Knowledge, Beliefs, and Practices of a Cambodian Traditional Postpartum Medicine, Sra Thnam, among Cambodian Women (15-30 Years) Living in Massachusetts.
Bibliographic record
Abstract
Abstract Background: Cambodian refugees arrived in the U.S. with limited English proficiency, low educational attainment, poor health status, and significant trauma. Combined with poor healthcare access, this fostered an environment for continued reliance on cultural health practices. Maternal health, including the postpartum period, was particularly influenced by traditional Cambodian medicine. This study investigated associations between sociodemographic factors and Cambodian women’s knowledge, beliefs, and practices related to sra thnam, a traditional postpartum medicine used in the Cambodian diaspora. Methods: This cross-sectional study was conducted with Cambodian women ages 15-35 years (N=162) living in Massachusetts. A community-academic team developed study materials and administered surveys and focus groups on knowledge, beliefs, and use of sra thnam. Focus group discussions were entered into NVivo 10. Survey data was analyzed using Stata version 14.0 and SPSS version 27. A series of statistical analyses were performed to assess associations between participant use of sra thnam and socio-demographic, health, and psychometric factors. Results: Knowledge of sra thnam was almost universal (92%), with 44% these participants reporting ever consuming it. Pregnant women (N=56) reported not having consumed sra thnam during the current pregnancy and after childbirth, 52% reported an intention to consume sra thnam, 42.9% did not, and 5.4% were uncertain. After adjusting for covariates, being born in the U.S., having at least one child, older age, and larger households were predictive of ever consuming sra thnam. Conclusion: These findings show traditional postpartum knowledge and practices are common among Cambodian women living in the U.S. These practices may have benefits, as well as pose some risks, for maternal health. Given that perceptions of pregnancy, childbirth, and postpartum experiences are nested in culture, it is important that healthcare providers are aware of traditional health beliefs and practices in refugee and immigrant communities. Greater understanding of traditional postpartum practices can facilitate culturally relevant support and health care services to mothers.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".