ethics and widespread implementation in digital health research. Digital health and data analytics are transforming our world. As we consider the striking unmet SUD treatment needs as well as the variability in quality of SUD care across the national and global landscape, digital technologies promise to extend and enhance our SUD clinical workforce to make on-demand, state of the science SUD treatment a reality worldwide. The incidence of HIV infection remains high among minority men who have sex with men.
Frequent testing for HIV infection can identify new infections early, and it is essential in ending the HIV epidemic. HIV self-testing is an alternative HIV screening method that is commercially available, approved by the Food and Drug Administration, and can reach individuals who have never tested before. It can reach populations at risk, such as Black and Latinx individuals, identify new cases of HIV infection, and lead individuals to seek additional HIV prevention options, such as testing for sexually transmitted infections or pre-exposure prophylaxis. Prevention studies and public health programs have been adopting HIV self-tests and combining them with new technologies, such as smartphone apps or smart devices, to reach populations with high incidence of HIV infection, such as Black and Latinx MSM. Despite multiple efforts, the uptake of HIV testing remains inadequate, especially among individuals at high risk for HIV infection. Thus, optimizing the promotion of HIV testing is important. Due to their extensive popularity, social media sites and dating apps have been used to promote and recruit participants for HIV prevention research studies with high rates of success. According to a recent Centers for Disease Control and Prevention report reviewing HIV self-testing programs, 27 health departments and community organizations used multiple platforms for promotion, mainly social media followed by “traditional” printed media and dating apps . Compared to in-person recruitment, web-based platforms have the capacity to reach a high number of difficult-to-reach populations and individuals at risk , overcoming stigma or other logistic obstacles in a cost-efficient manner.
Indeed, the New York Department of Public Health used advertisements on social media, dating apps, and websites to reach 28,921 users, identifying 17,383 eligible MSM, transgender, and gender nonconforming individuals during its HIV self-testing campaign. Most of the participants were under the age of 35 years and identified as Black or Latinx. In addition, the first wave of this campaign reached 3359 users in only 23 days, distributing 2497 home test kit voucher codes to eligible users. Social media and dating apps have been widely adopted as means of promoting HIV home testing. Although different from dating apps and social media sites, information search sites are commonly used for seeking information on HIV testing and PrEP and could represent a promising outreach avenue. Their use for enrollment and HIV testing promotion has not been evaluated. However, little is known about the relative effectiveness of these different web-based platforms in promoting HIV self-testing. Parker et al conducted a secondary analysis in a study enrolling substance-using sexual and gender minority adolescents and young adults to evaluate the efficacy of their enrollment strategy. The study used multiple methods to enroll participants, including social media platforms , dating apps , internet-based health boards, and venue-based enrollment. They recorded 17,328 visits to the eligibility screener on the landing page, with a 36.2% screener survey completion ratio. Researchers identified 580 participants among those who consented and were eligible to participate , indicating a high recruitment proportion. The majority of their participants were enrolled from Facebook, Instagram, and Grindr. Studies and programs use these platforms based on the experience of previous studies and expert recommendations. Data on the effectiveness of public health promotion through different platforms leading to testing or PrEP are missing. We can only infer the effectiveness of promotion indirectly, as head-to-head comparisons of the effectiveness of the different platforms and sites to reach individuals for public health promotion are missing. This would allow researchers and prevention programs to optimize their budget and strategy. The primary objective of this study was to compare ordering of HIV self-testing kits among users recruited through 3 different types of web-based platforms, including social media, dating apps, and information search sites. Test kit ordering was used as a proxy for analyzing the effectiveness of promoting HIV self-testing on different sites. The secondary goal was to evaluate the association of key moderating variables—substance use, psychological readiness to test,vertical farming pros and cons and perceptions and attitudes related to HIV testing—with the ordering of HIV self-testing kits. In this longitudinal observational cohort study, advertisements promoting free HIV self-testing were placed on three platform types: social media , dating apps , and information search sites .
The advertisements were organized in 2 “waves,” with each wave consisting of 1 social media website, 1 dating app, and 1 information search site. The Wave 1 recruitment stopped early, as Grindr unexpectedly stopped running all self-service platform advertisements due to a change in corporate ownership. We continued with Wave 2 as planned and a relaunched Wave 1 once Grindr access was restored. Before launching each wave, we allocated the same amount of funds for each of the 3 sites and optimized them to run for at least 30 calendar days by dividing the available funds in the prespecified promotional period. However, due to slow enrollment during the COVID-19 pandemic, we extended the second phase of Wave 1 up to 63 days. The advertisement used on social media and dating apps was an image that included a person and text , whereas promotional keywords related to HIV testing and PrEP were selected for information search sites . The same image and keywords were used in all waves. The advertisements were launched in the District of Columbia and 8 states , which were selected based on their high incidence of HIV infection. Upon clicking on the study advertisement, website users landed on the study information page, where they received general information about the study, underwent eligibility screening, and reviewed study procedures. Following electronic informed consent, participants completed the baseline assessment and were emailed a unique electronic code to order their HIV home self-test kit through Orasure.com . Participants also received an electronic coupon for a free telemedicine PrEP visit. Participants were followed up at 14 and 60 days after enrollment. At follow-up, participants were asked about their HIV self-test use and self-test results; depending on their self-test result, they were asked if they visited a PrEP provider and started PrEP, as well as their opinions on PrEP. If they tested positive for HIV antibodies with the home self-test kit, they were asked if they had visited a clinic for confirmatory testing and HIV treatment. In addition, we tracked test kit orders through automated reports, collected anonymous advertisement metrics through the web applications of the platforms, and recorded the costs for each promotion site and wave. The primary outcome was the number of HIV self-test kits ordered per day through each type of internet-based platform during the period in which each wave was operational. As a secondary outcome, we explored the association of reported substance use, stage of change for HIV testing based on the transtheoretical model, attitudes toward HIV testing and treatment, HIV-related stigma, medical mistrust, and opinions about PrEP measures and self-test kit ordering. As an exploratory outcome, we recorded the advertisement metrics of each campaign to measure differences in the reach and cost. Study assessments are described in the protocol. Participants were asked to self-report test kit and PrEP use. We calculated the substance-specific TAPS tool score of each participant. For each substance, a score of 1 was classified as “problem use” , whereas a score of 2 or higher was classified as “high-risk substance use.” We collected participants’ opinions about HIV treatment using a 10-item questionnaire. Each question was presented as a visual analog scale with “strongly disagree” and “strongly agree” anchoring the 2 extremes. We assumed an underlying continuous, linear relationship between the 2 anchors, and data for opinions about HIV treatment are presented as the mean score for each question with its SD. PrEP opinions, barriers, and facilitators were collected using a 5-point Likert scale . Finally, we monitored the performance of the promotional campaigns using the impressions , clicks , click-through rate , and funds spent.Per our primary research question, we intended to determine the statistical difference in the self-test kit ordering rates by platform type using a Poisson regression model; however, due to significant platform-by-wave interactions and widely differing order rates between sites within the same platform, it was not appropriate to combine or pool sites across the same platform for statistical evaluation of the platform difference. Therefore, we compared the specific platform differences in terms of the order rates within the same wave. We conducted pairwise comparison for all 6 sites from the 2 waves with multiple testing adjustments using the Hochberg method. Demographic and baseline characteristics were presented using summary statistics. Continuous variables were summarized using percentiles , and means with their SDs. Categorical variables were summarized with frequencies and percentages. To assess differences in the measures between participants who ordered a test kit and those who did not order a test kit, we used the Student t test for continuous variables, Fisher exact test for categorical variables, and Wilcoxon rank sum test for Likert responses. Data analysis was carried out using Statistical Analysis Software . In this study of MSM at risk for HIV infection, we investigated the effectiveness of promoting free home HIV self-test kits on various internet platforms. More than half of the participants ordered a self-test kit, although only a small proportion of HIV-negative individuals reported seeking PrEP services. Our results showed that dating apps were the most efficient platform to distribute HIV self-test kits to men at high risk for HIV infection.