Evidence map›Paper›PMID 30462718›Full record

ArticlePloS one2018

How does anonymous online peer communication affect prevention behavior? Evidence from a laboratory experiment.

Indrani Saran, Günther Fink, Margaret McConnell

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Analysis of Answers to Queries among Anonymous Users with Gastroenterological Problems on an Internet Forum.International journal of environmental research and public health · 2020
    Article
  5. 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

3 authors.

Indrani SaranBoston College School of Social Work, Chestnut Hill, MA, United States of America.ORCID 0000-0001-7416-652X
Günther FinkSwiss Tropical and Public Health Institute and University of Basel, Basel, Switzerland.
Margaret McConnellHarvard T.H. Chan School of Public Health, Boston, MA, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the importance of social networks for health behaviors is well-recognized, relatively little is known regarding the accuracy of anonymous online communication and its impact on health behavior. In 2012, we conducted a laboratory experiment in Boston, Massachusetts with 679 individuals to understand how anonymous online communication affects individual prevention decisions. Participants had to opt for or against investing in prevention over three sessions, each consisting of 15 experimental rounds. In the third session only, participants could share their experiences with a group of 1-3 other anonymous participants after each round. Groups exchanged an average of 16 messages over the 15 rounds of the third session. 70% of messages contained information about the subject's prevention decision and the resulting health outcome. Participants were more likely to communicate when they prevented than when they did not, with prevention failures resulting in the highest probability of sending a message. Nonetheless, receiving an additional message reporting prevention increased the odds a subject would prevent by 32 percent. We find that participants tend to adopt the prevention behavior reported by others, with less weight given to the reported outcomes of prevention, suggesting that social networks may influence behaviors through more than just information provision.

Indexed as

Health BehaviorOnline Social NetworkingAdultAlgorithmsAnonyms and PseudonymsFemaleHealth Information SystemsHealthy LifestyleHumansMalePeer Group

Identifiers

PMID30462718
PMCPMC6248974

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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.