Prevalence of Loss and Complicated Grief Among Psychiatric Outpatients
Bibliographic record
Abstract
OBJECTIVE: This study examined the prevalence of significant loss through the death of another person as well as complicated grief among patients at two psychiatric outpatient clinics for one year. METHODS: A total of 729 patients were interviewed about significant losses through death during their lives. Standard questionnaires were used to classify 235 patients who had experienced such losses into three groups: those who had minimal disturbance, those who had moderate complicated grief, and those who had severe complicated grief. Multivariate and univariate analyses of variance were used to test for differences in loss-specific variables (for example, pathological grief) and variables that were not specific to loss (for example, depression) among the three groups. RESULTS: More than half of the 729 patients reported that they had experienced one or more significant losses through death. About a third of all patients who came to the clinics met the criteria for either moderate or severe complicated grief. The average time since the loss was about ten years, indicating that these patients had long-term complicated grief. Significant differences in loss-specific variables and variables that were not specific to loss were detected among the three groups. Patients who had severe complicated grief scored higher than patients in the other two groups on both types of variables. Patients with moderate complicated grief had higher scores than those with minimal disturbance. CONCLUSIONS: Clinicians should routinely assess outpatients for loss and complicated grief and should consider addressing loss and complicated grief in treatment. Rather than a single classification of complicated grief, different levels should be considered.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".