Evidence map›Paper›PMID 21854279›Full record

Trial reportThe American journal of drug and alcohol abuse2011

Zero-inflated and hurdle models of count data with extra zeros: examples from an HIV-risk reduction intervention trial.

Mei-Chen Hu, Martina Pavlicova, Edward V Nunes

Open access · greenAbstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in The American journal of drug and alcohol abuse, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers.

0numbers the graph read from it
0cells of the map it votes in
111citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

111 citing papers in PubMed, 344 citations in OpenAlex.

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  12. Acute Mental Health Impacts and Mid-Term Symptom Trajectories Following Wildfire Exposure.International journal of environmental research and public health · 2026
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  13. Digital media balance and mental health: effects of a school-based program.Child and adolescent psychiatry and mental health · 2026
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51 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Mei-Chen HuDepartment of Psychiatry, Columbia University, New York, NY, USA.
Martina Pavlicova
Edward V Nunes
Columbia University · US

Funding

CU PARTNERS: NY/LONG ISLAND REGIONAL NODEU10DA013035 · NIDA · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI NUNES, EDWARD V., ROTROSEN, JOHN P · 2001 to 2015
$47.6M
Drug Abuse Treatment Development and Research MentoringK24DA022412 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI NUNES, EDWARD V. · 2007 to 2016
$1.7M
NIDA NIH HHS K24 DA022412NIDA NIH HHS U10 DA013035
6 · The paper itself

Abstract

backgroundIn clinical trials of behavioral health interventions, outcome variables often take the form of counts, such as days using substances or episodes of unprotected sex. Classically, count data follow a Poisson distribution; however, in practice such data often display greater heterogeneity in the form of excess zeros (zero-inflation) or greater spread in the values (overdispersion) or both. Greater sample heterogeneity may be especially common in community-based effectiveness trials, where broad eligibility criteria are implemented to achieve a generalizable sample.

objectivesThis article reviews the characteristics of Poisson model and the related models that have been developed to handle overdispersion (negative binomial (NB) model) or zero-inflation (zero-inflated Poisson (ZIP) and Poisson hurdle (PH) models) or both (zero-inflated negative binomial (ZINB) and negative binomial hurdle (NBH) models).

methodsAll six models were used to model the effect of an HIV-risk reduction intervention on the count of unprotected sexual occasions (USOs), using data from a previously completed clinical trial among female patients (N = 515) participating in community-based substance abuse treatment (Tross et al. Effectiveness of HIV/AIDS sexual risk reduction groups for women in substance abuse treatment programs: Results of NIDA Clinical Trials Network Trial. J Acquir Immune Defic Syndr 2008; 48(5):581-589). Goodness of fit and the estimates of treatment effect derived from each model were compared.

resultsThe ZINB model provided the best fit, yielding a medium-sized effect of intervention. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: This article illustrates the consequences of applying models with different distribution assumptions on the data. If a model used does not closely fit the shape of the data distribution, the estimate of the effect of the intervention may be biased, either over- or underestimating the intervention effect.

Indexed as

Models, StatisticalAdultBiasCommunity Health ServicesFemaleFollow-Up StudiesHIV InfectionsHumansPoisson DistributionRisk Reduction BehaviorRisk-TakingSubstance-Related DisordersUnsafe Sex

Identifiers

PMID21854279
PMCPMC3238139
OpenAlexW2143201841

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.