Evidence map›Paper›PMID 30778831›Full record

ArticleJournal of youth and adolescence2019

Online Sexual Experiences Predict Subsequent Sexual Health and Victimization Outcomes Among Female Adolescents: A Latent Class Analysis.

Megan K Maas, Bethany C Bray, Jennie G Noll

Open access · greenAbstract read
In one paragraph

Article in Journal of youth and adolescence, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
10.4field-weighted citation impact, top 1% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
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  7. Predictors of teen sexual behavior.Children and youth services review · 2024
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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

3 authors at 2 institutions in 1 country.

Megan K MaasDepartment of Human Development and Family Studies, Michigan State University, 552W. Circle Drive 13D Human Ecology, East Lansing, MI, 48824, USA. maasmeg1@msu.edu.ORCID http://orcid.org/0000-0003-2387-5224
Bethany C BrayThe Methodology Center, The Pennsylvania State University, 404 Health and Human Development Building, University Park, PA, 16802, USA.
Jennie G NollDepartment of Human Development and Family Studies, The Pennsylvania State University, 119 Health and Human Development Building, University Park, PA, 16802, USA.
Pennsylvania State University · USMichigan State University · US

Funding

STRATIFIED CLUSTER RANDOMIZED TRIAL (SCRT) OF A CLINICAL DECISION RULE (CDR) FOR ABUSIVE HEAD TRAUMA (AHT)P50HD089922 · NICHD · PENNSYLVANIA STATE UNIVERSITY, THE · PI Hannah Milena Caroline Schreier · 2017 to 2026
$16.9M
Pilot, Mentoring, and Professional Development CoreP50DA039838 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI LANZA, STEPHANIE T · 2015 to 2019
$13.9M
PREVENTION AND METHODOLOGY TRAINING (PAMT)T32DA017629 · NIDA · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI Eric D Claus, Rina D Eiden · 2005 to 2026
$9.5M
Abused and non-abused females' high-risk online behaviors: Impact on developmentR01HD073130 · NICHD · CINCINNATI CHILDRENS HOSP MED CTR · PI NOLL, JENNIE G · 2012 to 2016
$2.9M
Preventing Teen Pregnancy: Prepregnancy Psychosocial Mechanisms for at-risk FemalR01HD052533 · NICHD · CINCINNATI CHILDRENS HOSP MED CTR · PI NOLL, JENNIE G · 2007 to 2011
$2.5M
HIV and Substance Use Prevention Among Maltreated and Non-Maltreated Female AdolescentsF31DA039603 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI MAAS, MEGAN · 2015 to 2016
$40k
NICHD NIH HHS P50 HD089922NICHD NIH HHS R01 HD052533NICHD NIH HHS R01 HD073130NIDA NIH HHS F31 DA039603NIDA NIH HHS L40 DA044702NIDA NIH HHS P50 DA039838NIDA NIH HHS T32 DA017629
6 · The paper itself

Abstract

Adolescents' online sexual experiences (e.g., pornography use, sexual chatting, sexualized social media use, and nude image exchange) provide a new context for sexual socialization. Traditionally, online sexual experiences are often aggregated averages, which neglect their complexity and fail to identify individual differences in the experience. Moreover, the lack of longitudinal research in this area has failed to determine if these experiences predict later offline sexual health and violence outcomes. An analysis of two waves of surveys completed by ethnically and socioeconomically diverse female adolescents (N = 296; 49% maltreated; aged 14-16 years) participating in a larger cross-sequential study was conducted to address these gaps. Established latent classes from the prerequisite study of online sexual experiences at Time 1 were Online Abstinent (low probability of any online sexual experiences), Online Inclusive (high probability of all online sexual experiences), Attractors (high probability of attracting attention from others), and Seekers (high probability of seeking out sexual content and interaction). Class membership uniquely predicted HIV risk, number of physically violent romantic partners, and the occurrence of sexual assault at Time 2. Although membership in risker online sexual experience classes predicted later offline risk and victimization, this was especially true for maltreated participants. These findings demonstrate the advantages of examining online sexual experiences in a way that emphasizes their complexity and individual differences in influential susceptibility.

Indexed as

Adolescent HealthInternetSexual HealthAdolescentAdolescent BehaviorCrime VictimsEroticaFemaleHealth SurveysHumansLatent Class AnalysisLongitudinal StudiesRisk FactorsSex OffensesSexual BehaviorViolenceMaltreatmentMediaPornographySextingSexual violenceSocial media

Identifiers

PMID30778831
PMCPMC7135936
OpenAlexW2915402983

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.