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Record W2951602239 · doi:10.4081/jphia.2019.1032

Providing mothers with mobile phone message reminders increases childhood immunisation and vitamin A supplementation coverage in Côte d’Ivoire: a randomised controlled trial

2019· article· en· W2951602239 on OpenAlexaff
Romance Dissieka, Marissa Soohoo, Amynah Janmohamed, David Doledec

Bibliographic record

VenueJournal of Public Health in Africa · 2019
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsPublic Health OntarioToronto Public Health
Fundersnot available
KeywordsMedicineAttendanceRandomized controlled trialText messageIntervention (counseling)PediatricsFamily medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

We conducted a randomized controlled trial to assess the effect of providing mothers with mobile voice or text (SMS) reminder messages on health facility attendance at five infant immunization and vitamin A supplementation (VAS) visits. The study was conducted at 29 health facilities in Korhogo district. Mothers were randomized to receive a voice or text reminder message two days prior to each scheduled visit and two additional reminders for missed doses (n=798; intervention group), or no phone reminder messages (n=798; control group). Infants in the intervention group were 2.85 (95% CI: 1.85-4.37), 2.80 (95% CI: 1.88-4.17), 2.68 (95% CI: 1.84-3.91), and 4.52 (95% CI: 2.84-7.20) times more likely to receive pentavalent 1-3 and MMR/yellow fever doses, respectively, and 5.67 (95% CI: 3.48-9.23) times more likely to receive VAS, as compared to the control group. In the reminder group, 58.3% of infants completed all five visits, compared to 35.7% in the control group (P<0.001). Providing mothers mobile phone message reminders is a potentially effective strategy for improving immunization and VAS coverage in Cote d'Ivoire.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.093
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.282
Teacher spread0.266 · 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 teacher head, 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".

Quick stats

Citations30
Published2019
Admission routes1
Has abstractyes

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