Exploring the psychosocial challenges faced by pregnant teenagers in Ditsobotla subdistrict
Bibliographic record
Abstract
Background: Pregnant teenagers usually experience psychosocial challenges such as a great amount of stress when they have to deal with an unwanted pregnancy, unpreparedness for parenthood and a lack of income as well as labour and birth complications. These are further complicated by the stigma from their families, friends and community. Unaddressed psychosocial challenges during teenage pregnancy can adversely affect the health outcomes of both mother and the child. Aim: This study explores and describes the psychosocial challenges faced by pregnant teenagers in the Ditsobotla subdistrict. Setting: The study was conducted in three health centres in the Ditsobotla subdistrict. Methods: A qualitative-exploratory-descriptive and contextual research design was used. Non-probability purposive and convenience sampling techniques were used to select the participants. Semistructured individual interviews through WhatsApp video calls were used to collect data, which were analysed using conventional content analysis. Results: Three themes emerged from the findings of the study, namely psychological challenges, social challenges and suggestions to address psychosocial challenges faced by pregnant teenagers. Conclusion: The findings established that pregnant teenagers in the Ditsobotla subdistrict are faced with psychosocial challenges which negatively impact their psychological health and social life. Suggestions made in this study have the potential to improve the psychosocial well-being of pregnant teenagers in the Ditsobotla subdistrict if implemented. Contributions: The findings of this study provide important information that may be used to improve the psychosocial well-being of pregnant teenagers in the Ditsobotla subdistrict.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".