SEARCH Study: Text Messages and Automated Phone Reminders for HPV Vaccination in Uganda: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Cervical cancer is currently the leading female cancer in Uganda. Most women are diagnosed with late-stage disease. Human papillomavirus (HPV) vaccination is the single most important primary preventive measure. While research regarding text message vaccine reminder use is strong in the U.S., their use has not yet been demonstrated in a pre-teen and adolescent population in Sub-Saharan Africa or other low- and middle-income countries. OBJECTIVE: The objective of this pilot randomized controlled trial was to assess the impact of vaccine reminders with embedded interactive educational information on timeliness of HPV vaccination in Kampala, Uganda. METHODS: In this randomized-controlled trial conducted in 2022, caregivers of adolescents needing a first or second HPV vaccine dose were recruited from an adolescent clinic and three community health centres in Kampala, Uganda. Families (n=154) were randomized 1:1 into intervention vs. usual care, stratified by dose (initiation, completion), language (English, Luganda) within each site. Intervention caregivers received a series of automated, personalized text messages or automated phone calls, based on family preference. Five messages were sent before the due date including both static and interactive educational information with five follow-up messages for those unvaccinated. Receipt of needed dose by 24 weeks post-enrolment was assessed by chi square, regression and Kaplan-Meier with log rank test. All analyses were intention-to-treat. RESULTS: Overall, 154 caregivers enrolled (51.3% dose 1; 48.7% dose 2), and 64.3% spoke Luganda. Among the intervention arm, 62% requested text message and 38% automated phone reminders. There was no significant difference in requested mode by HPV vaccine dose or language. Intervention adolescents were more likely to receive a needed dose by 24 weeks (65.4% vs. 37.7%; p<0.001; RR 1.7 95% CI 1.2-2.4). There was no interaction by dose or language. There was no difference in vaccination by those requesting text message vs. phone reminders (65.3% vs 63.3%, p=0.86). The number needed to message for one additional vaccination was 3.6 (95% CI 2.3-8.2). Kaplan-Meier curves demonstrated more timely vaccination in the intervention arm (p<0.001). CONCLUSIONS: In this novel trial, text message and automated phone reminders were effective in promoting more timely HPV vaccination in this population. CLINICALTRIAL: ClinicalTrials.gov Identifier: NCT05151367.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".