Evidence map›Paper›PMID 27588539›Full record

ArticleJournal of studies on alcohol and drugs2016

Sources of Misspecification Bias in Assessments of Risks Related to Alcohol Use.

Paul J Gruenewald, Meme Wang-Schweig, Christina Mair

Abstract read
In one paragraph

Article in Journal of studies on alcohol and drugs, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Space and Place in Alcohol Research.Current epidemiology reports · 2019
    Article
  6. Heterogeneous Dose-Response Analyses of Alcohol Abuse and Dependence.Alcoholism, clinical and experimental research · 2019
    Article
  7. Article
  8. Article
  9. Article
  10. 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

3 authors.

Paul J GruenewaldPrevention Research Center, Oakland, California.
Meme Wang-SchweigPrevention Research Center, Oakland, California.
Christina MairDepartment of Behavioral and Community Health Sciences, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.

Funding

Transitions and Alcohol Use in the Later Lifespan: Environmental and Individual-level InfluencesP60AA006282 · NIAAA · PACIFIC INSTITUTE FOR RES AND EVALUATION · PI PAUL J GRUENEWALD · 2003 to 2026
$41.2M
NIAAA NIH HHS P60 AA006282
6 · The paper itself

Abstract

objectiveMany different measures of alcohol use are applied in survey-based epidemiological studies of alcohol-related risks. Differences in the selection of drinking measures and alternative specifications of quantitative relationships of these measures to problem outcomes limit researchers' abilities to compare and assess alcohol effects across studies. We used a quantitative definition of drinking patterns to identify relationships among drinking measures and uncover sources of bias in assessments of drinking risks.

methodA census of drinking measures from studies published in four leading journals in the first half of 2013 were mapped onto a "drinking patterns table," quantitatively relating each measure to every other. Relationships among these measures and in relation to two problem outcomes, physiological problems and sexual risks, were examined using data from 41,352 undergraduate college student drinkers in California.

resultsTwenty-nine sets of drinking measures appeared across 74 published studies; no common statistical procedure was used to assess drinking risks. Empirically observed distributions of heavy drinking (R(2) = .887, p < .001) and variances in drinking quantities (R(2) = .645, p < .001) were predicted from the drinking patterns table. Heteroscedasticity in drinking measures also biased estimates of physiological risks related to drinking quantities (z = -5.159, p < .001), volume (z = 4.592, p < .001), and heavy drinking (z = -5.431, p < .001).

conclusionsRelationships between drinking measures can be formally identified and related to one another using drinking patterns tables. Biases related to selections of different drinking measures and unobserved heteroscedasticity can be identified and controlled through formal quantitative assessments of relationships between drinking measures and observed outcomes.

Indexed as

Alcohol DrinkingAlcohol Drinking in CollegeBiasHumansRisk AssessmentStudentsSurveys and Questionnaires

Identifiers

PMID27588539
PMCPMC5015472

What OpenQuestion holds

Textmetadata
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.