Designing a behavioral program for a barrio in Tegucigalpa, Honduras.

Miller (1994) mapped out a city-wide health program for a poor neighborhood in Tegucigalpa, Honduras. The paper is a plan, not an experiment. It tells how to set up data sheets, train local workers, and track home repairs, clean-ups, and sickness days.

No children or adults were enrolled as subjects. No behavior counts were taken. The goal was to show that ABA methods can run at the barrio level, not just in clinics.

The study did not report any behavior-change results. It only gave the blueprint: what sheets to use, who would collect the data, and how leaders could earn small reinforcers for meeting block-level goals.

The author stated that large-scale community ABA is feasible if you pair simple data systems with local buy-in.

van der Miesen et al. (2024) later ran a similar city program and did measure outcomes. After one year of weekly health sessions, autistic kids got stronger and parents lost weight. Their work turns the 1994 blueprint into real numbers.

Manohar et al. (2019) and Luelmo et al. (2021) shrink the barrio idea down to brief parent classes in India and Latinx USA. Both found short programs can still help parents feel less stress and learn new skills. These studies extend the big-neighborhood model into smaller, faster doses.

Eussen et al. (2016) looked at 13 health programs and saw mixed success. The review warns that wide-area plans often fail without clear targets. This frames Miller (1994) as a first step that later trials must tighten and test.

You can copy the barrio plan when you consult for shelters, clubs, or church groups. Start with one simple count—bags of trash picked up, steps walked, or hand-washes per day. Let residents see the graph each week and earn a group reward. Once the data loop is alive, layer in new targets like mask wearing or veggie intake. The paper reminds us that good ABA can live outside clinic walls; it just needs visible numbers and shared wins.