Workshop (Knowledge Generation) ID 2001810
Bibliographic record
Abstract
Background Guided internet-delivered CBT (ICBT) offers an alternative approach for mental health service delivery in the community for those with spinal cord injury (SCI). However, there is a lack of evidence to support its use through large, controlled trials. Study Objectives The primary aim of the current study is to explore the efficacy of ICBT in reducing symptoms of depression and anxiety among persons with SCI compared to an online SCI Rehabilitation Education program. Learning Objectives Upon completing this workshop, attendees will: 1) understand the state of mental health among those post SCI; 2) explain the evidence behind guided ICBT among those post SCI; 3) apply cognitive behaviour therapy skills. Overview The presenters of this workshop will engage in lecture to provide current state of evidence for ICBT among those post SCI, conduct small-group discussions to apply CBT skills and examine barriers and facilitators of implementing the program. Methods Participants (n=122) endorsing symptoms of depression and/or anxiety related to SCI were randomized to an 8-week transdiagnostic ICBT program for those with SCI or an online SCI Rehabilitation Education program. Participants completed measures on depression, anxiety, self-efficacy, quality of life, and pain at pre-, post-, 3-months, and 6-months post-intervention. Results Significantly greater improvements in depression, anxiety, self-efficacy, quality of life, and pain interference were seen in the ICBT group compared to the Education group at post treatment and follow-up. Completion rates (∼90%) and satisfaction (>90%) were high in both groups. Conclusions The findings provide evidence for the superiority of ICBT over education in improving well-being among those with SCI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.886 | 0.646 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".