Considering efficacy and effectiveness trials of cognitive behavioral therapy among youth with autism: A systematic review
Bibliographic record
Abstract
Cognitive behavioral therapy is a widely studied and commonly used psychosocial intervention for treating emotional problems in individuals with autism. To date, most studies of cognitive behavioral therapy and autism have focused on efficacy. Effectiveness trials, by contrast, measure whether an intervention produces particular results under “real-world” clinical conditions. We conducted a systematic review of cognitive behavioral therapy interventions targeting affective disorders among youth with autism and (a) classified studies as either efficacy or effectiveness trials and (b) coded how the effectiveness trials reflect the implementation characteristics outlined in the Framework of Dissemination in Health Services Intervention Research. The systematic search yielded 2959 articles, with 33 studies meeting inclusion criteria. Thirteen studies were categorized as effectiveness and 20 as efficacy. We discuss how the effectiveness studies considered elements of the implementation framework and provide recommendations for future studies, including greater consideration and measurement of adoption and sustainability processes, as well as organizational- and system-level outcomes. Results shed light on our understanding of the effectiveness of cognitive behavioral therapy in routine clinical practice, how an implementation framework can be used to guide and improve effectiveness studies, and identify barriers, facilitators, and gaps in the implementation process. Lay abstract Cognitive behavioral therapy is a common treatment for emotional problems in people with autism. Most studies of cognitive behavioral therapy and autism have focused on efficacy, meaning whether a treatment produces results under “ideal” conditions, like a lab or research setting. Effectiveness trials, by contrast, investigate whether a treatment produces results under “real-world” conditions, like a community setting (e.g. hospital, community mental health center, school). There can be challenges in bringing a cognitive behavioral therapy treatment out of a lab or research setting into the community, and the field of implementation science uses frameworks to help guide researchers in this process. In this study, we reviewed efficacy and effectiveness studies of cognitive behavioral therapy treatments for emotional problems (e.g. anxiety, depression) in children and youth with autism. Our search found 2959 articles, with 33 studies meeting our criteria. In total, 13 studies were labelled as effectiveness and 20 as efficacy. We discuss how the effectiveness studies used characteristics of an implementation science framework, such as studying how individuals learn about the treatment, accept or reject it, how it is used in the community over time, and any changes that happened to the individual or the organization (e.g. hospital, school, community mental health center) because of it. Results help us better understand the use of cognitive behavioral therapy in the community, including how a framework can be used to improve effectiveness studies.
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 | 0.066 | 0.272 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.015 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".