Menopausal transition experiences and management strategies of Chinese immigrant women: a scoping review
Bibliographic record
Abstract
IMPORTANCE AND OBJECTIVE: Chinese immigrants are among some of the fastest growing groups in many Western countries, and experience challenges such as language barriers, education gaps, and gender discrimination, which highlights the need for special attention and consideration in Western health care. The purpose of this scoping review is to summarize existing research on the menopausal experiences of Chinese immigrant women (CIW). METHODS: This scoping review was written in accordance with PRISMA guidelines. MEDLINE, PsycINFO, CINAHL, AgeLine, ERIC, ProQuest, Nursing and Allied Health Database, PsycARTICLES, Sociology Database, and Education Research Complete were utilized for the literature search. Articles were included if they examined CIW experiencing menopausal transition. A total of 18 studies were included for review. DISCUSSION AND CONCLUSION: Findings suggested that CIW experienced a variety of physical symptoms, including muscle and joint pain, urogenital symptoms, vasomotor symptoms, weight gain, decreased physical strength, vision changes, and skin changes. Muscle and joint pain were particularly prevalent and emphasized. CIW also experienced psycho-behavioral symptoms including emotional changes, depression, memory loss, and sexual dysfunction. However, they had a decreased concern regarding symptoms of sexual dysfunction and decreased libido when compared with women from Western cultures. CIW interpreted menopause as a natural aging process involving the next step in life. Cultural expectations of stoicism and silence may cause immigrant women to be less vocal about their menopause experiences and result in feelings of loneliness. Acculturation may be both a facilitator and a barrier to a healthy menopausal transition. CIW were resistant to Western Medicine management such as hormone therapy but were willing to incorporate traditional medicine into their health care. They believed that a healthy mentality was important and used various psychocognitive strategies to maintain a good quality of life. Healthcare providers, researchers, and policymakers need to consider the unique characteristics of CIW's menopausal transition in research, intervention innovation, and practice.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".