Further analysis of psychotropic medication and severe problem behavior
Cox’s number tools still work in the toughest hospital cases, so you can finally see if the med or the behavior plan deserves credit.
01Research in Context
What this study did
Falligant et al. (2021) copied the math steps Cox et al. created. They used the same steps on kids in a hospital who had very bad self-harm or aggression. All kids also took strong mind drugs. The team wanted to know if the math still works when cases are tougher.
They ran single-case tests. They watched behavior while doctors changed pills. Then they used Cox’s numbers to pull apart what the drug did and what the behavior plan did.
What they found
The math held up. The steps showed clear splits between drug effects and behavior-treatment effects even in the hardest kids. No numbers were given, but the authors said the method ‘supported its broader use.’
How this fits with other research
Feinstein et al. (1988) and Cullinan et al. (2001) already told us to match treatment to the reason the behavior happens. Falligant gives us the tool to do that matching when pills are also in play.
Huguenin (2000) looked at lots of drug studies and found no pill works for everyone. The review said ‘use both drugs and behavior plans.’ Falligant shows exactly how to measure each part.
Weber et al. (2024) later showed that even good functional analyses often need tweaks. Falligant’s math can help you know if a tweak failed because the pill changed or because the behavior plan changed.
Why it matters
You now have a ready-made score sheet to show parents, psychiatrists, and insurance reviewers which part of the plan is working. Use it when a new med starts, when a dose changes, or when problem behavior spikes. One clean graph can save weeks of guessing and keep the team focused on behavior data, not pill rumors.
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02At a glance
03Original abstract
AbstractCox et al. (2021) recently outlined a number of analytic methods (i.e., procedures for estimating effect size, conditional rates, and nonparametric partial correlation tests) that may help quantify the relative contributions of psychotropic medication and behavioral interventions on problem behavior among individuals with intellectual and developmental disorders. The purpose of the current study was to examine the generality of these methods by applying these procedures in a novel clinical context (i.e., a hospital‐based inpatient unit for severe problem behavior). We extended the procedures described by Cox to include a larger sample size, cases with more frequent, severe and treatment‐resistant problem behavior, cases with both medication decreases and increases, and cases with at least one similar class of psychotropic medication in common (i.e., atypical antipsychotics). This work remains a proof of concept, but we replicated a number of the preliminary findings from Cox et al. Implications for future research and medication monitoring practices are discussed.
Behavioral Interventions, 2021 · doi:10.1002/bin.1823