Effectiveness and Social Validity of FBAs for Youth At-Risk or With High Incidence Disabilities: A Meta-Analysis
Bibliographic record
Abstract
This meta-analysis examined the effectiveness and social validity of 44 functional behavioral assessment (FBA) studies using single case research designs (SCRDs) conducted with youth displaying challenging behaviors or had high incidence disabilities. Three effect sizes were calculated: standard mean difference (SMD), Tau-U, and improvement rate difference (IRD). Fisher’s conservative dual criterion (CDC), which is a statistical aid to visual analysis, was also applied. Social validity was assessed by using indicators described by Kazdin (2010). Effect sizes were in ranges indicating moderate to large effects. Approximately 71% of AB contrasts reflected CDC systematic change. However, only 44% of studies assessed social validity. There were no significant differences in effectiveness of interventions whether or not a functional analysis was conducted nor whether the controlling function was escape or attention. Results are discussed in terms of FBA implementation issues related to social validity and the necessity for conducting a functional analysis for these youth.
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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 | 0.029 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.050 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".