Society for the Scientific Study of Religion

Slides:



Advertisements
Similar presentations
Grandparenting and health in Europe: a longitudinal analysis Di Gessa G, Glaser K and Tinker A Institute of Gerontology, Department of Social Science,
Advertisements

Impact of foster care on sexual activity of maltreated youth Monica Faulkner, PhD, LMSW Center for Social Work Research The University of Texas at Austin.
Study examined associations between adolescent information management (disclosure & secrecy), parenting behaviors (solicitation & rules), and adolescent.
EBI Statistics 101.
Background Research consistently indicates that numerous factors from multiple domains (e.g., individual, family) are associated with heavy alcohol use.
Audrey J. Brooks, PhD University of Arizona CA-AZ node.
Do Socio-Religious Characteristics Account for Later Alcohol Onset? Paul T. Korte, B.A. Jon Randolph Haber, Ph.D.
© Copyright McGraw-Hill CHAPTER 3 Data Description.
Disentangling the Relations between Discrimination, Cultural Orientation, Social Support, and Coping in Mexican American Adolescents Megan O’Donnell Mark.
CHILDHOOD MALTREATMENT AND ADOLESCENT ANTISOCIAL BEHAVIOR: Romantic Relationship Quality as Moderator Susaye S. Rattigan, M.A. & Manfred H.M. van Dulmen,
Trajectories of Sexual Risk Behavior in Adolescence and the Transition to Adulthood Marc A. Zimmerman School of Public Health University of Michigan Stevenson.
Personality and Substance Use Behaviors Associations of the Big Five traits with adolescent substance use, demonstrated through analysis of the MOFAM data.
◦ 1, th and 11 th grade high school students (53% girls) ◦ 58% Caucasian; 23% African-American; 12% Hispanic ◦ Mean age = (SD=.68); age range.
Tanya Nieri, PhD and Matt Grindal, MA Department of Sociology University of California at Riverside Acknowledgements: Data were collected as part of the.
TOMS/NOMS FY12- FY14 Adult Survey Analysis: Does treatment lead to changes over time? 2/16/2016 Prepared by: Abigail Howard, Ph.D.
Abstract A longitudinal study designed to follow children of alcohol and drug dependent fathers from adolescence into adulthood RISK began in 1993 and.
Crystal Reinhart, PhD & Beth Welbes, MSPH Center for Prevention Research and Development, University of Illinois at Urbana-Champaign Social Norms Theory.
Trends in Access to Substance Abuse Treatment for Women and Men: Jeanne C. Marsh, PhD, Hee-Choon Shin, PhD, Dingcai Cao, PhD University of Chicago.
Religious trends in Switzerland: disentangling age, cohort, individual flux and period effects Marion Burkimsher Affiliated to University of Lausanne.
Easton MA Public Schools Adolescent Wellness Survey Results.
Study Population In , 1,154 Mexican origin youth (aged years) indicated which of 50 movies (randomly selected from a pool of 250 popular movies.
T Relationships do matter: Understanding how nurse-physician relationships can impact patient care outcomes Sandra L. Siedlecki PhD RN CNS.
Development of Physical Aggression: Exploring the Relationship with Language Elizabeth Anson MS Kimberly Sidora-Arcoleo PhD Robert Cole PhD Harriet Kitzman.
Method Introduction Discussion Participants: Data came from Waves I and II of the National Longitudinal Study of Adolescent Health (Add Health). The analysis.
Protective Factors of Alaskan High School Students 2011 & 2013 Youth Risk Behavior Survey Alaska.
Comparison of Substance Use Trends and Consequences among Virgin Islands Public High School Students and their US Mainland Counterparts: Results of the.
Conclusions & Implications
Are Happy People Found in Connected Neighborhoods
Comparison of Four "Time in Intensity“ Physical Activity Indices as
Communities That Care Survey
Kimberly Jeffries Leonard, Ph.D.
Healthy Eating Similarities and Differences
Access to Dental Care Pre and Post Enrollment in a State Children’s Health Insurance Program (SCHIP) Beverly Mulvihill, PhD,1 Anita Jackson, BS,1 Alice.
Annual Meeting of the Society for Prevention Research, June 1, 2017
Murat KEZER1 Barış SEVİ1, Zeynep CEMALCILAR1, & Lemi BARUH2
A Comparison of Two Nonprobability Samples with Probability Samples
Parental Alcoholism and Adolescent Depression?
Acknowledgement: NIH/NICHD #1 R21 HD Elias Mpofu –PI
Increased Physical Activity And Senior Center Participation
Advanced Quantitative Techniques
Measurement and Observation
Aggression Types as Predictors of Adolescent Substance Use
Entitlement Behaviors
The Effects of Self-Esteem and Optimism on Alcohol Use in
DESCRIPTIVES AND CORRELATIONS
Jaclyn Shor Jeffrey Greenhaus Katrina Graham
Participants and Procedures
Descriptive e-cigarette norms on tobacco attitudes and smoking behavior: The importance of close friends and peers Michael Coleman & William D. Crano.
Implications and Future Research Research Subjects/Questions
The Role of Adolescent Relationships in Predicting Withdrawal in Emerging Adulthood J. Claire Stephenson, Amanda L. Hare, Nell N. Manning & Joseph P.
CHAPTER 3 Data Description 9/17/2018 Kasturiarachi.
Balfour, Nick CSU, Chico Math 615 INTRODUCTION METHODS RESULTS
A Global Comparative Study of Religiosity and Health
Facets of Impulsivity as Unique Predictors of Substance Use and Abuse
Being Prepared, Getting in Trouble and Other Student Misbehaviors: A Comparison of Immigrants and the Native-Born Stephanie Ewert Department of Sociology.
Prosocial Behaviors in Adolescence
The Role of Family in Religious Liminality
Year 10 Science Life - Psychology
Parent Survey High School 2018
Korey F. Beckwith & David E. Szwedo James Madison University
Epidemiology of exercise and physical activity
2015 Erie County Youth Religiosity Data
Morgan M. Welch & David E. Szwedo James Madison University
By A.Arul Xavier Department of mathematics
Alcohol, Other Drugs, and Health: Current Evidence July-August, 2018
OBJECTIVES / HYPOTHESIS Co-occurring Health Risk Behaviors
PNA Results: Lewis County, NY
Chong Ho Yu & Beverly Rasimas Azusa Pacific University
Hamilton County Power Up YOUth Survey
Presentation transcript:

Society for the Scientific Study of Religion Religiosity, Marijuana Use, and Binge Drinking: The Role of Dimensions of Faith Craig Rivera, PhD Niagara University Society for the Scientific Study of Religion November 8, 2013 Boston, MA

Background (Continued) Empirical support for direct effects of religiosity on substance use (e.g., Bahr & Hoffman, 2008; Ulmer et al., 2012; Wallace et al., 2007) Empirical support for indirect effects of religiosity, such as through peer selection or social bonds (e.g., Bahr et al., 1998; Ulmer et al., 2012) Baier & Wright (2001), Chitwood et al. (2008), and Johnson et al. (2000) have thorough reviews of the impact of religiosity on deviance in general and substance use in particular

Background (Continued) Religiosity has been operationalized both as a single global scale (e.g., Barr & Hoffmann, 2008; Ulmer et al., 2012) and as separate dimensions (e.g., Benda & Corwyn, 1997; Nonnemaker et al., 2003) Common dimensions examined are public vs. private expressions (e.g., Nonnemaker et al., 2003), as well as organizational religiosity, subjective religiosity, and religious affiliation (see Chitwood et al., 2008 for a review) Evidence exists that different dimensions may have different effects on outcomes (e.g., Chitwood et al., 2008; Nonnemaker et al., 2003)

Background (continued) To build upon this research, the current study first examines the effects of religiosity operationalized as a single global scale, and then examines the effects of religiosity operationalized as separate dimensions Specifically, the current study utilizes factor analysis to identify two dimensions of religiosity – public and private Similar to Nonnemaker et al. (2003), but adds measures to each dimension Public dimension consists of behaviors engaged in around others, such as attending religious services Private dimension consists of behaviors and expressions made alone, such as frequency of praying alone and closeness to God

Research Questions Is there an association between a youth’s overall religiosity and his or her use of marijuana and binge drinking? Do different dimensions of religious faith, specifically public vs. private dimensions, have different effects on marijuana use and binge drinking?

Methods – Sample National Study of Youth and Religion (Smith and Pearce) Three wave, nationally representative study of adolescents and emerging adults (n=3,290) Wave 1: ages 13-17; Wave 2: ages 16-20; Wave 3: ages 18-23 Data collection involved telephone interviews with youth on topics ranging from religious faith, to family and school life, to a range of developmental issues Current analyses use Waves 2 and 3 (n=2,532) Data were made available through the Association of Religion Data Archives

Methods – Measurement Marijuana Use – measured at Wave 3 Original survey question: “How often, if ever, do you use marijuana?” Seven category response set ranging from “Never” to “Once a Day or More” Highly skewed distribution – more than 80% answered “Never” or “A Few Times A Year” Variable recoded into a dichotomy reflecting whether or not the youth has ever used marijuana: 1=No (69.2%); 2=Yes (30.8%)

Methods -- Measurement Binge Drinking – measured at Wave 3 Original survey question: “How many times, if at all, over the past two weeks have you drunk at least 5 drinks [4 for females] in the same night?” Four category response set ranging from “Never” to “Five or More Times” Highly skewed distribution – more than 82% answered “Never” or “Once or Twice” Variable recoded into a dichotomy reflecting whether or not the youth has drunk at least 5 (or 4) drinks in one night at all in the past two weeks: 1=No (52.1%); 2=Yes (47.9%)

Methods – Measurement Religiosity – seven items, measured at Wave 2: How often do you attend religious services? (Six categories: “Never” to “Once a week or more”) How often do you attend Sunday School or other religious education classes? (Seven categories: “Never” to “More than once a week”) How often do you attend any organized religious groups such as Bible study, prayer group, or religious group?

Methods – Measurement Religiosity -- continued How often, if ever, do you pray by yourself? (Six categories: “Never” to “Once a day or more”) How often, if ever, do you read from the sacred scriptures of your particular religious tradition by yourself? How distant or close do you feel to God most of the time? (Four categories: “Very distant” to “Very close”) How important or unimportant is religious faith in shaping how you live your daily life? (Four categories: “Not important at all” to “Extremely important”)

Methods – Measurement Religiosity – continued Overall Religiosity Scale (α = .872) Standardized and computed mean for all seven items Public Dimension (α = .807) Frequency of attending religious services Frequency of attending Sunday School Frequency of attending organized religious groups Private Dimension (α = .835) Frequency of solitary prayer Frequency of reading sacred scriptures How close you feel to God Importance of religious faith

Methods – Measurement Overall scale and both subscales each recoded into three categories: Lowest quartile = Low Religiosity Middle quartiles = Medium Religiosity Upper quartile = High Religiosity Draws on Smith and Denton (2005) and logic of risk and protective factor research (e.g., Farrington and Loeber, 2000)

Methods – Measurement Control Variables – measured at Wave 2 All models control for the following variables: age gender # of friends who drink or use drugs closeness to mother how often they feel sad how much they like to take risks dichotomous measure of previous marijuana use or binge drinking

Methods – Analysis Plan Logistic regression models, run separately for marijuana use and binge drinking: Overall scale of religiosity Public dimension of religiosity Private dimension of religiosity Public and private dimensions of religiosity

Model 4: Public and Private Results – Logistic Regression Wave 2 Religiosity Predicting Wave 3 Marijuana Use Model 1: Overall (n=1,964) Model 2: Public (n=2,071) Model 3: Private (n=2,002) Model 4: Public and Private β High Overall Religiosity High Public Religiosity High Private Religiosity -.778*** -- -.533*** -.476*** -.384** -.319* *p < .10; ** p < .05; ***p < .01 Note: Combined low and medium religiosity is the comparison group

Model 4: Public and Private Results – Logistic Regression Wave 2 Religiosity Predicting Wave 3 Binge Drinking Model 1: Overall (n=1,971) Model 2: Public (n=2,078) Model 3: Private (n=2,010) Model 4: Public and Private β High Overall Religiosity High Public Religiosity High Private Religiosity -.563*** -- -.369*** -.525*** -.223* -.431*** *p < .10; ** p < .05; ***p < .01 Note: Combined low and medium religiosity is the comparison group

Summary and Conclusions When measured as a single, global scale, youth with high levels of religiosity have significantly lower odds of using marijuana and engaging in binge drinking, controlling for several relevant factors Findings are similar when religiosity is divided into public and private dimensions; however… Public religiosity may have a stronger impact on marijuana use compared to private religiosity Private religiosity may have a stronger impact on binge drinking compared to public religiosity

Directions for Future Research Examine additional outcomes such as hard drug use and serious delinquency Examine other dimensions of religiosity Examine denomination-specific effects (e.g., building on Regnerus, 2003)