Behavioral intervention grounded in motivational interviewing and behavioral economics shows promise with Black and English-speaking Latino persons living with HIV with unsuppressed HIV viral load in New York City: A mixed methods pilot study
Bibliographic record
Abstract
Introduction: Sustained HIV viral suppression is the ultimate goal of HIV treatment. African American/Black and Latino persons with HIV (PWH) in the United States are less likely than their White peers to achieve and sustain viral suppression. To address these disparities, we developed a "low-touch" behavioral intervention drawing on motivational interviewing and behavioral economics. The intervention had three main components: (1) a motivational interviewing counseling session, (2) 16 weeks of automated text messages and quiz questions about HIV management, where participants earned points by answering quiz questions, and 3) a lottery prize, based on viral suppression status, number of points earned, and chance (max. $275). Materials and methods: The intervention was tested in a pre-test/post-test design. The present pilot study used mixed methods to explore the intervention's feasibility, acceptability, impact, and ways it could be improved. Participants engaged in a baseline assessment, qualitative interview, and two structured follow-up assessments over an 8-month period, and provided laboratory reports to document HIV viral load. We carried out descriptive quantitative analyses. Qualitative data were analyzed using a directed content analysis approach. Data integration was carried out using the joint display method. Findings: = 40) were 50 years old, on average (SD = 11), and approximately half (58%) were male. Close to two-thirds (68%) were African American/Black and 32% were Latino. Participants were diagnosed with HIV 22 years ago on average (SD = 8). The intervention was feasible (e.g., mean number of quiz questions answered = 13/16) and highly acceptable. While not powered to assess efficacy, the proportion with suppressed HIV viral load increased from baseline to follow-up (46% participants at the first, 52% participants at the second follow-up evidenced HIV viral suppression). In qualitative analyses, perspectives included that overall, the intervention was acceptable and useful, it was distinct from other programs, lottery prizes were interesting and appreciated but not sufficient to motivate behavior change, and the structure of lottery prizes was not sufficiently clear. Regarding data integration, qualitative data shed light on and extended quantitative results, and added richness and context. Conclusion: This low-touch intervention approach is sufficiently promising to warrant refinement and study in future research.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".