Matt Harrington

This post is for clinic directors, BCBA supervisors, and senior clinicians seeking to promote equity in supervision practices. It shows how to use data-driven, ethical strategies to tailor support, remove barriers, and ensure fair advancement without lowering standards. Learn practical steps and examples for turning ABA supervision data into clear, transparent decisions that improve outcomes for supervisees and clients.

This piece is for ABA clinicians and intake staff seeking to start cases safely and efficiently. It explains how to identify and request relevant records early—medical, educational, prior ABA notes, incident reports—and how to review them to shape an informed assessment plan. It emphasizes turning ABA data from records into clear, ethical decisions—identifying safety concerns, avoiding duplicate testing, and aligning measurement with prior work—along with practical steps and common pitfalls.

This guide helps clinicians turn ABA data into clear, ethical decisions by aligning motivating operations (MOs) with discriminative stimuli (SDs) in behavior-change plans. It explains what MOs and SDs are, how they interact, and offers practical steps to assess MO, design SDs, and match reinforcers to current motivation. It’s written for clinicians, supervisors, and ABA students who design and monitor interventions. Ethical considerations, consent, and thorough documentation are emphasized to prevent brittle change and uphold client dignity.

This post is for clinicians, BCBA students, and behavior-support teams who design and implement ABA plans. It shows how to design and evaluate functional analyses to identify the function of problem behaviors and to create function-based, ethical interventions. You’ll learn about FA formats, reliable measurement, and common pitfalls so you can turn ABA data into clear, practical decisions that protect client dignity and improve outcomes.

Designed for practicing BCBAs, supervisors, and clinically minded RBTs who want to improve causal inferences in ABA. It explains threats to internal validity (history, maturation, instrumentation, etc.) and offers practical tools to rule them out using data and documentation. By emphasizing stable measurement, replication, and transparent ethics, it helps you turn ABA data into clear, ethical decisions about intervention effects.

Designed for BCBAs, BCaBAs, RBTs, and clinic teams who collect ABA data, this guide shows how to turn raw counts into clear, decision-ready visuals. It covers equal-interval line graphs, bar graphs, and cumulative records—explaining when to use each and how to build graphs that are honest and easy to interpret for families. You’ll learn quick visual analyses (level, trend, variability) to make ethical, data-driven decisions that prioritize client welfare and transparent communication.

This practical guide is for BCBAs, clinic leaders, supervisors, and clinically informed caregivers who want to refine an existing behavior by shaping one measurable dimension at a time. It explains how to turn ABA data into clear, ethical decisions—identifying a single dimension (frequency, duration, latency, magnitude, or topography), defining it precisely, and progressing in small, data-driven steps. With emphasis on safety, consent, and dignity, it shows how to plan, monitor, and adjust shaping plans to achieve durable, ethical outcomes.

This post is for ABA clinicians, supervisors, and students who implement behavior-change procedures and need to understand clients’ emotional and elicited responses. It explains how to measure these effects—using direct observation, simple rating scales, and client or caregiver reports—to distinguish temporary distress from potential harm. You’ll learn practical, data-driven steps to interpret the data, set stopping or modification rules, and adjust interventions to protect safety, dignity, and ethical practice. The focus is turning ABA data into clear, ethical decisions about continuing, modifying, or stopping procedures.

Designed for practicing BCBAs, clinic leaders, RBT supervisors, and clinically informed caregivers, this post explains how to select socially valid, functionally equivalent replacement behaviors that actually work in daily life. It shows how to turn FBA data into clear, ethical decisions—matching function, securing social validity, and planning teachability, measurement, and generalization. You’ll get a practical framework, common pitfalls to avoid, and concrete steps you can implement this week to replace problematic behavior with a better, ethically sound alternative.

This article is for behavior analysts, clinicians, and IEP teams who write intervention plans, helping them craft observable, measurable goals that are ethically grounded and data-driven. It outlines the five building blocks—target behavior, context, criterion, measurement method, and timeframe—with practical examples to ensure goals are concrete and trackable. By focusing on turning ABA data into clear, actionable decisions, readers can determine when to continue, adjust, or end interventions while honoring learner dignity and family collaboration.