Evidence map›Paper›PMID 39172368›Full record

ArticleJournal of psychopathology and clinical science2024

Machine learning models for temporally precise lapse prediction in alcohol use disorder.

Kendra Wyant, Sarah J Sant'Ana, Gaylen E Fronk, John J Curtin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of psychopathology and clinical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Observational
  3. Article
  4. Article
  5. Observational
  6. Review
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

4 authors.

Kendra WyantDepartment of Psychology, University of Wisconsin-Madison.ORCID 0000-0002-0767-7589
Sarah J Sant'AnaDepartment of Psychology, University of Wisconsin-Madison.
Gaylen E FronkDepartment of Psychology, University of Wisconsin-Madison.
John J CurtinDepartment of Psychology, University of Wisconsin-Madison.ORCID 0000-0002-3286-938X

Funding

Contextualized daily prediction of lapse risk in opioid use disorder by digital phenotypingR01DA047315 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI CURTIN, JOHN J., SHAH, DHAVAN · 2019 to 2023
$3.4M
Dynamic, real-time prediction of alcohol use lapse using mHealth technologiesR01AA024391 · NIAAA · UNIVERSITY OF WISCONSIN-MADISON · PI CURTIN, JOHN J. · 2015 to 2019
$1.9M
Machine learning-assisted precision mental health for cigarette smoking cessationF31DA056144 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI FRONK, GAYLEN E · 2022 to 2024
$116k
NIAAA NIH HHS R01 AA024391NIDA NIH HHS F31 DA056144NIDA NIH HHS R01 DA047315
6 · The paper itself

Abstract

We developed three machine learning models that predict hour-by-hour probabilities of a future lapse back to alcohol use with increasing temporal precision (i.e., lapses in the next week, next day, and next hour). Model features were based on raw scores and longitudinal change in theoretically implicated risk factors collected through ecological momentary assessment. Participants (

Indexed as

AlcoholismMachine LearningAdultAlcohol AbstinenceEcological Momentary AssessmentFemaleHumansMaleMiddle AgedRisk Factors

Identifiers

PMID39172368
PMCPMC11556439

What OpenQuestion holds

Textmetadata
LicenceTDM
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.