Carers’ Motivations for, and Experiences of, Participating in Suicide Research
Bibliographic record
Abstract
(1) Background: First-hand accounts of lived experience of suicide remain rare in the research literature. Increasing interest in the lived experience of suicide is resulting in more opportunities for people to participate in research based on their personal experience. How individuals choose to participate in research, and their experience of doing so, are important considerations in the ethical conduct of research. (2) Methods: To understand the experience of providing care for someone who has previously attempted suicide, a cross-sectional online community survey was conducted. This survey concluded with questions regarding motivation to participate and the experience of doing so. Of the 758 individuals who participated in the survey, 545 provided open-ended text responses to questions regarding motivation and 523 did so for questions regarding the experience of participating. It is these responses that are the focus of this paper. Data were analysed thematically. (3) Results: Motivations to participate were expressed as primarily altruistic in nature, with a future focus on improving the experience of the person who had attempted suicide alongside carers to ease distress. The experience of participating was difficult yet manageable, for all but a few participants. (4) Conclusions: With the increasing interest in first-hand accounts of suicide, how individuals experience participation in research is an important focus that requires further attention.
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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".