Evidence map›Paper›PMID 33960950›Full record

ArticleJMIR mHealth and uHealth2021

Postmarketing Safety Monitoring After Influenza Vaccination Using a Mobile Health App: Prospective Longitudinal Feasibility Study.

Minh Tam H Nguyen, Gérard Krause, Brigitte Keller-Stanislawski, Stephan Glöckner, Dirk Mentzer, Jördis J Ott

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Minh Tam H NguyenPhD Programme Epidemiology, Hannover Biomedical Research School, Hannover Medical School, Hannover, Germany.ORCID 0000-0002-8103-7344
Gérard KrausePhD Programme Epidemiology, Hannover Biomedical Research School, Hannover Medical School, Hannover, Germany.ORCID 0000-0003-3328-8808
Brigitte Keller-StanislawskiPaul Ehrlich Institute, Langen, Germany.ORCID 0000-0001-7559-3363
Stephan GlöcknerPhD Programme Epidemiology, Hannover Biomedical Research School, Hannover Medical School, Hannover, Germany.ORCID 0000-0002-7975-9049
Dirk Mentzer *Paul Ehrlich Institute, Langen, Germany.ORCID 0000-0002-6920-0057
Jördis J Ott *PhD Programme Epidemiology, Hannover Biomedical Research School, Hannover Medical School, Hannover, Germany.ORCID 0000-0003-3340-4944

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor the safety monitoring of vaccinations postlicensure, reports of adverse events after immunization (AEFIs) are crucial. New technologies such as digital mobile apps can be used as an active approach to capture these events. We therefore conducted a feasibility study among recipients of the influenza vaccination using an app for assessment of the reporting of AEFIs.

objectiveThe goal of the research was to determine factors influencing adherence to and correct use of a newly developed app for individuals to report AEFI for 3 months using regular reminder functions, to identify determinants of AEFI occurrence and define reported AEFI types.

methodsWe developed the app (SafeVac) and offered it to recipients of the influenza vaccination in 3 occupational settings in fall 2018. In this prospective longitudinal feasibility study, data on AEFIs were generated through SafeVac for 3 months. Using logistic and Cox regression, we assessed associations between app adherence, correct app entry, AEFIs, and sociodemographic parameters.

resultsOf the individuals who logged into SafeVac, 61.4% (207/337) used the app throughout a 3-month period. App use adherence was negatively associated with female sex (odds ratio [OR] 0.47; CI 0.25-0.91) and correct app entry was negatively associated with older age (OR 0.96; CI 0.93-0.99) and lower education (OR 0.31; CI 0.13-0.76). AEFI occurrence was associated with female sex (hazard ratio 1.41; CI 1.01-1.96) and negatively with older age (hazard ratio 0.98; CI 0.97-0.99). The most common AEFIs reported were injection site pain (106/337), pain in extremity (103/337), and fatigue/asthenia (73/337).

conclusionsDigital AEFI reporting was feasible with SafeVac and generated plausible results for this observation period and setting. Studies directly comparing SafeVac with conventional passive reporting schemes could determine whether such digital approaches improve completeness, timeliness, and sensitivity of vaccine vigilance. Further studies should evaluate if these results are transferable to other vaccinations and populations and if introduction of such a tool has an influence on vaccination readiness and therefore vaccine safety.

Indexed as

Influenza, HumanMobile ApplicationsTelemedicineAdverse Drug Reaction Reporting SystemsAgedFeasibility StudiesFemaleHumansProspective StudiesVaccinationactive reportingadverse effectadverse eventadverse event following immunizationdigital healthmHealthmobile healthpharmacovigilancetherapeutic use

Identifiers

PMID33960950
PMCPMC8140379

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Registered trials

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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.