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Journal ArticleDOI

Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms.

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TLDR
Proactive, home-based, and stage-matched expert systems can produce relatively high population impacts on multiple behavior risks for cancer and other chronic diseases.
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This article is published in Preventive Medicine.The article was published on 2005-08-01. It has received 374 citations till now. The article focuses on the topics: Population & Health care.

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Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions.

TL;DR: A meta-analytic review of the literature on tailored print health behavior change interventions found the sample size-weighted mean effect size of the effects of tailoring on health behaviorchange was found to be r = .074.
Journal ArticleDOI

Stages of change

TL;DR: An original meta-analysis of 39 studies, encompassing 8,238 psychotherapy patients, to assess the ability of stages of change and related readiness measures to predict psychotherapy outcomes finds clinically significant effect sizes were found.
Journal ArticleDOI

A review of eHealth interventions for physical activity and dietary behavior change.

TL;DR: In this paper, a review of eHealth intervention studies for adults and children that targeted behavior change for physical activity, healthy eating, or both behaviors is presented, where participants interacted with some type of electronic technology either as the main intervention or an adjunct component.
Reference EntryDOI

Self-help interventions for smoking cessation.

TL;DR: There is evidence that materials that are tailored for individual smokers are effective, and are more effective than untailored materials, although the absolute size of effect is still small, and that tailored materials as more helpful than standard materials are supported.
Journal ArticleDOI

Multiple health behavior change research: an introduction and overview.

TL;DR: The rationale and need for MHBC research and interventions are presented, the research base is briefly reviewed, and core conceptual and methodological issues unique to this growing area are identified.
References
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Missing data: Our view of the state of the art.

TL;DR: 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI) are presented and may eventually extend the ML and MI methods that currently represent the state of the art.
Journal ArticleDOI

Longitudinal data analysis for discrete and continuous outcomes.

Scott L. Zeger, +1 more
- 01 Mar 1986 - 
TL;DR: A class of generalized estimating equations (GEEs) for the regression parameters is proposed, extensions of those used in quasi-likelihood methods which have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as the authors often expect.
Book

Analysis of Incomplete Multivariate Data

TL;DR: The Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data and Inference by Data Augmentation Methods for Normal Data provide insights into the construction of categorical and mixed data models.
Journal ArticleDOI

Healthy People 2010.

TL;DR: These objectives and their associated baseline data and targets for the year 2010 are presented and members of the MCH community are encouraged to review and comment on these objectives during the public comment period.
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