Does screening mode matter? A repeated cross-sectional study of computer self-administered vs. clinician-administered screening of youth substance use in pediatric primary care
Notice bibliographique
Résumé
Introduction Universal youth substance use screening in pediatric primary care enables early detection and intervention, which, in turn, can help decrease the risk of problematic substance use. Screening mode [electronic self-administered survey (SA) vs. clinician-administered interview (CA)] may influence whether substance use is reported and, therefore, clinical decisions about whether and how to intervene. Methods We performed a secondary data analysis of substance use screening responses collected between 2018 and 2022 from individuals aged 12–20 years who were seen at 314 US pediatric practices utilizing the Comprehensive Health and Decision Information System (CHADIS) online clinical process support system. Patients responded to the Car, Relax, Alone, Forget, Family/Friends, and Trouble (CRAFFT), a well-validated adolescent substance use screening tool that measures past-12-month alcohol, cannabis, and other substance use (“anything else to get high”). We compared substance use rates by screening mode (SA vs. CA) using logistic regression modeling with generalized estimating equations to account for data clustering within practices and patients, controlling for US region, sex, submission year, and patient age in days. We stratified analyses by age group (12–13; 14–15; 16–17; 18–20 years) and sex (male vs. female). Results Data represented 201,134 screening responses among N = 130,688 patients. Patients were 50.9% female; 31.3% were from the Northeast, 6.7% from the Midwest, 52.7% from the South, and 9.4% from the West. Of the screening responses, 24.6% were from 12–13-year-olds, 29.5% from 14–15-year-olds, 28.7% from 16–17-year-olds, and 17.2% from 18–20-year-olds. Mode for the screening responses was 74.9% SA and 25.1% CA. Compared with CA screening, SA screening was associated with significantly higher adjusted odds of report of any substance use (adjusted odds ratio, 95% confidence interval by age group: 12–13 years 1.75, 1.43–2.15; 14–15 years 1.21, 1.11–1.33; 16–17 years 1.32, 1.24–1.41; 18–20 years 1.48, 1.39–1.58). Alcohol and cannabis, the most prevalent past-12-month substances used among all age groups, demonstrated similar patterns when examined individually. Report of other substance use only differed by screening mode among 12–13-year-olds, but overall, prevalence was low (0.1%–2.1%). Conclusion Electronic self-administered screening was associated with higher rates of reported substance use compared with clinician-administered interviews among youth being seen in primary care, suggesting that self-administered screening may improve substance use detection.
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 | 0,016 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».