Evidence map›Paper›PMID 34602705›Full record

ArticleJournal of development economics2021

Texts don't nudge: An adaptive trial to prevent the spread of COVID-19 in India.

Girija Bahety, Sebastian Bauhoff, Dev Patel, James Potter

Abstract read
In one paragraph

Article in Journal of development economics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
  2. Trial
  3. Inclusive Crisis Communication in a Pandemic Context: A Rapid Review.International journal of environmental research and public health · 2024
    Review
  4. Article
  5. Mortality risk information and health-seeking behavior during an epidemic.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  6. Article
  7. Teaching and Incentives: Substitutes or Complements?Economics of education review · 2022
    Article
  8. Review
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

4 authors.

Girija BahetyTufts University, Department of Economics and the Fletcher School of Law and Diplomacy, United States of America.
Sebastian BauhoffHarvard TH Chan School of Public Health, United States of America.
Dev PatelHarvard University, Department of Economics, United States of America.
James PotterHarvard TH Chan School of Public Health, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We conduct an adaptive randomized controlled trial to evaluate the impact of a SMS-based information campaign on the adoption of social distancing and handwashing in rural Bihar, India, six months into the COVID-19 pandemic. We test 10 arms that vary in delivery timing and message framing, changing content to highlight gains or losses for either one's own family or community. We identify the optimal treatment separately for each targeted behavior by adaptively allocating shares across arms over 10 experimental rounds using exploration sampling. Based on phone surveys with nearly 4,000 households and using several elicitation methods, we do not find evidence of impact on knowledge or adoption of preventive health behavior, and our confidence intervals cannot rule out positive effects as large as 5.5 percentage points, or 16%. Our results suggest that SMS-based information campaigns may have limited efficacy after the initial phase of a pandemic.

Indexed as

Adaptive trialCOVID-19Health behaviorsIndiaInformation and communicationSMS

Identifiers

PMID34602705
PMCPMC8464082

What OpenQuestion holds

Textmetadata
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.