Development and validation of the Japanese version of the Auckland Individualism and Collectivism Scale: Relationship between individualism/collectivism and mental health
Notice bibliographique
Résumé
The association between cultural factors and mental health has been reported through cross-cultural studies. Most studies addressing cultural effects on psychopathology have focused on two dimensions of cultural factors: individualism and collectivism. Individualism pertains to valuing personal independence, such as competition, uniqueness, and responsibility (Shulruf et al., 2007). On the other hand, collectivism involves valuing personal interdependence, such as advice and harmony (Shulruf et al., 2007). According to Hofstede (2010), individualistic countries include mainly Western countries, such as the United States (U.S.), Australia, the United Kingdom, Germany, Canada, the Netherlands, and New Zealand. Collectivistic countries include mainly East Asian countries, such as Japan, Korea and China. Oyserman et al. (2002) reviewed the literature of cross-cultural studies and suggested that individualism and collectivism are not two-dimensional but are divided into multiple domains for each variable. Specifically, they reported that individualism includes competition, uniqueness, and direct communication, whereas collectivism includes harmony, advice, and collective goals. Shulruf et al. (2007) developed the Auckland Individualism and Collectivism Scale (AICS), based on the components of individualism/collectivism identified by Oyserman et al. (2002). The scale has been reported to have high internal consistency, factor structure validity, and measurement invariance across cultures (Shulruf et al., 2023). The AICS has been translated in 12 different languages, including Turkey, Germany, Nepal, Portugal, China, and Italy (Shulruf et al., 2023), making it a useful assessment tool for examining cross-cultural differences. However, there is no Japanese-language version of the AICS. The development of a Japanese version of the AICS (J-AICS) would clarify the specific cultural characteristics of the Japanese and contribute to examine cultural comparisons with other countries, such as the U.S., Australia, and Germany, which are considered as individualistic countries, and China and Korea, which are collectivistic countries. Therefore, we will develop the J-AICS and examine its reliability and validity in this study. Specifically, we will examine internal consistency, factorial validity, and convergent validity. In addition, previous studies have revealed the relationships between individualism/collectivism and mental health (Germani et al., 2021; Nezlek & Humphrey, 2023). Nezlek & Humphrey (2023) reported that collectivism factors were negatively correlated with depressive symptoms and positively correlated with interpersonal well-being. However, the association between cultural factors in individualism and collectivism and mental health has not been fully examined in Japan. By examining cultural factors as measured by the J-AICS and mental health, it is possible to identify which cultural variables are associated with mental health. This finding would contribute significantly to the understanding of culture and mental health. Therefore, this study will also examine the association between cultural factors related to individualism and collectivism and variables related to mental health.
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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».