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The influences of intervention and other factors to specific domains are also described in Table 5.
We next used mixed modeling to assess the contributory influences of intervention- and time-related changes in weight, fasting insulin as a surrogate marker of insulin resistance, and fasting glucose on the differences in biomarker responses between those with versus without incident diabetes (Table 3).
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In addition, the influence of intervention on behavioral intention, action planning, and coping planning, were also presented.
Latent growth modeling was used to provide effect size estimates for the influence of intervention on outcomes.
Further separate analyses were then performed to determine the influence of intervention type (fluoxetine, clomipramine and synthetic feline facial pheromone F3).
Four other studies reported on the influence of intervention adherence on outcomes.
The influence of intervention on these secondary outcome measures was evaluated by a χ test.
The influence of intervention intensity was not clear from the results (data not shown).
Little is known about the nature and mechanisms that underlie the influence of intervention research on health policy or practice.
Also a longer follow-up period could reveal more clear influence of intervention on offspring weight development.
Multivariate logistic regression analyses were performed to assess the influence of intervention and contextual variables on care-seeking behaviours while controlling for individual and sociodemographic factors and living in an intervention or comparison village.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com