Social Class and Changes in Australian Women's Affect and Alcohol Consumption During COVID-19
Notice bibliographique
Résumé
Introduction: Before the pandemic, mid-life women in Australia were among the “heaviest” female alcohol consumers, giving rise to myriad preventable health risks. This paper uses an innovative model of social class within a sample of Australian women to describe changes in affective states and alcohol consumption patterns across two time points during COVID-19. Methods: Survey data were collected from Australian mid-life women (45–64 years) at two time points during COVID-19—May 2020 ( N = 1,218) and July 2020 ( N = 799). We used a multi-dimensional model for measuring social class across three domains—economic capital (income, property and assets), social capital (social contacts and occupational prestige of those known socially), and cultural capital (level of participation in various cultural activities). Latent class analysis allowed comparisons across social classes to changes in affective states and alcohol consumption patterns reported at the two time points using alcohol consumption patterns as measured by the Alcohol Use Disorders Identification Test—Consumption (AUDIT-C) and its component items. Results: Seven social classes were constructed, characterized by variations in access to capital. Affective states during COVID-19 differed according to social class. Comparing between the survey time points, feeling fearful/anxious was higher in those with high economic and cultural capital and moderate social capital (“emerging affluent”). Increased depression was most prominent in the class characterized by the highest volumes of all forms of capital (“established affluent”). The social class characterized by the least capital (“working class”) reported increased prevalence of uncertainty, but less so for feeling fearful or anxious, or depressed. Women's alcohol consumption patterns changed across time during the pandemic. The “new middle” class—a group characterized by high social capital (but contacts with low prestige) and minimal economic capital—had increased AUDIT-C scores. Conclusion: Our data shows the pandemic impacted women's negative affective states, but not in uniform ways according to class. It may explain increases in alcohol consumption among women in the emerging affluent group who experienced increased feelings or fear and anxiety during the pandemic. This nuanced understanding of the vulnerabilities of sub-groups of women, in respect to negative affect and alcohol consumption can inform future pandemic policy responses designed to improve mental health and reduce the problematic use of alcohol. Designing pandemic responses segmented for specific audiences is also aided by our multi-dimensional analysis of social class, which uncovers intricate differences in affective states amongst sub-groups of mid-life women.
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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 | 0,003 | 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 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 ».