This study illustrates the use of mixture analysis in evaluating preventive community interventions implemented in non-experimental framework. When no control groups was designed and no matched comparison group is available as full panel data, the question of the impact of an intervention can be addressed by investigating model implied latent classes of participants that responded differently to an intervention. We illustrate this approach with an intervention conducted in Hartford, CT aimed at increasing awareness and use of the female condom (FC) as a women-initiated HIV and sexually transmitted infections (STI) prevention method.
The best solution was deemed a three latent classes grouping for the no-covariate times used FC GMM mixture model, which divided up the sample into 222 fast increasing use participants, 201 moderate increase, and 38 consistent (stable) users.These groups differed significantly on: Times used FC at waves 2 and 3; FC stage of use at all three waves; FC beliefs at all three waves; FC knowledge at wave 3.
We might conclude these are distinct groups that need to targeted by differential (tailored) intervention strategies for female condom adoption/increased use.
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