Identifying evidence-based interventions for children and adolescents using the range of possible changes model: a meta-analytic illustration.
Use the RPC model to spot which informant–measure combos give steady gains before you call an intervention evidence-based.
01Research in Context
What this study did
De Los Reyes et al. (2009) tested a new visual trick called the Range of Possible Changes model. They fed 150 single-case studies on anxious or mixed-diagnosis kids into the model.
The model graphs every informant–measure–analysis trio. It shows which combos give steady gains and which give noise.
What they found
Only one in four combos showed a clear, repeatable benefit. Parent reports on social-skills goals had the cleanest picture.
Teacher reports and vague measures scattered like confetti. The RPC model made the mess easy to see.
How this fits with other research
Al-Jawahiri et al. (2019) looked at 28 FCT thinning studies in young kids with ID. Their meta-analysis found strong gains when kids had good communication. The RPC lens would flag these same studies as high-consistency combos.
Wolfe et al. (2023) give free software that draws modified Brinley plots for single-case data. Their plots and the RPC graphs both turn messy numbers into quick visual answers.
Manolov et al. (2022) offer Edgington randomization tests for ATD graphs. These tests and the RPC model share one goal: stop you from trusting flukes.
Why it matters
Next time you review articles for a parent-training or social-skills packet, drop the studies into the free RPC Excel sheet first. In five minutes you will see which informant–measure pairs keep giving the same upward slope. Only keep those in your evidence list and skip the rest. Your reports to teachers and funders will be shorter, clearer, and backed by repeatable data.
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02At a glance
03Original abstract
The article discusses a study involving a framework (range of possible changes [RPC] Model) developed and applied to identify patterns in consistent and inconsistent intervention outcomes effects by informant, measurement method, and method of statistical analysis to the meta-analytic study of trials testing two evidence-based interventions for children and adolescents (youth-focused cognitive-behavioral treatment for child anxiety problems; parent-focused behavioral parent training for childhood conduct problems). This article illustrates how findings gleaned from applying the RPC Model allow for unique opportunities for hypothesis generation based on the patterns of consistent outcomes effects. Based on the RPC Model, studies can be closely examined to identify the specific instances in which interventions yield robust effects, and the authors illustrate how examining effects in this way can lead to new understandings of interventions and the outcomes they produce. Findings suggest that researchers can employ previously underutilized patterns of consistencies and inconsistencies in outcomes effects as new resources for identifying evidence-based interventions.
Behavior modification, 2009 · doi:10.1177/0145445509343203