Using the Healthy Native Youth Implementation Toolbox to Provide Web-Based Adolescent Health Promotion Decision Support to American Indian and Alaska Native Communities: Implementation Study
Notice bibliographique
Résumé
Background: American Indian and Alaska Native (AI/AN) youth experience numerous health inequities, including those in sexual, reproductive, and mental health. Implementation of culturally relevant, age-appropriate evidence-based programs may mitigate these inequities. However, numerous barriers limit the adoption and implementation of evidence-based adolescent health promotion programs in AI/AN communities. Objective: This study examines user reach and engagement from 2022 to 2024 of web-based decision support (the Healthy Native Youth [HNY] website and the embedded HNY Implementation Toolbox), designed to increase the implementation of evidence-based adolescent health promotion programming in AI/AN communities. Methods: Promotional strategies were designed for optimal geographic reach to Tribal organizations, opinion leaders, federal decision makers, and funders. Promotional channels included grassroots, community, and professional networks. We used Google Analytics to examine the uptake of the HNY website and HNY Implementation Toolbox from January 2022 to January 2024. The Toolbox provides culturally relevant tools and templates to help users navigate through 5 phases of program adoption and implementation: Gather, Choose, Prepare, Implement, and Grow. User reach was estimated by demographic characteristics and geographic location; user engagement was estimated by visit frequency and duration, bounce rates, and frequency of page and tool access. Results: Over the study period, page views of the HNY website and HNY Toolbox increased 10-fold and 27-fold, respectively. Over the 2-year evaluation period since the Toolbox "go live" date, approximately 1 in 8 users of the HNY website visited the Toolbox. The majority of HNY website users were located in Washington (n=1515), California (n=1290), and Oregon (n=1019) and were aged between 18 and 24 (n=1559, 21.7%) and 25-34 (n=1676, 23.29%) years. Toolbox users were primarily located in California (n=1238), Washington (n=1142), and Oregon (n=986), mostly aged between 35 and 44 years (n=444, 35%). Both website and Toolbox users were primarily female, who accessed the site and Toolbox via desktop computers. The most frequently accessed phase pages within the Implementation Toolbox were Gather, Choose, Implement, and Prepare, as supported by bounce rates and average time on page. The most viewed phase was the "Gather" phase, with 3278 views. The most frequently downloaded tools within the Toolbox were Gather: Community Needs and Resource Assessment, with 136 downloads. The phases and tools accessed may have differed based on the user's goal or stage of implementation. Conclusions: Findings indicate positive initial reach and engagement of the HNY website and HNY Implementation Toolbox among AI/AN educators that has consistently increased over the 2 years. The provision of web-based decision support that guides AI/AN users through the adoption, implementation, and maintenance of culturally relevant, age-appropriate, evidence-based adolescent health promotion programs in their communities may help increase the implementation of effective adolescent health promotion programs to ultimately increase health equity among AI/AN youth.
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 | 0,015 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».