Developing a Tablet-Based Self-Persuasion Intervention Promoting Adolescent HPV Vaccination: Protocol for a Three-Stage Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus (HPV)-related cancers are a significant burden on the US health care system that can be prevented through adolescent HPV vaccination. Despite guidelines recommending vaccination, coverage among US adolescents is suboptimal particularly among underserved patients (uninsured, low income, racial, and ethnic minorities) seen in safety-net health care settings. Many parents are ambivalent about the vaccine and delay making a decision or talking with a provider about it. Self-persuasion-generating one's own arguments for a health behavior-may be particularly effective for parents who are undecided or not motivated to make a vaccine decision. OBJECTIVE: Through a 3-stage mixed-methods protocol, we will identify an optimal and feasible self-persuasion intervention strategy to promote adolescent HPV vaccination in safety-net clinics. METHODS: In Stage 1, we will define content for a tablet-based self-persuasion app by characterizing (1) parents' self-generated arguments through cognitive interviews conducted with parents (n=50) of patients and (2) parent-provider HPV vaccine discussions through audio recordings of clinic visits (n=50). In Stage 2, we will compare the effects of the four self-persuasion intervention conditions that vary by cognitive processing level (parents verbalize vs listen to arguments) and choice of argument topics (parents choose vs are assigned topics) on parental vaccine intentions in a 2 × 2 factorial design randomized controlled trial (n=160). This proof-of-concept trial design will identify which intervention condition is optimal by quantitatively examining basic self-persuasion mechanisms (cognitive processing and choice) and qualitatively exploring parent experiences with intervention tasks. In Stage 3, we will conduct a pilot trial (n=90) in the safety-net clinics to assess feasibility of the optimal intervention condition identified in Stage 2. We will also assess its impact on parent-provider discussions. RESULTS: This paper describes the study protocol and activities to date. Currently, we have developed the initial prototype of the tablet app for English- and Spanish-speaking populations, and completed Stage 1 data collection. CONCLUSIONS: Our systematic collaboration between basic and applied behavioral scientists accelerates translation of promising basic psychological research into innovative interventions suitable for underserved, safety-net populations. At project's end, we plan to have a feasible and acceptable self-persuasion intervention that can affect key cancer disparities in the United States through prevention of HPV-related cancers. TRIAL REGISTRATION: ClinicalTrials.gov http://clinicaltrials.gov/ct2/show/NCT02537756 and http://clinicaltrials.gov/ct2/show/NCT02535845 (Archived by WebCite at http://www.webcitation.org/6e5XcOGXz and http://www.webcitation.org/6e5XfHoic, respectively).
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 | 0.031 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.071 | 0.012 |
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".