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Journal ArticleDOI

Project Northland: long-term outcomes of community action to reduce adolescent alcohol use

01 Feb 2002-Health Education Research (Oxford University Press)-Vol. 17, Iss: 1, pp 117-132

TL;DR: Developmentally appropriate, multi-component, community-wide programs throughout adolescence appear to be needed to reduce alcohol use among adolescents in northeastern Minnesota.

AbstractProject Northland was a randomized trial to reduce alcohol use among adolescents in 24 school districts in northeastern Minnesota. Phase 1 (1991-1994), when the targeted cohort was in grades 6-8, included school curricula, parent involvement, peer leadership and community task forces. The Interim Phase (1994-1996) involved minimal intervention. Phase 2 (1996-1998), when the cohort was in grades 11 and 12, included a classroom curriculum, parent education, print media, youth development and community organizing. Outcomes of these interventions were assessed by annual student surveys from 1991 to 1998, alcohol purchase attempts by young-looking buyers in 1991, 1994 and 1998, and parent telephone surveys in 1996 and 1998. Growth curve analysis was used to examine the student survey data over time. Project Northland was most successful when the students were young adolescents. The lack of intervention in the Interim Phase when the students were in grades 9 and 10 had a significant and negative impact on alcohol use. The intervention used with the high school students as those in grades 11 and 12 made a positive impact on their tendency to use alcohol use, binge drinking and ability to obtain alcohol. There was no impact in Phase 2 on other student-level behavioral and psychosocial factors. Developmentally appropriate, multi-component, community-wide programs throughout adolescence appear to be needed to reduce alcohol use.

Topics: Binge drinking (56%), Peer leadership (54%), Psychological intervention (51%), Interim (51%), Positive Youth Development (51%)

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Book
01 Aug 2009
TL;DR: Mental, emotional, and behavioral (MEB) disorders—which include depression, conduct disorder, and substance abuse—affect large numbers of young people.
Abstract: This report builds on a highly valued predecessor, the 1994 Institute of Medicine (IOM) report entitled Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research. That report provided the basis for understanding prevention science, elucidating its then-existing research base, and contemplating where it should go in the future. This report documents that an increasing number of mental, emotional, and behavioral problems in young people are in fact preventable. The proverbial ounce of prevention will indeed be worth a pound of cure: effectively applying the evidence-based prevention interventions at hand could potentially save billions of dollars in associated costs by avoiding or tempering these disorders in many individuals. Furthermore, devoting significantly greater resources to research on even more effective prevention and promotion efforts, and then reliably implementing the findings of such research, could substantially diminish the human and economic toll.

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Abstract: Interventions to change everyday behaviors often attempt to change people's beliefs and intentions. As the authors explain, these interventions are unlikely to be an effective means to change behaviors that people have repeated into habits. Successful habit change interventions involve disrupting the environmental factors that automatically cue habit performance. The authors propose two potential habit change interventions. “Downstream-plus” interventions provide informational input at points when habits are vulnerable to change, such as when people are undergoing naturally occurring changes in performance environments for many everyday actions (e.g., moving households, changing jobs). “Upstream” interventions occur before habit performance and disrupt old environmental cues and establish new ones. Policy interventions can be oriented not only to the change of established habits but also to the acquisition and maintenance of new behaviors through the formation of new habits.

941 citations


Cites background from "Project Northland: long-term outcom..."

  • ...In this quadrant, there are many downstream strategies that have proved effective in changing nonhabitual behaviors (e.g., Perry et al. 1996, 2002; Webb and Sheeran 2006) and in generating short-term change in ongoing behaviors (e.g., Orleans 2000)....

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  • ...Habits are a form of automaticity in responding that develops as people repeat actions in stable circumstances ( Pascoe and Wood, in press; Verplanken 2006; Verplanken and Aarts 1999)....

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Journal ArticleDOI
TL;DR: The results of this review provide evidence for the effectiveness of some interventions based on the Health Promoting Schools framework for improving certain health outcomes but not others; however, there was a lack of long-term follow-up data for most studies.
Abstract: BACKGROUND: The World Health Organization's (WHO's) Health Promoting Schools (HPS) framework is an holistic, settings-based approach to promoting health and educational attainment in school. The effectiveness of this approach has not been previously rigorously reviewed. OBJECTIVES: To assess the effectiveness of the Health Promoting Schools (HPS) framework in improving the health and well-being of students and their academic achievement. SEARCH METHODS: We searched the following electronic databases in January 2011 and again in March and April 2013: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, CINAHL, Campbell Library, ASSIA, BiblioMap, CAB Abstracts, IBSS, Social Science Citation Index, Sociological Abstracts, TRoPHI, Global Health Database, SIGLE, Australian Education Index, British Education Index, Education Resources Information Centre, Database of Education Research, Dissertation Express, Index to Theses in Great Britain and Ireland, ClinicalTrials.gov, Current controlled trials, and WHO International Clinical Trials Registry Platform. We also searched relevant websites, handsearched reference lists, and used citation tracking to identify other relevant articles. SELECTION CRITERIA: We included cluster-randomised controlled trials where randomisation took place at the level of school, district or other geographical area. Participants were children and young people aged four to 18 years, attending schools or colleges. In this review, we define HPS interventions as comprising the following three elements: input to the curriculum; changes to the school's ethos or environment or both; and engagement with families or communities, or both. We compared this intervention against schools that implemented either no intervention or continued with their usual practice, or any programme that included just one or two of the above mentioned HPS elements. DATA COLLECTION AND ANALYSIS: At least two review authors identified relevant trials, extracted data, and assessed risk of bias in the trials. We grouped different types of interventions according to the health topic targeted or the approach used, or both. Where data permitted, we performed random-effects meta-analyses to provide a summary of results across studies. MAIN RESULTS: We included 67 eligible cluster trials, randomising 1443 schools or districts. This is made up of 1345 schools and 98 districts. The studies tackled a range of health issues: physical activity (4), nutrition (12), physical activity and nutrition combined (18), bullying (7), tobacco (5), alcohol (2), sexual health (2), violence (2), mental health (2), hand-washing (2), multiple risk behaviours (7), cycle-helmet use (1), eating disorders (1), sun protection (1), and oral health (1). The quality of evidence overall was low to moderate as determined by the GRADE approach. 'Risk of bias' assessments identified methodological limitations, including heavy reliance on self-reported data and high attrition rates for some studies. In addition, there was a lack of long-term follow-up data for most studies.We found positive effects for some interventions for: body mass index (BMI), physical activity, physical fitness, fruit and vegetable intake, tobacco use, and being bullied. Intervention effects were generally small but have the potential to produce public health benefits at the population level. We found little evidence of effectiveness for standardised body mass index (zBMI) and no evidence of effectiveness for fat intake, alcohol use, drug use, mental health, violence and bullying others; however, only a small number of studies focused on these latter outcomes. It was not possible to meta-analyse data on other health outcomes due to lack of data. Few studies provided details on adverse events or outcomes related to the interventions. In addition, few studies included any academic, attendance or school-related outcomes. We therefore cannot draw any clear conclusions as to the effectiveness of this approach for improving academic achievement. AUTHORS' CONCLUSIONS: The results of this review provide evidence for the effectiveness of some interventions based on the HPS framework for improving certain health outcomes but not others. More well-designed research is required to establish the effectiveness of this approach for other health topics and academic achievement.

387 citations


Journal ArticleDOI
Abstract: Community coalitions have become popular vehicles for promoting health. Which factors make coalitions effective, however, is unclear. The study's aim was to identify coalition-building factors related to indicators of coalition effectiveness through a review of the empirical literature. Published articles from 1980 to 2004 that empirically examined the relationships among coalition-building factors and indicators of coalition effectiveness were reviewed. Two indicators of coalition effectiveness were examined: coalition functioning and community-wide changes. A two-phase strategy was employed to identify articles by reviewing citations from previous literature reviews and then searching electronic reference databases. A total of 1168 non-mutually exclusive citations were identified, their abstracts reviewed, and 145 unique full articles were retrieved. The review yielded 26 studies that met the selection criteria. Collectively, these studies assessed 26 indicators of coalition effectiveness, with 19 indicators (73%) measuring coalition functioning, and only two indicators (7%) measuring changes in rates of community-wide health behaviors. The 26 studies identified 55 coalition-building factors that were associated with indicators of coalition effectiveness. Six coalition-building factors were found to be associated with indicators of effectiveness in five or more studies: formalization of rules/procedures, leadership style, member participation, membership diversity, agency collaboration, and group cohesion. However, caution is warranted when drawing conclusions about these associations due to the wide variations in indicators of coalition effectiveness and coalition-building factors examined across relatively few studies, discrepancies in how these variables were measured, and the studies' reliance on cross-sectional designs.

317 citations


Journal ArticleDOI
TL;DR: Findings from research on smoking, alcohol, and other drug use show that the network approach is instructive for understanding social influences on substance use, and how network analysis can be used to design more effective prevention programs and to monitor and evaluate these programs.
Abstract: We review findings from research on smoking, alcohol, and other drug use, which show that the network approach is instructive for understanding social influences on substance use. A hypothetical network is used throughout to illustrate different network findings and provide a short glossary of terms. We then describe how network analysis can be used to design more effective prevention programs and to monitor and evaluate these programs. The article closes with a discussion of the inherent transdisciplinarity of social network analysis.

251 citations


Cites background from "Project Northland: long-term outcom..."

  • ...Peer leaders are usually chosen by asking students to write the names of other students who they consider to be good leaders (Johnson et al., 1986; Perry et al., 2002)....

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References
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Book
01 Jan 1978
Abstract: 1. CONCEPTS AND EXAMPLES OF RESEARCH. Concepts. Examples. Concluding Remarks. References. 2. CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS. Classification of Variables. Overlapping of Classification Schemes. Choice of Analysis. References. 3. BASIC STATISTICS: A REVIEW. Preview. Descriptive Statistics. Random Variables and Distributions. Sampling Distributions of t, ?O2, and F. Statistical Inference: Estimation. Statistical Inference: Hypothesis Testing. Error Rate, Power, and Sample Size. Problems. References. 4. INTRODUCTION TO REGRESSION ANALYSIS. Preview. Association versus Causality. Statistical versus Deterministic Models. Concluding Remarks. References. 5. STRAIGHT-LINE REGRESSION ANALYSIS. Preview. Regression with a Single Independent Variable. Mathematical Properties of a Straight Line. Statistical Assumptions for a Straight-line Model. Determining the Best-fitting Straight Line. Measure of the Quality of the Straight-line Fit and Estimate ?a2. Inferences About the Slope and Intercept. Interpretations of Tests for Slope and Intercept. Inferences About the Regression Line ?YY|X = ?O0 + ?O1X . Prediction of a New Value of Y at X0. Problems. References. 6. THE CORRELATION COEFFICIENT AND STRAIGHT-LINE REGRESSION ANALYSIS. Definition of r. r as a Measure of Association. The Bivariate Normal Distribution. r and the Strength of the Straight-line Relationship. What r Does Not Measure. Tests of Hypotheses and Confidence Intervals for the Correlation Coefficient. Testing for the Equality of Two Correlations. Problems. References. 7. THE ANALYSIS-OF-VARIANCE TABLE. Preview. The ANOVA Table for Straight-line Regression. Problems. 8. MULTIPLE REGRESSION ANALYSIS: GENERAL CONSIDERATIONS. Preview. Multiple Regression Models. Graphical Look at the Problem. Assumptions of Multiple Regression. Determining the Best Estimate of the Multiple Regression Equation. The ANOVA Table for Multiple Regression. Numerical Examples. Problems. 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Regression Model for Fixed-effects One-way ANOVA Fixed-effects Model for One-way ANOVA. Random-effects Model for One-way ANOVA. -comparison Procedures for Fixed-effects One-way ANOVA. a Multiple-comparison Technique. Orthogonal Contrasts and Partitioning an ANOVA Sum of Squares. Problems. References. 18. RANDOMIZED BLOCKS: SPECIAL CASE OF TWO-WAY ANOVA. Preview. Equivalent Analysis of a Matched-pairs Experiment. Principle of Blocking. Analysis of a Randomized-blocks Experiment. ANOVA Table for a Randomized-blocks Experiment. Models for a Randomized-blocks Experiment. Fixed-effects ANOVA Model for a Randomized-blocks Experiment. Problems. References. 19. TWO-WAY ANOVA WITH EQUAL CELL NUMBERS. Preview. Using a Table of Cell Means. General Methodology. F Tests for Two-way ANOVA. Regression Model for Fixed-effects Two-way ANOVA. Interactions in Two-way ANOVA. Random- and Mixed-effects Two-way ANOVA Models. Problems. References. 20. TWO-WAY ANOVA WITH UNEQUAL CELL NUMBERS. Preview. Problem with Unequal Cell Numbers: Nonorthogonality. Regression Approach for Unequal Cell Sample Sizes. Higher-way ANOVA. Problems. References. 21. THE METHOD OF MAXIMUM LIKELIHOOD. Preview. The Principle of Maximum Likelihood. Statistical Inference Using Maximum Likelihood. Summary. Problems. 22. LOGISTIC REGRESSION ANALYSIS. Preview. The Logistic Model. Estimating the Odds Ratio Using Logistic Regression. A Numerical Example of Logistic Regression. Theoretical Considerations. An Example of Conditional ML Estimation Involving Pair-matched Data with Unmatched Covariates. Summary. Problems. References. 23. POLYTOMOUS AND ORDINAL LOGISTIC REGRESSION. Preview. Why Not Use Binary Regression? An Example of Polytomous Logistic Regression: One Predictor, Three Outcome Categories. An Example: Extending the Polytomous Logistic Model to Several Predictors. Ordinal Logistic Regression: Overview. A "Simple" Hypothetical Example: Three Ordinal Categories and One Dichotomous Exposure Variable. Ordinal Logistic Regression Example Using Real Data with Four Ordinal Categories and Three Predictor Variables. Summary. Problems. References. 24. POISSON REGRESSION ANALYSIS. Preview. The Poisson Distribution. Example of Poisson Regression. Poisson Regression: General Considerations. Measures of Goodness of Fit. Continuation of Skin Cancer Data Example. A Second Illustration of Poisson Regression Analysis. Summary. Problems. References. 25. ANALYSIS OF CORRELATED DATA PART 1: THE GENERAL LINEAR MIXED MODEL. Preview. Examples. General Linear Mixed Model Approach. Example: Study of Effects of an Air Polluion Episode on FEV1 Levels. Summary!XAnalysis of Correlated Data: Part 1. Problems. References. 26. ANALYSIS OF CORRELATED DATA PART 2: RANDOM EFFECTS AND OTHER ISSUES. Preview. Random Effects Revisited. Results for Random Effects Models Applied to Air Pollution Study Data. Second Example!XAnalysis of Posture Measurement Data. Recommendations about Choice of Correlation Structure. Analysis of Data for Discrete Outcomes. Problems. References. 27. SAMPLE SIZE PLANNING FOR LINEAR AND LOGISTIC REGRESSION AND ANALYSIS OF VARIANCE. Preview. Review: Sample Size Calculations for Comparisons of Means and Proportions. Sample Size Planning for Linear Regression. Sample Size Planning for Logistic Regression. Power and Sample Size Determination for Linear Models: A General Approach. Sample Size Determination for Matched Case-control Studies with a Dichotomous Outcome. Practical Considerations and Cautions. Problems. References. Appendix A. Appendix B. Appendix C. Solutions to Exercises. Index.

9,303 citations


Book
16 Jul 1996

9,072 citations


"Project Northland: long-term outcom..." refers methods in this paper

  • ...The procedure SAS GLIMMIX was used to conduct the analyses, specifying a binomial distribution ( Littell et al., 1996; SAS Institute, 1996)....

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Journal ArticleDOI
TL;DR: The authors suggest that the most promising route to effective strategies for the prevention of adolescent alcohol and other drug problems is through a risk-focused approach.
Abstract: The authors suggest that the most promising route to effective strategies for the prevention of adolescent alcohol and other drug problems is through a risk-focused approach. This approach requires the identification of risk factors for drug abuse, identification of methods by which risk factors have been effectively addressed, and application of these methods to appropriate high-risk and general population samples in controlled studies. The authors review risk and protective factors for drug abuse, assess a number of approaches for drug abuse prevention potential with high-risk groups, and make recommendations for research and practice.

5,216 citations


"Project Northland: long-term outcom..." refers background in this paper

  • ...Social, environmental and intrapersonal factors have consistently been found to be associated with alcohol use among adolescents (Hawkins et al., 1992; Epstein et al., 1995; Kumpfer and Alvarado, 1995; Newcomb, 1995; Komro et al., 1997; Kosterman et al., 2000)....

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  • ...Developmentally appropriate, multi-component, community-wide programs throughout adolescence appear to be needed to reduce alcohol use....

    [...]