Evidence map›Paper›PMID 38445244›Full record

ArticleIEEE open journal of engineering in medicine and biology2024

Expecting the Unexpected: Predicting Panic Attacks From Mood, Twitter, and Apple Watch Data.

Ellen W McGinnis, Bryn Loftness, Shania Lunna, Isabel Berman, Skylar Bagdon, Genevieve Lewis, Michael Arnold, Christopher M Danforth, Peter S Dodds, Matthew Price and 2 more

Abstract read
In one paragraph

Article in IEEE open journal of engineering in medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Discovering Digital Biomarkers of Panic Attack Risk in Consumer Wearables Data.medRxiv : the preprint server for health sciences · 2023
    Article
  6. Article
  7. 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

12 authors.

Ellen W McGinnisM-Sense Research GroupWake Forest School of Medicine Winston-Salem NC 27101 USA.
Bryn LoftnessVermont Center for Children, Youth and FamiliesUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0000-0003-4597-0783
Shania LunnaVermont Center for Children, Youth and FamiliesUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0009-0009-5992-7912
Isabel BermanVermont Center for Children, Youth and FamiliesUniversity of Vermont Burlington VT 05405 USA.
Skylar BagdonVermont Center for Children, Youth and FamiliesUniversity of Vermont Burlington VT 05405 USA.
Genevieve LewisVermont Center for Children, Youth and FamiliesUniversity of Vermont Burlington VT 05405 USA.
Michael ArnoldVermont Complex Systems CenterUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0000-0002-1218-0315
Christopher M DanforthVermont Complex Systems CenterUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0000-0002-9857-2845
Peter S DoddsVermont Complex Systems CenterUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0000-0003-1973-8614
Matthew PriceCenter for Research on Emotion, Stress and TechnologyUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0000-0001-5637-9230
William E CopelandVermont Center for Children, Youth and FamiliesUniversity of Vermont Burlington VT 05405 USA.ORCID https://orcid.org/0000-0002-1348-7781
Ryan S McGinnisM-Sense Research GroupWake Forest School of Medicine Winston-Salem NC 27101 USA.ORCID https://orcid.org/0000-0001-8396-6967

Funding

Digital Phenotyping To Screen For Early Childhood Internalizing DisordersK23MH123031 · NIMH · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI MCGINNIS, ELLEN WAXLER · 2021 to 2024
$643k
NIMH NIH HHS K23 MH123031
6 · The paper itself

Abstract

objectivePanic attacks are an impairing mental health problem that affects 11% of adults every year. Current criteria describe them as occurring without warning, despite evidence suggesting individuals can often identify attack triggers. We aimed to prospectively explore qualitative and quantitative factors associated with the onset of panic attacks.

resultsOf 87 participants, 95% retrospectively identified a trigger for their panic attacks. Worse individually reported mood and state-level mood, as indicated by Twitter ratings, were related to greater likelihood of

conclusionsThese promising results suggest that individuals who experience panic attacks may be able to anticipate their next attack which could be used to inform future prevention and intervention efforts.

Indexed as

apple watchmental healthPanic attackstwitterwearables

Identifiers

PMID38445244
PMCPMC10914138

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.