Experiences, Preferences, and Needs of Adolescents and Urban Youth in Contraceptive Use in Conakry, 2019, Guinea
Bibliographic record
Abstract
Introduction: The use of contraceptive methods is very low in Guinea, particularly among adolescents and young people. The purpose of this study is to analyze the experiences and expectations of adolescents and young people regarding the use of contraceptive methods in 2019 in Conakry, Guinea. Methods: We conducted a 6-month qualitative and descriptive study. Data were collected through individual in-depth interviews and focus group discussions with adolescents and young people, health providers and health policy makers. Two approaches of deductive and inductive analysis were used to synthesize the main insights from the data. Findings: Twenty-six participants were included in this study. Adolescents and young people have personal, family and community experiences that positively or negatively influence their contraceptive needs and preferences. Positive experiences include the relative cost of injectable forms, perceived absence of side effects of implants, proven efficacy and duration of action of the modern method used (implants and injectable form). Negative experiences included cost of implants remain high (15 Euros), perceived side effects including weight gain, pill compliance, method indiscretion, and low sensation of sexual pleasure for the condom. The preferences of the young participants were dominated by Implants and injectable forms that better meet their contraceptive needs. In terms of needs, the expectations expressed revolved around needs related to the health system, including sex education, reduction in the cost of some contraceptives (implants), availability of contraceptive methods, and equity in the provision of family planning services to adolescents and young people. Conclusion: Exploring the contraceptive experiences, needs and preferences of adolescents and young people reveals decision-making dilemmas. Adolescents and young people expressed their experiences in terms of the cost of preferred contraceptives (implants), side effects, proven efficacy, and duration of action. However, their decisions are still influenced by availability, equity in service delivery, and the involvement of parents and religious leaders in sex education. Decision-makers should then place particular emphasis on improving health service delivery, adolescent sexual and reproductive health, availability of preferred contraceptive methods at affordable cost, and a program on sexuality education with the involvement of parents and religious leaders and the promotion of condom use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".