Models of suicide in elderly: a protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: The rates of suicide in the elderly population are generally higher than other age groups. Models of suicide that explain the phenomenon of suicide in later life may have research, clinical and educational implications for the field of ageing. The primary purpose of this systematic review is to identify and review existing models of suicide that have a particular focus on the elderly. METHODS AND ANALYSIS: The authors intend reviewing the findings of observational studies including cohort studies, cross-sectional studies, case-control studies, and qualitative studies such as grounded theory designs which are published in Google Scholar, Scopus, PsycINFO, PubMed, Web of Science, Cochrane Database of Systematic Reviews and research-related journals. Models of suicide which specifically describe, explain and predict late life suicides will be included. Therapeutic, interventional and rehabilitation models, as well as models related to assisted suicide, will be excluded. The EndNote software will be employed for data management. Two independent reviewers will extract data. Methodological quality and the risk of bias of quantitative studies will be assessed using the Newcastle-Ottawa Scale and the Newcastle-Ottawa Scale adapted for cross-sectional studies, while that of qualitative studies will be assessed using the Critical Appraisal Skills Programme and the evaluative criteria of credibility, transferability, dependability and confirmability. The final report will present a range of models of suicide with a list of different subgroups. ETHICS AND PUBLICATION: There are no predictable ethical issues related to this study. The findings will be published in prestigious journals and presented at international and national conferences. PROSPERO REGISTRATION NUMBER: CRD42017070982.
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 | 0.080 | 0.122 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.087 | 0.013 |
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".