Evidence map›Paper›PMID 31022466›Full record

ArticleJournal of biomedical informatics2019

The transformation of a gold standard in-person substance use assessment to a web-based, REDCap integrated data capture tool.

R Martin-Willett, Z McCormick, W Newman, L D Larsen, M A Ortiz Torres, L C Bidwell

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
  4. Article
  5. Predicting Extent of Opioid Use Following Cardiac Surgery: A Pilot Study.Journal of cardiothoracic and vascular anesthesia · 2025
    Observational
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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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.

R Martin-WillettThe University of Colorado Boulder, Boulder, CO, United States. Electronic address: renee.martinwillett@colorado.edu.
Z McCormickTrailblazing Technology, New York, NY, United States.
W NewmanThe University of Colorado Boulder, Boulder, CO, United States.
L D LarsenThe University of Colorado Boulder, Boulder, CO, United States.
M A Ortiz TorresThe University of Colorado Boulder, Boulder, CO, United States.
L C BidwellThe University of Colorado Boulder, Boulder, CO, United States.

Funding

Novel approaches to understanding the role of cannabinoids and inflammation in anxietyR01DA044131 · NIDA · UNIVERSITY OF COLORADO · PI BIDWELL, L. CINNAMON · 2017 to 2021
$2.8M
NIDA NIH HHS R01 DA044131
6 · The paper itself

Abstract

The adoption of computer systems for gathering, managing, and analyzing health data is resulting in the replacement of pen-and-paper methods for collecting data and managing health records by computerized methods. One classic "pen-and-paper" assessment in health and substance use research is the Timeline Follow-Back (TLFB), the gold standard in self-reported substance use developed in 1996 by Sobell et al. to assess alcohol consumption patterns and later other substances such as marijuana or tobacco over discreet timeframes [1-7]. The TLFB has been modified by some research groups for use as a web-based assessment [8-10], but not without significant limitations. As such, this paper describes the team-oriented, interdisciplinary process by which a new online TLFB (O-TLFB) was conceptualized, the technical details of development towards a dynamic data capture tool fully integrated with REDCap via application programming interface (API), and the potential for this optimized O-TLFB to be leveraged broadly across the domains of substance use, health, and behavioral research.

Indexed as

InternetSystems IntegrationData CollectionHumansReproducibility of ResultsSubstance-Related DisordersBehavioral healthExtract-Transform-Load (ETL)Online self-reportREDCapSubstance useWeb-based assessment

Identifiers

PMID31022466
PMCPMC7299305

What OpenQuestion holds

Textmetadata
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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.