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Record W4408592526 · doi:10.2196/51524

Targeted Behavior Change Communication Using a Mobile Health Platform to Increase Uptake of Long-Lasting Insecticidal Nets Among Pregnant Women in Tanzania: Hati Salama “Secure Voucher” Study Cluster Randomized Controlled Trial

2025· article· en· W4408592526 on OpenAlexaff
Trinity Vey, Eleonora Kinnicutt, Andrew G. Day, Nicola West, Jessica Sleeth, Kenneth Bernard Nchimbi, Karen Yeates

Bibliographic record

VenueJournal of Medical Internet Research · 2025
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsVoucherTanzaniaRandomized controlled trialCluster (spacecraft)MedicineEnvironmental healthComputer scienceSocioeconomicsWorld Wide WebEconomicsComputer network

Abstract

fetched live from OpenAlex

BACKGROUND: Malaria remains a significant cause of maternal and neonate morbidity and mortality in sub-Saharan Africa. Long-lasting insecticidal nets (LLINs) represent an important component of malaria prevention and can decrease the adverse health outcomes associated with malaria infection during pregnancy. Voucher programs have been successfully implemented for a variety of initiatives across sub-Saharan Africa, including the distribution of subsidized LLINs in Tanzania. However, mobile messaging for behavior change communication (BCC), in combination with an e-voucher program, has not been explored for malaria prevention. OBJECTIVE: This study aimed to assess the efficacy of mobile messaging in increasing the redemption of e-vouchers for LLINs for pregnant women and adolescents in Tanzania. METHODS: This study was a blinded, 2-arm, cluster randomized controlled trial implemented in 100 antenatal health facilities in Tanzania (both urban and rural settings), with 50 clusters in both intervention and control groups. Clusters were antenatal clinics with e-voucher capabilities, with randomization stratified such that 25 urban and 25 rural clinics were randomized to each arm. Participants were pregnant females aged 13 years or older. Participants in both intervention and control groups were issued e-vouchers on their mobile phones that could be redeemed for LLINs at registered retailers within a 14-day redemption period. Participants in the intervention group received targeted BCC messages about the importance of malaria prevention and LLIN use during pregnancy, while participants in the control group did not receive BCC messages. Analyses were by intention to treat. The primary outcome was the redemption rate of e-vouchers for LLINs from retailers. Outcome measures pertain to clinic sites and individual participant-level data. RESULTS: The study enrolled 5449 participants; the analysis included 2708 participants in the intervention arm and 2740 participants in the control arm (49 clusters in each group analyzed). There was no significant difference in the raw redemption rate of e-vouchers between pregnant participants in the intervention group (70%) and the control group (67%). Younger participants were less likely to redeem e-vouchers. CONCLUSIONS: The use of a BCC mobile messaging intervention did not result in a significant increase in LLIN uptake for pregnant individuals. However, the study shows that e-voucher distribution through nurses in antenatal clinics in partnership with local retailers is feasible on a large scale. Consideration of women and adolescents who are low-income and live in rural areas is needed for future interventions leveraging e-vouchers or mHealth technology in low-resource settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT02561624; https://clinicaltrials.gov/ct2/show/NCT02561624.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.071
GPT teacher head0.431
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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