Using Values Affirmation to Reduce the Effects of Stereotype Threat on Hypertension Disparities: Protocol for the Multicenter Randomized Hypertension and Values (HYVALUE) Trial
Bibliographic record
Abstract
BACKGROUND: Medication nonadherence is a significant, modifiable contributor to uncontrolled hypertension. Stereotype threat may contribute to racial disparities in adherence by hindering a patient's ability to actively engage during a clinical encounter, resulting in reduced activation to adhere to prescribed therapies. OBJECTIVE: The Hypertension and Values (HYVALUE) trial aims to examine whether a values-affirmation intervention improves medication adherence (primary outcome) by targeting racial stereotype threat. METHODS: The HYVALUE trial is a patient-level, blinded randomized controlled trial comparing a brief values-affirmation writing exercise with a control writing exercise among black and white patients with uncontrolled hypertension. We are recruiting patients from 3 large health systems in the United States. The primary outcome is patients' adherence to antihypertensive medications, with secondary outcomes of systolic and diastolic blood pressure over time, time for which blood pressure is under control, and treatment intensification. We are comparing the effects of the intervention among blacks and whites, exploring possible moderators (ie, patients' prior experiences of discrimination and clinician racial bias) and mediators (ie, patient activation) of intervention effects on outcomes. RESULTS: This study was funded by the National Heart, Lung, and Blood Institute. Enrollment and follow-up are ongoing and data analysis is expected to begin in late 2020. Planned enrollment is 1130 patients. On the basis of evidence supporting the effectiveness of values affirmation in educational settings and our pilot work demonstrating improved patient-clinician communication, we hypothesize that values affirmation disrupts the negative effects of stereotype threat on the clinical interaction and can reduce racial disparities in medication adherence and subsequent health outcomes. CONCLUSIONS: The HYVALUE study moves beyond documentation of race-based health disparities toward testing an intervention. We focus on a medical condition-hypertension, which is arguably the greatest contributor to mortality disparities for black patients. If successful, this study will be the first to provide evidence for a low-resource intervention that has the potential to substantially reduce health care disparities across a wide range of health care conditions and populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT03028597; https://clinicaltrials.gov/ct2/show/NCT03028597 (Archived by WebCite at http://www.webcitation.org/72vcZMzAB). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12498.
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 | 0.030 | 0.038 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.010 |
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".