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*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.
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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.
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.
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.
We will test heterogeneity of intervention effects among trials using the standard χ statistic (p value) or the I statistic.
Standardized change scores will be calculated by subtracting pre-test score from post-test score of intervention and dividing by the SD for all participants combined.
Development and testing of interventions within actual program contexts is needed to facilitate translation to full-scale implementation.
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