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Association of Sexting With Sexual Behaviors and Mental Health Among Adolescents

2019· article· en· W2952032993 on OpenAlexaff
Camille Mori, Jeff R. Temple, Dillon T. Browne, Sheri Madigan

Bibliographic record

VenueJAMA Pediatrics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsUniversity of WaterlooAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineAssociation (psychology)Mental healthSexual behaviorPsychiatryClinical psychologyEnvironmental healthPsychotherapist

Abstract

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IMPORTANCE: Sexting is the exchange of sexual messages, photographs, or videos via technological devices and is common and increasing among youth. Although various studies have examined the association between sexting, sexual behaviors, and mental health, results are mixed. OBJECTIVE: To provide a meta-analytic synthesis of studies examining the associations between sexting, sexual behavior, and mental health using sex, age, publication date, and study methodological quality as moderators. DATA SOURCES: Electronic searches were conducted in April 2018 in MEDLINE, PsycINFO, Embase, and Web of Science, yielding 1672 nonduplicate records. STUDY SELECTION: Studies were included if participants were younger than 18 years and an association between sexting and sexual behaviors or mental health risk factors was examined. DATA EXTRACTION AND SYNTHESIS: All relevant data were extracted by 2 independent reviewers. Random-effects meta-analyses were used to derive odds ratios (ORs). MAIN OUTCOMES AND MEASURES: Sexual behavior (sexual activity, multiple sexual partners, lack of contraception use) and mental health risk factors (anxiety/depression, delinquent behavior, and alcohol, drug use, and smoking). RESULTS: Participants totaled 41 723 from 23 included studies. The mean (range) age was 14.9 (11.9-16.8) years, and 21 717 (52.1%) were female. Significant associations were observed between sexting and sexual activity (16 studies; OR, 3.66; 95% CI, 2.71-4.92), multiple sexual partners (5 studies; OR, 5.37; 95% CI, 2.72-12.67), lack of contraception use (6 studies; OR, 2.16; 95% CI, 1.08-4.32), delinquent behavior (3 studies; OR, 2.50; 95% CI, 1.29-4.86), anxiety/depression (7 studies; OR, 1.79; 95% CI, 1.41-2.28), alcohol use (8 studies; OR, 3.78; 95% CI, 3.11-4.59), drug use (5 studies; OR, 3.48; 95% CI, 2.24-5.40), and smoking behavior (4 studies; OR, 2.66; 95% CI, 1.88-3.76). Moderator analyses revealed that associations between sexting, sexual behavior, and mental health factors were stronger in younger compared to older adolescents. CONCLUSIONS AND RELEVANCE: Results of this meta-analysis suggest that sexting is associated with sexual behavior and mental health difficulties, especially in younger adolescents. Longitudinal research is needed to assess directionality of effects and to analyze the mechanisms by which sexting and its correlates are related. Educational campaigns to raise awareness of digital health, safety, and security are needed to help youth navigate their personal, social, and sexual development in a technological world.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.016
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.272
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations194
Published2019
Admission routes1
Has abstractyes

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