Designing for Prevention: Putting Evidence-Based Prevention Strategies into Practice in Diverse Communities

Bruce D. Rapkin, PhDProfessor of Epidemiology and Population Health

Division of Community Collaboration and Implementation ScienceAlbert Einstein College of Medicine

Conclusions• Participatory models of intervention research are superior

to top down models.

• Scientific rigor does not equal the randomized controlled trial.

• Communities of shared interest must form around Learning Systems - with successive studies leading to refinement of key distinctions among interventions, types populations and settings

• Comprehensive dynamic trials are intended to support the learning system, by inventing and evolving interventions in place, drawing upon multiple sources of information gained during the conduct of an intervention.

Why do we need alternatives to the Randomized Clinical Trial model?

• The community argument

• The business practices argument

• The statistical argument

• The scientific argument

• The psychological argument

Community-Academic Relationships Imposed by the Medical Model

• Funders resist changing interventions promoted as national standards (despite absence of external validity)

• Communities must figure out how to fit themselves to the program – the program dictates the terms

• What communities know about prevention or engaging clients is only relevant if it pertains to the manual

• A tightly scripted protocol does not respond to collaborators’ circumstances

• Danger that lessons learned will be framed as “what the community did wrong to make the program fail”

• Unwillingness to consider limits of research theories and methods, local problems will remain unsolved

Is this any way to run a business?

• Businesses including clinics examine their practices continually to seek improvements

• Research protocols are designed to resist or restrict change over the course of a study, to ensure “standardization”

• Lessons learned must be “ignored” until the next study

• Valuing fidelity over quality impedes progress to optimal intervention approaches

What is a “Treatment Effect”?

• The RCT is designed to determine an estimate of a population “treatment effect”

• Is the “treatment effect” a useful construct?– How is the effect determined by the initial

composition of the sample? – Is information beyond aggregate change error

variance or meaningful trajectories?– How does the control condition determine the

effect’? Is this ignorable?

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Does a Successful RCT Mean that Faithful Replication of an

Intervention will Ensure Outcomes?• Not necessarily because…

– Original RCT findings do not generalize to a “universe” – too dependent on context

– Mechanics of interventions have different implications, depending on setting norms

– Even the meaning & impact of core elements may be transformed by local ecology

• We don’t know because of the lack of attention to external validity!

Desirable Features for Study Designs

• Must take into account diversity inherent in the determinants of health and risk behavior

• Must recognize that different people can respond to the same intervention in different ways, or in the same way for different reasons

• Must accommodate diversity and personal preferences

• Must avoid ethical dilemmas associated with substandard treatment of some participants

• Must be responsive to evolving understanding of how to best administer an intervention, and to local innovations and ideas

• Must contribute to community capacity building and empowerment at every step of the research process

The Research Paradigm We Need…

• A Learning System • A Community Science = A “WIKI”• Who has input

– True integration of multiple methods and perspectives

• Who makes decisions?– The peer review process– The community review process

• Progress toward adequate intervention theory and practice can be quantified

We have (some of) the building blocks

But bridges are always built Somewhere -

Comprehensive Dynamic Trials Designs

• Comprehensive => use complete information from multiple sources to understand what is happening in a trial

• Dynamic => built-in mechanisms for feedback to respond to different needs and changing circumstances

• Trials => Systematic, replicable activities that yield high quality information useful for testing causal hypotheses

Three CDT Designs

• Community Empowerment to enable communities to create new interventions

• Quality Improvement to adapt existing manuals and procedures to new contexts

• Titration-Mastery to optimize algorithms for delivering a continuum of services

Rapkin & Trickett(2005)

CDT Community Empowerment Design

• Closest to the “orthodox” model of CBPR– No pre-conceived “intervention”– No need for externally-imposed explanation of

the problem or theory of change

• Common process of planning

• Common criteria for evaluating implementation across multiple settings and/or multiple “epochs”

CDT Quality Improvement Design

• Starting point– An evidence-based intervention– A established standard of practice– An innovation ready for diffusion

• Alternative to the traditional “top-down” model of intervention dissemination

• Begin with a baseline intervention, then systematically evolve and optimize it

CDT Titration toMastery Design

• Suited to practice settings committed to the client/patient/participant

• Does NOT ask about intervention effects?• Rather, asks what combination of

interventions will get closest to 100% positive outcome most efficiently?

• Begins with a tailoring algorithm to systematically apply a tool kit, which is then evolved and optimized

Contrasting Comprehensive Dynamic Trials with the Prevailing

ParadigmView of: CDT Paradigm RCT Paradigm

Outcomes Replicability of processes Direct generalizability of outcomes

Time Processes unfold over time Time dimension collapsed

Dynamics Continuous improvement Frozen intervention protocol

Knowledge Require community input Limited or no input

Ecology Examine research partnerships No inquiry about researchers’ roles

Rigor Problem solve using all evidence Closed to outside findings

Precision Focus on particular responses Focus on aggregate response

Causality Reciprocal causality Linear causality

Validity Findings framed by context Findings presumed universal

Synthesis Systems modeling is necessary Use of modeling limited

Ingredients of a Comprehensive Dynamic Trial

Just add community and stir…

How does the CDT Feedback Loop Work?

What Types of Data Are Needed?

• Outcome Indicators• Fidelity• Mechanistic Measures• Intervention Processes• Structural Impediments• Adverse Events• Propitious Events• Context Measures

The Deliberation Process

• Key stakeholders should be involved in deliberation

• Research systematically provides data to stakeholders to make decisions about how to modify and optimize interventions

• Timing is based upon the study design• The nature and extent of changes should be

measurable, and expressed in terms of intervention components and procedures

• Deliberation process should be bounded by theory

Ethical Principles – Lounsbury et al.

• Transparency• Shared Authority• Specific Relevance• Rights of Research Participants– Self-Determination– Third-Party Rights– Employees’ Rights

• Privacy• Sound Business Practice• Shared Ownership

A Model for Maximizing Partnership Success: Key Considerations for Planning, Development, and Self-Assessment – Weiss et al.

Environmental Factors

Composition, Structure and Functions

Characteristics of the Group Process

Intermediate Indicators of Partnership

Effectiveness

Development & Implementation of

Programs & Activities

Outcome Indicators of Partnership Effectiveness

A CDT-QI Model to Disseminate an Evidenced-Based Approach to Promote

Breast Cancer Screening

The Bronx ACCESS ProjectThe Albert Einstein Cancer Center

Program Project Application Under Development

Theoretical Underpinnings• Empowerment via Mediating Structures• Diffusion of Innovation• Community-Based Participatory Research• Intervention Tailoring/Lay Health Advisors• Amalgam of our team’s prior intervention research

– Weiss – effective partnerships– Lounsbury – collaborative capacity– Thompson – trust and adherence– Goodman – leadership– Rapkin – problem-solving

Bronx ACCESS Conceptual Model of Dissemination

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Building Agency Capacity & Readiness

Optimizing Health Promotion Continuum

Engaging Community in Adaptation & Tailoring

PopulationAdherence

AgencyRoutinization+

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Dissemination involves dynamic, mutually-reinforcing processes that unfold over time

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Multi-level interventions are

intrinsic to the dissemination

process, interacting to

counter interference and promote desired outcomes over

time

We hypothesize that this model of dissemination will

lead to ever greater

improvements in in adherence to

breast screening guidelines,

associated with increased agency institutionalization of a continuum

of evidence-based tailored

strategies

At any time, factors at individual, community,

organizational, or systems levels can

interfere with the dissemination process,

and must be countered.

Initial Conditions•Social, cultural and economic population characteristics •Baseline adherence to guidelines•Agency resources•Agency reach•Community resources & involvement•Local service ecology •Baseline levels of sources of interference

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Intervention at Three Levels

• Individual (Continuum via Lay Health Advisors)– Women from three Bronx neighborhoods, out of

adherence with, or uncertain about, screening guidelines

• Organizational (Process Consultation)– Community social service agencies able to reach large

numbers of medically-underserved women

• Community (Adaptation via Participatory Research)– Representatives of different sectors with relevant

knowledge to help guide disseminations

• PLUS – Modeling processes to inform

policy Building Agency

Capacity & Readiness

Optimizing Health Promotion Continuum

Engaging Community in Adaptation & Tailoring

PopulationAdherence

AgencyRoutinization

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+

+ +

Changing the Rules to Conduct Research in the Real World

• How to incorporate local input in an evidence based paradigm?– Solution: Fidelity gets a vote, but not a veto

• How to deal with cultural and risk specificity of mammography screening interventions?– Solution: disseminate a “suite” of theoretically

equivalent strategies as a tool kit

• How to address agencies’ many priorities?– Solution: Encompass these as “community targeted

strategies” for outreach & retention

How Do You Get Science Out of All That Data?

In Any One CDT …

• Analyses are intrinsic to intervention

• The program should get better as it goes along

• Experimental effects may be examined in context

• Particularly interested in accounting for diverse trajectories and patterns of responses

• Ability to steer toward optimal intervention components

• Case study of community problem solving

• Able to examine setting impacts, sustainability

The Real Payoff – Science as a Community Process

The Epistemology of CDT

• A Community Science = A “WIKI”• A learning system• Who has input

– True integration of multiple methods

• Who makes decisions?– the peer review process

• Progress toward theory development can be quantified

• Theory can be (provisionally) completed

The Comparative Effectiveness Matrix

What outcomes distinct are associated with different intervention approaches?

How do characteristics of target population affect outcomes?

How are outcomes affected by history, resources, and contexts?

Oipc|t

The conditionalprobability of an outcome, for this type ofintervention with this population inthis context, givenwhat is known atthe present time.

Wiring Up the Comparative Effectiveness Matrix:

Systems Dynamics? Neural Networks? Genetic Algorithms?

1) An intervention

3) in different contexts

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2) experienced by different people

4) may lead to different outcomes.

ARROWS indicate probabilistic pathways Oipc|t at time T

Tx

Scientific Enterprise Needed to Support this paradigm

• Evaluation for funding will consider soundness of researchers’ relationships with communities

• Multiple sources of data will gain importance• Emphasis on practice-based evidence• Case studies of planning, decision making and

community involvement will be highly important• Awareness that results depend on context, so a single

trial will not receive undue weight• Investigators will work in tandem to create service

suites and knowledge bases• Meta-analysis will grow more important, as a way of

integrating multiple types of studies

Where’s the Science?

• In community process.

• In understanding how researchers’ roles and activities impact CBPR.

• In the evolution and refinement of intervention implementation strategies, through dynamic exchange and reflection.

• It emerges out of the synthesis of CBPR findings

Conclusions• Participatory models of intervention research are superior

to top down models.

• Scientific rigor does not equal the randomized controlled trial.

• Communities of shared interest must form around Learning Systems - with successive studies leading to refinement of key distinctions among interventions, types populations and settings

• Comprehensive dynamic trials are intended to support the learning system, by inventing and evolving interventions in place, drawing upon multiple sources of information gained during the conduct of an intervention.