Posttraumatic Growth Among Suicide-Loss Survivors: Protocol for an Updated Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Losing a loved one to suicide is an event that can have strong and potentially traumatic impacts on the lives of the bereaved survivors, especially regarding their grief, which can be complicated. These bereaved individuals are also less likely to receive social support following their bereavement. However, besides these adverse impacts, growing evidence supports the concept of posttraumatic growth following suicide bereavement. Posttraumatic growth is the personal improvement that occurs as a consequence of experiencing a traumatic or extremely challenging event or crisis. Only 1 systematic review and meta-analysis on posttraumatic growth following suicide bereavement has been conducted; this protocol is for the planned systematic review and meta-analysis update of the original systematic review and meta-analysis, as the original review collected its data in 2018. OBJECTIVE: This review aims to investigate demographic characteristics, correlational relationships, and facilitative factors of posttraumatic growth in individuals bereaved by suicide. In addition, as this is an update of a previous systematic review and meta-analysis, we aim to compare our findings with the original review and to identify any similarities or differences. METHODS: This protocol outlines the planned procedures of the updated systematic review and meta-analysis. MEDLINE, PsycINFO, Embase, CINAHL, Scopus, and Web of Science (Core Collection) were examined, and the search results were imported to Covidence, where title and abstract screenings and full-text screenings occurred. The inclusion and exclusion criteria for this updated review match those in the original review: (1) the study population must contain participants bereaved by suicide, (2) the study data must be quantitative, and (3) the study must report data on posttraumatic or stress-related growth. The original review conducted its search before 2019; thus, this updated review searched databases for the timeframe of January 2019 to January 2024. The updated meta-analysis will synthesize data from both the original and updated reviews to examine trends over time. The Newcastle-Ottawa Scale (NOS) will be used to assess publication quality. Random-effects meta-analyses will be conducted using RStudio (R Foundation for Statistical Computing). RESULTS: The review was funded in October 2023 and is currently in progress. Results are expected to be finalized in October 2024. There are 21 articles that have been included in the review and are being analyzed at this time. We aim to submit the full article for publication in December 2024. CONCLUSIONS: The results of this updated systematic review and meta-analysis will be used to examine key relationships and findings regarding posttraumatic growth in individuals bereaved by suicide. The discussion will also investigate the findings of this updated review in comparison to the findings of the original review. Any differences would be highlighted. Limitations of the current review will be discussed, such as the quality of the articles included. TRIAL REGISTRATION: PROSPERO CRD42024485421; https://tinyurl.com/3hzpnzr3. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64615.
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 | 0.062 | 0.104 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.028 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.080 | 0.006 |
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".