The Effects of Self-Control and Self-Awareness on Social Media Usage, Self-Esteem, and Affect
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Notice bibliographique
Résumé
Background: With the increase in social media usage due to the COVID-19 pandemic, investigation into factors that mitigate excessive and problematic usage is warranted. Factors such as self-awareness were included in the analysis of social media usage as it leads individuals to focus on personal ideal standards, begging the question as to whether high self-awareness limits problematic social media usage. Self-control, strengthened by self-awareness, was measured to examine its involvement in limiting excessive social media usage. Self-esteem and affect were included in analyses as they have never been examined in relation to both self-awareness and social media usage. It was hypothesized that self-awareness would be negatively related to social media usage, given self-control levels are high. Furthermore, self-awareness would be positively related to self-control, self-esteem, and affect, given social media usage is low. Methods: 125 psychology students (73.6% female) completed scales on self-awareness, social media usage, self-esteem, self-control, and affect. Linear regressions with moderation and mediation were conducted. Results: No moderation occurred but it was found that self-control mediated the relationship between self-awareness and social media usage. Self-awareness was positively related to self-esteem, self-control, and positive affect. Social media usage was not significantly related to self-esteem, positive affect, or negative affect. Self-control acted as a mediator in numerous analyses involving self-awareness and social media usage. Conclusions: Self-awareness promotes self-control, resulting in reduced social media usage. Future research should focus on cultivating self-awareness and the consequent self-control to help avoid the negative outcomes associated with social media usage (e.g., reduced self-esteem).
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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 | 0,001 | 0,001 |
| 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 | 0,001 | 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