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Enregistrement W4411750668 · doi:10.1093/humrep/deaf097.1029

P-724 Hashtags, Hope, or Hype? A systematic review of fertility and reproductive health on social media platforms: A systematic literature review

2025· review· en· W4411750668 sur OpenAlexaboutno aff
C Bou-Nehme, Bola Grace

Notice bibliographique

RevueHuman Reproduction · 2025
Typereview
Langueen
DomaineMedicine
ThématiqueReproductive Health and Technologies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFertilitySocial mediaSystematic reviewReproductive healthMEDLINEGynecologyMedicineDemographyBiologySociologyPolitical sciencePopulation

Résumé

récupéré en direct d'OpenAlex

Abstract Study question To what extent are fertility and reproductive health topics discussed on social media and what is being discussed? Summary answer Evidence obtained from 157 studies, across 9 online platforms, and 13 countries, covered themes on fertility and pregnancy, psychosocial, sexual and reproductive health and ‘others.’ What is known already 1 in 6 individuals are affected by infertility globally. Despite this, the topic remains associated with a high level of stigma. In recent years, social media has become an influential channel for health information sharing, and an outlet for people dealing with fertility issues as well as a means of engaging with fertility and reproductive health topics. Individuals, patients, healthcare professionals (HCPs), educators, influencers and other stakeholder groups also use social media to disseminate information on reproductive health. This study therefore aimed to review fertility and reproductive health discussions on social media platforms to understand how information is disseminated. Study design, size, duration A systematic review was conducted according to Preferred Reporting Items for Systematic-Reviews and Meta-Analyses (PRISMA) guidelines. Databases Medline, PsycINFO, Emcare, and PubMed were searched for primary studies investigating fertility and reproductive health information on social media. Separate search strategies were conducted for fertility and reproductive health, and social media. Studies were analysed thematically and categorised. Participants/materials, setting, methods Inclusion and exclusion criteria were established using the Population, Intervention, Comparator and outcome (PICO) framework. Only studies published in English between January 2014, and December 2024 were included. Observational studies of any design were eligible for inclusion. Studies specifically focused on post-natal child health, parenting techniques, campaign implementation, and other media such as TV and newspapers were excluded. Main results and the role of chance A total of 157 studies were included. Countries included USA(52), UK(52), Canada(9), Switzerland(11), Netherlands(9), China(3), Brazil(3), Germany(2), Ireland(2), Jordan(1), Spain(1), South Korea(1), and Australia(1). Social media platforms reported included Facebook(37), YouTube(27), Twitter(26), Instagram(26), TikTok(6), Reddit(6), Forums(5), Blogs(4), Pinterest(2), Weibo(1), and others(17). Key themes and subthemes included: Fertility and pregnancy: (in)fertility, pregnancy loss, fertility treatments, pregnancy / complications, perinatal health male infertility, egg freezing, oncofertility, preterm birth, and childbirth, Sexual and reproductive health: women’s health, contraception, vaccination, sexual health, abortion, post-partum, nutrition, patient provider, underlying health conditions, non-invasive prenatal testing, sexually transmitted infections, HCPs, and maternal health. Psychosocial aspects: knowledge and awareness, mental health and support, body image, physical activity, communication. Others: Covid-19, fake news, medicine, drug and alcohol, finance, and stigma. Posts were authored by individuals, patients, HCPs and medical organisations. Stories of personal experiences or opinions received a higher rate of engagement compared with educational posts. Similarly, inspirational and support groups, and patient accounts had more engagement than HCPs, academic or fertility clinic accounts, despite the latter having better content quality. A number of studies found no significant difference in engagement between accurate and misleading information, raising the concern of misinformed decisions and health harming behaviours. Limitations, reasons for caution Of the studies included, some were self-reported, hindering the robustness of their conclusions. Only studies published in English were eligible for inclusion, thus limiting the generalisability of study findings. Wider implications of the findings Social media remains a powerful tool for understanding patient experiences of fertility and reproductive health. Experts must continue to engage with these platforms in order to amplify the positives and mitigate negative impacts such as misinformation, poor mental health and barriers to achieving reproductive intentions. Trial registration number No

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,038
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,037
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0080,038
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0130,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,111
Tête enseignante GPT0,415
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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