Piloting a Coping Skills Group Intervention to Reduce Depression and Anxiety Symptoms in Patients Awaiting Kidney or Liver Transplant
Bibliographic record
Abstract
The authors evaluated the use of a coping skills group (CSG) therapy intervention to decrease depression and anxiety and increase healthy coping skills in a population of kidney and liver transplant candidates. The study, using a pre-posttest design, piloted a CSG with a convenience sample of 41 consenting participants on a waiting list or in workup for kidney or liver transplant. Two transplant social workers led five eight-week closed psychoeducational groups. Coping skills, depression symptoms, and anxiety symptoms were assessed preintervention, postintervention, and at follow-up one month later. Results suggest that the CSG group created significant changes in some coping areas, such as decreasing the use of denial and self-blame and increasing the use of acceptance, religion, and instrumental supports. In this study, instrumental supports are strategies such as seeking assistance, finding information, or asking for advice about what to do. The effects on instrumental supports did not sustain at the one-month follow-up. Anxiety and depression scores were significantly reduced, and these changes were sustained at one-month follow-up. This study supports the use of a group-based psychosocial intervention for the pretransplant population and will be most relevant to social workers practicing in the transplant field.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".