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. Author manuscript; available in PMC: 2015 Oct 1.
Published in final edited form as: Exp Clin Psychopharmacol. 2015 Jun 8;23(5):303–313. doi: 10.1037/pha0000022

A Laboratory-Based Test of the Relation between Adolescent Alcohol Use and Panic-Relevant Responding

Heidemarie Blumenthal 1,*, Renee M Cloutier 2, Byron L Zamboanga 3, Liviu Bunaciu 4, Ashley A Knapp 5
PMCID: PMC4578981  NIHMSID: NIHMS698603  PMID: 26053320

Abstract

A burgeoning literature supports a link between alcohol use and panic-spectrum problems (e.g., panic attacks, disorder) among adolescents, but the direction of influence has yet to be properly examined. From a theoretical perspective, panic-spectrum problems may increase risk for problematic drinking via affect regulation efforts (e.g., self-medication), and problematic consumption also may increase or initiate panic-relevant responding (e.g., learning or kindling models). The objective of the current investigation was to examine the role of prior alcohol use in predicting panic-relevant responding, as well as panic symptom history in predicting the desire to consume alcohol, in the context of either a voluntary hyperventilation or a low-arousal task. Participants were community-recruited adolescents aged 12-17 years (n = 92, Mage = 15.42, SD = 1.51; 39.1% girls). Results indicated that prior alcohol use predicted panic-relevant responding among those undergoing the hyperventilation task (but not the low-arousal task), and that this finding was robust to the inclusion of theoretically-relevant covariates (i.e. age, sex, negative affectivity). However, panic symptom history did not predict the desire to consume alcohol as a function of either the hyperventilation or low-arousal condition. This work sheds further light on the nature of the relation between panic-spectrum problems and problematic alcohol use in adolescence. Specifically, the current findings suggest that frequent alcohol use may increase panic vulnerability among adolescents, whereas acute panic symptoms may not elicit the immediate (self-reported) desire to drink.

Keywords: Alcohol, Panic, Adolescence, Voluntary Hyperventilation, IAPS

The association between alcohol use and panic-spectrum problems (e.g., panic attacks, panic disorder) has received increasing attention over the past two decades (Bunaciu et al., 2010; Hayward et al., 1997). In research with adult (e.g., Mathew et al., 2011) and adolescent (e.g., Zimmerman et al., 2003) samples, a positive relation between alcohol use and panic-spectrum problems has been observed. Indeed, with only two exceptions (i.e., Clark et al., 1995; Hayward et al., 1995), a high degree of co-occurrence has been identified in adolescent samples across qualitative (Gardner & Kutcher, 1993), laboratory-based (Blumenthal et al., 2012), and prospective designs (e.g., Goodwin et al., 2004). This growing literature indicates that alcohol use disorders (AUDs) are positively associated with a concurrent diagnosis of panic disorder (PD; Zimmerman et al., 2003). Moreover, alcohol use behaviors (e.g., frequency of use, amount typically consumed) are positively linked with panic-relevant responding (i.e., fearful responding to somatic arousal; Blumenthal et al., 2012), and panic attack history (Hayward et al., 1997), suggesting that this association may emerge prior to meeting diagnostic criteria in either domain.

Research examining the alcohol-panic linkage among adolescents is important for at least three reasons. First, the incidence of panic-spectrum problems (e.g., full-symptom panic attack) typically occurs during adolescence (Goodwin & Gotlib, 2004). For example, pubertal status (indexed via the Tanner staging system; Tanner, 1962) positively relates to both panic-relevant responding (Leen-Feldner, Reardon, & Zvolenksy, 2007) and panic attack history (Hayward et al., 1992). Second, experimentation with alcohol is a common feature of this period (Chen, Yi, & Faden, 2011; Masten, Faden, Zucker, & Spear, 2009). Epidemiological work indicates that over 70% of high school students in the United States report lifetime alcohol use, and 21.9% report heavy consumption (i.e., 5 or more drinks within a couple hours) in the past 30 days (Centers for Disease Control & Prevention [CDC], 2012). Finally, the rapid neurological and somatic development that characterizes puberty may set the stage for enhanced risk associated with the use of alcohol (Brown et al., 2008; Nixon & McClain, 2010). For instance, adolescents evidence distinct acute effects of alcohol consumption (e.g., attenuated motor impairment; Behar et al., 1983; Windle et al., 2008), and greater risk for the transition to problematic use behaviors (Deas, Riggs, Langenbucher, Goldman, & Brown, 2000; Masten et al., 2009), as compared to adults.

From a theoretical perspective, panic-spectrum problems may increase risk for problematic drinking via affect regulation efforts (e.g., Robinson, Sareen, Cox, & Bolton, 2009), and problematic drinking also may increase or initiate panic-relevant responding (e.g., via repeated pairing of somatic arousal and negative affect; Johnson et al., 2000; Zvolensky, Schmidt, & Stewart, 2003). Data drawn from the Munich Early Developmental Stages of Psychopathology study (e.g., Goodwin et al., 2004) provide initial support for affect regulation models asserted in much of the adult anxiety (broadly defined) and alcohol use literature (Gorka et al., 2013; Kushner et al., 1996; Stewart & Conrod, 2008). For example, Zimmerman and colleagues (2003) reported that panic attack history at age 14-24 years positively related to the onset of hazardous drinking by a four-year follow-up assessment, even after controlling for several important variables (e.g., sex, other anxiety and mood disorders). Additional work indicates that trauma-exposed adults drink excessively in the presence of bodily arousal (Sharkansky et al., 1999), and that bodily arousal induced in the laboratory elicits an urge to drink when participants endorse tension reduction expectancies (Mulligan & McKay, 2001). Other work with clinical (Lehman et al., 2002) and non-clinical (MacDonald et al., 2000) adult samples demonstrates that alcohol does indeed reduce reactivity to a biological challenge in a dose-dependent fashion. These data provide preliminary support for the contention that panic-relevant problems may increase risk for problematic drinking; however, limited work has been conducted with adolescents.

Importantly, the physiological arousal associated with repeated or heavy alcohol consumption (e.g., heart palpitations, dizziness), combined with potential negative affectivity (Hussong, Hicks, Levy, & Curran, 2001) and/or disruptions in neurological function and structure as a result of excessive alcohol use (Brown et al., 2008; Nixon & McClain, 2010), may in turn increase risk for panic-spectrum problems (Allan, 1995; Kushner et al., 1990; Stewart & Conrod, 2008). For example, drinking increases opportunities for the concurrent experience of bodily arousal and anxiety (e.g., common post-intoxication symptoms; Verster, 2008), thus enhancing panic vulnerability via repeated pairing (Bouton, Mineka, & Barlow, 2001). This viewpoint is supported by retrospective data drawn from the National Epidemiological Survey on Alcohol and Related Conditions (Grant, Moore, Shepard, & Kaplan, 2003). For instance, Falk and colleagues (2008) reported that AUD onset preceded the development of PD across a significant majority of adults presenting with co-occurring AUDs and PD.

Of note, order of onset is a necessary, but insufficient criterion for establishing causality (Chilcoat & Breslau, 1998). Further, data exist in support of “both directions,” and few studies have sought to establish directionality in regard to sub-clinical indices (e.g., panic symptoms) as opposed to diagnostic status. Experimental psychopathology techniques (i.e. laboratory procedures to elicit relevant responding) may therefore provide key data to complement and extend the literature. Although ethical constraints preclude alcohol administration to underage populations (cf., Behar et al., 1983), there is a rich tradition of the safe and effective use of panic-relevant procedures among adolescents (e.g., Hawks, Blumenthal, Feldner, Leen-Feldner, & Jones, 2011; Leen-Feldner, Feldner, Bernstein, McCormick, & Zvolensky, 2005; Rabian, Embry, & MacIntyre, 1999). Such procedures elicit a state analogous to that of panic (Olatunji, Leen-Feldner, Feldner, & Forsyth, 2007), and thus reduce concerns related to potential affective or memory biases by examining “real-time” responding (Nisbett & Ross, 1980). Further, factors related to the degree of panic-relevant responding can be subjected to causally-oriented hypothesis testing with the inclusion of a low-arousal task and random assignment to condition (Kazdin, 2003). Finally, this approach can be employed with non-clinical samples to aid in the development of etiologic models of panic and co-occurring issues (e.g., Zvolensky et al., 2001).

In the only study to date to employ an induction procedure among youth, adolescents reporting alcohol use (at least one standard beverage a few times a year) evidenced elevated panic symptoms in response to a voluntary hyperventilation challenge as compared to abstainers and experimenters (i.e. ‘tried but quit;’ Blumenthal et al., 2012). Although promising, several limitations characterized that study. First, alcohol use was categorized broadly (i.e., non-users, experimenters, users). Second, there was no comparison condition. Assessment of participants all undergoing the same challenge procedure limits conclusions, particularly in regard to specificity; for example, youth reporting alcohol use also may be ‘high responders’ to all assessments and procedures. Finally, only the link between prior alcohol use and challenge response was examined; observing alcohol use indices as a function of induction procedures will be key to ascertaining the relevance of existing theoretical models in the alcohol-panic link among youth.

The current study was designed to extend this work in three ways: to (1) oversample youth who have consumed alcohol, allowing for continuous rather than categorical assessment, (2) include a low-arousal condition, and (3) assess both the role of prior alcohol use in predicting acute panic symptoms as well as the role of prior panic symptoms in predicting acute desire to drink. Consistent with prior work, it was expected that alcohol use would positively relate to panic symptoms following the panic-relevant, but not the low-arousal, task. Given limited work directly supporting affect regulation models among youth (cf. work conducted with adults; e.g., Kushner et al., 1996), panic symptoms were not expected to relate to the desire to drink following either task. It was expected that significant relations would be robust to the addition of age, sex (Blumenthal et al., 2012; Chorpita, Yim, Moffitt, Umemoto, & Francis, 2000), and generalized negative affectivity (Craske, Poulton, Tsao, & Plotkin, 2001; Hayward, Wilson, Lagle, Killen, & Taylor, 2004) in the model. Finally, given work indicating sex differences in the incidence of panic (Mathyssek, Olino, Verhulst, & van Oort, 2012), alcohol use (Eaton et al., 2012), and the relation between anxiety and drinking (Schry, Norberg, Maddox, & White, 2014), post-hoc analyses addressed whether the relations above differed as a function of sex.

Method

Participants

Participants were 92 adolescents (age 12-17 years; Mage = 15.42, SD = 1.51; 39.1% girls) recruited from the community to take part in a study on adolescent emotions and health-behaviors. Primary sampling criteria included oversampling of youth reporting experience with alcohol (i.e., 88% in the current sample as opposed to 70.8% recently reported in the United States; CDC, 2012), as well as exclusion of those reporting: a) lifetime history of PD, posttraumatic stress disorder, or an AUD; b) chronic cardiac (e.g., hypertension) or respiratory (e.g., asthma) problems; c) possible pregnancy; d) active suicidality; e) limited mental capacity or inability to provide informed, written assent to participate; or f) absence of a parent or legal guardian to provide written informed consent prior to participation.

Approximately 600 parents and youth contacted the laboratory about the study. Seventeen interested participants did not fall within the required age range (12-17 years); 435 reported limited/no history of having consumed a full, standard alcoholic beverage (excluded for oversampling purposes or additional exclusionary criterion). Additional exclusionary criteria reported at screening included: relevant respiratory problems (primarily asthma; n = 68), cardiovascular problems (n = 6), potential lifetime panic disorder (n = 5) and/or AUD (n = 14); none were excluded for current pregnancy or suicidality. Finally, 49 individuals were not interested in participation following study description and/or were unable to provide assent/consent for participation. One hundred and six adolescents met the listed screening criteria; participants included in the current analyses (n = 92) were those with complete predictor (e.g., alcohol use history) and criterion (e.g., desire to drink) data. It is important to note that participants selected for analysis did not differ significantly from those in the larger study across any of the primary predictor, criterion, or demographic variables.

The ethnic (Hispanic/Latino; not Hispanic/Latino) and racial composition of the analyzed sample was consistent with that of the local community (southern Midwest United States; U.S. Bureau of the Census, 2010): 13.5% Hispanic/Latino, 76.1% Caucasian, 4.3% African American, 2.2% Asian, 1.1% Native American, 1.1% Hawaiian/Pacific Islander, 7.6% bi/multi-racial, and 7.6% “other” or did not respond. Also consistent with community estimates (U.S. Bureau of the Census, 2012), parents who accompanied participants to the laboratory and agreed to provide demographic information (63% of the sample; 65.5% biological mothers) reported a median family income of $50,000 (M = $70,231, SD = $67, 277). Parental education was as follows: 5.2% did not complete high school, 15.5% received a high school diploma or equivalent degree, 24.1% completed some college, 31.1% held Associate’s or Bachelor’s degrees, 6.9% reported some graduate or professional schooling, and 17.2% completed graduate or professional school. Seven percent of parents reported having never been married, 75.4% were married or living with someone, 12.3% were divorced, and 5.3% separated.

Measures

Alcohol use history

Frequency of alcohol use was assessed via the well-established Adolescent Alcohol and Drug Involvement Scale (AADIS; Moberg, 2000; Moberg & Hahn, 1991). This face-valid measure asks participants to select a single response that best reflects how often they drink alcohol on a scale of 0 (never used) to 7 (several times a day). Each response point was accompanied by a written descriptor, with higher numbers reflecting increased alcohol consumption (e.g., 2 = several times a year; 3 = several times a month). This scale has been successfully used in prior work examining similar community-based samples of adolescents (e.g., Blumenthal et al., 2010, 2012; Collins & Cellucci, 1991). Data collected by this instrument in terms of tobacco and marijuana use also are presented for descriptive purposes.

Panic symptom history

The Revised Child Anxiety and Depression Scale-Panic subscale (RCADS-P; Chorpita et al., 2000) was used to index symptoms of panic. The nine-item panic subscale asks participants to rate the frequency with which they experience panic-type sensations (e.g., “All of a sudden I feel really scared for no reason at all”) on a four-point Likert-type scale (0 = never to 3 = always). Responses were summed, providing a total subscale score. Designed to reflect the dimensions of several DSM-IV-defined anxiety disorders among adolescents, this measure evidences good reliability and validity (e.g., α = .86 in the current sample; Chorpita et al., 2000; Chorpita, Moffitt, & Gray, 2005).

Laboratory challenge

Participants were randomly assigned to either a voluntary hyperventilation challenge or a low-arousal comparison condition.

Voluntary hyperventilation

Hyperventilation was selected as the experimental procedure as it can reliably produce panic-relevant bodily arousal (e.g., increased heart rate, breathlessness, tingling in the extremities; Fried & Grimaldi, 1993; Hornsveld, Garssen, & van Spiegel, 1995), and it has been safely employed with children and adolescents (Blumenthal et al., 2012; Hawks et al., 2011; Leen-Feldner et al., 2007; Unnewehr et al., 1996). The challenge involved a three-minute procedure during which participants were asked to breathe at a rate of 30 respiratory cycles per minute. Audio-taped instructions were used to standardize procedures and ensure consistency of breathing rates across participants throughout the challenge. These instructions are thoroughly described elsewhere (Leen-Feldner et al., 2006). Evidence suggests that this procedure effectively elicits somatic aroual (Antony, Ledley, Liss, & Swinson, 2006; Spinhoven, Onstein, Sterk, & Le Haen-Versteijnen, 1992), as well as anxiety and panic symptoms among youth at risk for panic-spectrum problems (e.g., Hawks et al., 2011; Leen-Feldner et al., 2005).

Low-arousal condition

Participants in the comparison condition engaged in all aspects of the procedure (e.g., pCO2 monitoring, self-report assessments; please see below) except the hyperventilation challenge itself. Participants in this condition instead viewed a three-minute loop of neutral images (e.g., spoon; chair) from the International Affective Picture System (Center for the Study of Emotion and Attention, 1995). Specifically, a set of 12 neutral pictures were presented 3 times each: each of the pictures remained on the computer screen for 5 seconds (Lang, Bradley, & Cuthbert, 1997; 2008) and each picture was presented in random order within each set. These slides have been successfully used in the past to elicit neutral affective states and minimal physiological arousal among adolescents (e.g., Leen-Feldner, Zvolensky, & Feldner 2004; McManis, Bradley, Berg, Cuthbert, & Lang, 2001; Lang et al., 2008).

Manipulation check: Expired carbon dioxide

Participants were fitted with a continuous positive pressure C-Pap Mask and expired levels of carbon dioxide (pCO2) were monitored via a Novametrix CO2/SMO Capnograph. Baseline (immediately pre-task) and task-mean (average level during the task) were recorded. These data were used to evaluate the degree to which participants adhered to the instructions for the hyperventilation challenge (Rapee et al., 1992).

Panic symptoms following the challenge

The Acute Panic Inventory (API; Dillon, Gorman, Liebowitz, Fyer, & Klein, 1987) was used to index panic-relevant responding elicited by the laboratory tasks. On a four-point scale (0 = not at all to 3 = a lot) participants rated the degree to which they were currently experiencing 23 items reflecting DSM-IV defined panic attack symptoms (e.g., “Do you feel your heart beating fast?” and “Are you afraid of going crazy?”). Responses were summed, providing a total symptom level score immediately post-challenge. Importantly, the API has been employed in prior biological challenge work with children and adolescents (Blumenthal et al., 2012; Pine et al., 1998, 2000), and evidences sound psychometric properties (e.g., α = .86 in the current sample).

Desire for alcohol

Participants’ desire to consume alcohol was determined using the well-established Desires for Alcohol Questionnaire (DAQ; Love, James, & Willner, 1998). The DAQ includes 28 items to which participants indicated their agreement with how much each statement reflects how they currently feel on a scale of 1 (strongly disagree) to 7 (strongly agree). Items reflect moderate (e.g., “I might like a drink now”), and strong (e.g., “I need a drink now”) desires; responses were summed to reflect an overall score. Participants completed both a baseline (i.e., shortly after introduction to the laboratory) as well as a post-challenge assessment (items randomized to limit order effects). The DAQ evidences excellent psychometric properties (e.g., baseline α = .97, post-challenge α = .98 in the current sample; Love et al., 1998), and has been successfully employed in studies examining social drinkers (Duka, Jackson, Smith, Stephens, 1999; Schulze & Jones, 2000), as well as adolescent samples (Tapert et al., 2003).

Covariates.

Chronological age, sex (e.g., Chorpita et al., 2000), and negative affectivity (e.g., Craske et al., 2001; Hayward et al., 2004) were selected as covariates. General proclivity toward negative affectivity was measured via the negative affect scale of the Positive and Negative Affect Schedule for Children (PANAS-C; Joiner, Catanzaro, & Laurent, 1996). This measure asks participants to use a five-point Likert-type scale (1 = very slightly to 5 = extremely) to rate how they have been feeling during the past few weeks in terms of 15 descriptors (e.g., upset, nervous, sad). The PANAS-C, negative affect scale evidences good internal consistency (e.g., α = .89 in the present sample) and validity (Joiner et al., 1996).

Additional Parent Data

Participating parents also were asked about lifetime panic attack history (e.g., ‘out of the blue’) via the relevant item on the Panic Attack Questionnaire-Short version (Norton, Dorward, & Cox, 1986; n = 50 responders), as well as lifetime alcohol use (n = 53 responders), marijuana use (n = 52 responders), and nicotine use (n = 53 responders) via the Drug use History Questionnaire-Revised (Sobell, Kwan, & Sobell, 1995). Finally, the Structured Clinical Interview for DSM-IV (SCID)-Alcohol abuse/dependence module (First et al., 2002) was used to assess the presence/absence of lifetime AUD (n = 61 responders). Given limited parent participation, these data are included for descriptive purposes only.

Procedure

All procedures were approved by the University Institutional Review Board prior to participant contact. Interested participants and parents responding to community advertisements (e.g., flyers; radio) were informed about the study, and adolescents were screened for the exclusionary criteria noted above. Eligible youth were scheduled for a laboratory visit, at which time written informed assent and parental consent were obtained. Parents interested in providing information completed a brief interview and questionnaire battery (e.g., demographics; 66% completed any data), after which parents were thanked, debriefed, and compensated $5 for their time. Adolescent participants completed a battery of randomly ordered questionnaires, including demographics, the baseline DAQ, AADIS, RCADS, and PANAS-C, followed by a series of activities including the randomly assigned challenge. For the laboratory challenge, participants were outfitted with the C-Pap mask, and task procedures were explained. The protocol was comprised of three stages: 1) five minute baseline; 2) three minute hyperventilation challenge/low-arousal activity; and 3) ten minute recovery. Immediately following completion of the task, participants provided current API and DAQ ratings. After completion of the procedures adolescent participants were thanked, debriefed, and compensated $40 for their time.

Analytic Approach

Manipulation checks included a paired-samples t-test examining pCO2 as a function of task assignment, as well as Pearson’s correlations addressing panic symptom history (i.e., RCADS-P total) in relation to challenge response. Chi-square analyses, independent samples t-tests, and Pearson’s correlations were used to examine zero-order relations among predictor and criterion variables, including the efficacy of random assignment. Primary hypotheses were examined via a series of regression analyses: post-challenge API scores were regressed on alcohol use frequency, experimental condition (step 1), and the interaction (step 2), and post-challenge DAQ scores on baseline DAQ (step 1), RCADS-P total and experimental condition (step 2), and the interaction (step 3). Conditional effects of significant interactions were examined, and covariates (i.e., age, sex, PANAS-N total) included in follow-up assessments of significant relations. Finally, the three-way interaction between the primary predictor (i.e. alcohol use frequency, RCADS-P total), experimental condition, and sex were examined.

Results

Preliminary Analyses

Adolescent report on the AADIS indicated that 12% of the current sample had never consumed a full alcoholic beverage, 10.9% ‘tried but quit,’ 34.8% drink several times a year, 22.8% several times a month, 16.3% weekends only, 2.2% several times a week, and 1% daily. Please see Tables 1 and 2 for zero-order relations among all continuous variables and additional descriptive data. A paired samples t-test indicated that pCO2 significantly decreased during the hyperventilation challenge (t[46] = 16.64, p < .001, r = .92), but not the low-arousal task (t[33] = −0.29, p = .769, r = .05). Further, as seen in Table 1, panic symptom history (RCADS-P total) was significantly, positively correlated with acute panic responding (API total) in response to the hyperventilation challenge, but not the low-arousal condition. As illustrated in Table 2, chi-square analyses identified no significant differences in group assignment as a function of sex (χ2 [1, N = 92] = 1.09, p = .296, ϕ = 0.10) or ethnicity/race (i.e., non-Hispanic Caucasian/White, Hispanic and/or non-Caucasian/White; χ2[1, N = 92] = 0.37, p =.542, ϕ = 0.06). Finally, the groups did not significantly differ across any of the baseline assessments (i.e., age, negative affectivity, alcohol use frequency, baseline DAQ, RCADS-P totals; p’s range .425-.905). Together, these data suggest that the manipulation and random assignment were largely effective. Of note, as seen in Table 2, groups did differ in terms of parental history of marijuana use; however, importantly, adolescent marijuana use did not differ across conditions.

Table 1.

Zero-order Relations among all Continuous Variables as a Function of Condition

Variable 1 2 3 4 5 6 7 8 9
1. Age -- −.05 −.19 .02 .21 .12 .00 −.00 −.10
2. pCO2 Baseline −.08 -- .65** .02 .16 −.06 .13 .21 .15
3. pCO2 Task mean −.01 .98** -- .14 −.01 −.05 .11 .15 .03
4. PANAS-N .07 −.71** −.70** -- .06 .48** .24 .09 .16
5. AADIS - Alcohol .50** .14 .21 −.17 -- .19 .60** .54** .26
6. RCADS-P .03 −.52** −.50** .44** −.10 -- .30* .07 .27
7. DAQ Baseline .19 .09 .15 −.03 .59** .19 -- .88** .28*
8. DAQ Post task .25 .27 .33 −.14 .56** .00 .86** -- .20
9. API −.16 −.22 −.17 .19 −.12 .08 .09 .14 --
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Note. Data for youth assigned to the low-arousal condition are below the diagonal (n = 42); data for youth assigned to the voluntary hyperventilation condition are above the diagonal (n = 50). AADIS: Adolescent Alcohol and Drug Involvement Scale – Alcohol use frequency (Moberg, 2000). API: Acute Panic Inventory (Dillon et al., 1987). DAQ: Desire for Alcohol Questionnaire (Love et al., 1998). PANAS-N: Positive and Negative Affect Schedule for Children – Negative affect subscale (Joiner, Catanzaro, & Laurent, 1996). pCO2: Expired carbon. RCADS-P: Revised Child Anxiety and Depression Scale – Panic subscale (Chorpita et al., 2000).

*

p < .05

**

p < .01

Table 2.

Descriptive Data as a Function of Condition and Sex

Condition Sex
Low-Arousal
M (SD)a 		Hyperventilation
M (SD) 		Girls
M (SD) 		Boys
M (SD)
Demographic Characteristics
 % Girls2 33.30 44.00 100.00 0.00
 % Non-Hispanic White2 73.80 68.00 58.33 78.57
 Age 15.29 (1.53) 15.54 (1.50) 15.11 (1.80) 15.62 (1.27)
 AADIS-Tobacco 1.73 (2.24) 1.63 (1.92) 1.47 (2.16) 1.80 (2.01)
 AADIS - Marijuana 2.22 (2.21) 2.35 (2.36) 1.82 (1.78) 2.57 (2.52)
 Days since last drink 50.33 (95.29) 38.65 (52.06) 49.83 (47.79) 40.28 (85.70)
Parent Characteristicsb
 % Lifetime Panic Attack 28.57 9.00 12.50 23.52
 % Lifetime Alcohol use 100.00 100.00 100.00 100.00
 % Lifetime Marijuana use1 44.44 80.00 56.25 63.88
 % Lifetime Nicotine use 55.55 65.38 43.75 67.56
 % Lifetime AUD 36.36 42.85 31.57 42.85
Primary Variables
 pCO2 Baseline 36.94 (6.27) 35.04 (7.33) 34.40 (7.17) 36.74 (6.70)
 pCO2 Task mean1 37.00 (6.07) 21.07 (6.17) 26.46 (9.16) 28.60 (10.48)
 PANAS-N2 28.51 (9.82) 29.76 (11.95) 32.30 (12.06) 27.35 (10.05)
 AADIS - Alcohol 2.33 (1.47) 2.30 (1.19) 2.11 (1.19) 2.45 (1.40)
 RCADS-P 3.40 (2.75) 4.04 (5.15) 4.72 (5.19) 3.12 (3.36)
 DAQ Baseline 60.87 (36.41) 67.04 (41.67) 55.88 (36.33) 69.50 (40.47)
 DAQ Post2 54.16 (31.95) 59.68 (41.41) 46.13 (34.49) 64.25 (37.60)
 API1 26.26 (3.09) 34.06 (7.96) 31.27 (7.18) 30.00 (7.44)
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Note: N = 92 (n = 42 Low-Arousal; n = 50 Hyperventilation).

a

Unless otherwise noted.

b

Total n’s range 50-61. AADIS: Adolescent Alcohol and Drug Involvement Scale – Alcohol use frequency (Moberg, 2000). API: Acute Panic Inventory (Dillon et al., 1987). AUD – Alcohol use disorder. DAQ: Desire for Alcohol Questionnaire (Love et al., 1998). PANAS-N: Positive and Negative Affect Schedule for Children – Negative affect subscale (Joiner, Catanzaro, & Laurent, 1996). pCO2: Expired carbon dioxide. RCADS-P: Revised Child Anxiety and Depression Scale – Panic subscale (Chorpita et al., 2000).

1

Group difference p < .05

2

Sex difference p < .05

Primary Analyses

Alcohol use history predicting panic response

As seen in Table 3, both the main effect of group assignment and the interaction between condition and alcohol use frequency were significant, with the final step accounting for 30% of the total variance in API total, F(3,88) = 14.34, p < .001. Examination of the conditional effect indicated that alcohol use frequency significantly predicted API totals among youth completing the hyperventilation (β = 1.83, SE = 0.75, p=.017, 95% CI [0.32, 3.33]), but not the low-arousal (β = −0.19, SE = 0.67, p=.773, 95% CI [−1.53, 1.14]), task. Further, alcohol use frequency remained a significant predictor of API total among youth completing the hyperventilation task (standardized β = .29, t = 2.04, p = .047, sr2 = .08) with age (p = .478, sr2 = .01), sex (p = .984, sr2 = .00), and PANAS-NA total (p = .264, sr2 = .02) included in the model. Finally, the interaction between condition and alcohol use frequency remained significant (p =.018, sr2 = .04) when sex (and the interactions) was included as a primary predictor, and the three-way interaction between sex, condition, and alcohol use frequency was not statistically significant (t = −1.21, p = .226, sr2 = .01). Accordingly, tests including covariates were not conducted.

Table 3.

Primary analyses: Relations between alcohol use history and acute panic responding and that of panic symptom history and desire to drink

ΔR2 t (each predictor) β p sr2
Dependent Variable: API
Step 1 .29 < .001
 AADIS-Alcohol 1.25 .11 .214 .01
 Condition 6.00 .53 < .001 .28
Step 2 .03 .043
 AADIS × Condition 2.05 .39 .043 .03
Dependent Variable: DAQ Post-Task
Step 1 .77 < .001
 DAQ Baseline 17.54 .88 < .001 .77
Step 2 .03 .001
 RCADS-P −4.00 −.19 < .001 .03
 Condition 0.17 .00 .864 .00
Step 3 .00 .702
 RCADS × Condition 0.38 .04 .702 .00
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Note. N = 92 (Condition: n = 42 Low-Arousal; n = 50 Hyperventilation). β = standardized beta. AADIS: Adolescent Alcohol and Drug Involvement Scale – Alcohol use frequency (Moberg, 2000). API: Acute Panic Inventory (Dillon et al., 1987). DAQ: Desire for Alcohol Questionnaire (Love et al., 1998). RCADS-P: Revised Child Anxiety and Depression Scale – Panic subscale (Chorpita et al., 2000).

Panic symptom history predicting post-task desire to drink

As seen in Table 3, after accounting for pre-task DAQ total, there was a significant main effect of RCADS-P scores on post-task DAQ total; however, neither group assignment nor the interaction were significant. The final step of the model accounted for 80% of the variance in post-task DAQ total (F[4,86] = 92.22, p < .001); an effect largely accounted for by pre-task DAQ total. Importantly, when pre-task DAQ total was excluded from the analyses, neither main effect (RCADS-P: standardized β = .05, t = 0.49, p = .619, sr2 = .00; Condition: standardized β = .07, t = 0.66, p = .510, sr2 = .00) nor the interaction (standardized β = .06, t = 0.23, p = .819, sr2 = .08) were significant (Final step F[3,88] = 0.26, p = .853). Accordingly, tests of conditional effect and the inclusion of covariates were not conducted. Finally, the interaction between condition and RCADS-P total also was not statistically significant (p =.545, sr2 = .00) when sex (and the interactions) was included as a primary predictor, and the three-way interaction between sex, condition, and RCADS-P total was not statistically significant (t = −0.12, p = .905, sr2 = .00).

Discussion

A burgeoning literature indicates that panic-spectrum problems and problematic alcohol use are linked among adolescents (e.g., Goodwin et al., 2004; Zimmerman et al., 2003); however, the majority of this work has focused on the degree of co-occurrence across clinical indices (e.g., panic attack incidence; alcohol use disorder diagnosis), and work examining order of onset provides support for “both directions.” The current study was a preliminary test of sub-clinical directionality via a quasi-experimental laboratory design. Findings indicated that frequency of alcohol use was positively correlated with panic-relevant responding to a voluntary hyperventilation challenge (but not a low-arousal comparison condition), and that age, sex, and generalized negative affectivity did not better account for this relation. Conversely, panic symptom history did not predict an increased desire to drink following the hyperventilation challenge (or the low-arousal condition). These data provide additional support for the applicability of interoceptive conditioning or kindling models (as opposed to self-medication) in better understanding the early panic-alcohol use link during adolescence.

The results of the current study are consistent with work conducted with large-scale adult surveys indicating a relation between other substance use behaviors and panic vulnerability (e.g., Bernstein, Zvolensky, Schmidt & Sachs-Ericsson, 2007; Zvolensky et al., 2006). For example, the onset of daily cigarette smoking typically precedes panic attack onset among adults with this type of comorbidity (Bernstein et al., 2007), and rates of panic-spectrum difficulties are greater among adolescent and young adult smokers with a lifetime history of nicotine use disorder, compared to both nonsmokers (Nelson & Wittchen, 1998) as well as young adult smokers without history of a nicotine use disorder (Breslau, Kilbey, Andreski, 1991). Moreover, the link between smoking and panic-spectrum problems demonstrated in these cross-sectional investigations is reinforced by multiple large-scale longitudinal studies showing that smoking rate and nicotine dependence status prospectively predict the development of panic attacks and PD (e.g., Breslau & Klein, 1999; Johnson et al., 2000; Isensee, Wittchen, Stein, Hofler, & Lieb, 2003). The current data complement and extend this work, suggesting that adolescent alcohol use also may enhance risk for panic vulnerability. Although the observed effect of alcohol use frequency on hyperventilation response was small-moderate (sr2 = .08; Cohen, 1992; Fritz et al., 2012), this is notable given the inclusionary and exclusionary criteria (e.g., oversampling of youth reporting prior alcohol use; exclusion of possible PD), as well as the decision not to target adolescents evidencing established risk for panic-spectrum problems (e.g., high anxiety sensitivity; Schmidt, Zvolensky, & Maner, 2006). Further, it is important to note that there was a failure of random assignment in terms of parental marijuana use history; although adolescent marijuana use history did not differ significantly across conditions, given extensive work identifying a link between marijuana use and panic-spectrum problems (e.g., Bonn-Miller, & Zvolensky, 2009; Zvolensky, Cougle, Johnson, Bonn-Miller, & Bernstein, 2010) and the multi-faceted role of parents in predicting offspring outcomes (e.g., gene-environment correlations; Jaffee & Price, 2007), work addressing this limitation as well as disentangling the complex, dynamic role(s) of parents is needed. Future efforts monitoring the onset and progression of panic- and alcohol-relevant indices is warranted, including work powered to examine the role of demographic (e.g., sex; Buckner & Turner, 2009) behavioral (e.g., other substance use; Zvolensky et al., 2008), and individual difference (e.g. anxiety sensitivity; Schmidt, Buckner, & Keough, 2007) characteristics that may qualify this relation. Indeed, certain descriptive data (e.g., parental characteristics) and inferential statistics (i.e. regarding sex) in the current analyses should be considered with caution given the small cell sizes.

Of note, the current data stand in contrast to work conducted with adults indicating self-medication motives as key in explaining the relation between alcohol use and panic-spectrum problems (e.g., Kushner et al., 1996; Kushner, Abrams, Thuras, & Hanson, 2000; Stewart & Zeitlin, 1995). This may be due, in part, to social and legal constraints limiting adolescents’ access to alcohol, and thus opportunities to associate the consumption of alcohol with remittance of panic-related negative affectivity. Emerging evidence suggests that adolescents’ beliefs about the effects of alcohol may be primarily informed by external sources (e.g., peers, media; Andrews & Hops, 2011; Snyder & Nordoff, 2011). Although coping-related motives for alcohol consumption have been identified among adolescents struggling with other forms of anxiety psychopathology (e.g., social anxiety; Blumenthal et al., 2010), the comparatively infrequent, and unpredictable, incidence of panic-spectrum issues may not facilitate the immediate learning of symptom-related alcohol use. Accordingly, coping-related consumption may emerge as a maintaining, rather than etiological, feature of the alcohol-panic relation among youth; efforts directly examining use motives in these relations (e.g., frequency of alcohol use in relation to panic vulnerability, incidence of panic attacks, disorder), as well as ‘real-time’ assessments outside of the laboratory context (e.g., ecological momentary sampling) are required.

Experimental and prospective work identifying developmental constellations and cascades (i.e. interactive and cumulative effects within and across developmental domains and levels; Cicchetti & Rogosch, 1999; Masten & Cicchetti, 2010) clearly is needed. For example, whereas the current data suggest that adolescent alcohol use enhances risk for panic-spectrum problems, youth already endorsing coping-related motives, or other relevant factors (e.g., high anxiety sensitivity, parental coping-related use; Comeau et al., 2001; Conrod et al., 2006), still may be at risk for the use of alcohol in an effort to reduce panic-relevant negative affect. Further, the current study excluded youth who met clinical criteria for PD, limiting the generalizability of the current findings in terms of those experiencing more severe symptomology. Data regarding the direct, indirect, and multivariate relations relevant to intervention efforts require further study, and mapping the onset and progression of alcohol relevant indices (e.g., behaviors and cognitions), panic-spectrum markers, as well as potential shared factors (e.g., genetic or epigenetic transmission) will be necessary in the formation of developmentally-sensitive models of the alcohol-panic relation. It is important to note that no other work has directly examined “both directions” in a single study; conceptual replication of these data across other community-based and clinical (e.g., those presenting with an AUD and/or PD) samples will be required to better understand the nature and boundaries of this relation. Nonetheless, the current findings suggest that alcohol use may be a promising target for selective or indicated programs aimed at the prevention of panic-spectrum problems among youth (Cuijpers, 2014), and further support existing efforts targeting “personality risk factors” such as anxiety sensitivity in reducing both alcohol-related and internalizing problems (Conrod et al., 2006).

Additional limitations warrant consideration. First, the current investigation included a relatively homogeneous sample (e.g., largely White/Caucasian) of older adolescents. Additional cross-sectional, cohort-sequential, as well as prospective work is needed to tease apart the timing of this relation, and will be important in determining the generalizability of the current findings (e.g., across racial/ethnic groups; Cooper et al., 2008). The current study also included several medical and relevant psychological exclusionary criteria (e.g, PD, PTSD, AUD), further limiting the sample of adolescents willing and able to participate in a laboratory-based study for monetary compensation. In an effort to rule out potential sampling biases, future work employing alternative assessment (e.g., at home or school) and sampling (e.g., school-wide screening; multi-site data collection) techniques is required. The low-arousal condition selected for use in the current study, although well-established (e.g., Leen-Feldner et al., 2004; Lang et al., 2008), differed from the experimental condition in multiple ways (e.g., visual as opposed to respiratory). Efforts to validate a low-arousal task akin to the voluntary hyperventilation procedure (e.g., paced breathing) among youth would benefit this literature. Finally, acute panic symptoms were not assessed prior to group assignment; although there is little reason to expect meaningful differences across individuals prior to task engagement, the current project could not directly speak to change in panic symptoms as a function of experience and condition. Together, the current findings suggest that frequent alcohol use may increase panic vulnerability among adolescents, whereas acute panic symptoms may not elicit the immediate (self-reported) desire to drink. These data uniquely extend extant work, and lay the foundation for more advanced methodological and analytic approaches necessary for the design of targeted preventative intervention efforts in this domain.

Acknowledgements

... The funding agency played no role in study design; the collection, analysis and interpretation of data; the writing of the report; or the decision to submit the article for publication.

Footnotes

Disclosures

The authors have no conflicts of interest to declare.

All authors contributed in a significant way to the manuscript, and all authors have read and approved the final manuscript.

Contributor Information

Heidemarie Blumenthal, University of North Texas, Department of Psychology.

Renee M. Cloutier, University of North Texas, Department of Psychology

Byron L. Zamboanga, Smith College, Department of Psychology

Liviu Bunaciu, Houston OCD Program; Alpert Medical School of Brown University

Ashley A. Knapp, University of Arkansas, Department of Psychology

References

  1. Allan CA. Alcohol problems and anxiety disorders - A critical review. Alcohol and Alcoholism. 1995;30:145–151. [PubMed] [Google Scholar]
  2. Andrews JA, Hops H. The influences of peers on substance use. In: Scheier LM, editor. Handbook of drug use etiology: Theory, methods, and empirical findings. American Psychological Association; Washington DC: 2011. pp. 403–420. [Google Scholar]
  3. Antony MM, Ledley DR, Liss A, Swinson RP. Responses to symptom induction exercises in panic disorder. Behaviour Research and Therapy. 2006;44:85–98. doi: 10.1016/j.brat.2004.12.005. doi:10.1016/j.brat.2004.12.005. [DOI] [PubMed] [Google Scholar]
  4. Behar D, Berg CJ, Rapoport JL, Nelson W, Linnoila M, Cohen M, Bozevich C, Marshall T. Behavioral and physiological effects of ethanol in high-risk and control children: A pilot study. Alcoholism, Clinical and Experimental Research. 1983;7:404–410. doi: 10.1111/j.1530-0277.1983.tb05495.x. doi:10.1111/j.1530-0277.1983.tb05495.x. [DOI] [PubMed] [Google Scholar]
  5. Bernstein A, Zvolensky MJ, Schmidt NB, Sachs-Ericcson N. Developmental course(s) of lifetime cigarette use and panic attack comorbidity: An equifinal phenomenon? Behavior Modification. 2007;31:117–135. doi: 10.1177/0145445506295056. doi:10.1177/0145445506295056. [DOI] [PubMed] [Google Scholar]
  6. Blumenthal H, Leen-Feldner EW, Frala JL, Badour CL, Ham LS. Social anxiety and motives for alcohol use among adolescents. Psychology of Addictive Behaviors. 2010;24(3):529–534. doi: 10.1037/a0019794. doi: 10.1037/a0019794. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Blumenthal H, Leen-Feldner EW, Zamboanga BL, Knapp AA, Bunaciu L. Alcohol use history and panic-relevant responding among adolescents: A test using a voluntary hyperventilation challenge. Psychology of Addictive Behaviors. 2012;26(4):683–692. doi: 10.1037/a0027364. doi: 10.1037/a0027364. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bonn-Miller MO, Zvolensky MJ. Marijuana use, abuse, and dependence: Evaluation of panic responsivity to biological challenge. Journal of Psychoactive Drugs. 2009;41(4):331–336. doi: 10.1080/02791072.2009.10399770. [DOI] [PubMed] [Google Scholar]
  9. Bouton ME, Mineka S, Barlow DH. A modern learning theory perspective on the etiology of panic disorder. Psychological Review. 2001;108:4–32. doi: 10.1037/0033-295x.108.1.4. doi:10.1037/0033-295X.108.1.4. [DOI] [PubMed] [Google Scholar]
  10. Breslau N, Kilbey M, Andreski P. Nicotine dependence, major depression, and anxiety in young adults. Archives of General Psychiatry. 1991;48:1069–1074. doi: 10.1001/archpsyc.1991.01810360033005. doi:10.1001/archpsyc.1991.01810360033005. [DOI] [PubMed] [Google Scholar]
  11. Breslau N, Klein DF. Smoking and panic attacks: An epidemiologic investigation. Archives of General Psychiatry. 1999;56:1141–1147. doi: 10.1001/archpsyc.56.12.1141. doi:10.1001/archpsyc.56.12.1141. [DOI] [PubMed] [Google Scholar]
  12. Brown SA, McGue M, Maggs J, Schulenberg J, Hingson R, Swartzwelder S, Murphy S. A developmental perspective on alcohol and youths 16 to 20 years of age. Pediatrics. 2008;121:S290–S310. doi: 10.1542/peds.2007-2243D. doi: 10.1542/peds.2007-2243D. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Buckner JD, Turner RJ. Social anxiety disorder as a risk factor for alcohol use disorders: A prospective examination of parental and peer influences. Drug and Alcohol Dependence. 2009;100:128–137. doi: 10.1016/j.drugalcdep.2008.09.018. doi:10.1016/j.drugalcdep.2008.09.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Bunaciu L, Feldner MT, Blumenthal H, Babson K, Schmidt NB, Sachs-Ericsson N. A test of the relations between avoidance of panic-related situations and substance use, substance dependence, and depression among subclinical panickers. Behaviour Research and Therapy. 2010;48:158–163. doi: 10.1016/j.brat.2009.10.001. doi:10.1016/j.brat.2009.10.001. [DOI] [PubMed] [Google Scholar]
  15. Center for the Study of Emotion and Attention (CSEA-NIMH; The international affective picture system. The Center for Research in Psychophysiology, University of Florida; Gainesville, FL: 1995. [IAPS; photographic slides] [Google Scholar]
  16. Centers for Disease Control and Prevention [CDC] Trends in the prevalence of alcohol use national YRBS: 1991-2011. 2012 Retrieved from http://www.cdc.gov/healthyyouth/yrbs/pdf/us_alcohol_trend_yrbs.pdf.
  17. Chen CM, Yi H, Faden VB. Surveillance report #96: Trends in underage drinking in the United States, 1991-2011. NIAAA, Division of Epidemiology and Prevention Research, Alcohol Epidemiologic Data System; Rockville, MD: 2011. [Google Scholar]
  18. Chilcoat HD, Breslau N. Investigations of causal pathways between ptsd and drug use disorders. Addictive Behaviors. 1998;23(6):827–840. doi: 10.1016/s0306-4603(98)00069-0. doi: 10.1016/S0306-4603(98)00069-0. [DOI] [PubMed] [Google Scholar]
  19. Chorpita BF, Moffitt CE, Gray J. Psychometric properties of the revised child anxiety and depression scale in a clinical sample. Behaviour Research and Thearapy. 2005;43:309–322. doi: 10.1016/j.brat.2004.02.004. doi:10.1016/j.brat.2004.02.004. [DOI] [PubMed] [Google Scholar]
  20. Chorpita BF, Yim L, Moffitt C, Umemoto LA, Francis SA. Assessment of symptoms of DSM-IV anxiety and depression in children: A revised child anxiety and depression scale. Behavior Research and Therapy. 2000;38:835–855. doi: 10.1016/s0005-7967(99)00130-8. doi:10.1016/S0005-7967(99)00130-8. [DOI] [PubMed] [Google Scholar]
  21. Cicchetti D, Rogosch FA. Psychopathology as risk for adolescent substance use disorders: A developmental psychopathology perspective. Journal of Clinical Child Psychology. 1999;28(3):355–365. doi: 10.1207/S15374424jccp280308. [DOI] [PubMed] [Google Scholar]
  22. Clark DB, Bukstein OG, Smith MG, Kaczynski NA, Mezzich AC, Donovan JE. Identifying anxiety disorders in adolescents hospitalized for alcohol abuse or dependence. Psychiatric Services. 1995;46:618–620. doi: 10.1176/ps.46.6.618. [DOI] [PubMed] [Google Scholar]
  23. Cohen J. A power primer. Psychological Bulletin. 1992;112:155–159. doi: 10.1037//0033-2909.112.1.155. [DOI] [PubMed] [Google Scholar]
  24. Collins D, Cellucci T. Effects of a school-based alcohol education program with a media prevention component. Psychological Reports. 1991;69:191–197. doi: 10.2466/pr0.1991.69.1.191. doi:10.2466/PR0.69.5.191-197. [DOI] [PubMed] [Google Scholar]
  25. Comeau N, Stewart SH, Loba P. The relations of trait anxiety, anxiety sensitivity, and sensation seeking to adolescents' motivations for alcohol, cigarette, and marijuana use. Addictive Behaviors. 2001;26:803–825. doi: 10.1016/s0306-4603(01)00238-6. doi:10.1016/S0306-4603(01)00238-6. [DOI] [PubMed] [Google Scholar]
  26. Conrod PJ, Stewart SH, Comeau N, Maclean AM. Efficacy of cognitive-behavioral interventions targeting personality risk factors for youth alcohol misuse. Journal of Clinical Child & Adolescent Psychology. 2006;35:550–563. doi: 10.1207/s15374424jccp3504_6. doi: 10.1207/s15374424jccp3504_6. [DOI] [PubMed] [Google Scholar]
  27. Cooper ML, Krull JL, Agocha VB, Flanagan ME, Orcutt HK, Jackson M. Motivational pathways to alcohol use and abuse among Black and White adolescents. Journal of Abnormal Psychology. 2008;117:485–501. doi: 10.1037/a0012592. doi: 10.1037/a0012592. [DOI] [PubMed] [Google Scholar]
  28. Cosci F, Knuts IE, Abrams K, Griez EL, Schruers KJ. Cigarette smoking and panic: A critical review of the literature. Journal of Clinical Psychiatry. 2010;71:606–615. doi: 10.4088/JCP.08r04523blu. doi:10.4088/JCP.08r04523blu. [DOI] [PubMed] [Google Scholar]
  29. Craske MG, Poulton R, Tsao JCI, Plotkin D. Paths to panic disorder/agoraphobia: An exploratory analysis from age 3 to 21 in an unselected birth cohort. Journal of the American Academy of Child & Adolescent Psychiatry,X. 2001;40(5):556–563. doi: 10.1097/00004583-200105000-00015. doi: 10.1097/00004583-200105000-00015. [DOI] [PubMed] [Google Scholar]
  30. Cuijpers P. Examining the effects of prevention programs on the incidence of new cases of mental disorders: The lack of statistical power. The American Journal of Psychiatry. 2014;160:1385–1391. doi: 10.1176/appi.ajp.160.8.1385. http://dx.doi.org/10.1176/appi.ajp.160.8.1385 [DOI] [PubMed] [Google Scholar]
  31. Deas D, Riggs P, Langenbucher J, Goldman M, Brown S. Adolescents are not adults: Developmental considerations in alcohol users. Alcoholism: Clinical and Experimental research. 2000;24:232–237. doi:10.1111/j.1530-0277.2000.tb04596.x. [PubMed] [Google Scholar]
  32. Dillon DJ, Gorman JM, Liebowitz MR, Fryer AJ, Klein DF. Measurement of lactate-induced panic and anxiety. Psychiatry Research. 1987;20(2):97–105. doi: 10.1016/0165-1781(87)90002-3. doi: 10.1016/0165-1781(87)90002-3. [DOI] [PubMed] [Google Scholar]
  33. Duka T, Jackson A, Smith DC, Stephens DN. Relationship of components of an alcohol interoceptive stimulus to induction of desire for alcohol in social drinkers. Pharmacology, Biochemistry, and Behavior. 1999;64:301–309. doi: 10.1016/s0091-3057(99)00080-5. doi:10.1016/S0091-3057(99)00080-5. [DOI] [PubMed] [Google Scholar]
  34. Eaton DK, Kann L, Kinchen S, Shanklin S, Flint KH, Hawkins J, Wechsler H. Youth risk behavior surveillance-United States, 2011. Morbidity and mortality weekly report. Surveillance summaries (Washington, DC: 2002) 2012;61(4):1–162. [PubMed] [Google Scholar]
  35. Falk DE, Yi H, Hilton ME. Age of onset and temporal sequencing of lifetime DSM-IV alcohol use disorders relative to comorbid mood and anxiety disorders. Drug and Alcohol Dependence. 2008;94:234–245. doi: 10.1016/j.drugalcdep.2007.11.022. doi:10.1016/j.drugalcdep.2007.11.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured clinical interview for DSM-IV axis I disorders: Research version. Non-patient edition (SCID-I/NP) New York State Psychiatric Institute, Biometrics Research; New York, NY: 2002. [Google Scholar]
  37. Fried R, Grimaldi J. The psychology and physiology of breathing: In behavioral medicine, clinical psychology, and psychiatry. Plenum press; New York: 1993. [Google Scholar]
  38. Fritz CO, Morris PE, Richler JJ. Effect size estimates: Current use, calculations, and interpretation. Journal of Experimental Psychology: General. 2012;141:2–18. doi: 10.1037/a0024338. [DOI] [PubMed] [Google Scholar]
  39. Gardner DM, Kutcher S. Dimenhydrinate abuse among adolescents. Canadian Journal of Psychiatry. 1993;38:113–116. doi: 10.1177/070674379303800208. [DOI] [PubMed] [Google Scholar]
  40. Goodwin RD, Lieb R, Hoefler M, Pfister H, Bittner A, Beesdo K, Wittchen H-U. Panic attack as a risk factor for severe psychopathology. American Journal of Psychiatry. 2004;161:2207–2214. doi: 10.1176/appi.ajp.161.12.2207. doi:10.1176/appi.ajp.161.12.2207. [DOI] [PubMed] [Google Scholar]
  41. Goodwin RD, Gotlib IH. Panic attacks and psycopathology among youth. Acta Psychiatrica Scandinavaca. 2004;109(3):216–221. doi: 10.1046/j.1600-0447.2003.00255.x. doi: 10.1046/j.1600-0447.2003.00255.x. [DOI] [PubMed] [Google Scholar]
  42. Gorka SM, Nelson BD, Shankman SA. Startle response to unpredictable threat in comorbid panic disorder and alcohol dependence. Drug and Alcohol Dependence. 2013;132:216–222. doi: 10.1016/j.drugalcdep.2013.02.003. http://dx.doi.org/10.1016/j.drugalcdep.2013.02.003 doi: [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Grant BF, Moore TC, Shepard J, Kaplan K. Source and Accuracy Statement: Wave 1 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) National Institute on Alcohol Abuse and Alcoholism; Bethesda, MD: 2003. [Google Scholar]
  44. Hawks E, Blumenthal H, Feldner MT, Leen-Feldner E, Jones R. An examination of the relation between traumatic event exposure and panic-relevant biological challenge responding among adolescents. Behavior Therapy. 2011;42(3):427–438. doi: 10.1016/j.beth.2010.11.002. doi: 10.1016/j.beth.2010.11.002. [DOI] [PubMed] [Google Scholar]
  45. Hayward C, Killen JD, Hammer LD, Litt. IF, Wilson DM, Simmonds B, Barr Taylor C. Pubertal stage and panic attack history in sixth- and seventh-grade girls. The American Journal of Psychiatry. 1992;149:1239–1243. doi: 10.1176/ajp.149.9.1239. [DOI] [PubMed] [Google Scholar]
  46. Hayward C, Killen JD, Wilson DM, Hammer LD, Blair-Greiner A, Strachowski D, Taylor CB. School refusal in young adolescent girls with nonclinical panic attacks. Journal of Anxiety Disorders. 1995;9:329–338. doi: 10.1016/s0887-6185(96)00032-1. doi:10.1016/0887-6185(95)00013-E. [DOI] [PubMed] [Google Scholar]
  47. Hayward C, Killen JD, Wilson DM, Litt IF, Kraemer HC, Haydel F, Varady A, Barr Taylor C. Psychiatric risk associated with early puberty in adolescent girls. Journal of the American Academy of Child & Adolescent Psychiatry. 1997;36:255–262. [PubMed] [Google Scholar]
  48. Hayward C, Wilson KA, Lagle K, Killen JD, Taylor CB. Parent-reported predictors of adolescent panic attacks. Journal of the American Academy of Child & Adolescent Psychiatry. 2004;43(5):613–620. doi: 10.1097/00004583-200405000-00015. doi: 10.1097/00004583-200405000-00015. [DOI] [PubMed] [Google Scholar]
  49. Hornsveld H, Garssen B, van Spiegel P. Voluntary hyperventilation: The influence of duration and depth on the development of symptoms. Biological Psychology. 1995;40:299–312. doi: 10.1016/0301-0511(95)05120-y. doi: 10.1016/0301-0511(95)05120-Y. [DOI] [PubMed] [Google Scholar]
  50. Hussong AM, Hicks RE, Levy SA, Curran PJ. Specifying the relations between affect and heavy alcohol use among young adults. Journal of Abnormal Psychology. 2001;110(3):449–461. doi: 10.1037//0021-843x.110.3.449. doi:10.1037//0021-843X.110.3.449. [DOI] [PubMed] [Google Scholar]
  51. Isensee B, Wittchen H, Stein MB, Hofler M, Lieb R. Smoking increases the risk of panic: Findings from a prospective community study. Archives of General Psychiatry. 2003;60:692–700. doi: 10.1001/archpsyc.60.7.692. doi:10.1001/archpsyc.60.7.692. [DOI] [PubMed] [Google Scholar]
  52. Jaffee SR, Price TS. Gene–environment correlations: a review of the evidence and implications for prevention of mental illness. Molecular Psychiatry. 2007;12:432–442. doi: 10.1038/sj.mp.4001950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Johnson JG, Cohen P, Pine DS, Klein DF, Kasen S, Brook JS. Association between cigarette smoking and anxiety disorders during adolescence and early adulthood. Journal of the American Medical Association. 2000;284:2348–2351. doi: 10.1001/jama.284.18.2348. [DOI] [PubMed] [Google Scholar]
  54. Joiner TE, Catanzaro SJ, Laurent J. Tripartite structure of positive and negative affect, depression, and anxiety in child and adolescent psychiatric inpatients. Journal of Abnormal Psychology. 1996;105:401–409. doi: 10.1037//0021-843x.105.3.401. doi:10.1037//0021-843X.105.3.401. [DOI] [PubMed] [Google Scholar]
  55. Kazdin AE. Research design in clinical psychology. 4th Allyn & Bacon; Boston, MA: 2003. [Google Scholar]
  56. Kushner MG, Sher KJ, Beitman BD. The relation between alcohol problems and the anxiety disorders. American Journal of Psychiatry. 1990;147:685–695. doi: 10.1176/ajp.147.6.685. [DOI] [PubMed] [Google Scholar]
  57. Kushner MG, Abrams K, Thuras P, Hanson KL. Individual differences predictive of drinking to manage anxiety among non-problem drinkers with panic disorder. Alcoholism: Clinical and Experimental Research. 2000;24(4):448–458. doi:10.1111/j.1530-0277.2000.tb02011.x. [PubMed] [Google Scholar]
  58. Kushner MG, Mackenzie TB, Fiszdon J, Valentiner DP, Foa E, Anderson N, Wangensteen D. The effects of alcohol consumption on laboratory-induced panic and state anxiety. Archives of General Psychiatry. 1996;53(3):264–270. doi: 10.1001/archpsyc.1996.01830030086013. doi:10.1001/archpsyc.1996.01830030086013. [DOI] [PubMed] [Google Scholar]
  59. Lang PJ, Bradley MM, Cuthbert BN. International affective picture system (IAPS): Technical manual and affective ratings. University of Florida; Gainesville, FL: 1997. [Google Scholar]
  60. Lang PJ, Bradley MM, Cuthbert BN. International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Technical Report A-8. University of Florida; Gainesville, FL: 2008. [Google Scholar]
  61. Leen-Feldner EW, Reardon LE, McKee LG, Feldner MT, Babson KA, Zvolensky MJ. The interactive role of anxiety sensitivity and pubertal status in predicting anxious responding to bodily sensations among adolescents. Journal of Abnormal Child Psychology. 2006;34:799–812. doi: 10.1007/s10802-006-9079-y. doi: 10.1007/s10802-006-9079-y. [DOI] [PubMed] [Google Scholar]
  62. Leen-Feldner EW, Feldner MT, Bernstein A, McCormick JT, Zvolensky MJ. Anxiety sensitivity and anxious responding to bodily sensations: A test among adolescents using a voluntary hyperventilation challenge. Cognitive Therapy and Research. 2005;29:593–609. doi:10.1007/s10608-005-3510-5. [Google Scholar]
  63. Leen-Feldner EW, Reardon LE, Zvolensky MJ. Pubertal status and emotional reactivity to a voluntary hyperventilation challenge predicting panic symptoms and somatic complaints: A laboratory-based multi-informant test. Behavior Modification. 2007;31:8–31. doi: 10.1177/0145445506295058. doi:10.1177/0145445506295058. [DOI] [PubMed] [Google Scholar]
  64. Leen-Feldner EW, Zvolensky MJ, Feldner MT. Behavioral inhibition sensitivity and emotional response suppression: A laboratory test among adolescents in a fear-relevant paradigm. Journal of Clinical Child and Adolescent Psychology. 2004;33:783–791. doi: 10.1207/s15374424jccp3304_13. doi:10.1207/s15374424jccp3304_13. [DOI] [PubMed] [Google Scholar]
  65. Lehman CL, Brown TA, Palfai T, Barlow DH. The effects of alcohol outcome expectancy on a carbon-dioxide challenge in patients with panic disorder. Behavior Therapy. 2002;33:447–463. [Google Scholar]
  66. Love A, James D, Willner P. A comparison of two alcohol craving questionnaires. Addiction. 1998;93:1091–1102. doi: 10.1046/j.1360-0443.1998.937109113.x. doi:10.1046/j.1360-0443.1998.937109113.x. [DOI] [PubMed] [Google Scholar]
  67. MacDonald AB, Baker JM, Stewart SH, Skinner M. Effects of alcohol on the response to hyperventilation of participants high and low in anxiety sensitivity. Alcoholism: Clinical and Experimental Research. 2000;24:1656–1665. [PubMed] [Google Scholar]
  68. Masten AS, Cicchetti D. Developmental cascades. Development and Psychopathology. 2010;22:491–495. doi: 10.1017/S0954579410000222. doi: 10.1017/S0954579410000222. [DOI] [PubMed] [Google Scholar]
  69. Masten AS, Faden VB, Zucker RA, Spear LP. A developmental perspective on underage alcohol use. Alcohol Research & Health. 2009;32:3–15. [PMC free article] [PubMed] [Google Scholar]
  70. Mathew AR, Norton PJ, Zvolensky MJ, Buckner JD, Smits JA. Smoking behavior and alcohol consumption in individuals with panic attacks. Journal of Cognitive Psychotherapy. 2011;25:61–70. doi: 10.1891/0889-8391.25.1.61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Mathyssek CM, Olino TM, Verhulst FC, van Oort FV. Childhood internalizing and externalizing problems predict the onset of clinical panic attacks over adolescence: the TRAILS Study. PloS ONE. 2012;7(12):e51564. doi: 10.1371/journal.pone.0051564. doi:10.1371/journal.pone.0051564. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. McManis MH, Bradley MM, Berg WK, Cuthbert BN, Lang PJ. Emotional reactions in children: Verbal, physiological, and behavioral responses to affective pictures. Psychophysiology. 2001;38:222–231. doi:10.1111/1469-8986.3820222. [PubMed] [Google Scholar]
  73. Moberg DP. The Adolescent Alcohol and Drug Involvement Scale. University of Wisconsin, Center for Health Policy and Program Evaluation; Madison, WI: 2000. [Google Scholar]
  74. Moberg DP, Hahn L. The adolescent drug involvement scale. Journal of Adolescent Chemical Dependency. 1991;2:75–88. doi:10.1080/10678289109512338. [Google Scholar]
  75. Mulligan ME, McKay D. Hyperventilation, anxiety sensitivity, and the expectations for alcohol use: Subjective and physiological reactivity to alcohol cues. Addictive Behaviors. 2001;26:375–383. doi: 10.1016/s0306-4603(00)00113-1. [DOI] [PubMed] [Google Scholar]
  76. Nelson CB, Wittchen H-U. Smoking and nicotine dependence – Results from a sample of 14- to 24-year-olds in Germany. European Addiction Research. 1998;4:42–49. doi: 10.1159/000018929. [DOI] [PubMed] [Google Scholar]
  77. Nisbett R, Ross L. Human Inference: Strategies and Shortcomings of Social Judgment. Prentice Hall; Englewood Cliffs, NJ: 1980. [Google Scholar]
  78. Nixon K, McClain JA. Adolescence as a critical window for developing an alcohol use disorder: Current findings in neuroscience. Current Opinion in Psychiatry. 2010;23:227–232. doi: 10.1097/YCO.0b013e32833864fe. doi: 10.1097/YCO.0b013e32833864fe. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Norton GR, Dorward J, Cox BJ. Factors associated with panic attacks in nonclinical subjects. Behavior Therapy. 1986;17:239–252. [Google Scholar]
  80. Olatunji BO, Leen-Feldner EW, Feldner MT, Forsyth JP. Experimental psychopathology. In: McKay D, editor. Handbook of Research Methods in Abnormal and Clinical Psychology. SAGE; Thousand Oaks, California: 2007. pp. 47–59. [Google Scholar]
  81. Pine DS, Coplan JD, Papp LA, Klein RG, Martinez JM, Kovalenko P, Gorman JM. Ventilatory physiology of children and adolescents with anxiety disorders. Archives of General Psychiatry. 1998;55(2):123–129. doi: 10.1001/archpsyc.55.2.123. doi:10.1001/archpsyc.55.2.123. [DOI] [PubMed] [Google Scholar]
  82. Pine D, Klein RG, Coplan JD, Papp LA, Hoven CW, Martinez J, Gorman JM. Differential carbon dioxide sensitivity in childhood anxiety disorders and nonill comparison group. Archives of General Psychiatry. 2000:960–967. doi: 10.1001/archpsyc.57.10.960. doi:10.1001/archpsyc.57.10.960. [DOI] [PubMed] [Google Scholar]
  83. Rabian B, Embry L, MacIntyre D. Behavioral validation of the childhood anxiety sensitivity index in children. Journal of Clinical Child Psychology. 1999;28(91):105–112. doi: 10.1207/s15374424jccp2801_9. doi:10.1207/s15374424jccp2801_9. [DOI] [PubMed] [Google Scholar]
  84. Rapee RM, Brown TA, Antony MA, Barlow DH. Response to hyperventilation and inhalation of 5.5% carbon dioxide-enriched air across the DSM-III-R anxiety disorders. Journal of Abnormal Psychology. 1992;101:538–552. doi: 10.1037//0021-843x.101.3.538. doi:10.1037//0021-843X.101.3.538. [DOI] [PubMed] [Google Scholar]
  85. Robinson J, Sareen J, Cox BJ, Bolton J. Self-medication of anxiety disorders with alcohol and drugs: Results from a nationally representative sample. Journal of Anxiety Disorders. 2009;23:38–45. doi: 10.1016/j.janxdis.2008.03.013. doi:10.1016/j.janxdis.2008.03.013. [DOI] [PubMed] [Google Scholar]
  86. Schmidt NB, Buckner JD, Keough ME. Anxiety sensitivity as a prospective predictor of alcohol use disorders. Behavior Modification. 2007;31:202–219. doi: 10.1177/0145445506297019. doi:10.1177/0145445506297019. [DOI] [PubMed] [Google Scholar]
  87. Schmidt NB, Zvolensky MJ, Maner JK. Anxiety sensitivity: Prospective prediction of panic attacks and Axis I pathology. Journal of psychiatric research. 2006;40(8):691–699. doi: 10.1016/j.jpsychires.2006.07.009. doi:10.1016/j.jpsychires.2006.07.009. [DOI] [PubMed] [Google Scholar]
  88. Schry AR, Norberg MM, Maddox BB, White SW. Gender Matters: The Relationship between Social Anxiety and Alcohol-Related Consequences. PloS ONE. 2014;9(12):e115361. doi: 10.1371/journal.pone.0115361. doi:10.1371/journal.pone.0115361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Schulze D, Jones BT. Desire for alcohol and outcome expectancies as measures of alcohol cue-reactivity in social drinkers. Addiction. 2000;95:1015–1020. doi: 10.1046/j.1360-0443.2000.95710154.x. doi:10.1046/j.1360-0443.2000.95710154.x. [DOI] [PubMed] [Google Scholar]
  90. Sharkansky EJ, Brief DJ, Peirce JM, Meehan JC, Mannix LM. Substance abuse patients with posttraumatic stress disorder (PTSD): Identifying specific triggers of substance abuse and their associations with PTSD symptoms. Psychology of Addictive Behaviors. 1999;8:89–97. [Google Scholar]
  91. Sobell LC, Kwan E, Sobell MB. Reliability of a drug history questionnaire (DHQ) Addictive Behaviors. 1995;20:233–241. doi: 10.1016/0306-4603(94)00071-9. [DOI] [PubMed] [Google Scholar]
  92. Spinhoven P, Onstein EJ, Sterk PJ, Le Haen-Versteijnen D. The hyperventilation provocation test in panic disorder. Behavior Research and Therapy. 1992;30:453–461. doi: 10.1016/0005-7967(92)90029-g. doi:10.1016/0005-7967(92)90029-G. [DOI] [PubMed] [Google Scholar]
  93. Stewart SH, Conrod PJ. Anxiety and substance use disorders. Springer US: 2008. Anxiety disorder and substance use disorder co-morbidity: Common themes and future directions; pp. 239–257. [Google Scholar]
  94. Stewart SH, Zeitlin SB. Anxiety sensitivity and alcohol use motives. Journal of Anxiety Disorders. 1995;9:229–240. doi:10.1016/0887-6185(95)00004-8. [Google Scholar]
  95. Snyder LB, Nardoff PG. Youth substance use and the media. In: Scheier LM, editor. Handbook of drug use etiology: Theory, methods, and empirical findings. American Psychological Association; Washington DC: 2011. pp. 475–491. [Google Scholar]
  96. Tanner JM. Growth at adolescence. Thomas; Springfield, IL: 1962. [Google Scholar]
  97. Tapert SF, Cheung EH, Brown GG, Frank R, Paulus MP, Schweinsburg AD, Brown SA. Neural response to alcohol stimuli in adolescents with alcohol use disorder. Archives of General Psychiatry. 2003;60:727–735. doi: 10.1001/archpsyc.60.7.727. doi:10.1001/archpsyc.60.7.727. [DOI] [PubMed] [Google Scholar]
  98. U.S. Bureau of the Census American FactFinder fact sheet: Arkansas race and Hispanic or Latino origin 2010. 2010 Retrieved from http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml.
  99. U.S. Bureau of the Census American FactFinder fact sheet: 2008-2012 American Community Survey 5-Year Estimates, Income in the past 12 months. 2012 Retrieved from http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_ 12_5YR_S1901.
  100. Unnewehr S, Schneider S, Margraf J, Jenkins M, Florin I. Exposure to internal and external stimuli: Reactions in children of patients with panic disorder and animal phobia. Journal of Anxiety Disorders. 1996;10:489–508. doi:10.1016/S0887-6185(96)00025-4. [Google Scholar]
  101. Verster JC. The alcohol hangover–a puzzling phenomenon. Alcohol and Alcoholism. 2008;43:124–126. doi: 10.1093/alcalc/agm163. doi:10.1093/alcalc/agm163. [DOI] [PubMed] [Google Scholar]
  102. Windle M, Spear LP, Fuligini AJ, Angold A, Brown JD, Pine D, Dahl RE. Transitions into underage and problem drinking: Developmental processes and mechanisms between 10 and 15 years of age. Pediatrics. 2008;121:S273–S289. doi: 10.1542/peds.2007-2243C. [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Zimmerman P, Wittchen H, Höfler M, Pfister H, Kessler RC, Lieb R. Primary anxiety disorders and the development of subsequent alcohol use disorders: A 4-year community study of adolescents and young adults. Psychological Medicine. 2003;33:1211–1222. doi: 10.1017/s0033291703008158. doi:10.1017/S0033291703008158. [DOI] [PubMed] [Google Scholar]
  104. Zvolensky MJ, Cougle JR, Johnson KA, Bonn-Miller MO, Bernstein A. Marijuana use and panic psychopathology among a representative sample of adults. Experimental and Clinical Psychopharmacology. 2010;18(2):129. doi: 10.1037/a0019022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  105. Zvolensky MJ, Lejuez CW, Stuart GL, Curtin JJ. Experimental psychopathology in psychological science. Review of General Psychology. 2001;5:371–381. doi:10.1037//1089-2680.5.4.371. [Google Scholar]
  106. Zvolensky MJ, Bernstein A, Sachs-Ericsson N, Schmidt NB, Buckner JD, Bonn-Miller MO. Lifetime associations between cannabis, use, abuse, and dependence and panic attacks in a representative sample. Journal of Psychiatric Research. 2006;40:477–486. doi: 10.1016/j.jpsychires.2005.09.005. doi:10.1016/j.jpsychires.2005.09.005. [DOI] [PubMed] [Google Scholar]
  107. Zvolensky MJ, Leen-Feldner EW, Feldner MT, Bonn-Miller MO, Lejuez CW, Kahler CW, Stuart G. Emotional responding to a biological challenge as a function of panic disorder and smoking. Journal of Anxiety Disorders. 2004;18:19–32. doi: 10.1016/j.janxdis.2003.07.004. doi:10.1016/j.janxdis.2003.07.004. [DOI] [PubMed] [Google Scholar]
  108. Zvolensky MJ, Lewinsohn P, Bernstein A, Schmidt NB, Buckner JD, Seeley J, Bonn-Miller MO. Prospective associations between cannabis use, abuse, and dependence and panic attacks and disorder. Journal of psychiatric research. 2008;42:1017–1023. doi: 10.1016/j.jpsychires.2007.10.012. doi:10.1016/j.jpsychires.2007.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  109. Zvolensky MJ, Schmidt NB, McCreary BT. The impact of smoking on panic disorder: An initial investigation of a pathoplastic relationship. Journal of Anxiety Disorders. 2003;17:447–460. doi: 10.1016/s0887-6185(02)00222-0. doi:10.1016/S0887-6185(02)00222-0. [DOI] [PubMed] [Google Scholar]
  110. Zvolensky MJ, Schmidt NB, Stewart SH. Panic disorder and smoking. Clinical Psychology: Science and Practice. 2003;10:29–51. [Google Scholar]

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