Latest research: Assessment & FBA

What it found: A meta-analysis of 14 Parkinson’s and 10 Alzheimer’s studies found reliably greater variability in time estimates in both diseases, but impaired average accuracy only in Alzheimer’s disease.

Why it matters: When assessing timing performance in people with these diseases, practitioners should consider variability across responses rather than average accuracy alone.

AI-written summary of the published abstract. Read the original before applying it.

What it found: Teach-back training helped all participating behavior technicians meet mastery criteria for two preference assessment procedures, although one required added feedback and modeling, and participants rated the training as acceptable.

Why it matters: Supervisors could consider teach-back for training preference assessments while checking performance and adding feedback and modeling when needed.

AI-written summary of the published abstract. Read the original before applying it.

What it found: This article reviewed four families of case-specific effect sizes, explained their assumptions and limitations, and offered a framework for choosing whether and how to use them alongside visual analysis.

Why it matters: This guidance can help ABA staff choose appropriate numerical summaries of intervention effects without replacing visual analysis of single-case data.

AI-written summary of the published abstract. Read the original before applying it.

What it found: This article reviewed research on false positives in single-case experimental designs across visual analysis, machine learning, effect estimation, and randomization approaches, outlining ways to reduce errors and areas needing more research.

Why it matters: Understanding false positives can help ABA staff avoid crediting an intervention for changes it did not cause and spending resources on ineffective treatment.

AI-written summary of the published abstract. Read the original before applying it.

What it found: Free-operant assessments compared food, toy, and social preferences in four adult cats, and three cats made more nose-poke responses for their most preferred stimulus than for their least preferred stimulus.

Why it matters: For staff working with cats, systematic preference assessments can identify candidate reinforcers for training and enrichment, with direct testing confirming whether they maintain responding.

AI-written summary of the published abstract. Read the original before applying it.

What it found: The study compared rows, groups, and semicircles for four elementary students and found that students could differ in disruption and on-task behavior within the same seating arrangement.

Why it matters: Staff can use individual behavior and academic data alongside teacher feedback to choose seating arrangements rather than assume one layout works best for everyone.

AI-written summary of the published abstract. Read the original before applying it.

What it found: In 1,395 community adults assessed three times over one year, lower alcohol price sensitivity predicted greater subsequent alcohol use and problems, while greater alcohol use also predicted lower price sensitivity and higher maximum expenditure.

Why it matters: For staff working with alcohol-related concerns, demand measures may help assess risk over time, although this observational study does not establish causation or treatment effectiveness.

AI-written summary of the published abstract. Read the original before applying it.

What it found: In 105 participants, a 100-point preference scale replicated established delay-discounting effects and showed greater ambivalence among people who discounted delayed rewards less and when individuals preferred delayed over immediate rewards.

Why it matters: For everyday reward-choice assessments, these findings suggest that measuring how strongly someone prefers a reward may reveal uncertainty that a simple choice alone misses.

AI-written summary of the published abstract. Read the original before applying it.

What it found: Daily surveys of 75 rural adults with at-risk drinking showed that alcohol demand and the proportion of alcohol-free activities predicted next-day drinking in unadjusted analyses, while adjusted analyses showed that demand–drinking relationships varied by alcohol use severity.

Why it matters: Brief daily measures of alcohol demand and alcohol-free activities may help inform timely digital support for at-risk drinking, although this study did not test an intervention.

AI-written summary of the published abstract. Read the original before applying it.

What it found: This mixed-method study explored how behavior-analytic professionals define and measure caregiver adherence to interventions for challenging behavior and identified needs for clearer definitions, reliable and valid measures, organizational support, and professional training.

Why it matters: Clear definitions and practical, reliable measures of caregiver adherence can help clinicians assess intervention follow-through and identify support needs.

AI-written summary of the published abstract. Read the original before applying it.

What it found: Across two crowdsourced studies, alcohol demand generally increased with suicide risk, while steeper discounting of delayed monetary gains was associated with recent suicide preparations but not suicidal ideation.

Why it matters: These findings suggest alcohol demand and delay discounting may help researchers understand suicide risk, but they do not establish these measures as clinical screening tools.

AI-written summary of the published abstract. Read the original before applying it.

What it found: In hypothetical purchase tasks with employed adults who use LLMs, demand decreased as cost increased, with preferred models retaining demand more strongly than least-preferred models and multi-model platforms valued between them.

Why it matters: Organizations could use demand measures to guide AI access and spending decisions, but hypothetical monetary costs may not predict use under real-world time or effort constraints.

AI-written summary of the published abstract. Read the original before applying it.

What it found: Researchers used functional analyses to guide teaching three Brazilian children with autism to request tangible items, and all three learned the requests while their disruptive behaviors decreased.

Why it matters: The study supports using functional assessment results to select communication skills that can replace disruptive behavior in everyday practice.

AI-written summary of the published abstract. Read the original before applying it.