Cognitive behavioral therapies for individuals with cerebral palsy: A scoping review
Bibliographic record
Abstract
AIM: To synthesize the evidence about the main intervention characteristics of cognitive behavioral therapies (CBTs) for individuals with cerebral palsy and identify barriers and facilitators to their success, focusing on aspects of feasibility and markers of success. METHOD: A scoping review methodology informed a literature search for papers published between 1991 and 2021. Articles were screened, reviewed, and categorized using the DistillerSR systematic review software, and critically appraised for quantitative and/or qualitative criteria. RESULTS: Out of 1265 publications identified, 14 met the inclusion criteria. Elements associated with the specific study participant characteristics (46% female; aged 6-65 years), type of CBT techniques used (third-wave [n = 6], cognitive [n = 3], cognitive and behavioral [n = 2], biofeedback training [n = 2]), and features of the study context and methodological quality (two randomized clinical trials and small sample sizes [n ≤ 12]), were identified. Most studies had psychological targets of intervention (n = 10) and secondary physiological (n = 3) or social (n = 2) objectives. Feasibility indicators were described in nearly one-third of the papers. INTERPRETATION: This study highlights the high flexibility within CBT interventions, enabling their adaptation for individuals with cerebral palsy. However, relatively little, and only low-certainty evidence was identified. More high-quality research in terms of specific CBT techniques, optimal treatment doses, and detailed population characteristics are needed.
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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 | 0.024 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".