Comparison of the Effects of Telephone Suicide Prevention Help by Volunteers and Professional Paid Staff: Results from Studies in the <scp>USA</scp> and <scp>Q</scp>uebec, <scp>C</scp>anada
Bibliographic record
Abstract
Research since the 1960s has consistently found that lay volunteers are better at helping suicidal callers than professionals. Yet, professional degrees are increasingly becoming requirements for helpline workers. In our first study, we conducted post hoc comparisons of U.S. helplines with all professional paid staff, all lay volunteers, and a mix of both, using silent monitoring and standardized assessments of 1,431 calls. The volunteer centers more often conducted risk assessments, had more empathy, were more respectful of callers, and had significantly better call outcome ratings. A second study of five Quebec suicide prevention centers used silent monitoring to compare telephone help in 1,206 calls answered by 90 volunteers and 39 paid staff. Results indicate no significant differences between the volunteers and paid employees on outcome variables. However, volunteers and paid staff with over 140 hours of call experience had significantly better outcomes. Unlike the United States, Quebec paid employees were not required to have advanced professional degrees. We conclude from these results and previous research that there is no justification for requiring that suicide prevention helpline workers be mental health professionals. In fact, the evidence to date indicates that professionals may be less effective in providing telephone help to suicidal individuals when compared to trained lay volunteers.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".