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Enregistrement W3207415141 · doi:10.2196/31172

Exploring Middle School Students’ Perspectives on Using Serious Games for Cancer Prevention Education: Focus Group Study

2021· article· en· W3207415141 sur OpenAlexvenueno aff
Olufunmilola Abraham, Lisa Szela, Mahnoor Khan, Amrita Geddam

Notice bibliographique

RevueJMIR Serious Games · 2021
Typearticle
Langueen
DomainePsychology
ThématiqueEducational Games and Gamification
Établissements canadiensnon disponible
Organismes subventionnairesNational Institutes of HealthNational Center for Advancing Translational SciencesInstitute for Clinical and Translational Research, University of Wisconsin, MadisonUniversity of Wisconsin-Madison
Mots-clésCancer preventionFocus groupPsychological interventionCurriculumPromotion (chess)Health promotionMedicinePopulationCancerPsychologyMedical educationGerontologyPublic healthNursingPedagogyEnvironmental healthPolitical scienceMarketing

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Cancer in the United States is a leading cause of mortality. Educating adolescents about cancer risks can improve awareness and introduce healthy lifestyle habits. Public health efforts have made significant progress in easing the burden of cancer through the promotion of early screening and healthy lifestyle advocacy. However, there are limited interventions that educate the adolescent population about cancer prevention. Previous studies have demonstrated the effectiveness of serious games (SGs) to teach adolescents about healthy lifestyle choices, but few research efforts have examined the utility of using SGs to educate youth specifically on cancer prevention. OBJECTIVE: This study aimed to investigate middle school students' preferences for the use of SGs for cancer prevention education. The study also characterized the students' perceptions of desired game design features for a cancer prevention SG. METHODS: Focus groups were held to allow adolescents to review a game playbook and discuss gaming behaviors and preferences for an SG for cancer education. The game playbook was developed based on "Cancer, Clear & Simple," a curriculum intended to educate individuals about cancer, prevention, self-care, screening, and detection. In the game, the player learns that they have cancer and is given the opportunity to go back in time to reduce their cancer risk. A focus group discussion guide was developed and consisted of questions about aspects of the playbook and the participants' gaming experience. The participants were eligible if they were 12 to 14 years old, could speak and understand English, and had parents who could read English or Spanish. Each focus group consisted of 5 to 10 persons. The focus groups were audio recorded and professionally transcribed; they were then analyzed content-wise and thematically by 2 study team members. Intercoder reliability (kappa coefficient) among the coders was reported as 0.97. The prevalent codes were identified and categorized into themes and subthemes. RESULTS: A total of 18 focus groups were held with 139 participants from a Wisconsin middle school. Most participants had at least "some" gaming experience. Three major themes were identified, which were educational video games, game content, and purpose of game. The participants preferred customizable characters and realistic story lines that allowed players to make choices that affect the characters' outcomes. Middle school students also preferred SGs over other educational methods such as lectures, books, videos, and websites. The participants desired SGs to be available across multiple platforms and suggested the use of SGs for cancer education in their school. CONCLUSIONS: Older children and adolescents consider SGs to be an entertaining tool to learn about cancer prevention and risk factors. Their design preferences should be considered to create a cancer education SG that is acceptable and engaging for 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 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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,566
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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 Opus0,116
Tête enseignante GPT0,416
Écart entre enseignants0,300 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations7
Publié2021
Routes d'admission1
Résumé présentoui

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