Centering Youth Voice in the Adaptation of an mHealth Intervention for Young Adults With HIV in South Texas, United States: Human-Centered Design Approach
Bibliographic record
Abstract
Background: Young adults living with HIV are less likely to engage in care and achieve viral suppression, compared to other age groups. Young adults living with HIV also have a high degree of self-efficacy and willingness to adopt novel care modalities, including mobile health (mHealth) interventions. Interventions to increase care engagement could aid young adults living with HIV in overcoming structural and social barriers and leveraging youth assets to improve their health outcomes. Objective: The objective of the paper was to use an assets-based framework, positive youth development, and human-centered design principles to adapt an existing mHealth intervention, PositiveLinks (PL), to support care engagement for 18- to 29-year-olds with HIV. Methods: We conducted a formative evaluation including semistructured interviews with 14 young adults with HIV and focus groups with 26 stakeholders (providers, nurses, case managers, and clinic staff). Interviews covered barriers to care, provider communication, and concerns or suggestions about mHealth interventions. The research team used thematic analysis to review interview transcripts. In the second phase, human-centered design processes informed adaptation of the existing PL platform using data from real-time use suggestions of 3 young adults with HIV. Throughout the formative evaluation and adaptation, a Youth Advisory Board (YAB) provided input. Results: Young adults with HIV and stakeholders identified common elements of an mHealth intervention that would support care engagement including: the convenience of addressing needs through the app, online support groups to support interconnection, short videos or live chats with other young adults with HIV or providers, appointment and medication reminders, and medical information from a trustworthy source. Stakeholders also mentioned the need for youth empowerment. Concerns included worries about confidentiality, unintentional disclosures of status, urgent content in an unmoderated forum, and the impersonality of online platforms. Design suggestions from young adults with HIV included suggestions on appearance, new formatting for usability of the online support group, and prioritization of local content. Based on the feedback received, iterative changes were made to transform PL into Positive Links for Youth (PL4Y). Final votes on adaptations were made by the YAB. The overall appearance of the platform was changed, including logo, color, and font. The online support group was divided into 3 channels which support hashtags and content searches. The "Resources" and "Frequently Asked Questions" sections were condensed and revised to prioritize South Texas-specific content. Conclusions: Our assets-based framework supported young adults with HIV and stakeholder input in the transformation of an mHealth intervention to meet the needs of 18- to 29-year-olds in South Texas. The human-centered design approach allowed young adults with HIV to suggest specific changes to the intervention's design to support usability and acceptability. This adapted version, PL4Y, is now ready for pilot testing in the final phase of this implementation science project.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".