Quittr: The Design of a Video Game to Support Smoking Cessation
Notice bibliographique
Résumé
BACKGROUND: Smoking is recognized as the largest, single, preventable cause of death and disease in the developed world. While the majority of smokers report wanting to quit, and many try each year, smokers find it difficult to maintain long-term abstinence. Behavioral support, such as education, advice, goal-setting, and encouragement, is known to be beneficial in improving the likelihood of succeeding in a quit attempt, but it remains difficult to effectively deliver this behavioral support and keep the patient engaged with the process for a sufficient duration. In an attempt to solve this, there have been numerous mobile apps developed, yet engagement and retention have remained key challenges that limit the potential effectiveness of these interventions. Video games have been clearly linked with the effective delivery of health interventions, due to their capacity to increase motivation and engagement of players. OBJECTIVE: The objective of this study is to describe the design and development of a smartphone app that is theory-driven, and which incorporates gaming characteristics in order to promote engagement with content, and thereby help smokers to quit. METHODS: Game design and development was informed by a taxonomy of motivational affordances for meaningful gamified and persuasive technologies. This taxonomy describes a set of design components that is grounded in well-established psychological theories on motivation. RESULTS: This paper reports on the design and development process of Quittr, a mobile app, describing how game design principles, game mechanics, and game elements can be used to embed education and support content, such that the app actually requires the user to access and engage with relevant educational content. The next stage of this research is to conduct a randomized controlled trial to determine whether the additional incentivization game features offer any value in terms of the key metrics of engagement-how much content users are consuming, how many days users are persisting with using the app, and what proportion of users successfully abstain from smoking for 28 days, based on user-reported data and verified against a biochemical baseline using cotinine tests. CONCLUSIONS: We describe a novel, and theoretically-informed mobile app design approach that has a broad range of potential applications. By using the virtual currency approach, we remove the need for the game to comprehensively integrate the healthy activity as part of its actual play mechanics. This opens up the potential for a wide variety of health problems to be tackled through games where no obvious play mechanic presents itself. The implications of this app are that similar approaches may be of benefit in areas such as managing chronic conditions (diabetes, heart disease, etc), treating substance abuse (alcohol, illicit drugs, etc), diet and exercise, eating disorders (anorexia, bulimia, and binge eating), and various phobias.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| 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) | 0,001 | 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 tête enseignante, 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 ».