Description and evaluation of a function‐informed and mechanisms‐based framework for treating challenging behavior
A plug-and-play, function-first treatment menu helps some clients hit meaningful improvement, but you must stay ready to adjust when it stalls.
01Research in Context
What this study did
Lambert et al. (2022) looked back at six years of a university practicum.
They asked: does a step-by-step, function-first decision tree help grad students treat severe problem behavior?
The team pulled 39 clinic cases. Each client got a full functional analysis, then a treatment plan picked from a fixed menu that matched the function.
What they found
The framework worked like a light switch for some kids—problem behavior dropped a large share or more.
But it flopped for others; gains were small or faded fast.
In short: big wins, but not for everyone.
How this fits with other research
Feinstein et al. (1988) showed the same core rule: match the treatment to the function and you win. Lambert’s menu simply turns that rule into a practicum checklist.
Weber et al. (2024) used the same look-back method, but stopped at the FA results. Lambert goes one step further—tracking what happens after the FA.
Kaur et al. (2025) counts 76 similar case-series papers, so this design is now common currency for busy clinics.
Why it matters
You already do FAs; this paper gives you a ready-made decision tree you can tape to the wall. Use it, but keep measuring. When data dip, tweak—don’t blame the kid. The paper screams one lesson: even good frameworks need live edits.
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Join Free →After the FA, pick the matched treatment from the FIMB chart, then set a daily data rule: if behavior isn’t down a large share by day five, change one variable.
02At a glance
03Original abstract
Individualization and iterative design are essential components of the assessment and treatment of challenging behavior. Currently, there are few validated frameworks for engaging in iterative processes. Due to the nature of single-case design, empirically rigorous evaluations of decision-tree processes are particularly prohibitive. Notwithstanding, evaluations are needed. In this paper we first describe a function-informed and mechanisms-based (FIMB) framework for selecting treatment components employed by a university-based practicum experience designed to expose pre-service practitioners to a valid treatment process for challenging behavior. Then, we share a completed retrospective consecutive case series across a 6-year period in which we conducted a technique analysis to identify which procedures were most commonly selected in the practicum, and the impact of those choices on client outcomes. The results suggest that the model can be highly effective for some, but not all, cases. Implications are discussed.
Journal of Applied Behavior Analysis, 2022 · doi:10.1002/jaba.940