User Perceptions of E-Cigarette Cessation Apps: Content Analysis of App Reviews (Preprint)
Notice bibliographique
Résumé
BACKGROUND Vaping rates in Canada are continuing to increase. In 2019, 4.7% of Canadians used an electronic cigarette (e-cigarette) in the past 30 days, which rose to 5.8% in 2022. In the same year, young adults aged 20-24 years demonstrated the highest use among Canadians, at 19.7%. Given this, existing interventions are not resulting in the desired outcomes, and smartphone apps have the potential to address this gap. Although limited, current evidence highlights that apps can be an effective cessation support; however, a gap persists in understanding the user experience of vaping cessation apps. OBJECTIVE The purpose of this study was to explore the user experience of vaping cessation apps through an analysis of app reviews. More specifically, this study aimed to identify positive and negative experiences of app users, as well as highlight recommendations from app users to improve the quality of these apps. METHODS Vaping cessation apps were identified through searches on the Canadian and US versions of Apple App Store and Android Google Play Store in August 2022. Searches revealed a total of 11 vaping cessation apps with app reviews, which resulted in a total of 310 reviews for analysis. Review material was analyzed using a deductive content analysis approach and divided into the following primary categories: content, functionality, aesthetic, cost, and other. These were further divided into 3 secondary categories (praise, criticism, and recommendations) and various tertiary categories. RESULTS The most discussed primary categories were content, functionality and cost. Comments regarding content tended to be positive (n=103, 33.2%), praising features, such as hypnosis audio sessions (n=29, 28.2%) and tracking features. In contrast, comments tended to criticize functionality (n=58, 18.7%), indicating issues with the functioning of an app that either made the whole app unusable (n=29, 50%) or a specific feature unusable (n=28, 48.3%). Reviews regarding cost were mixed, with 27 (8.7%) positive comments, the majority of these encompassing reviewers satisfied with their purchase (n=17, 63%), and 38 (12.3%) negative comments, including individuals both unsatisfied with their purchase (n=15, 39.5%) and unsatisfied with the free version (n=12, 31.6%). CONCLUSIONS This study is the first of its kind to evaluate the user experience with vaping cessation apps via an analysis of app reviews. App developers may benefit from reading our findings to identify areas to focus on when developing and updating apps. Our study forms a basis for the development of future vaping interventions, as well as future studies. Future research should be conducted on vaping cessation interventions with an emphasis on the user experience because there is limited research available for comparison with the promising results from this study.
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 | 0,097 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,008 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 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 ».