Fathers’ Childhood Experiences, Adult Mental Health Problems and Perceptions of Interactions With Their 36 Month-Old Children
Bibliographic record
Abstract
Perceptions of poor care in the family of origin can relate to adverse mental health and poor adaptation for mothers but there is less evidence about fathers. This study investigated the relevance of fathers’ recollections of their own parents (Generation 1) for their (Generation 2) current mental health symptoms and for interactions with their 3-year-old children (Generations 2/3), in a community sample of 482 British fathers. Recollections of G1 maternal and paternal behaviour were associated in uncontrolled correlations with G2 paternal mental health, but taking family social class and maternal (G2) mental health into account they did not significantly predict G2 fathers’ mental health symptoms at 36 months postpartum, though a trend remained for G1 paternal care. Significant predictors were paternal depression symptoms in the first year postpartum and G2 mothers’ current mental health. Predictors of more dysfunctional father-child (G2/G3) interactions at 36 months postpartum were working class status, recall of more G1 maternal controlling behaviour and more concurrent paternal mental health symptoms; predictors of less G2/G3 dysfunction were G2 paternal use of more positive discipline. Potential implications of the results for parenting support and advice are discussed, recognising that intergenerational transmission of parent-child relationships is likely for fathers.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".