Family Members’ Perspectives on Family and Social Support Available to Suicidal Patients, and Health Systems’ Interactions and Responses to Suicide Cases in Alberta: Protocol for a Quantitative Research Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Suicide is a major cause of preventable death globally and a leading cause of death by injury in Canada. To support people who experience suicidal thoughts and behaviors and to ultimately prevent people from dying by suicide, it is important to understand individual and familial experiences with the health care system. OBJECTIVE We present the protocol for a study, the objective of which is to explore how people who died by suicide, and their family members, interacted with the health care system. METHODS This is a quantitative research study. Data will be collected through a self-administered paper-based or online survey of the family member of patients who died by suicide. The sample size was calculated to be 385 (margin of error ±3%). RESULTS Data collection will start in October 2020 and results will be available by March 2021. We expect the results to shed light on the experiences of individuals who died by suicide and their family members with the health care system. The study has received ethical clearance from the Health Ethics Research Board of the University of Alberta (Pro00096342). CONCLUSIONS Our study may inform practice, policy, and future research. The findings may shape how members of the health care system respond to people who are at risk of suicide and their families. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/19112
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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 | 0.044 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.053 | 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".