Comparing the Influences of Spouses or Partners With Other Family Members in the Ability of Young Asian Americans to Maintain a Healthy Lifestyle
Bibliographic record
Abstract
The relationship between family dynamics and health has been extensively studied, but the specific pathways involved are not yet fully understood. The role of intimate partner relationships in promoting and maintaining healthy lifestyle behaviors remains understudied, particularly in minority populations. This study addressed this gap by examining how frequent spousal and familial interactions affect healthy lifestyle behaviors in young Asian Americans. Survey data from Asian American adults aged 18 to 35, collected in March 2021, is used to compare two groups: one interacting most with an intimate partner and the other interacting most with other non-intimate family members. The results showed that young Asian Americans interact most with their spouses/partners and mothers. Participants who interacted most frequently with their spouses/partners reported a greater influence in maintaining a healthy lifestyle, particularly in the domains of exercise and sleep. Moreover, those who interacted more with their spouses/partners exhibited a greater sense of connectedness, which impacted spousal and personal influence on healthy lifestyle behaviors. The findings suggest that promoting interaction and fostering stronger spousal/partner relationships can positively influence the healthy lifestyle behaviors of young Asian Americans.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".