De la dépression postnatale à la détresse relationnelle : une approche intégrative pour repenser la clinique en santé mentale périnatale
Bibliographic record
Abstract
La dépression postnatale est généralement abordée sous son prisme binaire, opposant parents déprimés et non déprimés. Cet article propose une approche intégrative en remplaçant cette catégorisation par le concept de détresse relationnelle périnatale, soulignant ainsi l’importance des dynamiques parent-enfant et des vulnérabilités réactivées par la dépendance du nourrisson. Inspirée par la théorie de l’attachement, cette perspective met en avant la nécessité de structurer les soins autour de la contenance et de la continuité – dans le temps, le lieu et le langage – pour prévenir les ruptures institutionnelles et favoriser un soutien adapté aux parents. L’article explore les implications cliniques de cette approche, en détaillant des modèles thérapeutiques centrés sur la relation et en plaidant pour une organisation des soins plus cohérente et intégrative. Postnatal depression is typically framed in a binary manner, distinguishing between depressed and non-depressed parents. This article proposes an integrative approach by replacing this categorization with the concept of perinatal relational distress, emphasizing the role of parent-child dynamics and the vulnerabilities triggered by infant dependency. Drawing from attachment theory, this perspective highlights the need to structure care around containment and continuity — across time, space, and professional discourse — to prevent institutional gaps and provide tailored support for parents. The article explores the clinical implications of this approach, detailing therapeutic models centered on relationships and advocating for a more coherent and integrative organization of perinatal mental health care.
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 | 0.024 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.006 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".