Evidence map›Paper›PMID 36817845›Full record

ArticleJournal of family violence2023

Problem Drinking is Associated with Intimate Partner Cyber Abuse Perpetration but is Buffered by High Relationship Satisfaction.

Jacqueline Woerner, Erica R Fissel, Jessica N Flori, Robyn N Memphis

Abstract read
In one paragraph

Article in Journal of family violence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Jacqueline WoernerDepartment of Sociology, University of Central Florida, Orlando, FL USA.
Erica R FisselDepartment of Criminal Justice, University of Central Florida, Orlando, FL USA.
Jessica N FloriDepartment of Sociology, University of Central Florida, Orlando, FL USA.
Robyn N MemphisDepartment of Sociology, University of Central Florida, Orlando, FL USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Intimate partner cyber abuse (IPCA) is a prevalent form of intimate partner violence (IPV) that has detrimental effects on victims' well-being. Although research has documented associations with other forms of IPV perpetration, additional research is needed to identify IPCA perpetration risk factors. One of the most common risk factors for offline IPV is perpetrators' alcohol use; however, less is known about how this translates to online contexts. There is also a need to identify protective factors that mitigate the effects of alcohol. Methods: This study evaluated associations between drinking, relationship satisfaction, and IPCA perpetration via self-report questionnaires within a longitudinal framework. Participants included 544 adults in an intimate relationship ( Results: Results indicated that relationship satisfaction buffered the effects of problem drinking on IPCA perpetration at T1, but not at T2. Further, 20.2% of individuals who perpetrated IPCA at T1 drank alcohol during at least one incident, and these individuals reported more problem drinking and more frequent IPCA perpetration compared to those who reported IPCA without alcohol. Conclusion: Results from this study provide insight into both risk and protective factors for IPCA perpetration among adults and have the potential to guide concurrent prevention strategies that target intersections between problem drinking, IPCA, and offline IPV, and promote healthy and satisfying intimate relationships.

Indexed as

AlcoholIntimate partner cyber abusePerpetrationProblem drinkingRelationship satisfaction

Identifiers

PMID36817845
PMCPMC9925923

What OpenQuestion holds

Textmetadata
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Registered trials

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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.