Health status of Chinese women in Northern Ireland: SF-36 health survey
Bibliographic record
Abstract
In contrast to the remainder of the UK, the largest ethnic minority group inNorthern Ireland is Chinese. There are few research findings on the health status of Chinese in the UK, especially with respect to women. This research aimed to investigate the general health status of Chinese women in Northern Ireland, and to make suggestions for health promotion. A survey methodology was used. This consisted of questionnaires that included demographic measures, open-ended questions and the SF-36 (Hong Kong version) health survey. A convenience sample of non-pregnant Chinese women in Northern Ireland (n = 48) was collected during 2002–2003. Data were analysed by using the online scoring system, andsubsequently coded into and analysed using SPSS (v11.0). The findings showed that more than a quarter of the participants understood only a little English, which was a potential obstacle to obtaining health information. About 26.6% of participants stated that they were suffering from health problems, for example, anaemia, bronchiectasis, back pain anddepression. SF-36 results showed that the psychosocial health status of Chinese women living in Northern Ireland was significantly below average for women in the UK. However, the physical health status of the participants was at or above the average for the UK female population. It was concluded that the health status of Chinese women might be influenced by multiple factors, for example, their sociocultural characteristics and beliefs, heterogeneity and interaction of risk factors,acculturated dietary intake, late hospitalisation and high stress. Psychological and social wellbeing need to be improved, and more social support should be provided to improve their overall health status. Health professionals should be aware of the transcultural issues in a multicultural environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".