A Distress-Processing Model for Clients in Suicidal Crisis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: Background: While crisis intervention frameworks have indicated the importance of clients in suicidal crisis better understanding their distress to decrease suicidality, it is unclear how clients in suicidal crisis process their distress. Aims: To develop (Study 1) and validate (Study 2) a sequential distress-processing model for clients in suicidal crisis. Methods: Applying task analysis, Study 1 consisted of three phases, which resulted in a theoretically and empirically informed model. In Study 2, we examined the distress-processing model’s validity using a longitudinal design. In both studies, data were online crisis chats with adults in suicidal crisis. Results: In Study 1, we developed a sequential five-stage distress-processing model: (Stage 1) unengaged with distress, (Stage 2) distress awareness, (Stage 3) distress clarity, (Stage 4) distress insight, and (Stage 5) applying distress insight. In Study 2, the model’s validity was supported via evidence that (H1) progression through the processing stages was sequential and (H2) clients with good outcomes had greater progression in their processing than clients with poor outcomes. Limitation: Clients who were suicidal but did not disclose their suicidality were not included. Conclusion: Our findings provide a framework for conceptualizing and operationalizing how clients move through suicidal crises, which can facilitate intervention and research developments.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it