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Post-traumatic growth, stressfullife events, and relationships withsubstance use behaviors amongalternative high school students: Aprospective studyThalida E. Arpawonga, Steve Sussmanab, Joel E. Milamb, JenniferB. Ungerb, Helen Landc, Ping Sunb & Louise A. Rohrbachb

a Department of Psychology, University of Southern California, LosAngeles, CA, USAb Department of Preventive Medicine, University of SouthernCalifornia, Los Angeles, CA, USAc Department of Social Work, University of Southern California,Los Angeles, CA, USAAccepted author version posted online: 27 Oct 2014.Publishedonline: 14 Nov 2014.

To cite this article: Thalida E. Arpawong, Steve Sussman, Joel E. Milam, Jennifer B. Unger, HelenLand, Ping Sun & Louise A. Rohrbach (2014): Post-traumatic growth, stressful life events, andrelationships with substance use behaviors among alternative high school students: A prospectivestudy, Psychology & Health, DOI: 10.1080/08870446.2014.979171

To link to this article: http://dx.doi.org/10.1080/08870446.2014.979171

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Post-traumatic growth, stressful life events, and relationships withsubstance use behaviors among alternative high school students: A

prospective study

Thalida E. Arpawonga*, Steve Sussmana,b, Joel E. Milamb, Jennifer B. Ungerb,Helen Landc, Ping Sunb and Louise A. Rohrbachb

aDepartment of Psychology, University of Southern California, Los Angeles, CA, USA;bDepartment of Preventive Medicine, University of Southern California, Los Angeles, CA, USA;

cDepartment of Social Work, University of Southern California, Los Angeles, CA, USA

(Received 25 March 2014; accepted 16 October 2014)

A highly stressful life event (SLE) can elicit positive psychosocial growth,referred to as post-traumatic growth (PTG) among youth. We examined PTGand the number of SLEs for their influence on substance use behavioursamong a sample of older, diverse alternative high school students participatingin a drug prevention programme (n = 564; mean age = 16.8; 49% female;65% Hispanic). Surveys assessed PTG, SLEs and substance use behaviours atthe two-year follow-up. Multilevel regression models were run to examine theeffect of PTG and the number of SLEs on frequency of substance use at thetwo-year follow-up, controlling for baseline substance use, sociodemographicvariables, peer substance use, attrition propensity and treatment group. GreaterPTG scores were associated with lower frequencies of alcohol use, gettingdrunk on alcohol, binge drinking, marijuana use and less substance abuse atthe two-year follow-up, but not associated with cigarette or hard drug use.Also, PTG did not moderate the relationship between cumulative number ofSLEs and substance use behaviours, rather PTG appears to be protectiveagainst negative effects of a single, life-altering SLE. Fostering PTG from aparticularly poignant SLE may be useful for prevention programmes targetingalcohol, marijuana and substance abuse behaviours among high-risk youth.

Keywords: posttraumatic growth; high-risk; older youth; substance use;stressful life events

Substance use is one of the most problematic health concerns for adolescents and youngadults in the United States (Johnston, O’Malley, Bachman, & Schulenberg, 2013). Ithas been estimated that by the 10th grade, over 27% of youth have smoked cigarettes,54% have tried alcohol, 35% have been drunk on alcohol, 34% have tried marijuanaand 15% have used illicit drugs in their lifetime (Johnston et al., 2013). Adolescentswho use or misuse substances have a higher likelihood of having experienced highlystressful events in their past (e.g. childhood sexual abuse, witnessing violence, naturaldisaster), as substances have long been used as a method of coping and relief fromdistress (e.g. Holahan, Moos, Holahan, Cronkite, & Randall, 2001; Low et al., 2012;

*Corresponding author. Email: arpawong@usc.edu

© 2014 Taylor & Francis

Psychology & Health, 2014http://dx.doi.org/10.1080/08870446.2014.979171

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McConnell, Memetovic, & Richardson, 2014). Unsuccessful coping with stressful lifeevents (SLEs) and the resulting emotional distress are consistent predictors of earlierand more frequent substance use among adolescents (e.g. Booker, Gallaher, Unger,Ritt-Olson, & Johnson, 2004; Dube et al., 2006; Newcomb & Harlow, 1986; Ungeret al., 1998; Wagner et al., 2009; Wills, 1986). Moreover, use of any of the three mostaccessible drugs – tobacco, alcohol or marijuana – during adolescence increases thelikelihood that an individual will develop a substance use dependence disorder later inlife (Palmer et al., 2009).

Some youth are at greater risk than others for engaging in substance use behavioursand experiencing higher levels of stress. In particular, youth who attend alternative highschools (also referred to as continuation, contract or community high schools in theUnited States) may experience greater levels of stress than their regular high schoolcounterparts, including emotional and physical abuse or victimisation, loss of a parent,cycling in-and-out of foster care, being a witness to violence and other occurrences thatcause them to feel disconnected from mainstream society (Zweig & Institute, 2003).Generally, these students have left regular high schools, because of excessive truancy,poor academic performance, drug use, violence, other illegal activity or disruptivebehaviour (Rohrbach, Sussman, Dent, & Sun, 2005). Compared with regular high schoolstudents, alternative high school students report higher prevalence rates for the currentuse of tobacco, alcohol, episodic heavy alcohol, marijuana and cocaine (between 33.4,14.1, 18.1, 27.7 and 12.6 higher rates, respectively; Grunbaum, Lowry, & Kann, 2001).

Although the relationship between self-reported SLEs and elevated substance usehas been well established (Wagner et al., 2009; Wiechelt, 2007; Wills, 1986), not alladolescents exhibit maladaptive behaviours after having experienced a highly stressfullife event. Instead, many youth undergo a process of reevaluation and redefinition oftheir life’s priorities, allowing them to successfully adapt despite their high-risk environ-ment and potentially more vulnerable backgrounds (Austin, 2004; Masten, 2004); assuch, they emerge in the aftermath of a highly stressful experience with a more positiveperspective on life. Such individuals develop post-traumatic growth (PTG), variablyreferred to as benefit finding or meaning-making coping.

PTG has been defined as having garnered positive life changes and having developeda level of psychological functioning and awareness beyond pre-SLE level, as a result ofstruggling with and managing at least one highly stressful life event (Calhoun &Tedeschi, 2001). According to theories of PTG (Schaefer & Moos, 1998; Tedeschi,1995; Tedeschi & Calhoun, 2004), the occurrence of some SLE, whether or not it quali-fies as a diagnosable traumatic stressor1, according to the Diagnostic and StatisticalManual of Mental Disorders-IV (DSM-IV; American Psychiatric Association [APA],2000), is a prerequisite for the development of PTG. Thus, in the endeavour to betterunderstand PTG, it is important to further explore the theoretical relationship with SLEs;more specifically, to test whether or not PTG develops in relation to a specific SLE.

Joseph’s person-centered theory (Joseph, 2003; Joseph & Linley, 2006) posits thatPTG develops, because individuals are intrinsically motivated to become fully functioning.This means that in the aftermath of an SLE, they strive to accommodate stress-relatedexperiences into their new sense of self, find purpose and meaning in the SLE, experiencelife as a process, find value in trusting relationships, gain a greater sense of their spiritual-ity and find an augmented sense of personal strength to, therefore, function at a higherlevel than the pre-SLE self (Joseph, 2003; Joseph & Linley, 2006; Tedeschi & Calhoun,

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1996). Because those who develop PTG strive to become fully functioning and perceivecertain behaviours as incongruent with their improved post-SLE self, it follows that suchindividuals would likely engage in fewer health-compromising behaviours. PTG may,therefore, serve as a resilience factor that directly promotes congruent behaviours or func-tions through a stress-buffering effect to discourage health-compromising coping-relatedbehaviours.

Prior research on the relationship between PTG and substance use behaviours has beenprimarily conducted among adults. Exemplified in several studies, women who developedPTG as a result of being diagnosed with HIV/AIDS report that the diagnosis served as a‘wake-up call’, and was the impetus for them to reduce their use of alcohol and/or otherdrugs (Milam, 2006; Siegel & Schrimshaw, 2000; Updegraff, Taylor, Kemeny, & Wyatt,2002). In a study among successful ex-smokers, many reported that a specific SLE in theirlives, such as the break-up of a long-term relationship, had provided them with the neces-sary motivation to quit (Tsourtos et al., 2011). Furthermore, two studies conducted amonghomeless women experiencing a wide range of SLEs and breast cancer patients intreatment have demonstrated similar results, an inverse relationship between PTG andsubstance use (Stump & Smith, 2008; Urcuyo, Boyers, Carver, & Antoni, 2005).

Only two quantitative studies have been conducted to examine the relationshipbetween PTG and substance use among high school students, and both were cross sec-tional. In the first study, conducted among regular high school students (average age of15.8 years, SD = 1.52), PTG was assessed with respect to a range of SLEs, includingdeath of a close family member, moving to a new home, loss of a close friend, majorillness/injury to a close family member, parents’ separation and being held back a grade(Milam, Ritt-Olson, & Unger, 2004). Among the sample, PTG was inversely related tosubstance use (a composite index of tobacco, alcohol, and marijuana). In the second study,PTG was assessed with respect to the stress from the September 11 attacks among middleschool students (mean age 13.5 years, SD = 0.52) (Milam, Ritt-Olson, Tan, Unger, &Nezami, 2005). Although an inverse relationship was found between PTG and alcohol use(r = −.15, p < .001), inverse and non-significant relationships were found between PTGand cigarette smoking and marijuana use. A possible reason for the lack of findings is thatthe sample was comprised of younger adolescents with relatively low prevalence rates ofcigarette (5.8% for past 30-day use) and marijuana use (10.3% for prior year use) com-pared with alcohol use (34.4% for prior year use), resulting in less statistical variation.

With the current study, we aimed to expand the empirical literature by testing thehypothesis that in accordance with the person-centered theory, older at-risk adolescentswho report higher levels of PTG in the aftermath of a life-altering SLE will concur-rently report reduced substance use behaviours at the two-year follow-up assessment.Further, because a possible stress-buffering relationship between PTG and high cumula-tive stress from multiple SLEs has not been characterised, we explore whether PTGmoderates the relationship between cumulative number of SLEs and substance use.

Methods

Participants

Participants were enrolled in a randomised controlled trial of Project Towards No DrugAbuse (TND), a 12-lesson drug abuse prevention curriculum that targets youth inalternative high schools (for programme and recruitment details, see Sussman, Sun,

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Rohrbach, & Spruijt-Metz, 2012). The current trial examined the efficacy of a boosterprogramme component that utilises motivational interviewing techniques. Twenty-fouralternative high schools were randomly assigned to one of the three experimental condi-tions: control, TND only or TND plus motivational interviewing booster. A total of1704 (71.1%) of students enrolled in classes selected from the 24 alternative highschools consented to participate in the intervention study, for which results are reportedelsewhere (see Sussman et al., 2012).

Data collection

Data for this study were collected before programme implementation (baseline) and atthe two-year follow-up. All procedures and protocols for this study were approved bythe IRB at the University of Southern California. Informed consent was obtained fromstudents who were at least 18 years of age. For those under 18, informed consent wasobtained from parents, in addition to student assent. Trained data collectors administereda paper and pencil survey in one 50-min classroom period at the baseline. Students whoprovided consent but were absent the day of survey administration received a telephonecall and were given the option to complete the survey verbally at that time. Of the 1704participants who were consented, 1676 completed the baseline survey. For the two-yearfollow-up data collection, 703 (41.9%) students completed surveys that were adminis-tered by telephone (76.3%), in-person (at school or via home visit; 8.8%) or bymail-back (14.8%). For this study, the analytic sample was comprised of students fromboth intervention and control groups, who reported having experienced a SLE within thepast two years and answered PTG items referring to the SLE (n = 564).

Measures

Study condition

A covariate was included in order to control for the study condition to which studentswere assigned. Because the goal of this study was not to assess effects of the inter-vention, and previous studies have shown no differences in substance use outcomesbetween the two intervention conditions (see Sussman et al., 2012), the variable forstudy condition was dichotomously coded as TND-any (either intervention arm) orcontrol. Additionally, sensitivity analysis demonstrated that results of this study werethe same when the treatment condition was coded dichotomously (0 = control,1 = intervention) or categorically with three levels (0 = control, 1 = intervention onlyand 2 = intervention + motivational interviewing booster).

Demographics

Socio-demographic information was collected at baseline for age (in years), gender,socio-economic status (a single variable reflecting either mother’s or father’s highesteducational attainment, whichever was higher) and race/ethnicity categories (Asian orAsian American; Latino or Hispanic; African American or Black; White, Caucasian,Anglo, or European American, not Hispanic; American Indian or Native American;Mixed (‘My parents are from two different groups’); or Other). Because of insufficientnumbers in the race/ethnic categories other than Hispanic (35%), race/ethnicity wasrecoded to Hispanic or non-Hispanic.

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Stressful life events

The SLE checklist included in the two-year follow-up survey was derived from anabbreviated (18-item) version of the Adolescent Negative Life Events Inventory (Wills,1986; Wills & Cleary, 1996) used in a previous study among adolescents (meanage = 14.4 years ± .8) (Rohrbach, Grana, Vernberg, Sussman, & Sun, 2009). For thepresent study, we included a checklist of the eight life events that were most commonlyreported among adolescents in the Rohrbach et al. (2009) study. Because thedistribution of events has been shown to vary according to contextual factors of age,race/ethnicity, gender and socio-economic status (Hatch & Dohrenwend, 2007), wordingfor some items was altered in order to be more relevant to this older adolescent popula-tion (mean age at the time of the two-year follow-up survey = 18.8 ± 9.3). For example,because many of these youth were no longer living with parents or guardians, or depen-dent on others financially, ‘My parents had problems with money’ was changed to ‘Idid not have enough money for basics (like food)’, and ‘I had a lot of arguments withmy parents’ was changed to ‘There were a lot of arguments that happened at home’.Participants were given the checklist of the eight life events and asked to indicate whichevents they had experienced within the past two years (yes/no response to each). Aninth question allowed for participants to indicate that they had experienced otherevents not listed in the checklist with a free-entry field for them to write in the event ormultiple events. Responses were summed to get a nominal total for the SLEs experi-enced within the past two years. Relevant for assessing PTG, participants were asked toindicate which of the listed events (including anything they wrote into the ‘Other’category) affected their life the most.

Post-traumatic growth

The instrument used to assess PTG at the two-year follow-up was an eight-itemself-report scale. Due to constraints on space and time, these items were derived from an11-item version of the Post-traumatic Growth Inventory (PTGI), which was modifiedfrom the original inventory by Tedeschi and Calhoun (Tedeschi, 1995; Tedeschi &Calhoun, 1996) and used among diverse adolescent and adult samples previously(Arpawong, Richeimer, Weinstein, Elghamrawy, & Milam, 2013; Milam, 2004, 2006;Milam et al., 2005). We selected eight items from the 11-item PTGI (used in Arpawonget al., 2013) in order to both maximise the variation that would be captured by the itemsand preserve statistical reliability and validity. First, we removed an item asking about‘my religious faith’ because it correlated highly (r = .81) with another item on ‘under-standing of spiritual matters’ and the factor loading was lower. Second, we removed anitem on ‘priorities about what is important’ as it had the lowest factor loading of all itemsin the 11-item scale. Third, we removed an item on ‘willingness to express my emotions’because among the three items representing PTG domain of relationships with others, ithad the lowest factor loading. Overall, the eight items used reflected a single dominantglobal factor. In a factor analysis, each item had high factor loadings on the first unrotatedfactor, all at or above .61, with an eigenvalue of 5.44. The means calculated for the8-item and 11-item scales correlated at r = .98. The internal reliability/consistency(Cronbach’s α) for the mean of the eight items used in this study was .81.

Participants were asked to respond to the PTG items in reference to the single SLEthat they designated as the most life altering of the past two years. To avoid the

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potential bias from participants only being able to report positive valenced change thatmay have resulted from their stressful event, the response format for this scale allowedparticipants to endorse both negative and positive changes. Responses ranged from 1(‘Negative change’) to 3 (‘Positive change’), with 2 indicating ‘No change’. Althoughthe response options were restricted from 1 to 3, in contrast to prior assessments ofPTG in which responses were allowed on a broader range (from 1 to 5), prior analysescomparing the use of mean PTG scores for the full format to the restricted formatyielded similar results (data not shown).

Similar to the previous research on PTG (e.g. Antoni et al., 2001; Milam, 2004;Milam et al., 2004), a factor analysis suggests that a unitary score is appropriate for themeasure. Although the two factors had eigenvalues greater than 1 (3.40 for factor 1),the eigenvalue of the second value was only 1.01, and all items loaded at or above .61on the first unrotated factor. Thus, a composite score, averaging responses on all eightitems. Because the distribution of the PTG variable had negative skewness, PTG wasreflected to convert the distribution to positive skewness, log-transformed andrereflected for use as a continuous variable for all analyses.

Peer substance use

Perceived peer substance use is a well-established indicator of maladaptive adjustmentby its relationship with health-compromising behaviours (Sussman, Dent, & McCullar,2000). Four items were used at baseline to assess perceptions of use among five closestpeers for each of the subcategories (cigarettes, alcohol, marijuana and hard drugs) withresponse options from 1 (0 friends) to 6 (5 friends). The four items were averagedyielding a scale with high internal consistency (Cronbach’s α = .85).

Substance use

Items assessing past month substance use were used to create dependent variables aswell as baseline control variables. At both baseline and two-year follow-up, the item‘How many times have you used each of these drugs in the last month (last 30 days)?’was posed, with a list of 12 substance categories: cigarettes, alcohol, getting drunk onalcohol, marijuana, cocaine, hallucinogens, stimulants, inhalants, ecstasy, pain killers,tranquillisers and other hard drugs. For each category, response options were providedon a 12-point scale to indicate use between 0 and over 100 times (1 = 0 times,2 = 1–10 times, 3 = 11–20 times, … , 12 = Over 100 times). The reliability of the sub-stance use item format has been established previously (Graham et al., 1984; Needle,McCubbin, Lorence, & Hochhauser, 1983; Stacy et al., 1990). Responses to the firstfour substance categories were used to create continuous, ordinal variables for fre-quency of past month cigarette use, alcohol use, getting drunk on alcohol and marijuanause, respectively. Responses to the last eight substance categories (cocaine through otherhard drugs) were summed to create an index for the frequency of past month hard druguse (Cronbach’s α = .73). Average number of cigarettes smoked daily was assessedthrough a single item, ‘How many cigarettes do you smoke per day on average?’Responses were used to create a continuous variable for average daily cigarette use.Lastly, participants were asked ‘How many days have you had 5 or more alcoholicdrinks within a 5 h period over the last 30 days?’ Responses used to create a

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continuous variable for past month number of times reported binge drinking. Foranalysis, all substance use variables were coded as log-transformed use levels.

Substance abuse

An index for the past year substance abuse was created using four questions (e.g. ‘Inthe last 12 months, have you kept using alcohol or drugs even though it was keepingyou from meeting your responsibilities at work, school, or home?’, ‘In the last12 months, has your alcohol or drug use caused you to have repeated problems withthe law?’), serving as proxy items of the DSM-IV substance abuse disorder categories.Responses from the four items were summed into a single variable (Cronbach’sα = .66), and if the score was 1 or more, the participant was coded as having abusedsubstances in the past year. The sum score for level of past year substance abuse wasused as a continuous variable.

Statistical analysis

Of the 1676 students who completed a survey at baseline, 703 students completed thetwo-year follow-up survey (58.1% attrition rate). To account for the effect of possibledifferential study attrition on important baseline variables in the analytic models, a pro-pensity-for-attrition score was calculated for each participant retained in the sample (vs.those lost-to-follow-up at 2 years) and included as a covariate in regression models suchthat results could be interpreted as if there was no imbalance in attrition within thesample. First, the difference on key variables (18 variables) by actual attrition status(0 = not retained in the sample, 1 = retained in the sample) from baseline to thetwo-year follow-up was assessed using logistic regression analysis. The variables thatwere significantly associated with attrition were age, whether the participant lived withboth parents, and a four-item scale on attitudes of drug use (i.e. if they used drugs, theywould feel wrong, guilty or ashamed; see Sussman, Dent, & Galaif, 1997); these threevariables were included in the calculation of the propensity-for-attrition score. Thismethod has been used previously to control for the effects of differential attrition(Berger, 2005; Grunkemeier, Payne, Jin, & Handy, 2002; Sun et al., 2007). Addition-ally, when the analytic sample (n = 564) was compared with those who did not reportan SLE at the two-year follow-up (n = 139), there were no significant differences inbaseline age, gender, ethnicity, parents’ education or treatment group (p’s > .05). Allanalyses were performed using the SAS (v.9.1.3) statistical package.

Multilevel linear regression (PROC MIXED) models were run in order to examinethe primary study hypothesis (whether higher PTG is associated with lower levels ofsubstance use behaviours over time). In order to assess each substance use outcome, thefrequency of use (or level for substance abuse) at the two-year follow-up was used asthe dependent variable and baseline use was included as a covariate. The number ofSLEs and PTG were both entered as continuous variables as correlates of substanceuse behaviour at the two-year follow-up. An interaction term was created betweenstandardised variables (number of SLEs × PTG) to assess whether PTG moderated theeffect of cumulative stress from SLEs and substance use. All models included a propen-sity-for-attrition score, intervention condition, socio-demographic variables (i.e. age,gender, race/ethnicity, and parents’ education as a proxy for socio-economic status) and

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perceived peer substance use as covariates. Additionally, models included a schoolvariable as a random effect to allow for the statistical accounting of intraclasscorrelation of students within clustered units (schools) on computed significance levels,and for greater generalisability of findings.

Results

Participant characteristics

Table 1 provides characteristics of the sample. Every student reported at least onestressful life experience over the past two years (mean number of SLEs = 3.14,SD = 1.70). Of the sample, 20% reported experiencing only one event, 21% reportedtwo events, while the majority (59%) reported experiencing three or more events overthe two-year follow-up assessment period. Overall, 22% reported experiencing five ormore events. The most life-altering SLEs reported, in order of greatest to leastfrequency, were the following: someone in the family having a serious illness, accidentor injury (28%); conflict at home (13%); relationship problem (12%); being or havingsomeone in the family be arrested (11%); having a new person join the household(11%); not having enough money for basics such as food (6%); job or school change/problem (6%); being a victim of a violent or abusive crime (4%); personal injury,

Table 1. Selected sample characteristics (n = 564).

Variable % or mean (SD)

GenderMale 54.4Female 45.6Agea 16.78 (.90)Race/ethnicityAsian or Asian American 2.9Latino or Hispanic 65.3African American or Black 3.4White, Caucasian, Anglo, European American; not Hispanic 11.9American Indian or Native American .4Mixed: my parents are from two different groups 14.5Other 1.6Highest education completed by either mother or fatherDid not complete 8th grade 9.6Did not complete high school (12th grade) 25.0Completed high school (received a diploma) 26.5Some college or job training (1–3 years) 20.2Completed college (4 years) 13.9Attended or completed graduate school (Doctor, Lawyer) 4.8Peer substance useb 2.71 (.55)Number of stressful life events 3.14 (1.70)Post-traumatic growth 2.64 (.38)

Note: Number of stressful life events and post-traumatic growth were assessed at the two-year follow-up. Allother variables were assessed at baseline.aAge ranged from 14 to 20 years at baseline.bNumber of friends, out of the participant’s five closest friends, who had used cigarettes, alcohol, marijuana orhard drugs in the last 30 days (range 0–5).

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illness, accident or change in health status (2%); death of an extended family member(2%); being displaced from home (2%); injury or death of a friend (2%); and otherSLEs of which each was reported by less than 1% of participants (pregnancy, miscar-riage of self or partner; change in religious faith; death of a parent or both; witnessinga violent crime; and getting robbed).

The majority of students reported that some aspect of their life had improved in theaftermath of having experienced the most life-altering SLE of the past two years,demonstrated by a mean PTG score of 2.64 (SD = .38), on a scale of 1–3. Participantswere most likely to report positive changes on items, in order of greatest to least fre-quency, my own inner strength (83%), appreciation for the value of my own life (77%),direction for my life (75%), handling my difficulties (72%), involvement in things thatinterest me (69%), my compassion for others (69%), my sense of closeness with others(65%) and my understanding of spiritual matters (56%).

Table 2 provides means, standard deviations and frequencies for substance usebehaviours assessed at baseline. Alcohol and hard drugs were most and least prevalentlyused among all substances, respectively. Table 3 provides zero-order correlationcoefficients between all substance use outcomes, PTG, number of SLEs and modelcovariates.

Multilevel regression models

Table 4 presents results of multilevel regression models. Although testing of interven-tion group (treatment vs. control) effects on substance use at the two-year follow-upwas not a central research question, it was crucial to demonstrate that the treatmentgroup did not affect final model outcomes. For sensitivity analyses, interactions fortreatment × PTG and treatment × SLE number were tested and these were significantonly for the outcome of average daily cigarette use (p = .04 and p = .03, respectively).Also, the final regression models for all substance use outcomes were run in stratifiedsamples for the treatment and control groups separately yielding the same pattern ofresults found as presented in Table 4.

With regard to main effects tested, as shown in Table 4, several socio-demographic characteristics predicted greater use of certain substances at the two-yearfollow-up. Older age predicted greater frequency in past month use of cigarettes, alco-hol, marijuana, getting drunk and binge drinking and past year substance abuse.Being male predicted greater frequency in use of all substances and more substanceabuse; being of non-Hispanic ethnicity predicted greater frequency in daily and pastmonth cigarette and past month marijuana use; and higher parental educationpredicted more frequent binge drinking (p’s < .05). The perception of having moresubstance-using peers predicted greater frequencies in past month use of alcohol andmarijuana (p’s < .05). For all substances, use at baseline was a positive predictor ofuse at the two-year follow-up (p’s < .05). Lastly, experiencing more SLEs betweenbaseline and the two-year follow-up was associated with greater past month use ofcigarettes, alcohol, marijuana and hard drugs, greater frequency of getting drunk onalcohol in the past month among those who used alcohol as well as greater substanceabuse in the past year (p’s < .05).

With regard to hypothesis testing, results supported the assertion that greater PTGwas associated with less frequent alcohol and marijuana use in the past month, as

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well as less substance abuse in the past year. Also, among those who used alcohol,higher PTG scores were associated with a lower frequency of past month drunkennessand binge drinking (p’s < .05). However, higher PTG scores were not associated withfrequency of use of cigarettes, either average daily use or past month use, or pastmonth hard drug use. These results were further supported by sensitivity analysis, inwhich we examined differences in mean PTG scores when the dependent substanceuse variable was coded categorically with respect to differences in use from baselineto the two-year follow-up (0 = no use maintained, 1 = reduced/quit use, 2 = stayed atthe same level of use and 3 = increased/initiated use). Relationships between substanceuse and PTG were as hypothesised such that participants categorised as ‘increasing/initiating use’ had lower mean PTG scores than those categorised as ‘reducing/quit-ting use’. This pattern of relationships was true for level of use for all substances.Lastly, interaction terms exploring PTG as a moderator of cumulative stress fromSLEs on substance use were not included in the final models, because they were notsignificant.

Discussion

To our knowledge, this is the first prospective study to demonstrate that PTG is associ-ated with less use of alcohol and marijuana, and substance abuse behaviours amongalternative high school students. We found that positive psychosocial adjustment to aparticular life-altering stressor may counteract the negative impact of event-related

Table 2. Prevalence of substance use behaviours at baseline and the two-year follow-up.

Baseline Two-year follow-upSubstance use variable % %

Cigarette use (past month) 40.4 37.5Alcohol use (past month) 60.0 58.0**Drunk on alcohol (past month) 44.7 34.1***Binge drinking (past month) 35.1 36.3*Marijuana use (past month) 47.0 34.1***Hard drug use (past month) 28.0 13.5***Substance abuse (past year) 49.0 30.5***

Among those who reported past month use of thesubstance at each assessment point a,b

Baselinemean (SD)

Two-year follow-upmean (SD)

Average number of cigarettes smoked per day 3.09 (4.56) 6.07 (5.95)Number of times smoked cigarettes 26.04 (16.49) 32.71 (19.46)Number of times used alcohol 7.57 (1.78) 4.78 (2.34)Number of times drunk on alcohol 2.71 (1.58) 6.66 (.86)Number of times binge drinking 3.60 (5.90) 4.68 (5.38)Number of times used marijuana 25.95 (16.04) 19.10 (11.63)Number of times used hard drugs 21.00 (8.02) 8.29 (3.43)Level of substance abuse 2.03 (.93) 1.77 (.89)

*p < .05; **p < .01; ***p < .001 for change in prevalence compared with baseline.ap-value for difference between two-year and baseline is not calculated because of different denominators pervariable.bRange for average number of cigarettes smoked per day is 1–40, for number of times smoked cigarettes is1–90, used alcohol is1–100, drunk on alcohol is 1–50, binge drinking is 1–30, used marijuana is 1–100 andused hard drugs is 1–100. Range for past year levels of substance abuse is 1–4.

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Table3.

Bivariate

correlations

betweenPTG,nu

mberof

stressfullifeevents(SLEs),substanceusebehaviou

rsandcorrelates.

Cigarette

use:

pastmon

thCigarette

use:

averagedaily

Alcoh

oluse:

pastmon

thAlcoh

oluse:

getting

drun

kAlcoh

oluse:

bing

edrinking

Mariju

anause:

pastmon

thHarddrug

use:

pastmon

thSub

stance

abuse:

pastyear

Treatment

−.004

−.012

−.102

*−.063

−.058

−.041

−.081

#−.097

*Age

−.054

.044

.002

.009

.074

−.049

.048

−.054

Male

−.185

***

−.237

**−.151

***

−.145

***

−.174

**−.248

***

−.064

−.180

***

Hispanicethn

icity

−.251

***

−.335

***

−.036

−.065

.054

−.141

***

−.002

.036

Parents’education

.105

*.088

.022

.042

.062

.101

*−.027

−.048

Peersubstanceuse

.173

***

.177

*.183

***

.148

***

.194

**.243

***

.043

.169

***

Num

berof

SLEs

.181

***

.144

#.175

***

.189

***

.071

.217

***

.139

***

.276

***

PTG

−.030

−.011

−.125

**−.139

***

−.164

*−.137

**−.116

**−.152

***

Notes:Codingfordichotom

ousvariablesareas

follo

ws:Treatment=1vs.Control

=0;

Male=1vs.Fem

ale=0;

Hispanic=1vs.Other

=0.

Substance

usevariableswereassessed

aspast

month

frequencyof

useat

thetwo-year

follo

w-up(num

berof

times)except

foraveragedaily

cigarettes(assessedaverage

numberof

cigarettessm

oked

perday)andpastyear

substanceabuse(assessedas

levelof

substanceabuse).

#p<.10;

*p<.05;

**p<.01;

***p

<.001.

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Table4.

Impact

ofSLEsandPTG

onsubstanceusebehaviou

rsat

thetwo-year

follo

w-up.

Variable

Cigarettes

Alcoh

olMariju

ana

Harddrug

sSub

stance

abuse

Pastmon

thuse

Average

daily

use

Pastmon

thuse

Gettin

gdrun

kBinge

drinking

Pastmon

thuse

Pastmon

thuse

Pastyear

abuse

Treatmentgrou

p0.03

0.23

*−0.20

−0.08

−0.02

0.05

−0.13

0.14

(0.08)

(0.15)

(0.09)

(0.10)

(0.15)

(0.08)

(0.10)

(0.10)

Age

0.01

***

0.16

#0.01

***

0.01

**

0.03

*0.01

***

0.08

#0.05

***

(0.04)

(0.09)

(0.05)

(0.05)

(0.08)

(0.04)

(0.05)

(0.05)

Male

0.25

***

0.31

*0.31

***

0.27

**

0.33

*0.33

***

0.17

#0.41

***

(0.07)

(0.14)

(0.09)

(0.09)

(0.14)

(0.08)

(0.09)

(0.09)

Hispanicethn

icity

−0.26

**

−0.33

*−0.03

−0.05

0.14

−0.24

**

0.03

0.12

(0.09)

(0.15)

(0.10)

(0.11)

(0.15)

(0.09)

(0.11)

(0.10)

Parents’education

−0.01

−0.03

0.04

0.03

0.11

*0.03

0.01

−0.01

(0.03)

(0.05)

(0.03)

(0.04)

(0.06)

(0.03)

(0.04)

(0.04)

Peersubstanceuse

0.01

0.02

0.06

*0.04

0.09

#0.06

*−0.04

0.03

(0.03)

(0.05)

(0.03)

(0.03)

(0.05)

(0.03)

(0.03)

(0.03)

Baselineuse

0.96

***

0.12

***

0.57

***

0.75

***

0.06

***

0.76

***

0.64

***

0.18

***

(0.07)

(0.01)

(0.13)

(0.15)

(0.01)

(0.08)

(0.12)

(0.04)

Num

berof

stressfullife

events

0.08

***

0.07

#0.08

**

0.06

*−0.02

0.08

***

0.07

*0.13

***

(0.02)

(0.04)

(0.03)

(0.03)

(0.04)

(0.02)

(0.03)

(0.03)

Post-traumatic

grow

th0.13

0.02

−0.60

*−0.70

**

−1.38

**

−0.61

**

−0.33

−0.75

**

(0.22)

(0.39)

(0.26)

(0.28)

(0.44)

(0.24)

(0.28)

(0.27)

Mod

elF

28.19*

**

13.52*

**

7.79

***

6.84

***

5.22

***

23.05*

**

4.92

***

10.79*

**

AdjustedR2

0.36

0.48

0.12

0.11

0.17

0.32

0.08

0.17

Notes:Codingfordichotom

ousvariablesareas

follo

ws:Treatment=1vs.Control

=0;

Male=1vs.Fem

ale=0;

Hispanic=1vs.Other

=0.

Dependent

variablesforsubstanceuseweremodelledas

past

month

frequencyof

useat

thetwo-year

follo

w-up(num

berof

times)except

foraveragedailycigarettes

(assessedaveragenumberof

cigarettessm

oked

perday)andpastyear

substanceabuse(assessedas

levelof

substanceabuse).Allmodelsarecontrolledforpropensity-for-

attrition.

Estim

ates

arestandardised

beta

coefficients.StandardErrorsarein

parenthesis.

#p<.10;

*p<.05;

**p<.01;

***p

<.001.

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distress on use of health-compromising substances. Our results corroborate findingsfrom prior studies that were mostly cross-sectional, and therefore did not control forbaseline substance use levels, and were conducted among younger adolescent and olderadult samples. Further, these results support the notion that PTG includes a functionalcomponent such that individuals who report PTG demonstrate congruence betweenimproved psychological functioning and behavioural benefits. Although we did not findthat PTG moderates the relationship between cumulative number of stressors and sub-stance use, this study draws attention to health behaviour benefits of PTG.

Developing a higher level of PTG, as a result of a life-altering event, was associatedwith lower past month use of alcohol and marijuana, getting drunk on alcohol, bingedrinking and past year substance abuse. Because PTG was associated with changes inbehaviours that occurred over a two-year period, this suggests that positive perceptionsof the post-SLE self in the present sample represented some element of functionalchange and were not merely illusory self-enhancements. Prior studies have initiatedquestions with regard to the functional component of PTG, since perceived positivechange has not always correlated with demonstrated changes in well-being, actual PTGdomains or decreased distress (e.g. Frazier & Kaler, 2006; Frazier et al., 2009; Tomich& Helgeson, 2004). Nevertheless, results of our study and cross-sectional predecessorsprovide compelling evidence that the functional component of PTG may manifest asdemonstrated changes in behaviour. Hence, successfully managing the stress from alife-altering event can facilitate one’s ability to become more highly functional withregard to behaviour, post-crisis.

Even though some of our results supported the hypothesis that greater PTG is asso-ciated with less substance use, we found no associations between PTG and cigarette orhard drug use at the two-year follow-up. With regard to cigarettes, this corroborates astudy of younger adolescents that showed an inverse but non-significant relationshipbetween PTG and cigarette use (Milam et al., 2005). In that study, the prevalence ofpast month cigarette use was very low (5.8%), and thus there may have been too fewcigarette smokers to detect any significant statistical relationship. In the present study,the lack of relationship between PTG and frequency of past month cigarette use may bedue to their being very little change in prevalence from baseline to the two-year follow-up (non-significant difference of 2.9%, shown in Table 2). Otherwise, the research thusfar indicates that PTG does not associate strongly with youth cigarette smokingbehaviours in particular.

With regard to hard drug use, the lack of relationship is more difficult to explain,particularly given that the prevalence of hard drug use from baseline to the two-yearfollow-up was reduced by half, from 28 to 14%. One explanation is that proximal fac-tors that were not assessed in this study (e.g. access to hard drugs, money to buy themand a place to use them) may be more salient to hard drug use behaviour among theolder adolescents than is PTG. Another explanation is that those who continue toengage in hard drug use over the long-term have experienced more severe stressorsearlier in life, prior to the two-year period for SLEs assessed in this study. Thisexplanation coincides with prior research demonstrating that experiencing more severeevents in childhood (e.g. sexual abuse, physical assault) is related to hard drug usedependence in later adolescence (Kilpatrick et al., 2000; Schäfer, Schnack, & Soyka,2000).

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Of note, PTG was associated with less binge drinking, while the number of SLEswas not. This corroborates prior research (Low et al., 2012) that binge drinking may beused as a coping response elicited by a single acute event (e.g. romantic break-up, lossof a job), rather than by the accumulation of lower level stressors (e.g. financial orschool-related). Further, our finding extends prior work in which PTG was found to benegatively associated with binge drinking among university students in a cross-sectionalstudy (Foster et al., 2013). These results provide evidence for a promising approach tocombat binge drinking, the pattern of alcohol use that has been deemed the greatestconcern from a public health perspective (Johnston, O’Malley, Bachman, &Schulenberg, 2010). Encouraging the use of alternative coping mechanisms (e.g. prob-lem solving, spiritual coping) and cognitive processing towards thoughts of positive lifechange post-SLE may be a useful target for intervention to combat episodic heavydrinking.

The exploratory hypothesis of this study, that PTG would moderate the relationshipbetween cumulative number of SLEs and frequencies of substance use through a stress-buffering process, was not supported. Yet consistent with prior research amongadolescents (e.g. Booker et al., 2004; Dube et al., 2006; Low et al., 2012; Newcomb &Harlow, 1986), we found that a higher number of SLEs were related to higher substanceuse rates. Taken together, this suggests that the negative relationship between PTG andsubstance use occurs independently of the relationship between cumulative stress andsubstance use. The question remains on whether developing PTG at one point in timewould result in increased stress buffering to future life events. For instance, researchhas demonstrated that PTG predicts meaning-making at a future time point, which isthen related to greater overall psychological well-being (Park, Edmondson, Fenster, &Blank, 2008). Thus, a future study would be needed to answer the question of whethergreater PTG confers a stress-buffering benefit to long-term changes in substance usebehaviours.

A common approach of efficacious school-based programmes for at-risk, olderyouth is the incorporation of modules that focus on coping with stress and decreasinggeneral stress levels (Sussman et al., 2004; Sussman & Sun, 2009). Future modulesmay increase efficacy if they include recognising cues to emotional and mental distressstemming from a highly impactful SLE, facilitating cognitive processing that fostersPTG as well as enhancing skills to engage in activities that have demonstrated effect onpromoting PTG, such as expressive writing, physical activity or meditation (Marlo &Wagner, 1999; Sabiston, McDonough, & Crocker, 2007; Smyth, Hockemeyer, &Tulloch, 2008).

Limitations

The generalisability of these findings is applicable to older, mostly Hispanic youth whoattend alternative high schools. Evidence shows Hispanic students have higher preva-lence rates of substance use behaviours when compared with White/Caucasian, Black/African-American and Asian American students (CDHS, 2010; Johnston et al., 2013),although variations exist by grade level, state and school type. Some research connectsacculturation factors (e.g. discord between child and parent expectations, recentness ofimmigration), social factors related to culture (e.g. social self-control, precociousness)and Hispanic subgroup (i.e. Spanish, Cuban, Puerto Rican, Mexican, Central or South

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American, Dominican or mixed) to varying prevalence rates (e.g. Johnston et al., 2013;Pokhrel, Herzog, Sun, Rohrbach, & Sussman, 2013; Substance Abuse and MentalHealth Services Administration [SAMHSA], 2011; Unger, Ritt-Olson, Wagner, Soto, &Baezconde-Garbanati, 2009). Given this heterogeneity in the Hispanic group and factorsrelated to substance use behaviours, examination of how these factors influence PTGand the response to acute stressors warrants a subsequent study designed to capture andanalyse the relationships. Such analyses would be timely in that the proportion ofHispanic students is increasing in cities nationwide, particularly in alternative highschools.

An additional limitation is that the study findings are based on self-reportedbehaviours, cognitions and experiences, any of which may be influenced by multiplefactors. Self-reports of the number and types of SLEs one has experienced are sub-ject to memory lapses or selective disclosure (Dohrenwend, 2006). Not all partici-pants reported experiencing an SLE, and thus could not be included in the analyticsample. It is uncertain whether those who did not report experiencing an SLE selec-tively chose not to; however, those who did and did not report an SLE were com-parable on baseline characteristics. Thus, the analytic group does not appear torepresent a biased sample. Also, because we modified an existing checklist, thereare concerns with regard to the reliability and validity. The purpose of the checklistwas to capture variability and identify a single life-altering SLE in relation to whichparticipants would answer PTG questions. Because we did not use it to make com-parisons with other samples, with regard to prevalence or stressfulness ratings ofeach item, and 20% of SLEs were written into the ‘Other’ field, the checklist servedthe goals of this study. To address the hypothesis that more stressors positivelyinfluence substance use, it is also plausible that substance use results in more SLEs.Thus, future work may consider assessing a bidirectional hypothesis utilising a studydesign with multiple assessment points for SLEs and substance use. With regard tothe substance abuse variable, it did not indicate a clinical diagnosis of substanceabuse, rather can be interpreted as probable substance abuse. With further regard toself-report, PTG represents a construct of perceived positive change post-SLE. Thereis no evidence validating the veracity of the high levels of positive growth reportedby participants (e.g. reports by significant others, a trusted family member) or thatlevels of growth were not reflecting issues of social desirability, which was not mea-sured in the present study. Also, our use of a modified PTG scale with a narrowrange for responses was not expected to compromise construct validity or internalconsistency of the measure, yet restricting response options may have limited ourability to detect greater variation in the response levels of participants, and poten-tially stronger effects. Lastly, the effect sizes for PTG were small in this study, andit is likely that other variables not examined in this study have more proximalsalience to changes in substance use behaviours. However, the associations betweengreater PTG and less substance use suggest that positive growth was evident and,even if externally motivated, manifested in healthier behaviours.

Future research

Future directions for this research include examining these relationships among differentsamples of youth comprised of varying age ranges and race/ethnic backgrounds.

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Including more extensive checklists of both positive and negative valenced SLEs orusing a semi-structured interview format to assess SLEs may be useful. Also, there maybe other factors contributing to substance use behaviours that need to be accounted forin future studies, given the lack of association between PTG and use of cigarettes andhard drugs, and low variance explained by the variables included in the models. Forexample, taking into account the level of addiction to particular substances (i.e. nicotinetolerance, opiate dependence) may explain some level of differences in substance useover a two-year period. Lastly, an additional avenue of research that may help explainthe relationship between PTG and substance use behaviours among high-risk youthwould be to conduct a temporal examination on whether prior use of certain substances(i.e. alcohol vs. tobacco or marijuana vs. alcohol) impairs or promotes the developmentof PTG, and whether prior PTG effects changes in substance use behaviours over timeas a potentially interrelated process.

In conclusion, greater levels of positive psychosocial adjustment to a life-alteringSLE, indicated by higher PTG scores, was associated with lower levels of alcohol andmarijuana use, and substance abuse over two years. Also, the finding that PTG did notmoderate the relationship between number of SLEs and substance use behaviours sug-gests that PTG provides a protective effect on substance use behaviours in relation to aspecific SLE (i.e. the most life-altering SLE), irrespective of the cumulative number ofSLEs experienced. These results have implications for substance use interventions.Because PTG can be augmented through brief cognitive-behavioural stress reductionapproaches (Cryder, Kilmer, Tedeschi, & Calhoun, 2006; Garland, Carlson, Cook,Lansdell, & Speca, 2007; Lechner & Antoni, 2004), PTG represents a unique,salutogenic intervention target that may help to counteract the negative impact of aparticularly salient SLE on substance use among high-risk youth.

Funding

This work was supported by the Tobacco-Related Disease Research Program [20DT-0041] andthe National Institute on Aging, of the National Institutes of Health [F32AG048681].

Note1. An event qualifies as a traumatic stressor if it (a) involved an actual or threatened death or

serious injury, or a threat to the physical integrity of oneself or to others and (b) if theindividual’s response involved intense fear, helplessness or horror (APA 2000).

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