Improving adoption and acceptability of digital health interventions for HIV disease management: a qualitative study

Developing and testing a web-based platform for antiretroviral therapy (ART) adherence support among adolescents and young adults (AYA) living with HIV

Objective

Describe the development and testing of a web-based platform for antiretroviral treatment (ART) adherence support among HIV+ adolescents and young adults (AYA) in a randomized controlled trial (RCT).

Methods

A seven-member multi-disciplinary team operationalized the flat, password protected, web-based platform. Manualized protocols guided the objectives and content for each of the eight web-based sessions. Team members evaluated usability and content validity. Client satisfaction and perceived ease of use was evaluated with the first ten HIV+ AYA participants.

Results

The web-based platform was developed, evaluated, refined, implemented and pilot tested between September 2020 to April 2022. Usability was rated as high; the evaluation of content validity showed an excellent fit between session content and objectives. HIV+ AYA participants (mean age = 24.2 years) were satisfied with the quality, type, and amount of support/education received, and found the platform easy to use, operate, and navigate. Average time spent per session was 6.5 min.

Conclusion

Findings support the usability, validity, acceptability, and feasibility of this web-based platform for ART adherence support among HIV+ AYA.

Innovation

Our research and findings are responsive to research gaps and the need for transparency in the methodological development and testing of web-based control arms for ART adherence support among HIV+ AYA.

Barriers and Facilitators to the Uptake of Online and Telephone Services Targeting Health Risk Behaviours among Vocational Education Students: A Qualitative Study

Uptake of online and telephone services targeting health behaviours is low among vocational education students and barriers and facilitators are unknown. This study aimed to explore barriers and facilitators to uptake of online and telephone services for smoking, nutrition, alcohol, and physical activity (SNAP) risk behaviours via semi-structured individual telephone interviews with fifteen vocational education students. Two authors independently completed thematic analysis, classified themes according to the COM-B (Capability, Opportunity, Motivation, Behaviour) framework, and discussed disagreements until consensus was reached. Facilitators to uptake of online (e.g., desire to learn something new, cost-free, accessible) and telephone services (e.g., prefer to talk to provider, complements online support) primarily related to capability and opportunity. For telephone services, difficulty understanding accent/language was a capability-related barrier. Opportunity-related barriers for online and telephone services were preference for face-to-face interaction and lack of time, while preference for apps/online programs was a barrier for telephone services. For online and telephone services, not wanting to change SNAP behaviours was a motivation-related barrier and being able to change SNAP risk behaviours themselves was a motivation-related barrier for online services. Barriers and facilitators to online and telephone services are relevant for designing interventions vocational education students are more likely to use.

Patient-generated data in the management of HIV: a scoping review

OBJECTIVES

Patient-generated data (PGData) are an emergent research area and may improve HIV care. The objectives of this scoping review were to synthesise, evaluate and make recommendations based on the available literature regarding PGData use in HIV care.

DESIGN

Scoping review.

DATA SOURCES

Embase, Medline, CINAHL Plus, Web of Science, Scopus, PsycINFO and Emcare databases.

ELIGIBILITY CRITERIA

Studies involving PGData use within HIV care for people living with HIV and/or healthcare professionals (HCPs) published before February 2021.

DATA EXTRACTION AND SYNTHESIS

Data were extracted using a table and the Mixed Methods Appraisal Tool was used to assess empirical rigour. We used thematic analysis to evaluate content.

RESULTS

11 articles met the eligibility criteria. Studies were observational, predominantly concerned hypothetical or novel digital platforms, mainly conducted in high-income settings, and had small sample sizes (range=10-160). There were multiple definitions of PGData. In the majority of studies (n=9), participants were people living with HIV, with a few studies including HCPs, informatics specialists or mixed participant groups. Participants living with HIV were aged 23-78 years, mostly men, of diverse ethnicities, and had low educational, health literacy and income levels.We identified four key themes: (1) Perceptions of PGData and associated digital platforms; (2) Opportunities; (3) Anticipated barriers and (4) Potential impact on patient-HCP relationships.

CONCLUSIONS

Use of PGData within HIV care warrants further study, especially with regard to digital inequalities, data privacy and security. There is a need for longitudinal data on use within HIV in a variety of settings with a broad range of users, including impact on clinical outcomes. This will allow greater understanding of the role of PGData use in improving the health and well-being of people living with HIV, which is increasingly pertinent as digital healthcare becomes more widespread as a result of COVID-19.

Using Machine Learning to Predict Young People's Internet Health and Social Service Information Seeking

Machine learning creates new opportunities to design digital health interventions for youth at risk for acquiring HIV (YARH), capitalizing on YARH's health information seeking on the internet. To date, researchers have focused on descriptive analyses that associate individual factors with health-seeking behaviors, without estimating of the strength of these predictive models. We developed predictive models by applying machine learning methods (i.e., elastic net and lasso regression models) to YARH's self-reports of internet use. The YARH were aged 14-24 years old (N = 1287) from Los Angeles and New Orleans. Models were fit to three binary indicators of YARH's lifetime internet searches for general health, sexual and reproductive health (SRH), and social service information. YARH responses regarding internet health information seeking were fed into machine learning models with potential predictor variables based on findings from previous research, including sociodemographic characteristics, sexual and gender minority identity, healthcare access and engagement, sexual behavior, substance use, and mental health. About half of the YARH reported seeking general health and SRH information and 26% sought social service information. Areas under the ROC curve (≥ .75) indicated strong predictive models and results were consistent with the existing literature. For example, higher education and sexual minority identification was associated with seeking general health, SRH, and social service information. New findings also emerged. Cisgender identity versus transgender and non-binary identities was associated with lower odds of general health, SRH, and social service information seeking. Experiencing intimate partner violence was associated with higher odds of seeking general health, SRH, and social service information. Findings demonstrate the ability to develop predictive models to inform targeted health information dissemination strategies but underscore the need to better understand health disparities that can be operationalized as predictors in machine learning algorithms.

Crowdsourcing to design a marketing package to promote a WHO digital mental health intervention among Chinese young adults

BACKGROUND

Digital mental health is an emerging field that can leverage technology and mobile apps to deliver mental health treatment to populations in areas with limited mental health services. Despite widespread availability of these apps, uptake remains low. Enhanced marketing is necessary to increase public engagement. There is growing recognition that mental health intervention beneficiaries should be engaged in all phases of treatment development, adaptation, and delivery. Crowdsourcing - consulting the public to solve problems and sharing the solutions - can foster community-informed ideas for public health, but has yet been applied to digital mental health marketing.

OBJECTIVE

With the goal of engaging potential intervention beneficiaries in digital mental health dissemination, the current project implemented a digital mental health crowdsourcing designathon for Chinese college students in Macao SAR, China and evaluated the feasibility of the contest and the products. The contest asked participants to design marketing packages for Step-by-Step, a scalable WHO digital mental health intervention focusing on depression.

METHODS

Designathon participants, recruited from a global health class, were sorted into teams with balanced areas of expertise. Two judging panels - one of experts in relevant fields and another of Chinese college students - evaluated the marketing packages and selected finalists. The designathon was held in-person over four days and involved debriefing, workshops, a contest, and an awards ceremony. A parallel mixed-methods approach was applied, including qualitative feedback from judges and participants alongside quantitative data on participant satisfaction and depressive symptoms to enrich our understanding of the event. Additionally, based on judges' feedback given to participants, the communication packages of the contest were ranked.

RESULTS

49 participants (8 teams of 6-7 members each) were involved in the designathon. Using a cutoff score of 10 on the Patient Health Questionnaire-9 (PHQ-9), 11.4% of participants had moderate or higher depressive symptoms. All teams successfully produced complete digital mental health marketing packages. Four finalists' packages were selected quantitatively with judges' scores and the top finalist's package was described by judges' comments as simple, thoughtful, and appealing, although not informative enough. Participants were overall satisfied with the designathon, but some mentioned that time was insufficient and that organization/instruction clarity could have been improved.

CONCLUSIONS

The designathon is a novel, feasible strategy to collect crowd input for the dissemination of a mental health intervention. Compared with traditional communication strategies, this bottom-up approach included and engaged potential intervention beneficiaries to take an active role in creating digital mental health marketing communication. Future contests should allow participants more time and reconsider aspects of event organization.