Unveiling Barriers to the Modern Contraceptive Uptake in the Urban Slums of Karachi: Perceptions, Attitude, and Accessibility
Bibliographic record
Abstract
Background Modern contraception plays a vital role in family planning and preventing unintended pregnancies. However, its uptake remains limited in many developing countries, including Pakistan. This study aimed to evaluate the barriers to modern contraception and identify strategies to enhance its adoption in the urban slums of Karachi. Methods A multi-site, cross-sectional study was conducted in 38 slum areas of Karachi, Pakistan. Women aged 15-49 years were interviewed using a comprehensive questionnaire. The questionnaire covered socio-ethnic and economic demographics, knowledge and perceptions of modern contraception, accessibility, affordability, attitudes, and usage. Data analysis was performed using the Statistical Package for Social Sciences (SPSS) version 24 (IBM SPSS Statistics, Armonk, NY). Results The majority of the respondents identified as Pathan ethnicity (49%), and the age range was predominantly from 23 to 34 years (45.5%). A high proportion of participants demonstrated satisfactory knowledge of contraceptives (87.6%). However, a significant portion perceived contraception or family planning to be in conflict with religious beliefs (84%). Many women expressed a desire for more children (56%) and had concerns about contraceptive side effects (78%). A notable proportion of women reported that their spouses forbade the use of contraceptives (12%). Among the surveyed population, the most widely used contraceptives were injections among women (15.5%) and condoms among their male partners (12%). Conclusion Despite sufficient knowledge and accessibility, considerable barriers exist in the uptake of modern contraception in the urban slums of Karachi, Pakistan. These barriers include religious conflicts, cultural norms, concerns about side effects, spousal disapproval, and desires for larger families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".