Whether and when disclosing the trauma to one’s children in a migratory context? A pilot mixed methods investigation
Bibliographic record
Abstract
BACKGROUND: Disclosing traumatic events experienced by parents to their children is a central issue in the intergenerational trauma transmission. However, little is known about this question among migrant population. The main objective of this study was to examine the choice to disclose the traumatic experiences of migrant women in France to their children. METHODS: This pilot study examined fourteen mother-child dyads in which migrant mothers (M = 30 years; range = 19-42 years) were exposed to traumatic events. A sequential mixed method design was used. In addition to the completion of the Impact Event Scale-Revised, qualitative data were collected through semi-structured interviews. These data were analyzed using thematic and cross-cultural methods. The survey took place from May 2019 to July 2020. RESULTS: Our study revealed three profiles of mothers with regard to the choice to disclose the traumatic story to the child: one group of mothers opted for silence (n = 4), the other for disclosure (n = 7) and the last group who were hesitant (n = 3). The modalities of choice were statistically associated with the severity of the post-traumatic stress symptoms, F (2, 11) = 4,62, p < .05. Specifically, women who made the choice of silence (M = 72.75, SD = 4.99) and those hesitated on the choice to disclosure (M = 71.33, SD = 7.51) reported higher scores on IES-R than those who made the choice to disclosure (M = 59.86, SD = 12.44). Six main themes emerged from the thematic and cross-cultural analysis of participants' narratives: (1) the personalization of the traumatic experience, (2) the child seen as a weapon against collapse, (3) the fear of the child's personal reactions, (4) the possible partial disclosure, (5) the trauma narrative according to the child's age, and (6) the trap of the in-between two cultures. CONCLUSION: Our results suggest that the recovery of these mothers from their trauma, through culturally appropriate therapeutic care, can effectively contribute to the choice to disclose their traumatic experiences to their children. This treatment can support them in developing open and healthy communication strategies to prevent the transmission of traumatic effects to their children.
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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".