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Early tests of intervention effects should test a broad array of plausible mechanisms and outcomes in order to expand our knowledge base and help refine our theoretical models.
Tests of intervention effects analysed participants in their original randomised group, regardless of attendance; participants who completed all four surveys were weighted to represent all those randomised into intervention and control groups.
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For example, these smaller scale studies may contribute to the larger research trajectory by developing measures of constructs and by providing preliminary tests of interventions through student-level quasi-experimental studies.
The cmRCT design allows for tests of interventions that can be compared in the same overall population with similar trial methods, thus increasing the ability to compare and contrast different trial results.
Predictive models, or action frameworks, are needed to organise existing knowledge and enable a more systematic approach to the selection and testing of intervention strategies.
However, further testing of intervention material and evaluation methods is needed.
*Baseline score as covariate and least squares weighted by number of patients within cluster; P value from multivariate test of intervention was 0.002, and cross effect between week and intervention was <0.001.
*Baseline score as covariate and least squares weighted by number of patients within cluster; P values from multivariate test of intervention and cross effect between week and intervention were both <0.001.
The proposed approach and its rationale can serve to contribute to building the science base for the development and testing of intervention approaches for health-promoting practices, and in particular the protection of children from tobacco smoke exposure.
The breadth of rehabilitation treatment requires that many different theoretical perspectives be incorporated into the design and testing of treatment interventions.
Effect sizes were small to medium in paired t tests (comparison of intervention to control) and paired analysis of key variables in the pre- and post-tests.
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