The design and implementation of a randomized controlled trial of a risk reduction and human immunodeficiency virus prevention videogame intervention in minority adolescents: <i>PlayForward: Elm City Stories</i>
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
BACKGROUND: To address the need for risk behavior reduction and human immunodeficiency virus prevention interventions that capture adolescents "where they live," we created a tablet-based videogame to teach skills and knowledge and influence psychosocial antecedents for decreasing risk and preventing human immunodeficiency virus infection in minority youth in schools, after-school programs, and summer camps. METHODS: We developed PlayForward: Elm City Stories over a 2-year period, working with researchers, commercial game designers, and staff and teens from community programs. The videogame PlayForward provides an interactive world where players, using an avatar, "travel" through time, facing challenges such as peer pressure to drink alcohol or engage in risky sexual behaviors. Players experience how their choices affect their future and then are able to go back in time and change their choices, creating different outcomes. A randomized controlled trial was designed to evaluate the efficacy of PlayForward. Participants were randomly assigned to play PlayForward or a set of attention/time control games on a tablet at their community-based program. Assessment data were collected during face-to-face study visits and entered into a web-based platform and unique real-time "in-game" PlayForward data were collected as players engaged in the game. The innovative methods of this randomized controlled trial are described. We highlight the logistical issues of conducting a large-scale trial using mobile technology such as the iPad(®), and collecting, transferring, and storing large amounts of in-game data. We outline the methods used to analyze the in-game data alone and in conjunction with standardized assessment data to establish correlations between behaviors during gameplay and those reported in real life. We also describe the use of the in-game data as a measure of fidelity to the intervention. RESULTS: In total, 333 boys and girls, aged 11-14 years, were randomized over a 14-month period: 166 were assigned to play PlayForward and 167 to play the control games. To date (as of 1 March 2016), 18 have withdrawn from the study; the following have completed the protocol-defined assessments: 6 weeks: 271 (83%), 3 months: 269 (84%), 6 months: 254 (79%), 12 months: 259 (82%), and 24 months: is ongoing with 152 having completed out of the 199 participants (76%) who were eligible to date (assessment windows were still open). CONCLUSION: Videogames can be developed to address complex behaviors and can be subject to empiric testing using community-based randomized controlled trials. Although mobile technologies pose challenges in their use as interventions and in the collection and storage of data they produce, they provide unique opportunities as new sources of potentially valid data and novel methods to measure the fidelity of digitally delivered behavioral interventions.
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.
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 | 0,053 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découle