A scoping review of bereavement service outcomes
Bibliographic record
Abstract
OBJECTIVE: This scoping literature review, through finding and assessing researched bereavement service outcomes, sought to determine the state of bereavement services evaluation, to catalogue service types, and to identify which service or services, if any, demonstrate clear evidence of effectiveness. METHOD: Our methods included: (1) a literature search for published English-language research articles from 2005-2015; (2) critical appraisal of articles to identify findings; (3) compilation of findings; and (4) determination of the relevance of our findings. RESULTS: Some 38 papers were found, and all were retained to identify the outcomes researched and research findings. Many different outcomes were studied in the 18 quantitative, 11 qualitative, and 9 mixed-methods investigations undertaken worldwide. Ten studies focused on level of grief, six on stress/distress level, six on grief knowledge, six on level of depression, and five on somatization or physical symptoms. Most commonly, a group of bereavement services was evaluated as a whole, followed by group therapy, individual counseling, written information, and other less common services. No group of services or individual service was determined to yield clear and convincing evidence of effectiveness. Regardless, all but one service were shown to have value-most often related to gaining grief information and/or emotional support. Until high-quality research studies have repeatedly revealed evidence of effectiveness, it is possible that the positive outcomes of bereavement services will be largely based on bereaved people receiving helpful educational information and emotional support from organizations and people prepared to help them. SIGNIFICANCE OF RESULTS: This project outlines existing bereavement service types and the state of science in relation to determination of outcomes. It offers suggestions to advance the state of science to validate or refine bereavement services. It brings to light the issue that bereavement service outcomes need to be carefully researched so that evidence can drive service refinement and expansion. It also highlights the importance of effective bereavement services.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".