Harnessing the Impact of the Arts for Well-being

LATEST DEVELOPMENTS

NEW LEGISLATION

Performance Hypothesis led the collaborative development of Georgia House Resolution 1007 acknowledging the effectiveness of the arts for mental health outcomes. The unique legislation makes Georgia the first state in the nation to formally recognize the arts as a resource for mental health treatment. Read the press release here.

MUSIC & BRAIN HEALTH

The Alzheimer’s Foundation of America awarded a $200,000 research grant exploring how artistic engagement may promote brain health, emotional well-being, and social connection for individuals living with cognitive change and their care partners. The award is a collaboration among Emory Goizueta Brain Health Institute, the Atlanta Symphony Orchestra, and Performance Hypothesis.

ONLINE EDUCATION

Along with the New Jersey Performing Arts Center (NJPAC) and Rutgers University, Performance Hypothesis is a co-creator of a new affordable, accessible online education courses to help arts, health, and allied practitioners provide arts programming for health promotion and well-being. Check out this exciting community resource.

what we do

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We activate science, strategy, and creativity to evaluate and expand the connection between artistic expression and measurable wellness outcomes.

We partner with arts institutions, healthcare organizations, and academic partners to design, scale, and evaluate arts and health programs.

what we offer

IMPACT
ASSESSMENT

We bring together data, stories, and creativity-infused methods to create a complete picture of your programs – celebrating progress while identifying opportunities for growth.

PROGRAM
DESIGN & LAUNCH

We partner to design programs where research, evaluation, and community input shapes strategy from the beginning – creating real-world impact and building credibilty.

STRATEGIC
GROWTH & SCALE

We collaborate to scale effective arts and health programs strategically – generating evidence and evaluation capacity that turns local successes into replicable models.