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Record W4406437432 · doi:10.2196/50709

Online Tailored Decision Aid for Maternal Pertussis Vaccination in a Randomized Controlled Trial: Process Evaluation Study

2025· article· en· W4406437432 on OpenAlexvenueno aff
Charlotte Anraad, Pepijn van Empelen, Robert A. C. Ruiter, Hilde van Keulen

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsnot available
FundersZonMw
KeywordsPreprintRandomized controlled trialVaccinationMedicineProcess (computing)Computer scienceVirologyWorld Wide WebInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: To promote informed decision-making and maternal pertussis vaccination (MPV) uptake, we systematically developed an interactive, web-based decision aid for pregnant users. Intervention reach (the percentage of participants in the intervention group who used the intervention), use (how much and how long those participants used the intervention), and acceptability (how positively they evaluated the intervention) are essential for it to be effective and should be reported to assess which intervention components may have been effective. OBJECTIVE: This is a process evaluation aiming to evaluate (1) the reach and (2) the use, and (3) the acceptability of the intervention. METHODS: We analyzed the reach and use of the intervention among participants in the intervention group of a randomized controlled trial (RCT) that assessed the effects of an online tailored decision aid in the form of a web app. Participants were recruited via social media and midwifery clinics and invited via email to use the intervention at 18 weeks of pregnancy. Reach was measured objectively by assessing the number of participants who visited the intervention at least once. Use of the intervention was logged and included time spent on the decision aid, the number of times clicked, pages visited, and answers given in interactive components. Data from the baseline survey (at <18 wk of pregnancy) were used to measure sociodemographics, informed decision-making, MPV uptake, and determinants of uptake. A posttest survey (20-22 weeks of pregnancy) was used to evaluate the acceptability of the decision aid. We report the findings descriptively and assess baseline differences between those who used versus those who did not use the intervention. RESULTS: Of the 586 participants in the intervention group, 463 (79%) reached the home page of the intervention. Intervention reach appeared higher among those in their first pregnancy (8.35% difference, P=.11), those recruited via their midwife rather than via social media (10.56% difference, P=.04), and those who had completed a higher educational level (7.35% difference, P=.06). On average, participants spent 4.25 (SD 4.39) minutes on the decision aid. Most participants used the decision aid once (56.2% of those who reached it, n=260) or twice (26.6%, n=123). The average number of clicks was 27.24 (SD 25.08) and varied widely. Regarding acceptability, participants evaluated the decision aid positively with an overall grade of 8.0 out of 10 (SD 1.01). In total, 38.9% (180/463) of participants who used the intervention indicated that the decision aid helped them with their MPV decision-making. CONCLUSIONS: The reach of the decision aid was successful with 79%, and participants were very positive about the decision aid. The use of the intervention (eg, time spent on the intervention) leaves room for improvement and should be improved to maximize intervention effects.

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)0.040
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.062
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.052
GPT teacher head0.462
Teacher spread0.410 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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