Capture recapture estimation of the prevalence of mild intellectual disability and substance use disorder.
Merging addiction and disability agency lists reveals twice as many men with both mild ID and substance use disorder.
01Research in Context
What this study did
Researchers used capture-recapture math to count older men with both mild intellectual disability and substance use disorder. They merged client lists from addiction clinics and disability agencies in one region.
The team wanted to see if single-agency counts miss people who appear in both systems.
What they found
Combining the two agency lists doubled the known number of dual-diagnosis clients. One service alone captured only half of the true caseload.
The merged count gave a far better picture of local treatment needs.
How this fits with other research
Slayter (2010) saw the same dual group in Medicaid claims but reported a low 2.6 % rate. The new capture method shows that single-source data still under-count, even in big administrative files.
Pitetti et al. (2007) already proved that one Finnish health register missed ID cases. Koegel et al. (2014) now extends that lesson to the ID-plus-addiction subgroup.
To et al. (2014) surveyed Flanders clinics and described the harm these clients face. The current paper adds the missing piece: how many such clients actually exist.
Why it matters
If you plan services or write grants, do not trust one agency’s caseload as your denominator. Ask addiction and ID programs to share client IDs, then run a simple capture-recapture analysis. You will likely see hidden demand, justify new funding, and design interventions that match the real local prevalence.
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02At a glance
03Original abstract
Persons with mild to borderline intellectual disability (MID) have been identified as a group at risk for substance use disorder (SUD). However, prevalence estimates of co-occurring SUD and MID rely largely on single source studies performed in selected samples. To obtain more reliable population estimates of SUD and MID, this study combines data from an Intellectual Disability Facility (IDF), and an Addiction Treatment Centre (ATC) in a semi-rural area in the Netherlands. Capture-recapture analysis was used to estimate the hidden population (i.e., the population not identified in the original samples). Further analyses were performed for age and gender stratified data. Staff members reported on 88 patients with SUD and MID in the IDF (4.0% of the IDF sample) and 114 in the ATC (5.2% of the ATC sample), with 12 patients in both groups. Only strata for males over 30 years provided reliable population estimates. Based on 97 patients in these strata, the hidden population was estimated at 215. Hence the estimated total population of males over 30 years old with MID and SUD was 312 (95% CI 143-481), approximately 0.16% (0.05-0.25%) of the total population of this age and gender group. This illustrates that while patients with co-occurring SUD and MID often receive professional help from only one service provider, single source data underestimate its prevalence, and thus underestimate treatment and service needs. Therefore, population prevalence estimations of co-occurring SUD and MID should be based on combined multiple source data.
Research in developmental disabilities, 2014 · doi:10.1016/j.ridd.2014.01.018