Evidence map›Paper›PMID 38309010›Full record

ArticlePsychiatry research2024

Identifying mechanisms of persecutory ideation maintenance with smartphone technology: Examining threat importance, certainty, rumination, and behavior change.

Benjamin Buck, Justin S Tauscher, Erica Whiting, Weichen Wang, Andrew T Campbell, Dror Ben-Zeev

Abstract read
In one paragraph

Article in Psychiatry research, 2024. 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
–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

2 citing papers in PubMed.

  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

6 authors.

Benjamin BuckBehavioral Research in Technology and Engineering Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States. Electronic address: buckbe@uw.edu.
Justin S TauscherBehavioral Research in Technology and Engineering Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.
Erica WhitingBehavioral Research in Technology and Engineering Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.
Weichen WangDepartment of Computer Science, Dartmouth College, Hanover, NH, United States.
Andrew T CampbellDepartment of Computer Science, Dartmouth College, Hanover, NH, United States.
Dror Ben-ZeevBehavioral Research in Technology and Engineering Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.

Funding

Mobile RDoC: Using Smartphone Technology to Understand Auditory Verbal HallucinationsR01MH112641 · NIMH · UNIVERSITY OF WASHINGTON · PI BEN-ZEEV, DROR · 2017 to 2020
$2.8M
User-centered design of a mobile health intervention to promote help-seeking and reduce duration of untreated illness among young adults with early psychosisK23MH122504 · NIMH · UNIVERSITY OF WASHINGTON · PI BUCK, BENJAMIN EDWARDS · 2020 to 2024
$930k
NIMH NIH HHS K23 MH122504NIMH NIH HHS L30 MH124097NIMH NIH HHS R01 MH112641
6 · The paper itself

Abstract

Previous cross-sectional and laboratory research has identified risk factors for persecutory ideation including rumination, negative affect, and safety-seeking behaviors. Questions remain about what in-the-moment factors link general negative affect to PI as well as which maintain PI over time. In the present study, N = 219 individuals completed momentary assessments of PI as well as four factors (attributing threats as certain and important, ruminating, and changing one's behavior in response) proposed to maintain PI over time. Linear mixed effects models were used to analyze multiple time-varying relationships, including these factors predicting negative affect and vice versa, as well as factors predicting maintenance of PI over time. Linear mixed effects models were used to analyze multiple time-varying relationships, examining each PI-related factor predicting negative affect, negative affect predicting each PI-related factor, as well as each factor predicting maintenance of PI over time. All four factors were associated with increases in subsequent day self-reported severity of PI, suggesting all four increased the likelihood of maintaining or worsening next-day PI. Results of this study confirm that the proposed factors are key in maintaining a cycle by which PI and negative affect are maintained over time. These factors may represent targets for momentary interventions.

Indexed as

Behavioral SymptomsSmartphoneCross-Sectional StudiesHumansMental ProcessesEcological momentary assessmentExperience samplingMobile health (mHealth)ParanoiaPersecutory ideation

Identifiers

PMID38309010
PMCPMC10923100

What OpenQuestion holds

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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.