Leveraging telemedicine to explore contraceptive use and attitudes among refugee women: an observational cross-sectional analysis
Bibliographic record
Abstract
OBJECTIVE: The study examined how refugees in Pakistan who accessed e-health clinics to get sexual and reproductive health (SRH) care perceived and used contraception. The prevalence, attitudes and variables affecting the adoption or non-adoption of contraceptives were the intended outcomes. The study additionally investigated how frequently refugee women used these clinics and how satisfied they were with the way telemedicine met their SRH needs. DESIGN: An observational cross-sectional methodology was used in this study to observe SRH-related telemedicine consultations. The study was conducted from 17 April 2024 to 31 May 2024. SETTING: The data collection was done using a survey instrument and it was preserved in the organisation's electronic health record. The investigation was conducted at nine Sehat Kahani e-health clinics, four in Balochistan and five in Khyber Pakhtunkhwa provinces. PARTICIPANTS: The study enrolled 576 women who were refugees; they were recruited after they attended Sehat Kahani e-health clinics for SRH services and gave their consent to participate. RESULTS: The study reported that refugee women visiting e-health clinics used contraception at a significant rate (68.1%). The majority (71.4%) of women rely on partners for family planning decisions. The primary reasons for using contraception were child spacing (33.2%) and preventing unintended pregnancy (31.1%). Housewives and those with an income of 20 000-40 000 Pakistan rupees (PKR) were more likely to use contraception. Women with limited access to SRH services, as well as those whose spouses make healthcare decisions, were less likely to use them. CONCLUSION: Women seeking refugee status who visited Sehat Kahani e-clinics depend substantially on contraception, with a preference for shorter-term options. Consumption of contraceptives was enhanced by collaborative decision-making and availability of SRH services, while it was hampered by a lack of education and healthcare control by husbands. Improving SRH outcomes for remote refugees confronting cultural hurdles is possible through telemedicine by overcoming these gaps.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".