Breaking the Cycle: How Parents with Childhood Adversity Perceive Intergenerational Risks
Bibliographic record
Abstract
Adverse Childhood Experiences (ACEs) are linked to long-term health, mental health, and relational problems, with growing evidence of their intergenerational transmission. While prior research has established correlations between parental ACEs and children’s adversity, less is known about how parents perceive and address this risk. The involved study examined how eleven parents (seven women, four men) aged 30–68 years, from the Midwestern United States, with self-reported high ACE experiences of 4 or more, interpret their perceived influence of their childhood experiences on their children’s risk of adversity. Participants were racially diverse and varied in socioeconomic and educational backgrounds. Using a qualitative grounded theory, participants completed in-depth, semi-structured interviews exploring their ACE histories and parenting practices. Four themes emerged from the data analysis, which included: (1) mental health and relationship concerns; (2) patterns of continuity; (3) education and awareness; and (4) intentional vs. reactive parenting. These themes emerged to introduce a trauma-informed concept of an intentional, transformative parenting model, describing a deliberate and adaptive process aimed at reducing intergenerational risk. Within this model, parents can act as agents of resilience by combining self-awareness, education, therapeutic support, and intentional caregiving as a way to strengthen and promote intergenerational healing.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".