The Ambiguous Loss Inventory Plus (ALI+): Introduction of a Measure of Psychological Reactions to the Disappearance of a Loved One
Bibliographic record
Abstract
BACKGROUND: The disappearance of a significant person is an ambiguous loss due to the persistent uncertainty about the whereabouts of the person. Measures specifically capturing the psychological consequences of ambiguous loss are lacking. Therefore, this study aimed to develop the Ambiguous Loss Inventory Plus (ALI+) and evaluated its suitability for use with relatives of missing persons. METHODS: ALI+ items were generated based on established measures for prolonged grief symptoms and literature on psychological responses to ambiguous loss. Eight relatives of missing persons (three refugees, five non-refugees) and seven international experts on ambiguous loss rated all items in terms of understandability and relevance on a scale from 1 (not at all) to 5 (very well). RESULTS: On average, the comprehensibility of the items was rated as high (all items ≥ 3.7). Likewise, all items were rated as relevant for the assessment of common responses to the disappearance of a loved one. Only minor changes were made to the wording of the items based on the experts' feedback. CONCLUSIONS: These descriptive results indicate that the ALI+ seems to cover the intended concept, thus showing promising face and content validity. However, further psychometric evaluations of the ALI+ are needed.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".