Adapting interpersonal psychotherapy for older adults at risk for suicide: Preliminary findings.
Bibliographic record
Abstract
We report preliminary findings of the first ever study testing a 16-week course of Interpersonal Psychotherapy (IPT) modified for older outpatients at elevated risk for suicide. Participants were referred from inpatient and outpatient medicine and mental health services. Psychotherapy sessions took place in a therapist's office in a teaching hospital. Twelve adults 60 years or older (M=70.5, SD=6.1) with current thoughts of suicide (suicide ideation) or a wish to die (death ideation) or with recent self-injurious behavior were recruited into weekly sessions of IPT; one was subsequently excluded due to severe cognitive impairment. Participants completed measures of suicide ideation, death ideation, and depressive symptom severity at pre-treatment, mid-treatment, post-treatment, and at 3-month follow-up periods, and measures of therapeutic process variables. Preliminary findings of this uncontrolled pre-post-treatment study support the feasibility of recruiting and retaining older adults at-risk for suicide into psychotherapy research and suggest that adapted IPT is tolerable and safe. Findings indicate a substantial reduction in participant suicide ideation, death ideation, and depressive symptoms; controlled trials are needed to further evaluate these findings. We discuss implications for clinical care with at-risk older adults.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".