ASSESSING E-CIGARETTE’S KNOWLEDGE AND PRACTICES AMONG COLLEGE STUDENTS AMID COVID-19 PANDEMIC
Notice bibliographique
Résumé
Background: E-cigarettes are a relatively new form of smokeless tobacco that has gained significant popularity in the past decade (American Lung Association, 2020). These products contain several harmful chemicals and compounds that can have long-term health effects. Among college students, knowledge and attitude have a large impact on the E-cigarette practices among this population and hence the need to address it is essential, especially with the possible impact that COVID-19 has had on many. Methods: This study utilized a qualitative research method to gather data that is focused on the Knowledge, Attitude, and Practices of college students relating to E-cigarette usage. A 14-question survey was developed using the KAP model and distributed electronically to three different introductory health science courses. Following the distribution of the survey, a voice recorded PowerPoint containing evidence-based education and resources on E-cigarettes was distributed to the instructors to provide an educational resource to surveyed participants. The results of this study were analyzed through SPSS statistical analysis version 27.0 and Microsoft Excel version 2013. Results: Findings from this study suggests that the majority of participants (93.2%) were aware that E-cigarettes could be harmful to their health. However, 31% of participants considered E-cigarettes to be either somewhat harmful or a little harmful. Furthermore, 33.8% of the participants stated they strongly agreed, agreed, or were neutral to the statement that E-cigarettes are safe when compared to regular cigarettes. This study also found that third year students had the highest rates of E-cigarette use among participants totaling 55% of all users. Finally, this study found that 27.0% of participants had used E-cigarettes at least once in their lifetime. Since the start of the COVID-19 pandemic, 6.8% of E-cigarette users stated that they had seen an increase in their usage of these products. Conclusion: This study aimed to assess for the Knowledge, Attitude, and Practices of E-cigarette use among college students at a public university in Southern California during the COVID-19 pandemic. The results suggest that there is currently a gap in knowledge relating to E-cigarettes that needs to be addressed. Many study participants were unsure of the addictive properties of E-cigarettes and considered these products to be safe when compared to traditional cigarettes. Furthermore, there is a possible relationship between COVID-19 pandemic and increased or continued use of E-cigarettes that merits further study. The use of evidence-based education among this population is highly recommended to discourage consumption among college students.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 ».