Psychosocial family-level mediators in the intergenerational transmission of trauma: Protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
ABSTRACT Introduction Family-level psychosocial factors appear to play a critical role in mediating the intergenerational transmission of trauma; however, no review article has quantitatively synthesized causal mechanisms across a diversity of trauma types. This study aims to systematically consolidate the epidemiological research on family-level psychosocial mediators and moderators to ultimately produce causal diagram(s) of the intergenerational transmission of trauma. Methods We will identify epidemiological peer-reviewed publications, dissertations, and conference abstracts that measure the impact of at least one psychosocial family-level factor mediating or moderating the relationship between parental trauma exposure and a child mental health outcome. English, French, Kinyarwanda, and Spanish articles will be eligible. We searched MEDLINE, PsycINFO, PTSDpubs, Scopus and ProQuest Dissertations and Theses and will conduct forward citation chaining of included documents. Two reviewers will perform screening independently. We will extract reported mediators, moderators, and relevant study characteristics for included studies. Findings will be presented using narrative syntheses, descriptive analyses, mediation meta-analyses, moderating meta-analyses, and causal diagram(s), where possible. We will perform a risk of bias assessment and will assess for publication bias. Discussion The development of evidence-based causal diagram(s) would provide more detailed understanding of the paths by which unresolved trauma can be transmitted intergenerationally at the family-level. This review could provide evidence to better support interventions that interrupt the cycle of intergenerational trauma. Systematic review registration PROSPERO registration ID #CRD42021251053.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.108 | 0.143 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.026 | 0.031 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.066 | 0.008 |
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".