Remaining Between the Cracks – The Long-Term Effect of Different Suicide Risk Exclusion Criterion on Outcomes of an Online Intervention for Depression
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: Previous studies have demonstrated that excluding individuals at risk of suicide from online depression interventions can impact recruited sample characteristics. Aim: To determine if a small change in suicide risk exclusion criterion led to differences in the usage and effectiveness of an Internet depression intervention at 6 months of follow-up. Method: A partial sample of a recently completed online depression intervention trial was divided into two groups: those with no risk of suicide versus those with some risk. The two groups were compared for baseline demographic and clinical measures, as well as intervention uptake and treatment success across 6 months. Results: Overall, individuals with less risk of suicide at baseline reported significantly less severe clinical symptoms. Both groups interacted with the intervention at the same rate, but specific use of modules was different. Finally, the impact of intervention usage on outcomes over time did not vary by group. Limitations: While different suicide risk exclusion criteria can change recruited sample characteristics, it remains unclear how these differences impact intervention uptake and success. Conclusion: Overall, the findings suggest that researchers should exercise caution when excluding individuals at risk of suicide, as they greatly benefit from web-based interventions.
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 | 0.001 | 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