Google for Sexual Relationships: Mixed-Methods Study on Digital Flirting and Online Dating Among Adolescent Youth and Young Adults
Notice bibliographique
Résumé
BACKGROUND: According to a 2015 report from the Pew Research Center, nearly 24% of teens go online almost constantly and 92% of teens are accessing the internet daily; consequently, a large part of adolescent romantic exploration has moved online, where young people are turning to the Web for romantic relationship-building and sexual experience. This digital change in romantic behaviors among youth has implications for public health and sexual health programs, but little is known about the ways in which young people use online spaces for sexual exploration. An examination of youth sexual health and relationships online and the implications for adolescent health programs has yet to be fully explored. OBJECTIVE: Although studies have documented increasing rates of sexually transmitted infections and HIV among young people, many programs continue to neglect online spaces as avenues for understanding sexual exploration. Little is known about the online sexual health practices of young people, including digital flirting and online dating. This study explores the current behaviors and opinions of youth throughout online sexual exploration, relationship-building, and online dating, further providing insights into youth behavior for intervention opportunities. METHODS: From January through December 2016, an exploratory study titled TECHsex used a mixed-methods approach to document information-seeking behaviors and sexual health building behaviors of youth online in the United States. Data from a national quantitative survey of 1500 youth and 12 qualitative focus groups (66 youth) were triangulated to understand the experiences and desires of young people as they navigate their sexual relationships through social media, online chatting, and online dating. RESULTS: Young people are using the internet to begin sexual relationships with others, including dating, online flirting, and hooking up. Despite the fact that dating sites have explicit rules against minor use, under 18 youth are using these products regardless in order to make friends and begin romantic relationships, albeit at a lower rate than their older peers (19.0% [64/336] vs 37.8% [440/1163], respectively). Nearly 70% of youth who have used online dating sites met up with someone in person (44.78% [30/67] under 18 vs 74.0% [324/438] over 18). Focus group respondents provided further context into online sexual exploration; many learned of sex through pornography, online dating profiles, or through flirting on social media. Social media played an important role in vetting potential partners and beginning romantic relationships. Youth also reported using online dating and flirting despite fears of violence or catfishing, in which online profiles are used to deceive others. CONCLUSIONS: Youth are turning to online spaces to build sexual relationships, particularly in areas where access to peers is limited. Although online dating site use is somewhat high, more youth turn to social media for online dating. Sexual relationship-building included online flirting and online dating websites and/or apps. These findings have implications for future sexual health programs interested in improving the sexual health outcomes of young people. Researchers may be neglecting to include social media as potential sources of youth hookup culture and dating. We implore researchers and organizations to consider the relationships young people have with technology in order to more strategically use these platforms to create successful and youth-centered programs to improve sexual health outcomes.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».