Implementation of a Mobile Health Approach to a Long-Lasting Insecticidal Net Uptake Intervention for Malaria Prevention Among Pregnant Women in Tanzania: Process Evaluation of the Hati Salama (HASA) Randomized Controlled Trial Study
Bibliographic record
Abstract
BACKGROUND: Malaria infection is associated with many adverse outcomes for pregnant women and neonates, yet pregnant women in East and Southern Africa remain frequently exposed to malaria. Long-lasting insecticidal nets (LLINs) can help prevent malarial infections and the associated adverse events. The Hati Salama (HASA) study was a cluster-randomized controlled trial implemented in 100 antenatal health facilities in urban and rural settings of Tanzania that provided pregnant women in both intervention and control groups with e-vouchers to redeem for LLINs for malaria prevention. The intervention group received behavior change communication mobile messages across a 14-day period while the e-voucher was active, and no significant difference between the rates of e-voucher redemption was found across the two groups. OBJECTIVE: This study was a process evaluation of the HASA randomized controlled trial to determine barriers and facilitators to e-voucher reception and LLIN acquisition for pregnant women enrolled in the trial, as well as challenges and lessons learned by nurses who worked at the antenatal health facilities supporting the trial. METHODS: Following the e-voucher's expiration at 14 days, voluntary phone follow-up surveys were conducted for nurses who supported the trial, as well as participants in both intervention and control groups of the trial who did not redeem their e-vouchers. Survey questions asked nurses about workflow, training sessions, network connectivity, proxy phone use, and more. Surveys asked participants about reasons for not redeeming e-vouchers. Both surveys provided lists of preset answers to questions, as well as the option to provide open-ended responses. Nurses and trial participants were contacted between January and June 2016 on up to three occasions. RESULTS: While nurses who supported the HASA trial seemed to recognize the value of the program in their communities, some barriers identified by nurses included network connectivity, workload increase, inadequate training and on-the-ground support, and difficulty following the workflow. Several barriers identified by trial participants included personal obligations preventing them from redeeming the e-voucher on time, network connectivity issues, losing the e-voucher number, no stock of LLINs at retailers when attended, inadequate explanation of where or how to redeem the e-voucher, or not receiving an SMS text message with the e-voucher number promptly or at all. CONCLUSIONS: Large-scale e-voucher platforms for health-related commodity interventions, such as LLIN distribution in sub-Saharan Africa, are feasible, but challenges, including network connectivity, must be addressed. Nurses identified issues to be considered in a future scale-up, such that the number of nurses trained should be increased and the e-voucher issuance workflow should be simplified. To address some of the key barriers impacting e-voucher redemption for trial participants, the network of retailers could be expanded and the e-voucher expiration period should be extended. 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 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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".