Development and validation of the Japanese version of the Auckland Individualism and Collectivism Scale: Relationship between individualism/collectivism and mental health
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".