Understanding Pediatric Experiences With Symptomatic Varicoceles: Mixed Methods Study of an Online Varicocele Community
Notice bibliographique
Résumé
BACKGROUND: Varicoceles affect up to 30% of postpubertal adolescent males. Studying this population remains difficult due to this topic's sensitive nature. Using the popularity of social media in this cohort and natural language processing (NLP) techniques, our aim was to identify perceptions of adolescent males on an internet varicocele forum to inform how physicians may better evaluate and counsel this pediatric population. OBJECTIVE: We aimed to characterize themes of discussion and specific concerns expressed by adolescents using a mixed methods approach involving quantitative NLP and qualitative annotation of an online varicocele community. METHODS: We extracted posts from the Reddit community "r/varicocele" (5100 members) with criteria of discussant age ≤21 years and word count >20. We used qualitative thematic analysis and the validated constant comparative method, as well as an NLP technique called the meaning extraction method with principal component analysis (MEM/PCA), to identify discussion themes. Two investigators independently interrogated 150 randomly selected posts to further characterize content based on NLP-identified themes and calculated the Kaiser-Meyer-Olkin (KMO) statistic and the Bartlett test. Both quantitative and qualitative approaches were then compared to identify key themes of discussion. RESULTS: A total of 1103 posts met eligibility criteria from July 2015 to June 2022. Among the 150 randomly selected posts, MEM/PCA and qualitative thematic analysis separately revealed key themes: an overview of varicocele (40/150, 27%), management (29/150, 19%), postprocedural experience (28/150, 19%), seeking community (26/150, 17%) and second opinions after visiting a physician (27/150, 18%). Quantitative analysis also identified "hypogonadism" and "semen analysis" as concerns when discussing their condition. The KMO statistic was >0.60 and the Bartlett test was <0.01, indicating the appropriateness of MEM/PCA. The mean age was 17.5 (SD 2.2; range 14-21) years, and there were trends toward higher-grade (40/45, 89% had a grade of ≥2) and left-sided varicoceles. Urologists were the topic of over 50% (53/82) of discussions among discussants, and varicocelectomy remained the intervention receiving the most interest. A total of 60% (90/150) of discussants described symptomatic varicoceles, with 62 of 90 reporting pain, 24 of 90 reporting hypogonadism symptoms, and 45 of 90 reporting aesthetics as the primary concern. CONCLUSIONS: We applied a mixed methods approach to identify uncensored concerns of adolescents with varicoceles. Both qualitative and quantitative approaches identified that adolescents often turned to social media as an adjunct to doctors' visits and to seek peer support. This population prioritized symptom control, with an emphasis on pain, aesthetics, sexual function, and hypogonadism. These data highlight how each adolescent may approach varicoceles uniquely, informing urologists how to better interface with this pediatric population. Additionally, these data may highlight the key drivers of decision-making when electing for procedural management of varicoceles.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».