Evidence map›Paper›PMID 39757813›Full record

ArticlePsychiatry investigation2024

What Is Excessive? The Screening Frequency of Online Sexual Activities Among Community and Subclinical Males.

Lijun Chen, Qiqi Wang, Xiaoliu Jiang, Ying Zhang

Abstract read
In one paragraph

Article in Psychiatry investigation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lijun ChenDepartment of Psychology, School of Humanities and Social Sciences, Fuzhou University, Fujian, China.
Qiqi WangDepartment of Psychology, School of Humanities and Social Sciences, Fuzhou University, Fujian, China.
Xiaoliu JiangDepartment of Social Psychology, School of Sociology, Nankai University, Tianjin, China.
Ying ZhangDepartment of Physical Education, Fuzhou University, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe purpose of this study was to investigate the different categories of males within two groups, namely a community male sample who engaged in online sexual activities (OSAs) and a subclinical male sample who were out of control in viewing pornography and had sought help. Additionally, the study aimed to determine the threshold for excessive OSAs in both samples.

methodsA total of 568 community adult males who engaged in OSAs and 567 adult males seeking help for pornography use were recruited online. A latent profile analysis (LPA) was used to identify potential profiles within the samples. Cut-point analyses were conducted to determine optimal cutoff scores for OSAs in each sample.

resultsThe LPA revealed two categories with different cutoff scores for OSAs within each sample. Excessive OSA can be a screening tool for detecting out-of-control behavior. More stringent criteria for identifying excessive OSAs can aid in distinguishing problematic pornography use (PPU) from impaired control in viewing sexually-explicit materials (SEMs). Two subcategories of loss of control emerged: high OSAs frequency impaired control and high viewing SEMs impaired control.

conclusionThe threholds of excessive OSAs varies among community and sub-clinical male samples; this knowledge can assist in screening out individuals with impaired control and selecting individuals with PPU from the subclinical sample.

Indexed as

Latent profile analysisOnline sexual activitiesOptimal cutoff valueProblematic pornography use

Identifiers

PMID39757813
PMCPMC11704803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.