An evidence-based review of the effectiveness of cognitive behavioral therapy for psychosocial issues post-spinal cord injury.
Bibliographic record
Abstract
STUDY DESIGN: Systematic review. OBJECTIVE: To examine the evidence supporting the effectiveness of cognitive behavioral therapy (CBT) for improving psychosocial outcomes in individuals with spinal cord injury (SCI). METHOD: Electronic databases (MEDLINE, CINAHL, EMBASE, and PsycINFO) were searched for studies published between 1990 and October 2010. Randomized control trials (RCTs) and nonrandomized control trials (non-RCTs) utilizing a CBT intervention to improve psychosocial outcomes (depressive symptomatology, anxiety, coping, and adjustment to disability) in outpatient persons with SCI were included for review. Levels of evidence were assigned to each study using a modified Sackett scale. Effect size calculations for the interventions were provided where possible. RESULTS: Nine studies met the inclusion criteria. The studies reviewed included two RCTs, six prospective controlled trials (PCTs) and one cohort study. All studies examined at least two groups. There is Level 1 and Level 2 evidence supporting the use of specialized CBT protocols in persons with SCI for improving outcomes related to depression, anxiety, adjustment, and coping. CONCLUSIONS: CBT holds promise as an effective approach for persons with SCI experiencing depression, anxiety, adjustment, and coping problems. As CBT may involve many different components, it is important in the future to determine which of these elements alone or in combination is most effective in treating the emotional consequences of SCI.
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.
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".