Psychiatric Morbidity Among Housemaids in Kuwait III: Vulnerability Factors
Bibliographic record
Abstract
BACKGROUND: Housemaids are a relatively homogenous immigrant subgroup in terms of their gender; ethnic origin; and socio-cultural, educational and occupational background. Psychiatric morbidity among housemaids is two to five times higher than the native female population. AIMS: To determine the possible pre-immigration risk factors for prospective psychiatric breakdown among the housemaids. METHODS: The sample consisted of all the housemaids (N = 197) hospitalised during the two-year study period. The controls comprised all the newly arrived housemaids (N = 502). The measures obtained included demographic characteristics and previous history of physical illness, psychiatric illness, hospitalisation and family history of psychiatric disorder. RESULTS: More than a quarter of the hospitalised group broke down within one month of their arrival. The hospitalised group had a significant excess of Sri Lankan housemaids; non-Muslims; those with less than four years of education and those with a previous history of physical illness, psychiatric illness or hospitalisation. CONCLUSIONS: A number of potential risk factors results in premature repatriation of housemaids on mental health grounds. Preventive measures involving recruitment procedures and pre-departure orientation courses are needed to minimise the expatriate failure among the housemaids.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".