Bill Overview
Title: Improving Data Collection for Adverse Childhood Experiences Act
Description: This bill authorizes the Centers for Disease Control and Prevention (CDC) to collect data, in cooperation with states, through relevant public health surveillance systems or surveys for a longitudinal study on the links between adverse childhood experiences and negative outcomes. In addition, the CDC may provide, directly or through grants or other agreements with public or nonprofit entities, technical assistance related to this data collection.
Sponsors: Sen. King, Angus S., Jr. [I-ME]
Target Audience
Population: People who have experienced adverse childhood experiences (ACEs)
Estimated Size: 82000000
- The bill focuses on adverse childhood experiences (ACEs), which are known to affect children who undergo traumatic events such as abuse, neglect, or household dysfunction.
- Children are the primary population directly impacted since the data collection aims to understand and eventually mitigate negative outcomes associated with their adverse experiences.
- The longitudinal study intends to understand the links between ACEs and their outcomes over time, impacting current and future generations of children who are evaluated in the study.
- Public health professionals, policymakers, and educators will use the findings to develop interventions to support children with ACEs.
- Relevant data collected and analyzed could indirectly impact mental health and social services for both children and adults who have experienced ACEs.
Reasoning
- The policy primarily targets children who have undergone adverse childhood experiences (ACEs) as well as adults who experienced them as children, a significant portion of the population.
- Considering about 46% of children in the US have experienced at least one ACE, the policy will likely affect a broad spectrum of the population.
- The budget limits the scale but is substantial enough for extensive data collection and analysis, which often requires sophisticated methodologies and large datasets.
- The initial impact directly affects public health professionals, social services, and policymakers who could utilize this data to improve interventions and allocate resources effectively.
- Indirect impacts include the potential for enhanced mental health and social services arising from the longitudinal data insights, benefiting individuals in the long-term.
Simulated Interviews
Public health researcher (Atlanta, GA)
Age: 35 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 5/20
Statement of Opinion:
- This policy is crucial for understanding long-term health impacts of childhood trauma.
- It will provide valuable data to support interventions.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 9 | 6 |
High school teacher (Denver, CO)
Age: 45 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 7/20
Statement of Opinion:
- Data from this policy will help schools tailor support for children facing ACEs.
- More targeted interventions will improve student outcomes.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 8 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 9 | 6 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 6 |
Retired social worker (Boston, MA)
Age: 60 | Gender: female
Wellbeing Before Policy: 8
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- This data collection could illuminate the path to better preventive measures.
- It's a step toward more informed social work.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 8 |
Mental health counselor (Los Angeles, CA)
Age: 30 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 15.0 years
Commonness: 4/20
Statement of Opinion:
- This policy may validate the experiences many clients face.
- Longitudinal data could strengthen therapeutic approaches.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 7 | 5 |
| Year 5 | 7 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 5 |
Grad student in public policy (Chicago, IL)
Age: 25 | Gender: other
Wellbeing Before Policy: 6
Duration of Impact: 7.0 years
Commonness: 7/20
Statement of Opinion:
- Government-led data can drive policy change.
- Building robust datasets is key to crafting effective interventions.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 7 | 6 |
Pediatrician (Miami, FL)
Age: 50 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 8/20
Statement of Opinion:
- Understanding ACEs can change treatment plans for vulnerable kids.
- The policy is necessary for informed healthcare provision.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 9 | 7 |
| Year 3 | 9 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 7 |
Child therapist (New York, NY)
Age: 40 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 6/20
Statement of Opinion:
- More informed policies will emerge from this research.
- This is a foundational step for future interventions.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 7 |
Community health advocate (Seattle, WA)
Age: 55 | Gender: female
Wellbeing Before Policy: 8
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- This policy could offer critical insights for marginalized groups.
- Utilizing data for education and preventive measures is crucial.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 8 |
| Year 10 | 8 | 8 |
| Year 20 | 8 | 8 |
Psychiatrist (Houston, TX)
Age: 65 | Gender: male
Wellbeing Before Policy: 9
Duration of Impact: 5.0 years
Commonness: 9/20
Statement of Opinion:
- This policy will enhance our understanding of childhood adversity.
- Results could influence both clinical and academic settings.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 9 | 9 |
| Year 2 | 9 | 9 |
| Year 3 | 9 | 9 |
| Year 5 | 9 | 9 |
| Year 10 | 9 | 9 |
| Year 20 | 9 | 9 |
Nonprofit worker (Phoenix, AZ)
Age: 29 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 15.0 years
Commonness: 4/20
Statement of Opinion:
- This initiative can lead to more targeted support at grassroots levels.
- Understanding long-term impacts is key to overcoming trauma.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 9 | 5 |
Cost Estimates
Year 1: $250000000 (Low: $200000000, High: $300000000)
Year 2: $250000000 (Low: $200000000, High: $300000000)
Year 3: $250000000 (Low: $200000000, High: $300000000)
Year 5: $250000000 (Low: $200000000, High: $300000000)
Year 10: $250000000 (Low: $200000000, High: $300000000)
Year 100: $250000000 (Low: $200000000, High: $300000000)
Key Considerations
- The longitudinal nature of the study implies long-term engagement and analysis, impacting budget estimates.
- Coordination with multiple state and federal entities is necessary for cohesive data collection.
- The technical assistance component requires additional resources, potentially increasing costs over time.