Redefining intimacy: a qualitative study on sexual function experiences and perspectives among migrant and refugee women in South Australia
Bibliographic record
Abstract
BACKGROUND: Sexual function is a fundamental aspect of sexual health, yet migrant and refugee women from Low- and Middle-Income Countries (LMICs) often face unique challenges in navigating intimacy and sexual function post-migration. While sociocultural norms, migration-related stressors, and healthcare access influence their experiences, yet these perspectives remain underexplored. METHODS: This qualitative exploratory study explored the perspectives and experiences of sexual function among first-generation migrant and refugee women from low- and middle-income countries residing in South Australia. Semi-structured interviews were conducted with 20 reproductive-aged cisgender heterosexual women from diverse cultural backgrounds, recruited through multiple culturally appropriate approaches including community organisations supporting migrant and refugee populations and online outreach via the purpose-built RISE website. Although multilingual support and professional interpreters were available, all participants opted to be interviewed in English. Interviews were conducted by a trained qualitative researcher with shared migrant background, and reflexive, inductive thematic analysis guided by social constructivist epistemology was used to identify key influences on sexual health and intimacy. RESULTS: Participants reported that cultural norms, sociocultural expectations, and migration-related stressors shaped their sexual experiences. Many described difficulties in navigating cultural taboos, communication barriers, and limited access to culturally sensitive healthcare services. Conversely, while migration provided opportunities for increased sexual autonomy, self-discovery, and improved partner communication, deeply ingrained cultural beliefs and emotional struggles continued to impact their sexual well-being. CONCLUSIONS: The findings highlight the need for culturally sensitive, gender-appropriate sexual health services and the removal of financial, linguistic, and systemic barriers to healthcare access. Healthcare providers, policymakers, and community organisations play a crucial role in fostering inclusive environments that support migrant and refugee women's sexual health and well-being.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".