Untangling risky discourse with evidence: A scoping review of outcomes for teen mothers’ offspring
Bibliographic record
Abstract
Concerns for the long-term health and social well-being of teen mothers and their children arose in the 1970s as early childbearing was depicted as a public health problem. Early researchers identified the high-risk nature of teen mothering and a host of unfavorable maternal-child outcomes. The purpose of this study is to review the research published since 2010 on the outcomes for teen mothers’ offspring ≥ 6 years of age; to examine trends in the types of studies conducted; and to identify the strengths and limitations of this research. We conducted a systematic search of 8 databases to identify studies that examined outcomes for offspring ≥ 6 years from high-income countries. We grouped studies by offspring age (child ≥ 6 years of age, adolescents, and adults) and outcomes in the domains of mental health, physical health, education, sexual activity, delinquency/crime, and substance use. Child outcomes were examined in 16 studies, adolescent outcomes in 31, and adult outcomes in 14. Of the 53 studies published between 2010 to November 2022, 32 originated in the U.S.; 9 in Sweden; 2 each in Canada and Taiwan; and 8 elsewhere. Since 2010, researchers have increasingly used national samples and sibling and cousin comparisons to control for selection into teen mothering. These studies have reduced, and in some cases, eliminated young maternal age as a predictor, suggesting that poor outcomes are largely due to factors related to teen mothers’ preexisting disadvantage. The results of this scoping review echo a chorus of scholars who have long argued that the poor outcomes attributed to teen mothering disregard the systemic inequities that predispose youth to become teen parents. Because these upstream conditions are baked into the social worlds that most teen mothers and their children inherit, delaying childbearing in the absence of mitigating these conditions is unlikely to improve maternal-child outcomes. We urge researchers to adjust for selection into teen mothering; examine heterogeneity in samples; adjust for birth year when multiple birth cohorts are combined in a study; place findings in historical context; consider variables that align with the perspectives of teen mothers; and study the intergenerational effects of adverse childhood experiences. Doing so would improve our understanding not only of causal relationships but the context and temporality of maternal-child outcomes.
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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 | 0.026 | 0.155 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.034 | 0.026 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".