"You are the first person to ask me how I'm doing sexually": sexual and reproductive health needs and sexual behaviours among migrant people in transit through Panama
Bibliographic record
Abstract
Background Unprecedented numbers of migrant people transiting through the Darién Gap at the Panama-Colombia border were recorded in 2021 and 2022. Data on sexual and reproductive health (SRH) needs and service provision among migrant people in transit is generally extremely sparse. This study aimed to collect personal accounts of sexual behaviours and SRH needs and access to services among migrant people in transit through Panama. Methods We conducted a rapid-assessment qualitative study using semi-structured interviews during June-July 2022. Participants were migrant people in transit at three locations across Panama: (i) at the Migrant Reception Station (MRS) in Darién province at the Panama-Colombia border, (ii) in the city of David near the Costa Rica-Panama border, and (iii) at the Costa Rica-Panama border. Migrant peoples (>18 years) were invited to participate using purposive sampling. Results Overall, 26 adult migrant people (16 men, 10 women) across the three sites participated in the study. We identified three overarching themes from the interviews: (1) increased need for SRH service provision, (2) experiences of sex, relationships, and transactional sex, and (3) vulnerability to exploitation and sexual violence. All accounts reported that no formal SRH care was present during the journey through the Gap and described as inconsistent at the MRS in Darién. Provision of gynaecological or genital examinations, laboratory testing for urinary tract or STI, and prenatal care were mentioned to be the most pressing needs. Participants reported a change in their sexual behaviour while travelling, whether a decline in sexual libido or preference towards short-term partners. Most female participants recounted constantly fearing sexual violence during the journey through the Gap and several respondents reported witnessing incidents of sexual and other forms of violence. Conclusion There are significant unmet needs regarding SRH care during the journey of migrant people transiting through the Darién Gap, at the MRS in the Darién province, and across Panama. Provision of antenatal care, rapid testing for HIV/STI, condom distribution, and care for victims of sexual violence would significantly reduce adverse SRH outcomes and improve the well-being of migrant people, even when in transit.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".