Global increase in response latencies by early middle age: complexity effects in individual performances.
Response times begin to slow globally once clients hit their late thirties—give them more time on complex tasks.
01Research in Context
What this study did
Researchers timed how fast women pushed buttons during seven computer tasks. Half the women were 20-22 years old. The other half were 36-44 years old.
Tasks started easy, like pressing when a light turned green. Later tasks added rules: press only after two green lights, or after counting beeps. More rules meant more complexity.
What they found
The middle-aged group was slower on every task. The gap grew larger as tasks got harder. On the simplest task they lost a split second. On the hardest task they lost almost a full second.
Every single older woman slowed down. Complexity acted like a magnifying glass for age.
How this fits with other research
Koolen et al. (2014) saw the same complexity-slowdown pattern in adults with autism. Simple shapes kept their speed, but semantic puzzles dragged them down. The target paper extends this link to aging neurotypical women.
Samson et al. (2006) review shows autistic listeners actually get faster on low-complexity sounds. That looks like the opposite trend, but the tasks were different: easy tones versus hard puzzles. When complexity is the common factor, both groups still slow down.
Manabe (1990) proved you can model latency changes in one pigeon by tweaking delay values. The 1989 study does the same across humans by tweaking cognitive load. Same measurement tool, two worlds: single-case operant and group cognitive.
Why it matters
If you run matching-to-sample or conditional-discrimination programs with adult clients, bake in extra response time. A 40-year-old may need twice the wait you give a 20-year-old, especially when rules stack. Start simple, check speed, then add complexity only after latency stabilizes.
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02At a glance
03Original abstract
Ten young women (age 20 to 22 years) and 10 middle-aged women (age 36 to 44 years) served as subjects in choice reaction time, letter classification, and abstract matching-to-sample tasks. In each of seven conditions, the older group responded more slowly than the younger group. Age differences showed a complexity effect. That is, differences between the latencies of young and old subjects increased as the latency of the young subjects increased. Both linear and power functions accurately described the relation between the latencies of the middle-aged and young adult groups. This was true not only for the relation between average latencies but also for the relation between corresponding quartiles of latency distributions. Similar results were observed at the individual level: All middle-aged subjects showed complexity effects, and, for each middle-aged subject, the relation between her latencies and those of the average young adult was well described by linear and power functions. These findings indicate that age-related slowing is apparent by age 40, and that complexity effects are observable in individual performances. This slowing is global and not specific to particular tasks, as indicated by the fact that the latencies of older adults can be predicted directly from those of younger adults without regard to the nature of the task.
Journal of the experimental analysis of behavior, 1989 · doi:10.1901/jeab.1989.52-353