Evaluating a Mobile Phone–Delivered Text Message Reminder Intervention to Reduce Infant Vaccination Dropout in Arua, Uganda: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Globally, suboptimal vaccine coverage is a public health concern. According to Uganda's 2016 Demographic and Health Survey, only 49% of 12- to 23-month-old children received all recommended vaccinations by 12 months of age. Innovative ways are needed to increase coverage, reduce dropout, and increase awareness among caregivers to bring children for timely vaccination. OBJECTIVE: This study evaluates a personalized, automated caregiver mobile phone-delivered text message reminder intervention to reduce the proportion of children who start but do not complete the vaccination series for children aged 12 months and younger in select health facilities in Arua district. METHODS: A two-arm, multicenter, parallel group randomized controlled trial was conducted in four health facilities providing vaccination services in and around the town of Arua. Caregivers of children between 6 weeks and 6 months of age at the time of their first dose of pentavalent vaccine (Penta1; containing diphtheria, tetanus, pertussis, hepatitis B, and Haemophilus influenzae type b antigens) were recruited and interviewed. All participants received the standard of care, defined as the health worker providing child vaccination home-based records to caregivers as available and providing verbal instruction of when to return for the next visit. At the end of each day, caregivers and their children were randomized by computer either to receive or not receive personalized, automated text message reminders for their subsequent vaccination visits according to the national schedule. Text message reminders for Penta2 were sent 2 days before, on the day of, and 2 days after the scheduled vaccination visit. Reminders for Penta3 and the measles-containing vaccine were sent on the scheduled day of vaccination and 5 and 7 days after the scheduled day. Study personnel conducted postintervention follow-up interviews with participants at the health facilities during the children's measles-containing vaccine visit. In addition, focus group discussions were conducted to assess caregiver acceptability of the intervention, economic data were collected to evaluate the incremental costs and cost-effectiveness of the intervention, and health facility record review forms were completed to capture service delivery process indicators. RESULTS: Of the 3485 screened participants, 1961 were enrolled from a sample size of 1962. Enrollment concluded in August 2016. Follow-up interviews of study participants, including data extraction from the children's vaccination cards, data extraction from the health facility immunization registers, completion of the health facility record review forms, and focus group discussions were completed by December 2017. The results are expected to be released in 2021. CONCLUSIONS: Prompting health-seeking behavior with reminders has been shown to improve health intervention uptake. Mobile phone ownership continues to grow in Uganda, so their use in vaccination interventions such as this study is logical and should be evaluated with scientifically rigorous study designs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04177485; https://clinicaltrials.gov/ct2/show/NCT04177485. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17262.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.006 |
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".