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Electronically Delivered Nudges to Increase Influenza Vaccination Uptake in Older Adults With Diabetes

2023· article· en· W4389992555 on OpenAlexaff
Mats Christian Højbjerg Lassen, Niklas Dyrby Johansen, Muthiah Vaduganathan, Ankeet S. Bhatt, Simin Gharib Lee, Daniel Modin, Brian Claggett, Erica Dueger, Sandrine Samson, Matthew M. Loiacono, Michael Fralick, Lars Køber, Scott D. Solomon, Pradeesh Sivapalan, Jens‐Ulrik Stæhr Jensen, Cyril Jean‐Marie Martel, Tyra Grove Krause, Tor Biering‐Sørensen

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsSinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsNudge theoryVaccinationDiabetes mellitusMedicineGerontologyPsychologyVirologySocial psychologyEndocrinology

Abstract

fetched live from OpenAlex

Importance: Influenza vaccination is associated with a reduced risk of mortality in patients with diabetes, but vaccination rates remain suboptimal. Objective: To assess the effect of electronic nudges on influenza vaccination uptake according to diabetes status. Design, Setting, and Participants: The NUDGE-FLU (Nationwide Utilization of Danish Government Electronic Letter System for Increasing Influenza Vaccine Uptake) trial was a nationwide clinical trial of Danish citizens 65 years or older that randomized participants at the household level to usual care or 9 different electronic nudge letters during the 2022 to 2023 influenza season. End of follow-up was January 1, 2023. This secondary analysis of the NUDGE-FLU trial was performed from May to July 2023. Intervention: Nine different electronic nudge letters designed to boost influenza vaccination were sent in September to October 2022. Effect modification by diabetes status was assessed in a pooled analysis of all intervention arms vs usual care and for individual letters. Main Outcomes and Measures: The primary end point was receipt of a seasonal influenza vaccine. Results: The trial included 964 870 participants (51.5% female; mean [SD] age, 73.8 [6.3] years); 123 974 had diabetes. During follow-up, 83.5% with diabetes vs 80.2% without diabetes received a vaccine (P < .001). In the pooled analysis, nudges improved vaccination uptake in participants without diabetes (80.4% vs 80.0%; difference, 0.37 percentage points; 99.55% CI, 0.08 to 0.66), whereas there was no evidence of effect in those with diabetes (83.4% vs 83.6%; difference, -0.19 percentage points; 99.55% CI, -0.89 to 0.51) (P = .02 for interaction). In the main results of NUDGE-FLU, 2 of the 9 behaviorally designed letters (cardiovascular benefits letter and a repeated letter) significantly increased uptake of influenza vaccination vs usual care; these benefits similarly appeared attenuated in participants with diabetes (cardiovascular gain letter: 83.7% vs 83.6%; difference, 0.04 percentage points; 99.55% CI, -1.52 to 1.60; repeated letter: 83.5% vs 83.6%; difference, -0.15 percentage points; 99.55% CI, -1.71 to 1.41) vs those without diabetes (cardiovascular gain letter: 81.1% vs 80.0%; difference, 1.06 percentage points; 99.55% CI, 0.42 to 1.70; repeated letter: 80.9% vs 80.0%; difference, 0.87 percentage points; 99.55% CI, 0.22 to 1.52) (P = .07 for interaction). Conclusions and Relevance: In this exploratory subgroup analysis, electronic nudges improved influenza vaccination uptake in persons without diabetes, whereas there was no evidence of an effect in persons with diabetes. Trials are needed to investigate the effect of digital nudges specifically tailored to individuals with diabetes. Trial Registration: ClinicalTrials.gov Identifier: NCT05542004.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.032
GPT teacher head0.347
Teacher spread0.315 · 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 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

Citations13
Published2023
Admission routes1
Has abstractyes

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