Evidence map›Paper›PMID 33230099›Full record

ArticleNPJ schizophrenia2020

Assessing the relationship between routine and schizophrenia symptoms with passively sensed measures of behavioral stability.

Joy He-Yueya, Benjamin Buck, Andrew Campbell, Tanzeem Choudhury, John M Kane, Dror Ben-Zeev, Tim Althoff

Open access · goldAbstract read
In one paragraph

Article in NPJ schizophrenia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Patient Perspectives on AI-Driven Predictions of Schizophrenia Relapses: Understanding Concerns and Opportunities for Self-Care and Treatment.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Anhedonia in Schizophrenia.Current topics in behavioral neurosciences · 2022
    Article
  16. Article
  17. Article
  18. Article
  19. 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.

Joy He-YueyaPaul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, USA. joyhe@cs.washington.edu.ORCID http://orcid.org/0000-0002-1831-7415
Benjamin BuckDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, USA.
Andrew CampbellDepartment of Computer Science, Dartmouth College, Hanover, USA.
Tanzeem ChoudhuryCornell Tech, New York City, USA.
John M KaneThe Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, East Garden City, USA.
Dror Ben-ZeevDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, USA.
Tim AlthoffPaul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, USA.
University of Washington · USCornell University · USDartmouth College · USDonald & Barbara Zucker School of Medicine at Hofstra/Northwell · US

Funding

A New Paradigm for Illness Monitoring and Relapse Prevention in SchizophreniaR01MH103148 · NIMH · DARTMOUTH COLLEGE · PI BEN-ZEEV, DROR · 2013 to 2016
$1.5M
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 R01 MH103148
6 · The paper itself

Abstract

Increased stability in one's daily routine is associated with well-being in the general population and often a goal of behavioral interventions for people with serious mental illnesses like schizophrenia. Assessing behavioral stability has been limited in clinical research by the use of retrospective scales, which are susceptible to reporting biases and memory inaccuracies. Mobile passive sensors, which are less susceptible to these sources of error, have emerged as tools to assess behavioral patterns in a range of populations. The present study developed and examined a metric of behavioral stability from data generated by a passive sensing system carried by 61 individuals with schizophrenia for one year. This metric-the Stability Index-appeared orthogonal from existing measures drawn from passive sensors and matched the predictive performance of state-of-the-art features. Specifically, greater stability in social activity (e.g., calls and messages) were associated with lower symptoms, and greater stability in physical activity (e.g., being still) appeared associated with elevated symptoms. This study provides additional support for the predictive value of individualized over population-level data in psychiatric populations. The Stability Index offers also a promising tool for generating insights about the impact of behavioral stability in schizophrenia-spectrum disorders.

Identifiers

PMID33230099
PMCPMC7683525
OpenAlexW3109432658

What OpenQuestion holds

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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.