Two of the larger projects that Connection Lab has been working on lately are related, but they’re not formally connected. The first project is helping the Greater Boston Suicide Prevention Coalition conduct and analyze a series of focus groups to learn about how best to provide suicide prevention to diverse populations. The second project is coordinating the development of a statewide strategic plan for problem gambling prevention and services. In both cases, the people involved in the projects are extremely knowledgeable about their subject areas and they are thinking carefully about how to make the best use of limited resources in order to have the greatest impact on the issue that they are concerned about; suicide or gambling.
In both cases, the age-old question has come up of how much money and energy to allocate to primary prevention, or keeping the healthy population healthy, and how much to allocate to “services” or treatment and support for people who are already experiencing a health concern.
While keeping people healthy is valuable, it’s not count-able and trackable in the same way that clients and service provision are quantifiable. It’s a struggle to think about how best to evaluate the outcomes and not just the outputs of prevention efforts. In a funding environment that’s becoming more evidence-based and outcome-driven, the strongest evaluation designs can secure the financial and emotional backing of important stakeholders. Since the evaluation of primary prevention is often the least robust (and/or the most expensive) section of an evaluation design, prevention can be easily be pushed aside to expand secondary and tertiary prevention initiatives like intervention with high-risk populations and treatment services.
The waters of evaluation design once again become murky at the recovery end of the prevention continuum. Whether the health concern is suicidal ideation, problem gambling or even a broken bone, at what point do the “ill” rejoin the ranks of the “well” population and stop being tracked, counted and measured except through population-based samples? How do we track the maintained health of the once-ill and how can we keep recovery, both physical and psychological, as strong components of our implementation plans even when they’re difficult to fit into our evaluation plans?