Automated reminders reduce incarceration for missed court dates: Evidence from a text message experiment.

Alex Chohlas-Wood, Madison Coots, Joe Nudell, Julian Nyarko, Emma Brunskill, Todd Rogers, Sharad Goel

Abstract read

In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Alex Chohlas-WoodApplied Statistics, Social Science, and Humanities, New York University, New York, NY 10012, USA.ORCID 0000-0002-8279-6270

Madison CootsHarvard Kennedy School, Harvard University, Cambridge, MA 02138, USA.ORCID 0009-0002-9819-8985

Joe NudellHarvard Kennedy School, Harvard University, Cambridge, MA 02138, USA.ORCID 0000-0002-8671-6557

Julian NyarkoStanford Law School, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-7121-5696

Emma BrunskillComputer Science, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-3971-7127

Todd RogersHarvard Kennedy School, Harvard University, Cambridge, MA 02138, USA.

Sharad GoelHarvard Kennedy School, Harvard University, Cambridge, MA 02138, USA.ORCID 0000-0002-6103-9318

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Millions of Americans must attend mandatory court dates every year. To boost appearance rates, jurisdictions nationwide are increasingly turning to automated reminders. However, previous research paints an incomplete picture of their effectiveness-in particular, there has been little work assessing the impact of reminders on downstream arrests and incarceration. In partnership with the Santa Clara County Public Defender's Office, we randomly assigned 5709 public defender clients to either receive automated text message reminders (treatment) or not receive reminders (control). We found that reminders reduced warrants issued for missed court dates by ~20%, with 12.1% of clients in control issued a warrant compared to 9.7% of clients in treatment. Further, we found that incarceration from missed court dates dropped by a similar amount, from 6.6% in control to 5.2% in treatment. The effectiveness of reminders bolsters the theory that lapses in memory or comprehension contribute to missed court appearances.

Indexed as

Reminder SystemsText MessagingAdultFemaleHumansIncarcerationMale

Identifiers

PMID41032609

DOI10.1126/sciadv.adx7483

PMCPMC12487872

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.