Evidence map›Paper›PMID 36735169›Full record

ArticleArchives of sexual behavior2023

The Structure of Compulsive Sexual Behavior: A Network Analysis Study.

Igor Marchetti

Open access · hybridAbstract read
In one paragraph

Article in Archives of sexual behavior, 2023. 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
3.6field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Igor MarchettiDepartment of Life Sciences, Psychology Unit, University of Trieste, 34128, Trieste, Italy. imarchetti@units.it.ORCID http://orcid.org/0000-0002-4709-7941
University of Trieste · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compulsive sexual behavior is a phenomenon characterized by a persistent failure to control intense, repetitive sexual impulses or urges, resulting in repetitive sexual behavior that causes marked distress or impairment in personal, familial, social, educational, or occupational areas of functioning. Despite its major impact on mental health and quality of life, little is known about its internal structure and whether this phenomenon differs across genders, age groups, and risk status. By considering a large online sample (n = 3186; 68.3% males), ranging from 14 to 64 years old, compulsive sexual behavior was explored by means of network analysis. State-of-the-art analytical techniques were adopted to investigate the pattern of association among the different elements of compulsive sexual behavior, identify possible communities of nodes, pinpoint the most central nodes, and detect differences between males and females, among different age groups, as well as between individuals at low and high risk of developing a full-blown disorder. The analyses revealed that the network was characterized by three communities, namely Consequence, Preoccupation, and Perceived Dyscontrol, and that the most central node was related to (perceived) impulse dyscontrol. No substantial differences were found between males and females and across age. Failing to meet one's own commitments and responsibilities was more central in individuals at high risk of developing a full-blown disorder than in those at low risk.

Indexed as

Paraphilic DisordersSexual Dysfunctions, PsychologicalAdolescentAdultCompulsive BehaviorFemaleHumansMaleMiddle AgedQuality of LifeSexual BehaviorYoung AdultCompulsive sexual behaviorDSM-5HypersexualityICD-11ImpulsivityNetwork analysis

Identifiers

PMID36735169
PMCPMC10102046
OpenAlexW4319058784

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.