Trial reportJournal of general internal medicine2024
"How" Versus "Why" Messaging to Increase Uptake of Booster Vaccination Against COVID-19: Results of a Pragmatic Randomized Trial.
Trial report in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04871776 (Use of Construal Level Theory to Inform Messaging to Increase Vaccination Against COVID-19), which is not on this map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Use of Construal Level Theory to Inform Messaging to Increase Vaccination Against COVID-19
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- A scoping review of studies on secure messaging through patient portals: persistent challenges and potential solutions.npj health systems · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundMessages aimed at increasing uptake of vaccines have been modestly successful, perhaps in part because they often focus on why individuals should receive a vaccine. Construal Level Theory posits that messages emphasizing "how" to get a vaccine may be more effective at encouraging vaccination than emphasizing "why." This message framing may be particularly important for COVID-19 booster acceptance.
objectiveTo determine if pre-visit patient portal messages designed using Construal Level Theory increase rates of COVID-19 booster vaccination. DESIGN AND
interventionsThis 3-arm randomized trial was conducted across three large, diverse primary care clinics in Massachusetts between February and May 2022, testing the impact of "how" versus "why" framed pre-visit messages versus no messages ("usual care"). Messages were sent by patient portal two business days before a visit.
participantsAdults with upcoming primary care visits who had electronic health record evidence of receiving their initial COVID-19 vaccination series but not a booster dose. MAIN MEASURES: Receipt of a COVID-19 booster vaccination after the message was sent through the visit date (primary outcome) or 6 weeks (secondary outcome). KEY
resultsA total of 3665 patients were randomized (mean age: 53.5 years (SD: 17.3), 59% female, 65.2% White, 26.6% Hispanic), with 1249 to "how" 1199 to "why," and 1217 to usual care arms. Except for clinic and preferred language, characteristics were well balanced across arms. Rates of COVID-19 booster were 13.6% (usual care), 11.7% ("how") (odds ratio (OR) "how" vs usual care: 0.87, 95%CI: 0.67-1.14), and 13.7% ("why") ("why" vs usual care: OR: 1.01, 95%CI: 0.81-1.28). At 6 weeks, "why" outperformed "how" for vaccination (OR: 1.26, 95%CI: 1.06-1.49), with no difference versus usual care.
conclusionsWe found no differences on visit booster receipt after single pre-visit portal messages designed using Construal Level Theory. Further studies to identify effective messaging interventions are needed, especially as additional doses are recommended. CLINICAL
trial registrationThis trial is registered at clinicaltrials.gov, ID: NCT04871776 . Initial release occurred 04/30/2021.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.