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4-2 Getting Started: Final Project Milestone Two

Begin working on Milestone Two of the final project. It will be due in Module Five.

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Psychology of Addictive Behaviors 2015, Vol. 29, No. 2, 329 –337 © 2015 American Psychological Association 0893-164X/15/$12.00 http://dx.doi.org/10.1037/adb0000082 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Prenatal Substance Exposure: What Predicts Behavioral Resilience by Early Adolescence? Jane M. Liebschutz Denise Crooks Boston Medical Center, Boston, Massachusetts, and Boston University School of Medicine Boston Medical Center, Boston, Massachusetts Ruth Rose-Jacobs Howard J. Cabral and Timothy C. Heeren Boston Medical Center, Boston, Massachusetts, and Boston University School of Medicine Boston University School of Public Health Jessie Gerteis Danielle P. Appugliese Abt Associates, Inc., Cambridge, Massachusetts Boston University School of Public Health Orlaith D. Heymann and Allison V. Lange Deborah A. Frank Boston Medical Center, Boston, Massachusetts Boston Medical Center, Boston, Massachusetts, and Boston University School of Medicine Understanding behavioral resilience among at-risk adolescents may guide public policy decisions and future programs. We examined factors predicting behavioral resilience following intrauterine substance exposure in a prospective longitudinal birth-cohort study of 136 early adolescents (ages 12.4 –15.9 years) at risk for poor behavioral outcomes. We defined behavioral resilience as a composite measure of lack of early substance use initiation (before age 14), lack of risky sexual behavior, or lack of delinquency. Intrauterine substance exposures included in this analysis were cocaine, tobacco, alcohol, and marijuana. We recruited participants from Boston Medical Center as mother–infant dyads between 1990 and 1993. The majority of the sample was African American/Caribbean (88%) and 49% female. In bivariate analyses, none and lower intrauterine cocaine exposure level predicted resilience compared with higher cocaine exposure, but this effect was not found in an adjusted model. Instead, strict caregiver supervision (adjusted odds ratio [AOR] ⫽ 6.02, 95% confidence interval (CI) [1.90, 19.00], p ⫽ .002), lower violence exposure (AOR ⫽ 4.07, 95% CI [1.77, 9.38], p ⬍ .001), and absence of intrauterine tobacco exposure (AOR ⫽ 3.71, 95% CI [1.28, 10.74], p ⫽ .02) predicted behavioral resilience. In conclusion, caregiver supervision in early adolescence, lower violence exposure in childhood, and lack of intrauterine tobacco exposure predicted behavioral resilience among a cohort of early adolescents with significant social and environmental risk. Future interventions should work to enhance parental supervision as a way to mitigate the effects of adversity on high-risk groups of adolescents. Keywords: resilience, intrauterine substance exposure, violence, adolescence Jane M. Liebschutz, Clinical Addiction Research and Education Unit, Boston Medical Center, Boston, Massachusetts, and Department of Medicine, Boston University School of Medicine; Denise Crooks, Department of Family Medicine, Boston Medical Center; Ruth RoseJacobs, Department of Pediatrics, Boston Medical Center, and Boston University School of Medicine; Howard J. Cabral, Department of Biostatistics, Boston University School of Public Health; Timothy C. Heeren, Data Coordinating Center, Boston University School of Public Health; Jessie Gerteis, Abt Associates, Inc., Cambridge, Massachusetts; Danielle P. Appugliese, Data Coordinating Center, Boston University School of Public Health; Orlaith D. Heymann and Allison V. Lange, Clinical Addiction Research and Education Unit, Boston Medical Center; Deborah A. Frank, Department of Family Medicine, Boston Medical Center, and Department of Pediatrics, Boston University School of Medicine. The analyses presented here and preparation of this article were supported in part by National Institute on Drug Abuse, National Insti- tutes of Health Grant DA 06532 (Deborah A. Frank, PI), and National Center for Research Resources, National Institutes of Health Grants RR000533 and RR025771. Its contents are solely the responsibility of the authors and do not represent the official view of National Center for Research Resources, National Institute of Drug Abuse, or the National Institutes of Health. Portions of this article were presented at the Pediatric Academic Societies Conference, Baltimore, Maryland, May 2009, and the College of Problems on Drug Dependence Annual Meeting, June 24, 2009, Reno, Nevada. We gratefully acknowledge analytic assistance from Brett Martin, data collection assistance from Shayna Soenksen and Laura Anatale, manuscript formatting and submission assistance from Shernaz Dossabhoy, and as always, the participants and their families. Correspondence concerning this article should be addressed to Jane M. Liebschutz, 801 Massachusetts Avenue, Second Floor, Boston Medical Center, Boston, MA 02118. E-mail: jane.liebschutz@bmc.org 329 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 330 LIEBSCHUTZ ET AL. Resilience is a dynamic process, influenced by multiple factors encompassing genetics, biology, environment, psychology, and exposure to adversity (Rutter, 2006). Resilience can be defined as positive adaptation or recovery in the context of adversity. An individual may display resilience in one functional domain at one period of development, but not necessarily in multiple domains or over different developmental epochs (Luthar & Brown, 2007). Of particular interest for policy and scientific inquiry is understanding behavioral resilience among children, adolescents, and young adults who grow up with the most extreme adversity, such as witnessed parental violence, parental addiction, and poverty. In this study, we focused specifically on a cluster of multiple problem behaviors in a high-risk cohort, as problem behaviors tend to co-occur and are also negatively related to prosocial behaviors (e.g., school attendance) and positive health behaviors (e.g., exercise, diet; Jessor, Donovan, & Costa, 1991). There are known links between intrauterine substance exposure (IUSE) and indicators of poorer behavioral and health outcomes in adolescence. In this study, we focused on intrauterine cocaine exposure (IUCE), intrauterine tobacco exposure (IUTE), intrauterine alcohol exposure (IUAE), and intrauterine marijuana exposure (IUME) because there is substantial literature linking these exposures to negative developmental and health outcomes in children and adolescents. IUCE has been linked to adolescent substance use (Delaney-Black et al., 2011; Frank et al., 2011; Richardson, Larkby, Goldschmidt, & Day, 2013), childhood externalizing behavior problems (Bennett, Marini, Berzenski, Carmody, & Lewis, 2013), inattention, and impulsivity (Richardson, Goldschmidt, Leech, & Willford, 2011). IUTE has been associated with childhood and adolescent conduct disorder, externalizing behavior (Cornelius, Goldschmidt, De Genna, & Larkby, 2012; Piper, Gray, & Birkett, 2012; Stene-Larsen, Borge, & Vollrath, 2009), adolescent delinquent behaviors, and adult criminal behavior (Paradis, Fitzmaurice, Koenen, & Buka, 2011; Rantakallio, Läärä, Isohanni, & Moilanen, 1992). IUAE has been correlated with attention difficulties (Mattson, Crocker, & Nguyen, 2011; Underbjerg et al., 2012), delinquent behaviors (Schonfeld, Mattson, & Riley, 2005), and higher rates of attention-deficit/hyperactivity disorder (Mattson et al., 2011). IUME in the context of environmental disadvantage has been linked to increased attention problems and aggression in 18-month-old girls (El Marroun et al., 2011), future substance use (Frank et al., 2011), delinquency in late childhood (Goldschmidt, Day, & Richardson, 2000) and adolescence (Day, Leech, & Goldschmidt, 2011), and poor academic performance (Goldschmidt, Richardson, Willford, Severtson, & Day, 2012). Given this well-established literature on intrauterine exposure to individual substances and adolescent outcomes, we examined multiple forms of IUSE simultaneously to see whether some exposures are more detrimental than others and to avoid mistakenly attributing the effects of one substance on outcomes to another. A prospective study design and biological markers to confirm IUSE are of particular importance when studying resilience because of the temporal relationship of the predictors of resilience and the markers of resilience over the lifetime of children and adolescents and to avoid ascertainment bias. For this reason, it is inappropriate to examine predictors of resilience and markers of resilience in a cross-sectional survey. Like many other research teams that have examined resilience (Bennett et al., 2013; Delaney-Black et al., 2011; Frank et al., 2011), we employed a prospective design. We also confirmed IUSE with at least one biological marker from each mother–infant dyad, including either maternal or neonatal urine drug tests or meconium radioimmunoassays. To gain a clearer understanding of what contributes to resilience, it is essential to examine the effects of IUSE in the context of other components that influence resilience. Other factors that influence adolescent resilience that we examined in this study included parental supervision, exposure to violence, and sex. Population-based studies in the United States have found that social support, including parental support and monitoring, increases healthy resilient behaviors in adolescents (Goldstein, Faulkner, & Wekerle, 2013; Mistry, McCarthy, Yancey, Lu, & Patel, 2009; Tiet, Huizinga, & Byrnes, 2010). In previous work, we found that parental incarceration correlated with depressive symptoms and externalizing behaviors (Wilbur et al., 2007), and others have found that it appears to increase not only antisocial behaviors but also mental health problems, drug use, or educational underperformance (Murray, Farrington, & Sekol, 2012). Thus, it is not clear how parental incarceration impacts long-term resilience. In violent neighborhoods and among high-risk populations, close parental supervision and monitoring increase adolescent resilience (Burlew et al., 2009; Li, Feigelman, & Stanton, 2000; Stanton et al., 2002). Macrosystem community influences, particularly exposure to violence and neighborhood safety, can strongly impact coping skills (Benzies & Mychasiuk, 2009; Li, Nussbaum, & Richards, 2007). Li et al. (2007) found that neighborhood hassles and violence exposure increased internalizing and externalizing symptoms in adolescents. Neighborhood cohesion may lead to positive behavioral outcomes for adolescents, whereas neighborhood disorganization may be related to delinquency (Cantillon, 2006; Chung & Steinberg, 2006). In addition, exposure to violence, either as victim or witness, correlates with increased suicidal ideation in 9- and 10-year-olds and delinquent behavior in early adolescence, irrespective of IUCE or parental distress (Gerteis et al., 2011; O’Leary et al., 2006). The relationship between sex and resilience is complex and not consistent across studies. Females show increased likelihood of behavioral resilience in young adulthood in some samples (Ackerman, Riggins, & Black, 2010; Skinner, Haggerty, Fleming, & Catalano, 2009). This may be the result of increased parental monitoring among female adolescents (Li et al., 2000). However, other samples have shown that female sex correlates with less resilience (Tusaie, Puskar, & Sereika, 2007). The interactions between sex and IUSE effects are also inconsistent (Bennett et al., 2013; Bridgett & Mayes, 2011; Dennis, Bendersky, Ramsay, & Lewis, 2006; Dixon, Kurtz, & Chin, 2008; El Marroun, et al., 2011). Non-White race has been associated with decreased resilience (Dumont, Widom, & Czaja, 2007; Fantuzzo, LeBoeuf, Rouse, & Chen, 2012; Mistry et al., 2009), not as a biologic factor but as a marker for discrimination and material deprivation, low socioeconomic status, or lack of supportive social networks (Brown, 2008; Li et al., 2007; Tusaie et al., 2007). In contrast, a sample of 489 rural African American youth developed psychosocial competence under conditions of high risk, even as they displayed lower health resilience outcomes (Brody et al., 2013). An ecological model, which takes into account the individual, family, community, environment, and larger social context, can facilitate understanding of contributing factors toward behavioral PRENATAL SUBSTANCES AND ADOLESCENT RESILIENCE This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. resilience in adolescents who have experienced violence and IUSE. Using an ecological model, this exploratory study examined selected predictors of components of resilience among high-risk adolescents. We hypothesized that both IUSE and the family and social environment during childhood and adolescence would predict presence or absence of behavioral resilience in adolescence. Specifically, we hypothesized that lower levels of intrauterine exposure to substances, lower household substance use, lower exposure to violence, lower rates of parental incarceration, greater parental supervision, and greater neighborhood cohesion would be associated with greater adolescent behavioral resilience. Method Study Design This was a masked prospective longitudinal cohort study of adolescents recruited at birth to examine the effects of levels of IUCE on behavior and development. Participants and their caregivers were repeatedly assessed from birth, using interviews and urine assays, as well as neuropsychological and behavioral assessments that have been reported elsewhere (Frank et al., 2011; Gerteis et al., 2011). Sample Selection Sample recruitment took place at the postpartum unit of Boston City Hospital (now Boston Medical Center) from 1990 to 1993. Mother–infant dyads met the following eligibility criteria: maternal age ⱖ18 years; infant gestational age ⱖ36 weeks; no need for neonatal intensive care; no diagnosis of fetal alcohol syndrome; and no indication (either by neonatal or maternal urine toxic screen or meconium assay or by history in medical record) of intrauterine exposure to illegal opiates, methadone, amphetamines, phencyclidine, barbiturates, or hallucinogens; and no history of HIV seropositivity in the infant or mother. Further information about recruitment procedures and sample characteristics has been previously described (Tronick, Frank, Cabral, Mirochnick, & Zuckerman, 1996). Boston Medical Center Institutional Review Board approval was obtained yearly. Mothers or primary caregivers also provided ongoing informed consent. Beginning at 8 years, study participants provided assent. Of the original 252 cohort members, we analyzed data from the 136 participants examined at early adolescence, targeted for ages 12.5–14.5 years. Due to challenges in getting participants for interviews in the target range, the actual age range was 12.4 –15.9 years. These participants did not differ significantly from the nonparticipants in terms of sex, ethnicity, maternal age at birth, or intrauterine exposure to alcohol, tobacco, marijuana, or cocaine. 331 and sexual activity were asked as part of an audio computerassisted self-interview (ACASI) in which the participant read and listened via headphones to written and audio text of the questions and answers. The participant answered questions by clicking the computer mouse. Using the ACASI is thought to promote more truthful answers to questions on potentially sensitive subjects than would be obtained via face-to-face interview (Riley et al., 2001). ACASI questions included items from the Hooked on Nicotine Checklist (DiFranza et al., 2002), parts of the Centers for Disease Control and Prevention’s 2005 Youth Risk Behavior Surveillance System (Eaton et al., 2006), the Wisconsin Youth Risk Behavior Surveillance Middle School Questionnaire and the Wisconsin Youth Risk Behavior Surveillance High School Questionnaire. In addition, urine samples were tested for cotinine, marijuana, and other illicit drugs (Frank et al., 2011). Dependent Variable Resilience was defined as the absence of three outcomes: HIV risk behavior, early initiation of substance use, and delinquency. Each of these was measured at the early adolescent interview at ages 12.4 –15.9 years. The latter two outcomes have been examined individually in previous publications from this study (Frank et al., 2011; Gerteis et al., 2011). Any of these three behaviors was considered an indicator that the participant was not showing resilience. Absence of these risk factors was analyzed cumulatively as a better indicator of resilience (Jessor, 1987). HIV risk behavior was defined as endorsement of one or more of the following behaviors: lack of condom use during first intercourse or most recent intercourse, injection drug use, or pregnancy (self or partner). Early initiation of substances was defined as use of substances (tobacco, alcohol, marijuana, or other illicit substances) before age 14 years. Specific questions included “How old were you when you smoked a whole cigarette for the first time?” and “How old were you when you had your first drink of alcohol other than a few sips?” It was specified that “a drink of alcohol is equal to having a can of beer (the same size as a soda can), a glass of wine, a wine cooler, or a shot of liquor such as rum, gin, vodka, or whiskey.” For misuse of prescription medications (e.g., amphetamines, steroids, oxycodone and other pain killers, or benzodiazepines), the question was “How old were you when you first tried taking [substance of interest] without a doctor or nurse telling you to take them?” In the case of illicit substances (marijuana, heroin, cocaine, “club drugs”), a quantity was not specified, with the question framed as “How old were you when you first tried [substance] for the first time?” Delinquency was defined as selfreport of at least three delinquent activities in response to seven questions on minor criminal behavior from the National Longitudinal Study of Adolescent Health (Gerteis et al., 2011; Udry, 2003). Data Collection This study used data collected at birth and ages 8.5 years, 9.5 years, 11 years, and early adolescence (12.4 –15.9 years). The primary outcomes were obtained during early adolescence. Primary caregivers were interviewed in parallel with the participants at each time point. Children’s evaluators were masked to participants’ IUCE status and to all information furnished by their caregivers. Questions about delinquent behavior, substance use, Independent Variables We identified a priori a set of caregiver and adolescent variables to be tested as predictors of behavioral resilience in the context of an ecological model: (a) no IUSE, (b) lack of household substance use during participants’ early adolescence, (c) lower exposure to violence, (d) higher neighborhood cohesion, (e) strict supervision during adolescence, (f) no history of parental incarceration, (g) This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 332 LIEBSCHUTZ ET AL. female sex, and (h) birth mother’s race/ethnicity (African American/African Caribbean vs. other). IUSE. Levels of IUSE were determined by infant urine and meconium assays as well as urine assays and postpartum interviews of the mothers using an adaptation of the Addiction Severity Index (5th ed.; McLellan et al., 1992). IUCE was classified as heavier, lighter, or none, where heavier was defined as the top quartile of self-reported days of maternal cocaine use during the index pregnancy and/or the top quartile of cocaine metabolites in the infant’s meconium. All other intrauterine cocaine use was defined as lighter. Self-reported IUTE was coded as yes/no and none, ⬍[1/2] pack per day, and ⱖ[1/2] pack of cigarettes per day. IUTE was initially coded in a three-level variable, but both levels of tobacco exposure had similar results. To conserve degrees of freedom in the analysis, we chose to combine them into a single variable (exposed or not) for the multivariable analyses. Selfreported IUAE was coded as none versus any drinking by the mother during last 30 days of the index pregnancy. IUME was determined by a positive result on any one of the following: mothers’ self-report and urine and meconium assays (any detection was considered positive), obtained from the mothers and newborns. A third of the marijuana users in this cohort who denied marijuana use were identified solely on the basis of meconium or urine assay. Household substance use. At each study visit, household substance use was determined by the caregivers’ responses to questions asking whether any member of the household where the child was living or spent considerable time used individual substances (marijuana, cocaine, tobacco, heroin, prescription medications not taken as prescribed, methadone) or had a drinking problem. Household tobacco use (yes/no) was analyzed separately from other household substance use because it was thought that it might have unique effects separate from other substances (Weitzman, Gortmaker, & Sobol, 1992). Of note, because caregiver’s own substance use was too highly correlated with prenatal exposure to give an independent effect, substance use by members other than the caregiver was used for this variable. Exposure to violence. Children’s self-reported exposure to violence (as either a witness or a victim) was measured using the Violence Exposure Scale for Children—Revised (Fox & Leavitt, 1995). This measure was used in its original cartoon format accompanying the questionnaire at ages 8.5, 9.5, and 11 years, and then as a modified questionnaire without cartoons in early adolescence. Scores at each age were grouped in quartiles, with the fourth quartile being the highest level of exposure and the first quartile being the lowest level of exposure. Quartiles were chosen because the scale total score is not weighted for severity (Frank et al., 2011; Gerteis et al., 2011). Others have used rank order in quartiles as a mode of analysis (Shahinfar, Fox, & Leavitt, 2000). Never being in the highest quartile of self-reported violence exposure at any study assessment was used as a predictor of resilience. Neighborhood cohesion. Caregiver-reported neighborhood cohesion during early adolescence was a composite variable of caregivers’ responses to three questions drawn from the National Survey of Children’s Health (U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, & National Center for Health Statistics, 2003) on perceived aspects of the neighborhood (e.g., “We watch out for each other’s chil- dren,” “People in my neighborhood help each other out,” and “There are people I can count on in this neighborhood”). The instrument uses a 7-point Likert scale that ranges from very strongly disagree to very strongly agree, with a composite score ranging from 3 to 21 (low to high cohesion). Supervision during adolescence. Participants reported on their perceptions of caregivers’ parenting during adolescence with relation to strictness/supervision (Eaton et al., 2006). The supervision scale consisted of questions that asked specifically about parental strictness about the adolescent’s activities (e.g., “In a typical week, what is the latest you can stay out on school nights?”) and parental knowledge about the adolescent’s activities (e.g., “My parents know exactly where I am most afternoons after school” [yes/no]; “How much do your parents really know what you do with your free time?” [don’t know/know a little/know a lot]). For each of these scale scores, we divided the continuous scores into quartiles and created a dichotomous variable of the highest quartile versus others in our sample. Parental incarceration. Parental incarceration at any time was determined by any positive caregiver response during childhood or adolescent interviews to the following questions: “In [child’s] lifetime, has his or her father been in jail or prison?” and “How many times since [the child] was born, have you been in jail or prison (either because you were serving a sentence or because you were detained before a trial)?” Caregiver type. Caregiver type in early adolescence was defined as birth mother, kin, or unrelated as identified by the adult accompanying the participant who gave informed consent at each study visit. This was measured at each study visit. Analysis Bivariate analyses using logistic regression models unadjusted for covariates were performed to determine associations with resilience for the seven theoretical predictor variables. A multivariable logistic regression analysis included all independent variables that were associated with resilience at p ⬍ .10, age, and all IUSEs, which were a main focus of the construction of the source sample. Multicollinearity was not found in the multivariable regression. Odds ratios (ORs) and 95% confidence intervals (CIs) were computed from the logistic regression models. Statistically significant results had two-tailed p values less than .05. All analyses were conducted using SAS, Version 9.3. Results Of the 136 participants, the mean age ⫽ 14.2 years (SD ⫽ 0.7, range 12.4 –15.9 years); 72 (53%) were classified as behaviorally resilient. Specifically, 94% of the cohort exhibited no HIV risk behaviors, 76% reported two or fewer delinquent acts, and 59% had not initiated alcohol, tobacco, or other substance use (see Table 1). In bivariate analyses, a number of variables were found to be significantly (p ⬍ .05) associated with resilience, including lower levels of violence exposure between ages 8.5–11.5 years, strict parental supervision, lack of substance use in the home during adolescence, no IUCE compared with heavy IUCE, and lack of IUAE and IUTE. Sex and race/ethnicity were not correlated with behavioral resilience (see Table 1). Scores on acceptance/involve- PRENATAL SUBSTANCES AND ADOLESCENT RESILIENCE 333 Table 1 Behavioral Resilience by Maternal and Adolescent Characteristics: Bivariate Analyses (N ⫽ 136) This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Variable Intrauterine cocaine exposure (global p ⫽ .12), n (%) None Lighter Heavier Intrauterine marijuana exposure, n (%) No Yes Intrauterine tobacco exposure (global p ⫽ .001), n (%) None ⬍1/2 pack per day ⱖ1/2 pack per day Intrauterine alcohol exposure, n (%) No Yes Mean (SD) maternal age at delivery (years) Mean (SD) education (years) Ethnicity, n (%) African American/Caribbean Other Adolescent sex, n (%) Male Female Violence exposure, n (%) Quartiles 1–3 Top quartile Parental strictness/supervision, n (%) Quartiles 1–3 Top quartile Household tobacco use at early adolescence, n (%) No Yes Note. Statistic Resilient (%) Odds ratio [95% CI] p 61 (45) 50 (37) 25 (18) 61 52 36 2.74 [1.04, 7.19] 1.93 [0.72, 5.17] Referent 103 (76) 33 (24) 53 52 1.08 [0.49, 2.36] Referent .85 66 (49) 32 (24) 38 (28) 68 31 45 2.65 [1.16, 6.03] 0.56 [0.21, 1.50] Referent .02 .25 97 (71) 39 (29) 26.6 (5.2) 11.5 (1.3) 60 36 2.66 [1.23, 5.74] Referent 0.99 [0.93, 1.06] 0.97 [0.75, 1.26] .01 120 (88) 16 (12) 52 63 1.56 [0.53, 4.56] Referent .42 70 (51) 66 (49) 49 58 Referent 1.44 [0.73, 2.83] .29 79 (58) 57 (42) 66 35 3.56 [1.74, 7.29] Referent .0005 105 (77) 31 (23) 44 84 Referent 6.67 [2.38, 18.72] .0003 104 (76) 32 (24) 57 41 1.92 [0.86, 4.29] Referent .11 .04 .19 .74 .83 CI ⫽ confidence interval. ment, psychological autonomy, parental incarceration, neighborhood cohesion, and caregiver type during early adolescence were not related to resilience and are not presented here. In multivariable logistic regression analysis, strictest supervision (adjusted odds ratio [AOR] ⫽ 6.02, 95% CI [1.90, 19.00], p ⫽ .002), lower violence exposure (AOR ⫽ 4.07, 95% CI [1.77, 9.38], p ⫽ .001), and lack of IUTE (AOR ⫽ 3.71, 95% CI [1.28, 10.74], p ⫽ .02) were statistically significant protective factors associated with behavioral resilience (see Table 2). Older age appeared protective, with results just above statistical significance (AOR ⫽ 0.52, 95 CI% [0.27, 1.02], p ⫽ .06). No statistically significant interactions were found with IUCE and other salient independent variables. To further explore the tobacco results, we conducted a (post hoc) multivariable analysis limited to those with both lighter and heavier IUCE to test whether the intrauterine tobacco effects found were due to high prevalence of IUTE in participants with heavy cocaine exposure. The results showed no difference by low versus high IUCE (results not shown). Discussion Strict caregiver supervision in early adolescence, lower violence exposure from ages 8 –14 years, and lack of IUTE were predictors of behavioral resilience in this exploratory analysis among a cohort of early adolescents with significant social and environmental risk regardless of IUCE status. In contrast to our hypothesis, although heavy IUCE was associated with decreased odds of resilience when compared with no IUCE in bivariate analyses, this effect was not identified after controlling for other factors. Viewed from an ecological stance, the biologic factor of IUTE, the microsystem factor of parental supervision, and the combined micro-/macrosystem factors of lower violence exposure each contributed significantly to behavioral resilience. The findings from this current study also support growing understanding of the potent effect of violence on development and behavior. Adverse childhood experiences, including exposure to violence, have been associated in retrospective studies with a number of lifelong problems, including depression, substance abuse, and high-risk health behaviors (Felitti et al., 1998). The proposed mechanism for this relationship is that violence exposure disrupts the normal stress response of the hypothalamic–pituitary–adrenal axis (Neigh, Gillespie, & Nemeroff, 2009), so that cortisol does not appropriately increase in response to stress. This blunted cortisol response is highly associated with depression and other mental health problems (Neigh et al., 2009). Lester and Padbury (2009) found an exaggerated blunting of the cortisol response in 11-year-olds who had both childhood exposure to domestic violence and IUCE, compared with those without IUCE, without violence, or without either. In our study, the impact of not experiencing high levels of violence on behavioral resilience points to an urgent need to prevent violence exposure. LIEBSCHUTZ ET AL. 334 Smoking cessation programs should focus on women of childbearing age (Chamberlain et al., 2013; Lumley et al., 2009; Valanis et al., 2001). Table 2 Predictors of Resilience: Multivariable Logistic Regression This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Variable Intrauterine cocaine exposure None Lighter Heavier Intrauterine marijuana exposure No Yes Intrauterine tobacco exposure No Yes Intrauterine alcohol exposure No Yes Parental strictness/supervision Top quartile Quartiles 1–3 Violence exposure Top quartile Quartiles 1–3 Household tobacco use at early adolescence No Yes Age, for each year older Note. AOR 95% CI p 0.67 1.02 Referent [0.13, 3.39] [0.27, 3.81] .97 .63 0.65 Referent [0.24, 1.76] .39 4.04 Referent [1.36, 12.04] .01 1.88 Referent [0.59, 5.96] .29 5.63 Referent [1.74, 18.25] .004 [1.49, 8.20] .004 [0.76, 5.55] .15 [0.27, 1.02] .06 Referent 3.49 2.06 Referent 0.52 AOR ⫽ adjusted odds ratio; CI ⫽ confidence interval. Our findings on parental supervision are consistent with work conducted in other studies that did not account for documented IUSE (Steinberg, Lamborn, Darling, Mounts, & Dornbusch, 1994). Chilcoat and Anthony (1996) reported that lower parental supervision increased the risk for early initiation of substances in a sample of largely minority children from an urban setting. Burlew et al. (2009) noted that parental supervision buffered the impact of increased neighborhood risk for early substance initiation in a sample of African American youth living in low-income neighborhoods. In intergenerational longitudinal studies, decreased parental monitoring was associated with externalizing behaviors (e.g., precursors of delinquency; Bailey, Hill, Oesterle, & Hawkins, 2009). Lahey, Van Hulle, D’Onofrio, Rodgers, and Waldman (2008) reported that parental knowledge of children’s peers and limit setting influenced risk of adolescent delinquency, particularly in adolescents in high-risk neighborhoods. Similarly, parental monitoring and supervision have been shown to decrease early sexual activity among high-risk adolescents (Boislard & Poulin, 2011; Browning, Leventhanl, & Brooks-Gunn, 2005). The continued impact of IUTE into adolescence confirms other studies that have shown that such exposure has been associated with conduct disorder and behavioral problems in childhood and adolescence in samples without IUCE (Brook, Zhang, Rosenberg, & Brook, 2006; Desrosiers et al., 2013; Gaysina et al., 2013; Rantakallio et al., 1992). Furthermore, the findings on IUTE expose misconceptions about relative impact of intrauterine exposure to legal compared with illegal substances on long-term behavioral outcomes. The fact that tobacco is legal and cocaine is not is often misinterpreted to suggest that IUTE is less harmful than intrauterine exposure to illicit substances. However, as our study has demonstrated, IUTE can have long-lasting behavioral consequences identifiable even when such use co-occurs with IUCE. Strengths and Limitations The strengths of this study include the prospective longitudinal cohort design and the detailed biological information on intrauterine exposures, as well as frequent prospective data collection on predictors and outcomes of interest. We acknowledge that this study has several limitations. First, the sample size may have affected the statistical power to detect a significant association of IUCE and resilience or lack of resilience. Although we may have failed to identify all factors associated with resilience because of lack of power, we did find three factors, one at each level predicted by the ecological model, which significantly influenced resilience. Furthermore, we constructed multiple models to test our predetermined hypothesis, which used a limited number of variables in order to diminish the impact of sample size on statistical power. Second, use of a dichotomous outcome (i.e., resilient vs. not resilient) may have obscured more subtle findings that relate to this complex developmental process. Third, the model in this study predicting resilience in early adolescence may not have predicted resilience in other developmental periods. In particular, this sample had a low rate of risky sexual behavior, which may have been due to the age itself. Prevalence of sexual behavior itself is low in this age group as compared with older age groups. The risky sexual behavior measure of resiliency likely played a minor role in this study, but in older age groups, resiliency to risky sexual behaviors may be more common. Lastly, our findings may be generalized only to urban, low-income, predominantly African American/African Caribbean populations. Further research needs to be conducted in other samples, including cohorts that are of higher socioeconomic status, rural, or of other ethnicities. Public Health Implications Family practices and environmental factors, particularly stricter caregiver supervision and less exposure to violence, may buffer the negative behavioral impact of IUSE for at-risk urban youth. While IUTE remains a risk for negative behavioral outcomes, this study points also to potential postnatal points of modifiable environmental experiences that can moderate early life disadvantages. Because this is an observational study, it was not known whether an intervention to reduce violence and increase parental supervision will enhance behavioral resilience. Conclusion Lower exposure to violence in childhood, close parental supervision in adolescence, and lack of IUTE predicted increased behavioral resilience in high-risk urban adolescents, half of whom had IUCE. Despite the presumed increased risk for adolescent maladaptive behaviors associated with IUCE, level of IUCE was not related to lower odds of behavioral resilience after covariate control. Interventions to enhance parental supervision in adolescence should be tested as a method to mitigate the effects of harmful exposures for high-risk youth. PRENATAL SUBSTANCES AND ADOLESCENT RESILIENCE This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 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Pediatrics, 120, e678 – e685. http://dx.doi.org/10.1542/peds.2006-2166 Received August 15, 2014 Revision received March 6, 2015 Accepted March 9, 2015 䡲 Correction to Field et al. (2015) In the Online First August 18, 2014, version of the brief report “The Validity of Different Measures of Automatic Alcohol Action Tendencies” by Inge Kersbergen, Marcella L. Woud, and Matt Field (Psychology of Addictive Behaviors, 2015, Vol. 29, No. 1, pp. 225–230. http://dx.doi.org/10.1037/ adb0000009), there was an error in the byline for Inge Kersbergen and Matt Field. Both authors are affiliated with the University of Liverpool and United Kingdom Centre for Tobacco and Alcohol Studies, Liverpool, United Kingdom. All versions of this article have been corrected. http://dx.doi.org/10.1037/adb0000099 PSY 211 Example Research Design Worksheet Complete each section of this worksheet. You will use this worksheet to inform the Research Design section of your final project submission. Citation of Literature Bechtold, J., Simpson, T., White, H. R., & Pardini, D. (2015). Chronic adolescent marijuana use as a risk factor for physical and mental health problems in young adult men. Psychology of Addictive Behaviors, 29(3), 552–563. Gap Identification Many studies look at the effects of marijuana use on prenatal development and possible physical and psychological effects throughout the life span, particularly in teenagers and young adults. Researchers have also studied the factors that influence marijuana use across different age groups and in various environments. Some states are legalizing recreational marijuana use, but there has not been much time to study how that influences marijuana use among people in different age groups from varying environmental and racial, ethnic, and cultural backgrounds (gap). Research Question Are adults who smoked marijuana recreationally during their teenage years more likely to continue recreational marijuana use in states where that use is legal? Research Design I would use a qualitative design for this study because I am looking at hard data (chosen design type and reason for choosing it. Note that this is an experimental design; however, your design may lend itself to descriptive or correlational). My independent variable is the legal status of marijuana. Marijuana use in adulthood is the dependent variable (independent and dependent variables). I would recruit participants from four states—two where recreational marijuana use is legal and two where it is not legal at all for recreational or medicinal use. I would use Colorado and Washington as the two legal states and Idaho and Wyoming as the two illegal states. The studies in my chosen track focused on certain cities, so I chose the latter two states to ensure that all four choices are within roughly the same geographical region. I chose Idaho and Wyoming specifically because personal use possession is not decriminalized in those states and is a misdemeanor rather than a felony (choosing study population). Previous and current marijuana use would be self-reported via questionnaires. I would use both male and female participants for this study, as the studies in my research track focused on males, which I see as a potential bias (identification and addressing of potential bias). I would like to see if there are gender-related differences. I would administer an initial screening assessment asking about frequency of marijuana use prior to age 20 and the way in which participants viewed their use (sporadically/experimentally vs. regularly/recreationally). I would select those who use marijuana recreationally on a regular basis for the actual study. (Additional study details, which can be added as necessary. Your study may span a longer time period, for example, a month or even years.) Issues of Ethics This study will potentially give me knowledge of people who are using marijuana illegally. I would make the assessments anonymous and use only demographic information to identify the subjects (accounting for issues of ethics). This study involves adults and is simply an assessment, so there are no major ethical problems as long as I obtain informed consent from all participants. There are no risks in this study, but if there were, I would need to fully inform potential participants to help them decide whether or not to give informed consent. If I included teenagers, I would have to get parental consent for those under age 18 (management of ethics). Previous studies involving minors as participants addressed this potential ethical issue by obtaining parental consent. For example, in the research I reviewed involving a group of adolescents from Pittsburgh who were followed through adulthood and assessed for physical and psychological effects of marijuana use (Bechtold, Simpson, White, & Pardini, 2015), the researchers obtained consent from both the youngsters and their parents annually until they reached age 18. Then they obtained consent from the nowadult participants annually (incorporation of things learned). PSY 211 Milestone Two Guidelines and Rubric Overview: For this milestone, you will identify a research gap in the articles you reviewed for your chosen track and develop a research question addressing the gap. Please note there may be more recent developments in the field related to your chosen track but for this assignment you will only focus on the articles provided. You will then determine an appropriate research design and how you will account for issues of ethics. The final project is meant for you to propose a hypothetical study. You are not and should not be conducting human subjects research for this project. It is not necessary for the purposes of this assignment. All human subjects research requires written approval from the SNHU COCE Institutional Review Board in order to protect the welfare and ensure ethical treatment of the subjects. Complete each section of the Research Design Worksheet based on the research gap you identified. You will use this worksheet to inform the Research Design section of your final project submission. The following elements must be addressed as outlined in the worksheet and the Final Project Guidelines and Rubric document: A. B. C. D. E. Identify a gap in the developmental psychology research presented in your chosen track. Develop a basic research question addressing the identified gap. Determine an appropriate research design that addresses your research question regarding developmental psychology, and explain why it was chosen. Explain how you will account for issues of ethics associated with your proposed research design. Explain how your approach to accounting for issues of ethics was informed by your review of the research presented in your chosen track. You will submit your worksheet to your instructor at the end of Module Five. Guidelines for Submission: Your will submit the completed Research Design Worksheet document with double spacing, 12-point Times New Roman font, oneinch margins, and any sources cited in APA format. Instructor Feedback: This activity uses an integrated rubric in Blackboard. Students can view instructor feedback in the Grade Center. For more information, review these instructions. Critical Elements Research Plan: Gap Exemplary (100%) Meets “Proficient” criteria, and response demonstrates an advanced ability to identify gaps in research Proficient (85%) Identifies a gap in the developmental psychology research presented in the chosen track Needs Improvement (55%) Identifies a gap in the developmental psychology research presented in the chosen track, but identification is inaccurate Not Evident (0%) Does not identify a gap in the developmental psychology research presented in the course Value 20 Research Plan: Research Question Research Design: Research Design Research Design: Issues of Ethics Research Design: Informed Articulation of Response Meets “Proficient” criteria, and developed research question demonstrates a keen insight into how to develop research questions that address gaps in research Meets “Proficient” criteria, and response demonstrates a sophisticated awareness of the research design that would be appropriate in addressing the research question Meets “Proficient” criteria, and explanation demonstrates an astute ability to account for issues of ethics within proposed research design Meets “Proficient” criteria, and explanation demonstrates keen insight regarding how issues of ethics are accounted for in various scenarios Develops a basic research question addressing the identified gap Develops a basic research question addressing the identified gap, but developed research question is cursory or illogical Does not develop a basic research question addressing the identified gap 20 Determines an appropriate research design that addresses the research question, explaining why it was chosen Determines a research design that addresses the research question and explains why it was chosen, but explanation is cursory or illogical Does not determine a research design that addresses the research question 20 Explains how issues of ethics would be accounted for with the proposed research design Does not explain how issues of ethics would be accounted for with the proposed research design 15 Does not explain how approach to accounting for issues of ethics was informed by review of the research presented in the chosen track 15 Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easy-toread format Submission has no major errors related to citations, grammar, spelling, syntax, or organization Explains how issues of ethics would be accounted for with the proposed research design, but explanation is cursory or illogical Explains how approach to accounting for issues of ethics was informed by review of the research presented in the chosen track, but explanation is cursory or illogical Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas 10 Explains how approach to accounting for issues of ethics was informed by review of the research presented in the chosen track Total 100%
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Behavioral Resilience by Early Adolescence Prediction Literature Citation Liebschutz, J.M, R Rose-Jacobs, D.A Frank, J Gerteis, O.D Heymann, A.V Lange, D Crooks, H.J Cabral, T.C Heeren, and D.P Appugliese. "Prenatal Substance Exposure: What Predicts Behavioral Resilience by Early Adolescence?" Psychology of Addictive Behaviors. 29.2 (2015): 329-337. Print. Gap Identification Most scholars have looked at the changes in the behavioral resilience of adolescents as a way of change in character. However, the changes in behavior can be predicted by the use of many factors available. The adolescents can develop changes in their eating habits, the mode of communication, the kind of friends they have, the need for privacy, and the timings of their activities. Some of the children are given freedom of choice while others are limited to the activities to engage. Research Question Do it for the adolescents who change b...


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