Codeveloping an Online Resource for People Bereaved by Suicide: Mixed Methods User-Centered Study
Bibliographic record
Abstract
BACKGROUND: Although suicide bereavement is highly distressing and is associated with an increased risk of suicidal behaviors and mental and physical health impairments, those bereaved by suicide encounter difficulties accessing support. Digital resources offer new forms of support for bereaved people. However, digital resources dedicated to those bereaved by suicide are still limited. OBJECTIVE: This paper aimed to develop and implement an evidence-based, innovative, and adaptive online resource for people bereaved by suicide, based on their needs and expectations. METHODS: We performed a mixed methods, participatory, user-centered study seeking to build resources from the perspectives of people bereaved by suicide and professionals or volunteers working in the field of postvention. We used the Information System Research framework, which uses a three-stage research cycle, including (1) the relevance cycle, (2) the design cycle, and (3) the rigor cycle, and the Design Science Research framework. RESULTS: A total of 478 people participated in the study, including 451 people bereaved by suicide, 8 members of charities, and 19 mental health professionals working in the field of postvention. The development stage of the resource lasted 18 months, from October 2021 to March 2023. A total of 9 focus groups, 1 online survey, 30 usability tests, and 30 semistructured interviews were performed. A website for people bereaved by suicide named "espoir-suicide" was developed that includes (1) evidence-based information on suicide prevention and bereavement, (2) testimonies of people bereaved by suicide, (3) a delayed chat to ask questions on suicide and bereavement to a specialized team of mental health professionals, and (4) an interactive nationwide resource directory. The mean system usability score was 90.3 out of 100 for 30 participants, with 93% (n=28) of them having a rating above 80. Since the implementation of espoir-suicide in March 2023, a total of 19,400 connections have been recorded, 117 local resources have been registered nationwide, and 73 questions have been posted in the chat. CONCLUSIONS: The use of a mixed methods, participatory, user-centered design allowed us to implement an evidence-based, innovative, and functional website for people bereaved by suicide that was highly relevant for fulfilling the needs and expectations of French people bereaved by suicide. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fpsyt.2021.770154.
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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 | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".