Bibliographic record
Abstract
The death of a neonate is an extremely heartbreaking loss that can result in overwhelming and overpowering grief responses. Because of the intensity of the grief reactions these parents experience it is absolutely imperative that social workers intervene appropriately with families whose baby has died. This article will review grief intervention and the application of this approach. Five grief intervention models will be discussed including Lindemann's (1944) stages of grief work, Bowlby's (1980) three phases of mourning, Rando's (1988) three phases of grief, Worden (2001) tasks of grief work and White's (1988) “saying hullo metaphor.” A case example will be used to describe the application of Worden's (2001) task model with a family whose twin babies have died on the NICU. Lastly, how this review and use of grief intervention models impacts social work practice on a NICU setting will be discussed. Ultimately, social workers should intervene according to the needs presented by these families or otherwise clinicians risk inflicting further pain and suffering on parents already experiencing the extreme anguish of grief.
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 | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| 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".