Behavioral Health Research
Rigorous research intelligence
applied to behavioral health.
Recovery Insights Lab brings high-stakes polling, data modeling, and behavioral analysis to the behavioral health sector — producing intelligence that drives better decisions.
Our Mission
Close the gap between what the data says and what the field needs to know.
Behavioral health organizations have been making decisions on stale, fragmented intelligence. Government data runs years behind. Academic research moves at an academic pace. We exist to close that gap — with precision research tools that high-stakes decision-making actually demands.
The Problem
The field is flying blind. Government data is 18 months old. Academic research is grant-driven. Nobody's connecting the dots.
18–24 Months Old
Government and academic data arrives 18 to 24 months after collection. By the time it reaches the field, the world has moved on.
Fragmented
Scattered across agencies, journals, and advocacy silos that never talk to each other — and never produce a coherent picture.
Spun
Shaped to fit a conclusion before the data arrives. Grant-driven research tells you what the funder wanted to hear.
Untranslated
Rarely telling a provider or funder what to actually do with it. Data without interpretation is just numbers.
Our Methodology
Proven research methods. A data set no one else has built.
The methods aren't new. The data set is. We bring rigorous applied research — audience profiling, panel design, large-scale survey operations, and high-stakes data analysis — to a domain that has never had it: behavioral health and recovery.
01
Survey Design
Every instrument is designed from scratch — sampling frames, question architecture, response options, and panel composition. We know how to reach hard-to-access populations and how to write questions in language that reflects how people in recovery actually talk about their lives.
02
Data Interpretation
Before results are analyzed, we map every assumption embedded in the design — where question framing inflates or suppresses a finding, where response-ordering effects distort the picture, and where a standard scale simply doesn't fit the population.
03
Analytical Techniques
We apply crosstab analysis, multivariate segmentation, and longitudinal trend modeling across dimensions behavioral health research rarely cuts: recovery pathway, duration, modality, mental health co-occurrence, and demographic intersections.
04
Insight Translation
We write findings for people making real decisions — plain language that names what the data says, contextualizes it against the longitudinal record, and tells you what it means for your program, policy, or population.
