Effect of Mobile Phone Text Message Reminders on Routine Immunization Uptake in Pakistan: Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Improved routine immunization (RI) coverage is recommended as the priority public health strategy to decrease vaccine-preventable diseases and eradicate polio in Pakistan and worldwide. OBJECTIVE The objective of this study was to ascertain whether customized, automated, one-way text messaging (short message service, SMS) reminders delivered to caregivers via mobile phones when a child is due for an RI visit can improve vaccination uptake and timelines in Pakistan. METHODS This was a randomized controlled trial, conducted in an urban squatter settlement area of Karachi, Pakistan. Infants less than 2 weeks of age with at least one family member who had a valid mobile phone connection and was comfortable receiving and reading SMS text messages were included. Participants were randomized to the intervention (standard care + one-way SMS reminder) or control (standard care) groups. The primary outcome was to compare the proportion of children immunized up to date at 18 weeks of age. Vaccine given at 6, 10, and 14 weeks schedule includes DPT-Hep-B-Hib vaccine (ie, diphtheria, pertussis, and tetanus; hepatitis B; and Haemophilus influenza type b) and oral poliovirus vaccine (OPV). Data were analyzed using chi-square tests of independence and tested for both per protocol (PP) and intention-to-treat (ITT) analyses. RESULTS Out of those approached, 84.3% (300/356) of the participants were eligible for enrollment and 94.1% (318/338) of the participants had a working mobile phone. Only children in the PP analyses, who received an SMS reminder for vaccine uptake at 6 weeks visit, showed a statistically significant difference (96.0%, 86/90 vs 86.4%, 102/118; P=.03).The immunization coverage was consistently higher in the intervention group according to ITT analyses at the 6 weeks scheduled visit (76.0% vs 71.3%, P=.36). The 10 weeks scheduled visit (58.7% vs 52.7%, P=.30) and the 14 weeks scheduled visit (31.3% vs 26.0%, P=.31), however, were not statistically significant. CONCLUSIONS Automated simple one-way SMS reminders in local languages might be feasible for improving routine vaccination coverage. Whether one-way SMS reminders alone can have a strong impact on parental attitudes and behavior for improvement of RI coverage and timeliness needs to be further evaluated by better-powered studies and by comparing different types and content of text messages in low-and middle-income countries (LMICs). CLINICALTRIAL ClinicalTrials.gov NCT01859546; https://clinicaltrials.gov/ct2/show/NCT01859546 (Archived by WebCite at http://www.webcitation.org/6xFr57AOc)
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".