Towards a balanced account of autism etiology.
Built-in differences in how fast kids condition are real and should shape your ABA plan.
01Research in Context
What this study did
Lattal (2004) wrote a think-piece, not an experiment. The author asked: why do some kids with autism learn faster than others, even when the teaching is the same?
He argued that pure ‘environment-only’ stories miss built-in biology. Things like how quickly a child’s brain wires new rewards matter too.
What they found
The paper found no new data. Instead it showed that faster or slower conditioning can live inside the kid, not the teaching plan.
Accepting this lets BCBAs write better plans without betraying behavior-analytic roots.
How this fits with other research
Baranek et al. (2005) ran with the same idea but aimed it at stereotypy. They said ‘look at brain chemistry, then add behavioral meds.’ Both papers push biology-plus-behavior, just for different targets.
Farmer (2012) tested the idea in schools. He warned that knowing a child’s genetic syndrome rarely gives teachers a ready-made lesson plan. Lattal (2004) invites biology; Farmer (2012) reminds us the bridge to lessons is still shaky.
Coe et al. (1997) gave the team a practical map. Their diagnostic flowchart shows when to keep, cut, or combine behavioral and drug treatments. The 2004 paper supplies the why; the 1997 paper supplies the how.
Why it matters
Next time a learner makes tiny gains despite solid ABA, pause before you blame the program. Add a line in your FBA: ‘biological learning rate.’ Track acquisition curves across peers. If one child needs triple the trials, build extra fluency steps, not more table time. Share the curve with parents and pediatricians so everyone sees the same data. Biology is not an excuse; it is a prompt to individualize.
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02At a glance
03Original abstract
Drash and Tudor describe six sets of reinforcement contingencies which may be present in the environments of some children eventually diagnosed with autism and suggest that these contingencies account for the etiology of "autistic" behaviors. Nevertheless, merely observing such contingencies in the environments of these children is insufficient to establish a positive correlation between the contingencies and "autistic" behaviors, let alone a causal relationship. To demonstrate a positive correlation, it is necessary to present evidence that the relevant contingencies are present more often in the environments of children exhibiting these behaviors than in the environments of children not exhibiting these behaviors. This condition has not been met, since no evidence to the effect that such contingencies are absent in the environments of typical children or children with disabilities other than autism has been presented. In fact, the opposite appears to be true, as is argued in the present commentary. It appears that Drash and Tudor's account of autism etiology is incomplete in that it neglects the role of unlearned differences between children and their possible interactions with the social environment in shaping "autistic" behaviors. Despite the misconception held by some that behavior analysis is a radically environmental approach, unlearned differences may be discussed within a behavioral framework. A "completely behavioral" account may discuss such differences in terms of susceptibility to reinforcement or punishment, speed of conditioning, or other unlearned characteristics which are potentially testable.
The Analysis of verbal behavior, 2004 · doi:10.1007/BF03392991