Evidence map›Paper›PMID 25490045›Full record

ArticlePloS one2014

Association between recruitment methods and attrition in Internet-based studies.

Paolo Bajardi, Daniela Paolotti, Alessandro Vespignani, Ken Eames, Sebastian Funk, W John Edmunds, Clement Turbelin, Marion Debin, Vittoria Colizza, Ronald Smallenburg and 9 more

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

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

  1. Pooled it
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  11. The PRIDE Study: Evaluation of online methods of data collection.Paediatric and perinatal epidemiology · 2020
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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

19 authors.

Paolo BajardiGECO- Computational Epidemiology Group, Department of Veterinary Sciences, University of Torino, Torino, Italy; ISI Foundation, Turin, Italy.
Daniela PaolottiISI Foundation, Turin, Italy.
Alessandro VespignaniISI Foundation, Turin, Italy; Laboratory for the Modeling of Biological and Socio-technical Systems Northeastern University, Boston, Massachusetts, United States of America; Institute for Quantitative Social Sciences at Harvard University, Cambridge, Massachusetts, United States of America.
Ken EamesLondon School of Hygiene and Tropical Medicine, London, United Kingdom.
Sebastian FunkLondon School of Hygiene and Tropical Medicine, London, United Kingdom.
W John EdmundsLondon School of Hygiene and Tropical Medicine, London, United Kingdom.
Clement TurbelinInstitut National de la Santé et de la Recherche Médicale, UMR-S 707, Paris, France; Université Pierre et Marie Curie-Paris 6, UMR-S 707, Paris, France.
Marion DebinInstitut National de la Santé et de la Recherche Médicale, UMR-S 707, Paris, France; Université Pierre et Marie Curie-Paris 6, UMR-S 707, Paris, France.
Vittoria ColizzaISI Foundation, Turin, Italy; Institut National de la Santé et de la Recherche Médicale, UMR-S 707, Paris, France; Université Pierre et Marie Curie-Paris 6, UMR-S 707, Paris, France.
Ronald SmallenburgAquisto-Inter BV, Amsterdam, The Netherlands.
Carl KoppeschaarAquisto-Inter BV, Amsterdam, The Netherlands.
Ana O FrancoInstituto Gulbenkian de Cincia, Oeiras, Portugal.
Vitor FaustinoInstituto Gulbenkian de Cincia, Oeiras, Portugal.
AnnaSara CarnahanPublic Health Agency of Sweden, Stockholm, Sweden.
Moa RehnPublic Health Agency of Sweden, Stockholm, Sweden.
Franco MerlettiDepartment of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy.
Jeroen DouwesCentre for Public Health Research, Massey University, Wellington, New Zealand.
Ridvan FirestoneCentre for Public Health Research, Massey University, Wellington, New Zealand.
Lorenzo RichiardiDepartment of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy.

Funding

Medical Research Council MR/K021680/1
6 · The paper itself

Abstract

Internet-based systems for epidemiological studies have advantages over traditional approaches as they can potentially recruit and monitor a wider range of individuals in a relatively inexpensive fashion. We studied the association between communication strategies used for recruitment (offline, online, face-to-face) and follow-up participation in nine Internet-based cohorts: the Influenzanet network of platforms for influenza surveillance which includes seven cohorts in seven different European countries, the Italian birth cohort Ninfea and the New Zealand birth cohort ELF. Follow-up participation varied from 43% to 89% depending on the cohort. Although there were heterogeneities among studies, participants who became aware of the study through an online communication campaign compared with those through traditional offline media seemed to have a lower follow-up participation in 8 out of 9 cohorts. There were no clear differences in participation between participants enrolled face-to-face and those enrolled through other offline strategies. An Internet-based campaign for Internet-based epidemiological studies seems to be less effective than an offline one in enrolling volunteers who keep participating in follow-up questionnaires. This suggests that even for Internet-based epidemiological studies an offline enrollment campaign would be helpful in order to achieve a higher participation proportion and limit the cohort attrition.

Indexed as

InternetPatient ParticipationPatient SelectionPopulation SurveillanceAdolescentAdultAgedCohort StudiesEuropeFemaleHumansInfluenza, HumanMaleMiddle AgedNew ZealandPrevalence

Identifiers

PMID25490045
PMCPMC4260912

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.