A review of how psychotropic medication can affect the motivation of challenging behavior
Bibliographic record
Abstract
Self-injury, aggression, stereotypy, and other forms of challenging behavior are highly prevalent among people with intellectual disabilities (ID). Psychopharmacological and behavioral interventions, often in combination, are common interventions for challenging behavior. However, little is known about the interaction between psychopharmacological treatment and the motivation or, more precisely, the function of challenging behavior. A better understanding of these processes may be critical to optimize treatment efficacy.Objectives: An overall review of the literature on the interaction between behavior function and psychotropic medication in people with ID, and directly related variables (e.g. motivating operations) was conducted. As a result, we discuss the behavioral processes involved in medication–behavior function interaction and the methodological and clinical implications of this research area.Methods: A comprehensive literature review was conducted of current peer-reviewed publications.Results and Conclusion: Evidence suggests medication can affect the function of challenging behavior in several ways (i.e. add new functions, decrease the number of functions, and/or change the function). Moreover, medication–function interaction was a relatively infrequent occurrence. We found the analysis of variables that alter the effectiveness of a reinforcing or punishing stimulus, called motivating operations (e.g. satiation, deprivation, illness) provides an experimental model for the analysis of the behavioral mechanisms associated with medication–function interactions. Further, single-subject designs and functional analysis methodology can be combined to evaluate medication–function interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".