Countertransference towards suicidal patients: a systematic review
Bibliographic record
Abstract
Abstract Countertransference towards suicidal patients may blur healthcare professionals’ clinical judgment and lead to suboptimal decision-making. We conducted a systematic review of the quantitative studies on this topic. Following PRISMA guidelines, various databases were searched for studies measuring countertransference in healthcare professionals treating suicidal patients. Two authors independently performed screening and the quality of included studies was formally assessed. Ten studies were identified (3/5/2 of low/intermediate/high quality, respectively). Cross-sectional studies showed evidence for specific and adverse countertransference (e.g., disinterest, anxiety, overwhelming, rejection, helplessness or distress) towards suicidal patients. Furthermore, countertransference was prospectively associated with suicidal behavior and ideation in studies that explored this issue, but the meaning of this association remains to be clarified. Healthcare professionals’ characteristics (e.g. professional background, gender, personality traits) influenced countertransference. Suicidal patients elicit adverse countertransference, which should be addressed in clinical practice and through dedicated training.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".