Evidence map›Paper›PMID 36749407›Full record

ArticleArchives of sexual behavior2023

Syndemic Profiles and Sexual Health Risks Among Sexually Exploited Adolescent Girls in Taiwan: A Latent Class Analysis.

Ji-Kang Chen, Shu-Chen Wang, Li-Chih Wang

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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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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4 · The record

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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.

Ji-Kang ChenDepartment of Social Work, Chinese University of Hong Kong, Sha Tin, Hong Kong. jkchen@swk.cuhk.edu.hk.ORCID http://orcid.org/0000-0001-7762-3888
Shu-Chen WangNational Academy for Educational Research, New Taipei, Taiwan.ORCID http://orcid.org/0000-0001-8818-9378
Li-Chih WangDepartment of Special Education, National Tsing Hua University, Hsinchu City, Taiwan.ORCID http://orcid.org/0000-0002-4011-7305

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sexually exploited adolescent girls are disproportionately affected by adverse psychosocial conditions, such as intra-familial child physical and sexual abuse, extra-familial violence and sexual assault, alcohol and drug use, and suicide. Syndemic theory suggests that these adverse psychosocial or syndemic conditions are concentrated and co-occurring in socially marginalized populations, including sexually exploited adolescents, and increase their sexual health risks, including pregnancy, abortion, and the acquisition of sexually transmitted diseases (STDs). To examine clusters of syndemic conditions, latent class analysis (LCA) was conducted to classify 335 sexually exploited girls in Taiwan into subgroups based on their probability of experiencing each syndemic condition. We used syndemic class membership to predict their sexual health outcomes, specifically pregnancy, abortion, and the acquisition of STDs. The results of LCA revealed three classes, which were "low-risk syndemic," "moderate-risk syndemic," and "high-risk syndemic." The risk of acquisition of STDs among sexually exploited girls in the "high-risk syndemic class" and "moderate-risk syndemic class" was 239% and 135% higher, respectively, than the risk of acquisition of STDs among sexually exploited girls in the "low-risk syndemic class." Differences between these three classes in pregnancy and abortion were not significant. Our findings support the syndemic theory that a pattern of syndemic conditions is associated with an increased risk of acquiring STDs. Interventions aimed at reducing the acquisition of STDs among sexually exploited girls in Taiwan should adopt a comprehensive approach to address co-occurring conditions.

Indexed as

Sexual HealthSexually Transmitted DiseasesSubstance-Related DisordersAdolescentFemaleHumansLatent Class AnalysisPregnancySexual BehaviorSyndemicTaiwanPoly-victimizationSexual exploitationSexually transmitted diseasesSubstance useSuicideSyndemic

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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.