Evidence map›Paper›PMID 36083138›Full record

ArticleSuicide & life-threatening behavior2023

Inferring sleep disturbance from text messages of suicide attempt survivors: A pilot study.

Ilana Ladis, Tara L Valladares, Daniel D L Coppersmith, Jeffrey J Glenn, Alicia L Nobles, Laura E Barnes, Bethany A Teachman

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Suicide & life-threatening behavior, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 41% of its field
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 citations in OpenAlex.

  1. Article
  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

7 authors at 4 institutions in 1 country.

Ilana LadisDepartment of Psychology, University of Virginia, Charlottesville, Virginia, USA.ORCID 0000-0002-9582-6563
Tara L ValladaresDepartment of Psychology, University of Virginia, Charlottesville, Virginia, USA.ORCID 0000-0002-0619-6839
Daniel D L CoppersmithDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.ORCID 0000-0002-9397-3228
Jeffrey J GlennDepartment of Psychology, University of Virginia, Charlottesville, Virginia, USA.
Alicia L NoblesDepartment of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0003-0472-3671
Laura E BarnesDepartment of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA.
Bethany A TeachmanDepartment of Psychology, University of Virginia, Charlottesville, Virginia, USA.
University of Virginia · USEngineering Systems (United States) · USHarvard University · USUniversity of California San Diego · US

Funding

Effectiveness of interpretation training to reduce anxiety: Evaluating technology-based delivery models and methods to reduce attritionR01MH113752 · NIMH · UNIVERSITY OF VIRGINIA · PI TEACHMAN, BETHANY A · 2017 to 2020
$2.5M
Testing Target Engagement and Effectiveness of Web-based Interpretation Training For AnxietyR34MH106770 · NIMH · UNIVERSITY OF VIRGINIA · PI TEACHMAN, BETHANY A · 2015 to 2016
$689k
Quantifying Treatment Help-Seeking Among Self-Identified Opioid Users on Social MediaK25DA049944 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NOBLES, ALICIA · 2020 to 2021
$339k
NIDA NIH HHS K25 DA049944NIMH NIH HHS R01 MH113752NIMH NIH HHS R34 MH106770
6 · The paper itself

Abstract

objectiveIdentifying digital markers of sleep disturbance-a known suicide risk factor-may aid in the detection of imminent suicide risk. This study examined sleep-related communication and texting patterns in personal text messages (N = 86,705) of suicide attempt survivors.

methodTwenty-six participants provided dates of past suicide attempts and 2-week periods of positive mood, depressed mood, or suicidal ideation. Linguistic Inquiry Word Count was used to identify sleep-related texts via a custom dictionary. Mixed effect models were fitted to test the association between suicide/mood episode type (e.g., attempt versus ideation) and three outcomes: likelihood of a text including sleep-related content, nightly count of texts sent from midnight to 5:00 AM, and sum of unique hour bins from midnight to 5:00 AM with outgoing texts.

resultsAnalyses with a sleep dictionary that was manually revised to be more accurate (but not the original unedited dictionary) showed sleep-related communication was more likely during depressed mood episodes than positive mood episodes. Otherwise, there were no significant differences in sleep-related communication or objective texting patterns across episode type.

conclusionsAlthough we did not detect differences in sleep-related communication tied to suicidal thoughts or behaviors, sleep-related communication may differ as a function of within-person mood level.

Indexed as

Suicide, AttemptedText MessagingHumansPilot ProjectsRisk FactorsSleepSuicidal Ideationdepressioninsomniarisk-assessmentsmartphonessuicide

Identifiers

PMID36083138
PMCPMC9908817
OpenAlexW4295047680

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.