Effectiveness of a Mobile Phone Messaging–Based Message Framing Intervention for Improving Maternal Health Service Uptake and Newborn Care Practice in Rural Jimma Zone, Ethiopia: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Ethiopia has high rates of maternal and neonatal mortality. In 2019 and 2020, the maternal and newborn mortality rates were estimated at 412 per 1,000,000 births and 30 per 10,000 births, respectively. While mobile health interventions to improve maternal and neonatal health management have shown promising results, there are still insufficient scientific studies to assess the effectiveness of mobile phone messaging-based message framing for maternal and newborn health. OBJECTIVE: This research aims to examine the effectiveness of mobile phone messaging-based message framing for improving the use of maternal and newborn health services in the Jimma Zone, Ethiopia. METHODS: A 3-arm cluster-randomized trial design was used to evaluate the effects of mobile phone-based intervention on maternal and newborn health service usage. The trial arms were (1) gain-framed messages (2) loss-framed messages, and (3) usual care. A total of 21 health posts were randomized, and 588 pregnant women who had a gestational age of 16-20 weeks, irrespective of their antenatal care status, were randomly assigned to the trial arms. The intervention consisted of a series of messages dispatched from the date of enrolment until 6-8 months. The control group received existing care without messages. The primary outcomes were maternal health service usage and newborn care practice, while knowledge, attitude, self-efficacy, iron supplementation, and neonatal and maternal morbidity were secondary outcomes. The outcomes will be analyzed using a generalized linear mixed model and the findings will be reported according to the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth) statement for randomized controlled trials. RESULTS: Recruitment of participants was conducted and the baseline survey was administered in March 2023. The intervention was rolled out from May 2023 till December 2023. The end-line assessment was conducted in February 2024. CONCLUSIONS: This trial was carried out to understand how mobile phone-based messaging can improve maternal and newborn health service usage. It provides evidence for policy guidelines around mobile health strategies to improve maternal and newborn health. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR202201753436676; https://tinyurl.com/ykhnpc49. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52395.
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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 | 0.028 | 0.022 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".