Addictive Behaviors 42 (2015) 162–166
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Addictive Behaviors
The role of intolerance of uncertainty in terms of alcohol use motives among college students Kristen M. Kraemer, Alison C. McLeish ⁎, Emily M. O'Bryan Department of Psychology, University of Cincinnati, PO Box 210376 Cincinnati, OH 45221-0376, USA
H I G H L I G H T S • • • •
Alcohol use problems are common among college students. Individuals often drink to cope with worry and to avoid social rejection. Intolerance of uncertainty, a worry-related risk factor, may motivate alcohol use. Greater intolerance of uncertainty predicted greater coping and conformity motives.
a r t i c l e
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Available online 25 November 2014 Keywords: Alcohol Alcohol use motives Coping Intolerance of uncertainty Worry
a b s t r a c t Introduction: Hazardous drinking rates among college students are exceedingly high. Despite the link between worry and alcohol use problems, there has been a dearth of empirical work examining worry-related risk factors in terms of motivations for alcohol use. Therefore, the aim of the present investigation was to examine the unique predictive ability of intolerance of uncertainty in terms of alcohol use motives. Methods: Participants were 389 college students (72.2% female, Mage = 19.92, SD = 3.87, Range = 18–58 years) who completed self-report measures for course credit. Results: As hypothesized, after controlling for the effects of gender, smoking status, marijuana use status, alcohol consumption, negative affect, and anxiety sensitivity, greater levels of intolerance of uncertainty were significantly predictive of greater coping (1.5% unique variance) and conformity (4.7% unique variance) drinking motives, but not social or enhancement drinking motives. Conclusions: These results suggest that intolerance of uncertainty is associated with drinking to manage or avoid negative emotions, and interventions aimed at reducing intolerance of uncertainty may be helpful in reducing problematic alcohol consumption among college students. © 2014 Elsevier Ltd. All rights reserved.
1. Introduction Approximately 44% of college students engage in binge drinking (i.e., consuming at least four to five alcoholic beverages within a two hour period), and 20% of college drinkers experience five or more problems related to alcohol use (Kuo et al., 2002; Wechsler et al., 2002). These alcohol-related problems include increased risk-taking behavior, trouble with police, injuries, academic problems, driving under the influence, and significant negative health effects (e.g., cognitive deficits, liver damage; Hingson, Heeren, Zakocs, Kopstein, & Wechsler, 2002; Wechsler et al., 2002). Despite a growing number of empirically supported interventions to address alcohol use problems among college students, hazardous drinking rates have remained relatively stable over ⁎ Corresponding author. Tel.: +1 513 5565123; fax: +1 513 5564168. E-mail addresses: [email protected] (K.M. Kraemer), [email protected] (A.C. McLeish), [email protected] (E.M. O'Bryan).
http://dx.doi.org/10.1016/j.addbeh.2014.11.033 0306-4603/© 2014 Elsevier Ltd. All rights reserved.
the past several decades (Wechsler et al., 2002). As a result, there is a clear need to better understand the underlying motivations for alcohol use and factors that influence drinking motives among college students. The most widely accepted theories of alcohol use suggest that it can be conceptualized within a social, cognitive, or motivational framework (e.g., Burke & Stephens, 1999; Cooper, Frone, Russell, & Mudar, 1995; Cooper, Russell & George, 1998; Cox & Klinger, 1988; Oei & Baldwin, 1994). Cognitive theories suggest that cognitions, such as the expected consequences of alcohol use, play an important role in the development of drinking behaviors while motivational theories suggest that an individual's motives for alcohol use, particularly related to the regulation of positive and negative emotions, are the most important determinants of alcohol use behaviors (Cooper, Russell & George, 1998; Cox & Klinger, 1988; Oei & Baldwin, 1994). Social theories, particularly social-cognitive theories, propose that drinking behaviors stem from outcome expectancies of use, social influence and self-efficacy expectations (i.e., perceived ability to resist social pressure; Dijkstra, Sweeny & Gebhardt, 2001).
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These theories have resulted in the development of a number of overlapping, yet distinct, constructs related to drinking behaviors (e.g., drinking motives, alcohol expectancies). Drinking motives, largely encompassed within the motivational and social-cognitive models, is one construct that has received considerable attention in the literature. Although conceptually overlapping with alcohol expectancies, research indicates that they are theoretically and empirically distinct constructs (Cooper, 1994). Indeed, research suggests that drinking motives, compared to alcohol expectancies, may be the more proximal factor to alcohol use and that drinking motives mediate the effects of alcohol expectancies on alcohol use (Cooper, 1994; Kuntsche, Knibbe, Engels & Gmel, 2007). One of the most commonly used measures to assess drinking motives, the Drinking Motives Questionnaire (DMQ), conceptualizes drinking motives as falling into four domains: (1) social (i.e., drinking to be sociable or celebrate); (2) enhancement (i.e., drinking to enhance positive emotions); (3) coping (i.e., drinking to reduce or manage negative emotions; and (4) conformity (i.e., drinking in order to fit in with a group); Cooper, 1994). These motives can be grouped into two larger categories: negative reinforcement motives (coping and conformity) and positive reinforcement motives (social and enhancement). Drinking to cope with negative affect is one of the more common alcohol use motives reported by college students and can result in significant negative consequences, such as increased alcohol consumption, more frequent drinking-related problems, higher prevalence of alcohol use disorders, and greater negative affect (Carpenter & Hasin, 1999; Cooper, Frone, Russell, & Mudar, 1995; Park & Levenson, 2002). Conformity motives, or drinking to avoid social rejection or embarrassment, have also been shown to be associated with more alcohol-related problems above and beyond the effects of frequency and quantity of alcohol consumption (Cooper et al., 1995). Given these negative outcomes, identifying factors that influence coping and conformity drinking motives is an important next step in this line of research and may ultimately provide information that would improve the efficacy of prevention and intervention efforts for problem drinking among college students. There is a well-established link between generalized anxiety disorder (GAD) and alcohol use (Grant et al., 2004; Kushner, 2000; Kushner et al., 2005; Regier et al., 1990). Indeed, 15% of individuals with GAD have a comorbid alcohol use disorder, and nearly half of individuals seeking treatment for an alcohol use disorder meet criteria for GAD (Grant et al., 2004; Smith & Book, 2010). Moreover, 20–25% of individuals with GAD and no comorbid alcohol use problem report using alcohol to cope with their GAD symptoms (Bolton, Cox, Clara, & Sareen, 2006; Robinson, Sareen, Cox, & Bolton, 2009). These rates of using alcohol to self-medicate are the highest of the anxiety disorders. While some researchers argue that GAD is a direct result of alcohol use (Kushner, Sher, & Beitman, 1990), recent studies have found that for up to two-thirds of individuals with comorbid GAD and alcohol use disorder, the onset of GAD preceded the onset of the alcohol use disorder (Falk, Yi, & Hilton, 2008; Smith & Book, 2010). Further, those with comorbid alcohol use disorders and GAD endorsed drinking expectancies related to worry reduction (Falk et al., 2008; Smith & Book, 2010). Taken together, these findings suggest that individuals with GAD may be motivated to drink in order to reduce or avoid the arousal related to excessive and chronic worry (Robinson et al., 2009) and point to a need for a better understanding of associations between worry-related factors and drinking motives. One factor that may be important to consider in this regard is intolerance of uncertainty (IU), or the tendency to react negatively to uncertainty because of beliefs that uncertainty is unfair and will result in negative consequences (Dugas, Gosselin, & Ladouceur, 2001). Individuals with high levels of IU find uncertain events and situations stressful or unbearable resulting in heightened levels of worry and worry-related symptomatology (e.g., negative affect, unwanted bodily sensations; Buhr & Dugas, 2006) and a tendency to avoid such situations. IU has been shown to be uniquely associated with the development and maintenance of worry, the defining feature of GAD (Buhr & Dugas, 2006; Ladouceur,
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Gosselin, & Dugas, 2000). Indeed, some researchers suggest that the inability to tolerate uncertainty is one of the main components of excessive worry (Dugas, Gagnon, Ladouceur & Freeston, 1998). Despite the strong link between GAD and alcohol use problems, particularly related to coping with worry (Robinson et al., 2009), there has been a dearth of empirical work examining worry-related risk factors, such as IU, in terms of motivations for alcohol use. Thus, individuals who are unable to tolerate uncertainty may be more motivated to use alcohol as an avoidance strategy aimed at reducing the negative emotions, cognitions (e.g., excessive worry) or bodily sensations (e.g., muscle tension, headaches) that result from uncertainty. Therefore, the aim of the current study was to examine the unique predicative ability of IU in terms of drinking motives among college students. An examination of this association is particularly important among college students given the high rates of problematic drinking (Kuo et al., 2002; Wechsler et al., 2002). Moreover, this developmental period of emerging adulthood is often associated with worry, stress, uncertainty, and is also the time during which psychopathology often begins to emerge (Kessler et al., 2005; Schulenberg, Sameroff & Cicchetti, 2004). It was hypothesized that, after controlling for gender, negative affectivity, smoking status, marijuana use status, alcohol consumption, and anxiety sensitivity, IU would significantly predict coping and conformity drinking motives, but not social or enhancement motives. Coping and conformity motives were selected based on prior work demonstrating associations with other anxiety-related risk factors (e.g., anxiety sensitivity; Howell, Leyro, Hogan, Buckner, & Zvolensky, 2010; Stewart & Zeitlin, 1995). The covariates were selected on an a priori basis due to previously documented associations between each of these factors and alcohol use (Miller & Gold, 1998; Nolen-Hoeksema, 2004; Regier et al., 1990; Stewart & Zeitlin, 1995). In particular, given the strong link between the anxiety-related cognitive risk factor of anxiety sensitivity and drinking motives (Stewart & Zeitlin, 1995), it was important to examine the unique role of intolerance of uncertainty in drinking motives above and beyond this construct. 2. Method 2.1. Participants Participants were 389 undergraduate students in Introductory Psychology courses (72.2% female, Mage = 19.92, SD = 3.87, Range = 18–58 years) who reported having consumed an alcoholic beverage in the past year. In terms of the racial composition of the sample, 85.6% self-identified as Caucasian, 6.4% as African American, 2.3% as Asian, 4.4% as multiracial, and .8% did not specify their race. 3.6% reported Hispanic ethnicity. On average, participants drank 3–4 drinks approximately 2–4 times per month. These rates of alcohol consumption are similar to what has been found in other studies examining anxiety-related risk factors in college student samples (e.g., Howell, Leyro, Hogan, Buckner & Zvolensky, 2010). 7.5% of the sample endorsed being a regular cigarette smoker and 57.1% endorsed current or past marijuana use. 2.2. Measures 2.2.1. Demographic form A general demographic questionnaire was used in order to collect information on participants' gender, race, ethnicity, smoking status, and marijuana use status. 2.2.2. Positive Affect Negative Affect Schedule (PANAS) The PANAS is a mood measure commonly used in psychopathology research (Watson, 2000). It assesses two global dimensions of affect: positive and negative. Only the negative affectivity subscale (PANASNA) was used in the present study. A large body of literature supports
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the validity of the PANAS (Watson, 2000; Watson, Clark, & Tellegen, 1988). Internal consistency for the PANAS-NA in the current study was good (α = .87) 2.2.3. Anxiety Sensitivity Index-3 (ASI-3) The ASI-3 is an 18-item self-report measure that assesses fear of anxiety and anxiety-related sensations (Taylor et al., 2007). Respondents are asked to rate the degree to which each statement applies to them on a 5-point Likert-type scale (0 = very little to 5 = very much). The ASI-3 consists of three subscales: physical concerns (e.g., “It scares me when my heart beats rapidly”), social concerns (e.g., “When I tremble in the presence of others, I fear what people might think of me”), and cognitive concerns (e.g., “When I cannot keep my mind on a task, I worry that I might be going crazy”). The ASI-3 demonstrates excellent psychometric properties in terms of reliability and validity indices (Taylor et al., 2007). Cronbach's alpha for the ASI-3 in the current sample was good (α = .88). 2.2.4. Intolerance of Uncertainty Scale (IUS) The IUS (Freeston, Rhéaume, Letarte, Dugas, & Ladouceur, 1994) is a 27-item self-report measure assessing beliefs about the degree to which uncertainty or unpredictability is acceptable (e.g., “It's unfair not having any guarantees in life”), and leads to frustration or stress (e.g., “The ambiguities in life stress me”) and inaction (e.g., “When I am uncertain, I can't go forward”). Respondents rate the extent to which each of the item statements are characteristic of them on a 5-point Likert-type scale (1 = not at all characteristic of me to 5 = entirely characteristic of me). Psychometric properties of the IUS indicate excellent internal consistency and good test-retest reliability (Buhr & Dugas, 2002). Internal consistency for the IUS in the current sample was excellent (α = .95). 2.2.5. Alcohol Use Disorders Identification Test (AUDIT) The AUDIT is a 10-item self-report measure that is used to identify individuals with alcohol problems (Babor, de la Fuente, Saunders, & Grant, 1992). Respondents rate the extent to which they consume alcohol and the degree to which drinking interferes with functioning. The AUDIT has demonstrated good psychometric properties (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). In the current study, alcohol consumption served as a covariate and was calculated using the frequency and quantity items of the AUDIT (frequency X quantity composite; Stewart et al., 2001). 2.2.6. Drinking Motives Questionnaire-Revised (DMQ-R) The DMQ-R (Cooper, 1994) is a 20-item self-report measure that assesses motives for alcohol use across four domains: social (e.g., “Because it helps you enjoy a party”), enhancement (e.g., “Because you like the feeling”), coping (e.g., “To forget your worries”), and conformity (e.g., “Because your friends pressure you to drink”). Respondents rate the degree to which their own drinking is motivated by each of the statements on a 5-point Likert-type scale from 1 = almost never/never to 5 = almost always/always. High scores on a particular DMQ-R subscale indicate the individual typically attributes their drinking to that motive, and scores are independent of drinking frequency. The DMQ-R has demonstrated excellent psychometric properties in nonclinical samples in terms of construct and criterion-related validity (Cooper, 1994). Internal consistency for each of the four subscales in the current sample was good (range: .85–.89). 2.3. Procedure Undergraduate students from Introductory Psychology courses at a large Midwest university who were over the age of 18 were eligible to participate in the study. A description of the study was provided to students on the subject pool management website, and students interested in participating in a study on college student health emailed the researcher to participate in the study. Those who were eligible were
provided with a link to complete study measures online at their convenience. Study data were collected and managed using REDCap (Research Electronic Data Capture; Harris et al., 2009), a secure, webbased application designed to support data capture for research studies. In order to ensure anonymity, information regarding participants' IP addresses was not collected. After submitting the survey online, participants contacted the researcher via email and were granted course credit for their participation. Research suggests that Internet samples generally do not differ from samples using traditional paper and pencil methods (Gosling, Vazire, Srivastava & Oliver, 2004). The Institutional Review Board approved all study materials and procedures prior to the collection of data.
2.4. Analytic approach The main effect of intolerance of uncertainty for the primary dependent variables was evaluated using a hierarchical multiple regression procedure (Cohen, Cohen, West, & Aiken, 2003). Separate models were constructed for predicting the four drinking motives: social, conformity, enhancement, and coping. In each model, gender, smoking status, marijuana use status, alcohol consumption, negative affectivity, and anxiety sensitivity were entered simultaneously at step one to control for these theoretically relevant factors. At the second step of the model, IU was entered in order to estimate the amount of variance accounted for by this variable.
3. Results Associations between the predictor and criterion variables are presented in Table 1. IU was significantly correlated with negative affectivity (r = .58, p b .01), anxiety sensitivity (r = .52, p b .01), DMQ-R Coping (r = .31, p b .01), and DMQ-R Conformity (r = .30, p b .01). DMQ-R Social and DMQ-R Enhancement were both significantly negatively associated with gender and positively associated with marijuana use status and alcohol consumption. DMQ-R Coping was significantly associated with marijuana use status (r = .17, p b .01), alcohol consumption (r = .33, p b .01), negative affectivity (r = .37, p b .01), and anxiety sensitivity (r = .33, p b .01). DMQ-R Conformity was significantly associated with negative affectivity (r = .18, p b .01) and anxiety sensitivity (r = .21, p b .01). Lastly, all of the drinking motives were significantly associated with one another (range = .11 to .75). Results of the regression analyses are presented in Table 2. In terms of social drinking motives, step one of the model accounted for 24.8% of the variance, and alcohol consumption (β = .47, t = 8.63, p b .01) was the only significant predictor. The second step of the model was not significant. In terms of enhancement drinking motives, step one of the model accounted for 29.8% of unique variance, and marijuana use status (β = .16, t = 3.02, p b .01) and alcohol consumption (β = .48, t = 9.06, p b .01) were the only significant predictors. The second step of the model was not significant. In terms of coping drinking motives, step one of the model accounted for 29.1% of unique variance. Alcohol consumption (β = .30, t = 5.80, p b .01), negative affectivity (β = .28, t = 4.97, p b .01), and anxiety sensitivity (β = .17, t = 3.07, p b .01), were significant predictors at this step. Step two accounted for 1.5% of unique variance, and intolerance of uncertainty (β = .16, t =2.57, p b .05) was a significant predictor. In terms of conformity drinking motives, step one of the model accounted for 7.9% of unique variance. Gender (β = -.13, t = − 2.20, p b .05) and anxiety sensitivity (β = .20, t = 3.15, p b .01) were the only significant predictors at step one. Step two accounted for 4.7% of unique variance and intolerance of uncertainty (β = .28, t = 3.98, p b .01) was a significant predictor.
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Table 1 Descriptive data and intercorrelations among predictor and criterion variables.
1. Gender 2. Smoking Status 3. Marijuana Use 4. Alcohol Consumption 5. PANAS-NA 6. ASI-3 7. IUS 8. DMQR-Social 9. DMQR-Enhance 10. DMQR-Coping 11. DMQR-Conform
1
2
3
4
5
6
7
8
9
10
11
Range
M
SD
– – – – – – – – – – –
.00 – – – – – – – – – –
−.17** .19** – – – – – – – – –
−.27** .04 .28** –
.18** .11* .02 .03 – – – – – – –
.08 .15** .10* .05 .48** – – – – – –
.08 −.06 −.06 .01 .57** .52** – – – – –
−.11* −.02 .21** .47** .06 .06 .06 – – – –
−.13** .00 .29** .49** .07 .02 −.01 .75** – – –
.00 .05 .17** .33** .37** .33** .31** .49** .45** – –
−.07 −.04 .01 −.02 .18** .21** .30** .27** .11* .40** –
– – – 0–20 10–45 0–68 27–131 5–25 5–25 5–25 5–24
– – – 4.99 20.75 14.99 66.53 15.84 14.55 9.95 7.83
– – – 3.71 6.75 10.68 20.32 5.26 5.46 4.41 3.59
* p b .05, ** p b .01. Note: Gender: 1 = male, 2 = female = 2; Smoking Status: 1 = yes, 2 = no; Marijuana Use: lifetime marijuana use, Yes = 1, No = 2; Alcohol Consumption: frequency X quantity; PANAS-NA: Positive and Negative Affect Schedule- Negative Affect subscale (Watson et al., 1988) ASI-3: Anxiety Sensitivity Index-3 (Taylor et al., 2007); IUS: Intolerance of Uncertainty Scale (Freeston et al., 1994); AUDIT: Alcohol Use and Disorders Identification Test (Babor et al., 1992); DMQR-Social: Drinking Motives Questionnaire Revised-Social Motives (Cooper, 1994); DMQR-Enhance: Drinking Motives Questionnaire Revised-Enhancement Motives (Cooper, 1994); DMQR-Coping: Drinking Motives Questionnaire Revised-Coping Motives (Cooper, 1994); DMQR-Conform: Drinking Motives Questionnaire Revised-Conformity Motives (Cooper, 1994).
4. Discussion The goal of the current study was to examine the role of IU in terms of drinking motives among college students. Consistent with prediction, greater levels of IU were associated with coping (1.5% of unique variance) and conformity (4.7% unique variance) drinking
Table 2 Intolerance of uncertainty predicting alcohol Use and drinking motives. ΔR2
t (each predictor)
Criterion Variable: DMQR-Social Step 1 .25 Gender .76 Smoking Status −1.12 Marijuana Use 1.75 Alcohol Consumption 8.63 PANAS-NA .95 ASI −.21 Step 2 .00 IUS .60 Criterion Variable: DMQR-Enhancement Step 1 .30 Gender .08 Smoking Status −1.41 Marijuana Use 3.02 Alcohol Consumption 9.06 PANAS-NA 1.13 ASI −.73 Step 2 .00 IUS −.51 Criterion Variable: DMQR-Coping Step 1 .29 Gender .45 Smoking Status −.46 Marijuana Use 1.73 Alcohol Consumption 5.80 PANAS-NA 4.97 ASI 3.07 Step 2 .02 IUS 2.57 Criterion Variable: DMQR-Conformity Step 1 .08 Gender −2.20 Smoking Status −.32 Marijuana Use .25 Alcohol Consumption −.43 PANAS-NA 1.55 ASI 3.15 Step 2 .05 IUS 3.98
β
sr2
.04 −.06 .09 .47 .06 −.01
.00 .00 .04 .19 .00 .00
.04
.00
.00 −.07 .16 .48 .06 −.04
.00 .00 .02 .20 .00 .00
−.03
.00
.02 −.02 .09 .30 .28 .17
.00 .00 .01 .08 .06 .03
.16
.02
−.13 −.02 .02 −.03 .10 .20
.01 .00 .00 .00 .02 .03
.28
.05
** = p b .01, * = p b .05. Note. β = standardized beta weight; sr 2 = squared semi-partial correlation.
p .00** .45 .25 .08 .00** .34 .84 .55 .55 .00** .94 .16 .00** .00** .26 .47 .61 .61 .00** .65 .65 .09 .00** .00** .00** .01* .01* .00** .03* .75 .80 .67 .12 .00** .00** .00**
motives. These significant effects were above and beyond the variance accounted for by gender, smoking status, marijuana use status, alcohol consumption, negative affectivity, and anxiety sensitivity. These results suggest that individuals who are unable to withstand uncertainty are motivated to drink alcohol as a way to manage or avoid negative emotional states and social rejection. Also consistent with prediction, intolerance of uncertainty was not significantly predictive of social and enhancement drinking motives. Thus, it appears that individuals who are unable to withstand uncertainty are more likely to drink to avoid negative states as opposed to drinking to enhance positive states. Individuals with high IU may use alcohol as a way to cope with or dampen the arousal or negative affectivity related to uncertain events or social situations. These results are consistent with previous work that has demonstrated the relationship between other anxiety-related risk factors (i.e., anxiety sensitivity) and coping and conformity drinking motives (Howell, Leyro, Hogan, Buckner & Zvolensky, 2010; Stewart & Zeitlin, 1995). Moreover, these findings are particularly important given that such negative reinforcement motives are directly linked to higher levels of alcohol use and more drinking-related problems, particularly among college students (Carpenter & Hasin, 1999; Cooper et al., 1995; Park & Levenson, 2002). Although not directly tested in the current study, the findings also point to the possibility that individuals with high IU may are increased risk for developing alcohol-related problems. Though promising, there are several limitations that warrant consideration. First, the sample is relatively homogeneous in terms of gender and race. Further studies are needed to explore the role of IU in alcohol use motives in more diverse college student samples. Second, no assessments for the presence of psychopathology were conducted. Thus, it is unclear what proportion of the current sample met criteria for an anxiety or alcohol use disorder. It will be important for future studies to examine how patterns of associations between IU and drinking motives differ based on alcohol use disorder and anxiety disorder, particularly GAD, diagnostic status. Third, self-report measures were utilized as the primary assessment methodology, which does not fully protect against reporting errors and may be influenced by shared method variance. Thus, future studies could build on the present work by utilizing a multi-method assessment approach to address this concern. For example, it may be beneficial to assess or manipulate IU behaviourally, via an experimental task such as a gambling task that has been used in previous IU research (Ladouceur et al., 2000). Finally, the present crosssectional design does not permit causal-oriented hypothesis testing. Longitudinal studies are needed to better understand how IU impacts drinking motives and drinking behavior, including attempts to cut down or stop drinking, over time.
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4.1. Conclusions The results of this study suggest that IU is associated with drinking to manage or avoid negative affect, which could potentially lead to more problematic drinking behavior. Thus, interventions aimed at reducing IU may be helpful in reducing problematic alcohol consumption among college students who report negative reinforcement drinking motives. Role of funding sources There was no funding for this study. Contributors KMK and ACM designed the study and wrote the protocol, conducted literature searches, and conducted the statistical analyses. EMO collected the data, conducted literature searches and drafted the Method and References sections. KMK and ACM wrote the first draft of the manuscript and EMO provided significant input in re-drafting. All authors contributed to and have approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgment Access to REDCap for data collection was supported by a Center for Clinical and Translational Science and Training Grant (UL1-RR026314) awarded to the University of Cincinnati.
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Contents lists available at ScienceDirect
Addictive Behaviors
The role of intolerance of uncertainty in terms of alcohol use motives among college students Kristen M. Kraemer, Alison C. McLeish ⁎, Emily M. O'Bryan Department of Psychology, University of Cincinnati, PO Box 210376 Cincinnati, OH 45221-0376, USA
H I G H L I G H T S • • • •
Alcohol use problems are common among college students. Individuals often drink to cope with worry and to avoid social rejection. Intolerance of uncertainty, a worry-related risk factor, may motivate alcohol use. Greater intolerance of uncertainty predicted greater coping and conformity motives.
a r t i c l e
i n f o
Available online 25 November 2014 Keywords: Alcohol Alcohol use motives Coping Intolerance of uncertainty Worry
a b s t r a c t Introduction: Hazardous drinking rates among college students are exceedingly high. Despite the link between worry and alcohol use problems, there has been a dearth of empirical work examining worry-related risk factors in terms of motivations for alcohol use. Therefore, the aim of the present investigation was to examine the unique predictive ability of intolerance of uncertainty in terms of alcohol use motives. Methods: Participants were 389 college students (72.2% female, Mage = 19.92, SD = 3.87, Range = 18–58 years) who completed self-report measures for course credit. Results: As hypothesized, after controlling for the effects of gender, smoking status, marijuana use status, alcohol consumption, negative affect, and anxiety sensitivity, greater levels of intolerance of uncertainty were significantly predictive of greater coping (1.5% unique variance) and conformity (4.7% unique variance) drinking motives, but not social or enhancement drinking motives. Conclusions: These results suggest that intolerance of uncertainty is associated with drinking to manage or avoid negative emotions, and interventions aimed at reducing intolerance of uncertainty may be helpful in reducing problematic alcohol consumption among college students. © 2014 Elsevier Ltd. All rights reserved.
1. Introduction Approximately 44% of college students engage in binge drinking (i.e., consuming at least four to five alcoholic beverages within a two hour period), and 20% of college drinkers experience five or more problems related to alcohol use (Kuo et al., 2002; Wechsler et al., 2002). These alcohol-related problems include increased risk-taking behavior, trouble with police, injuries, academic problems, driving under the influence, and significant negative health effects (e.g., cognitive deficits, liver damage; Hingson, Heeren, Zakocs, Kopstein, & Wechsler, 2002; Wechsler et al., 2002). Despite a growing number of empirically supported interventions to address alcohol use problems among college students, hazardous drinking rates have remained relatively stable over ⁎ Corresponding author. Tel.: +1 513 5565123; fax: +1 513 5564168. E-mail addresses: [email protected] (K.M. Kraemer), [email protected] (A.C. McLeish), [email protected] (E.M. O'Bryan).
http://dx.doi.org/10.1016/j.addbeh.2014.11.033 0306-4603/© 2014 Elsevier Ltd. All rights reserved.
the past several decades (Wechsler et al., 2002). As a result, there is a clear need to better understand the underlying motivations for alcohol use and factors that influence drinking motives among college students. The most widely accepted theories of alcohol use suggest that it can be conceptualized within a social, cognitive, or motivational framework (e.g., Burke & Stephens, 1999; Cooper, Frone, Russell, & Mudar, 1995; Cooper, Russell & George, 1998; Cox & Klinger, 1988; Oei & Baldwin, 1994). Cognitive theories suggest that cognitions, such as the expected consequences of alcohol use, play an important role in the development of drinking behaviors while motivational theories suggest that an individual's motives for alcohol use, particularly related to the regulation of positive and negative emotions, are the most important determinants of alcohol use behaviors (Cooper, Russell & George, 1998; Cox & Klinger, 1988; Oei & Baldwin, 1994). Social theories, particularly social-cognitive theories, propose that drinking behaviors stem from outcome expectancies of use, social influence and self-efficacy expectations (i.e., perceived ability to resist social pressure; Dijkstra, Sweeny & Gebhardt, 2001).
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These theories have resulted in the development of a number of overlapping, yet distinct, constructs related to drinking behaviors (e.g., drinking motives, alcohol expectancies). Drinking motives, largely encompassed within the motivational and social-cognitive models, is one construct that has received considerable attention in the literature. Although conceptually overlapping with alcohol expectancies, research indicates that they are theoretically and empirically distinct constructs (Cooper, 1994). Indeed, research suggests that drinking motives, compared to alcohol expectancies, may be the more proximal factor to alcohol use and that drinking motives mediate the effects of alcohol expectancies on alcohol use (Cooper, 1994; Kuntsche, Knibbe, Engels & Gmel, 2007). One of the most commonly used measures to assess drinking motives, the Drinking Motives Questionnaire (DMQ), conceptualizes drinking motives as falling into four domains: (1) social (i.e., drinking to be sociable or celebrate); (2) enhancement (i.e., drinking to enhance positive emotions); (3) coping (i.e., drinking to reduce or manage negative emotions; and (4) conformity (i.e., drinking in order to fit in with a group); Cooper, 1994). These motives can be grouped into two larger categories: negative reinforcement motives (coping and conformity) and positive reinforcement motives (social and enhancement). Drinking to cope with negative affect is one of the more common alcohol use motives reported by college students and can result in significant negative consequences, such as increased alcohol consumption, more frequent drinking-related problems, higher prevalence of alcohol use disorders, and greater negative affect (Carpenter & Hasin, 1999; Cooper, Frone, Russell, & Mudar, 1995; Park & Levenson, 2002). Conformity motives, or drinking to avoid social rejection or embarrassment, have also been shown to be associated with more alcohol-related problems above and beyond the effects of frequency and quantity of alcohol consumption (Cooper et al., 1995). Given these negative outcomes, identifying factors that influence coping and conformity drinking motives is an important next step in this line of research and may ultimately provide information that would improve the efficacy of prevention and intervention efforts for problem drinking among college students. There is a well-established link between generalized anxiety disorder (GAD) and alcohol use (Grant et al., 2004; Kushner, 2000; Kushner et al., 2005; Regier et al., 1990). Indeed, 15% of individuals with GAD have a comorbid alcohol use disorder, and nearly half of individuals seeking treatment for an alcohol use disorder meet criteria for GAD (Grant et al., 2004; Smith & Book, 2010). Moreover, 20–25% of individuals with GAD and no comorbid alcohol use problem report using alcohol to cope with their GAD symptoms (Bolton, Cox, Clara, & Sareen, 2006; Robinson, Sareen, Cox, & Bolton, 2009). These rates of using alcohol to self-medicate are the highest of the anxiety disorders. While some researchers argue that GAD is a direct result of alcohol use (Kushner, Sher, & Beitman, 1990), recent studies have found that for up to two-thirds of individuals with comorbid GAD and alcohol use disorder, the onset of GAD preceded the onset of the alcohol use disorder (Falk, Yi, & Hilton, 2008; Smith & Book, 2010). Further, those with comorbid alcohol use disorders and GAD endorsed drinking expectancies related to worry reduction (Falk et al., 2008; Smith & Book, 2010). Taken together, these findings suggest that individuals with GAD may be motivated to drink in order to reduce or avoid the arousal related to excessive and chronic worry (Robinson et al., 2009) and point to a need for a better understanding of associations between worry-related factors and drinking motives. One factor that may be important to consider in this regard is intolerance of uncertainty (IU), or the tendency to react negatively to uncertainty because of beliefs that uncertainty is unfair and will result in negative consequences (Dugas, Gosselin, & Ladouceur, 2001). Individuals with high levels of IU find uncertain events and situations stressful or unbearable resulting in heightened levels of worry and worry-related symptomatology (e.g., negative affect, unwanted bodily sensations; Buhr & Dugas, 2006) and a tendency to avoid such situations. IU has been shown to be uniquely associated with the development and maintenance of worry, the defining feature of GAD (Buhr & Dugas, 2006; Ladouceur,
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Gosselin, & Dugas, 2000). Indeed, some researchers suggest that the inability to tolerate uncertainty is one of the main components of excessive worry (Dugas, Gagnon, Ladouceur & Freeston, 1998). Despite the strong link between GAD and alcohol use problems, particularly related to coping with worry (Robinson et al., 2009), there has been a dearth of empirical work examining worry-related risk factors, such as IU, in terms of motivations for alcohol use. Thus, individuals who are unable to tolerate uncertainty may be more motivated to use alcohol as an avoidance strategy aimed at reducing the negative emotions, cognitions (e.g., excessive worry) or bodily sensations (e.g., muscle tension, headaches) that result from uncertainty. Therefore, the aim of the current study was to examine the unique predicative ability of IU in terms of drinking motives among college students. An examination of this association is particularly important among college students given the high rates of problematic drinking (Kuo et al., 2002; Wechsler et al., 2002). Moreover, this developmental period of emerging adulthood is often associated with worry, stress, uncertainty, and is also the time during which psychopathology often begins to emerge (Kessler et al., 2005; Schulenberg, Sameroff & Cicchetti, 2004). It was hypothesized that, after controlling for gender, negative affectivity, smoking status, marijuana use status, alcohol consumption, and anxiety sensitivity, IU would significantly predict coping and conformity drinking motives, but not social or enhancement motives. Coping and conformity motives were selected based on prior work demonstrating associations with other anxiety-related risk factors (e.g., anxiety sensitivity; Howell, Leyro, Hogan, Buckner, & Zvolensky, 2010; Stewart & Zeitlin, 1995). The covariates were selected on an a priori basis due to previously documented associations between each of these factors and alcohol use (Miller & Gold, 1998; Nolen-Hoeksema, 2004; Regier et al., 1990; Stewart & Zeitlin, 1995). In particular, given the strong link between the anxiety-related cognitive risk factor of anxiety sensitivity and drinking motives (Stewart & Zeitlin, 1995), it was important to examine the unique role of intolerance of uncertainty in drinking motives above and beyond this construct. 2. Method 2.1. Participants Participants were 389 undergraduate students in Introductory Psychology courses (72.2% female, Mage = 19.92, SD = 3.87, Range = 18–58 years) who reported having consumed an alcoholic beverage in the past year. In terms of the racial composition of the sample, 85.6% self-identified as Caucasian, 6.4% as African American, 2.3% as Asian, 4.4% as multiracial, and .8% did not specify their race. 3.6% reported Hispanic ethnicity. On average, participants drank 3–4 drinks approximately 2–4 times per month. These rates of alcohol consumption are similar to what has been found in other studies examining anxiety-related risk factors in college student samples (e.g., Howell, Leyro, Hogan, Buckner & Zvolensky, 2010). 7.5% of the sample endorsed being a regular cigarette smoker and 57.1% endorsed current or past marijuana use. 2.2. Measures 2.2.1. Demographic form A general demographic questionnaire was used in order to collect information on participants' gender, race, ethnicity, smoking status, and marijuana use status. 2.2.2. Positive Affect Negative Affect Schedule (PANAS) The PANAS is a mood measure commonly used in psychopathology research (Watson, 2000). It assesses two global dimensions of affect: positive and negative. Only the negative affectivity subscale (PANASNA) was used in the present study. A large body of literature supports
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the validity of the PANAS (Watson, 2000; Watson, Clark, & Tellegen, 1988). Internal consistency for the PANAS-NA in the current study was good (α = .87) 2.2.3. Anxiety Sensitivity Index-3 (ASI-3) The ASI-3 is an 18-item self-report measure that assesses fear of anxiety and anxiety-related sensations (Taylor et al., 2007). Respondents are asked to rate the degree to which each statement applies to them on a 5-point Likert-type scale (0 = very little to 5 = very much). The ASI-3 consists of three subscales: physical concerns (e.g., “It scares me when my heart beats rapidly”), social concerns (e.g., “When I tremble in the presence of others, I fear what people might think of me”), and cognitive concerns (e.g., “When I cannot keep my mind on a task, I worry that I might be going crazy”). The ASI-3 demonstrates excellent psychometric properties in terms of reliability and validity indices (Taylor et al., 2007). Cronbach's alpha for the ASI-3 in the current sample was good (α = .88). 2.2.4. Intolerance of Uncertainty Scale (IUS) The IUS (Freeston, Rhéaume, Letarte, Dugas, & Ladouceur, 1994) is a 27-item self-report measure assessing beliefs about the degree to which uncertainty or unpredictability is acceptable (e.g., “It's unfair not having any guarantees in life”), and leads to frustration or stress (e.g., “The ambiguities in life stress me”) and inaction (e.g., “When I am uncertain, I can't go forward”). Respondents rate the extent to which each of the item statements are characteristic of them on a 5-point Likert-type scale (1 = not at all characteristic of me to 5 = entirely characteristic of me). Psychometric properties of the IUS indicate excellent internal consistency and good test-retest reliability (Buhr & Dugas, 2002). Internal consistency for the IUS in the current sample was excellent (α = .95). 2.2.5. Alcohol Use Disorders Identification Test (AUDIT) The AUDIT is a 10-item self-report measure that is used to identify individuals with alcohol problems (Babor, de la Fuente, Saunders, & Grant, 1992). Respondents rate the extent to which they consume alcohol and the degree to which drinking interferes with functioning. The AUDIT has demonstrated good psychometric properties (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). In the current study, alcohol consumption served as a covariate and was calculated using the frequency and quantity items of the AUDIT (frequency X quantity composite; Stewart et al., 2001). 2.2.6. Drinking Motives Questionnaire-Revised (DMQ-R) The DMQ-R (Cooper, 1994) is a 20-item self-report measure that assesses motives for alcohol use across four domains: social (e.g., “Because it helps you enjoy a party”), enhancement (e.g., “Because you like the feeling”), coping (e.g., “To forget your worries”), and conformity (e.g., “Because your friends pressure you to drink”). Respondents rate the degree to which their own drinking is motivated by each of the statements on a 5-point Likert-type scale from 1 = almost never/never to 5 = almost always/always. High scores on a particular DMQ-R subscale indicate the individual typically attributes their drinking to that motive, and scores are independent of drinking frequency. The DMQ-R has demonstrated excellent psychometric properties in nonclinical samples in terms of construct and criterion-related validity (Cooper, 1994). Internal consistency for each of the four subscales in the current sample was good (range: .85–.89). 2.3. Procedure Undergraduate students from Introductory Psychology courses at a large Midwest university who were over the age of 18 were eligible to participate in the study. A description of the study was provided to students on the subject pool management website, and students interested in participating in a study on college student health emailed the researcher to participate in the study. Those who were eligible were
provided with a link to complete study measures online at their convenience. Study data were collected and managed using REDCap (Research Electronic Data Capture; Harris et al., 2009), a secure, webbased application designed to support data capture for research studies. In order to ensure anonymity, information regarding participants' IP addresses was not collected. After submitting the survey online, participants contacted the researcher via email and were granted course credit for their participation. Research suggests that Internet samples generally do not differ from samples using traditional paper and pencil methods (Gosling, Vazire, Srivastava & Oliver, 2004). The Institutional Review Board approved all study materials and procedures prior to the collection of data.
2.4. Analytic approach The main effect of intolerance of uncertainty for the primary dependent variables was evaluated using a hierarchical multiple regression procedure (Cohen, Cohen, West, & Aiken, 2003). Separate models were constructed for predicting the four drinking motives: social, conformity, enhancement, and coping. In each model, gender, smoking status, marijuana use status, alcohol consumption, negative affectivity, and anxiety sensitivity were entered simultaneously at step one to control for these theoretically relevant factors. At the second step of the model, IU was entered in order to estimate the amount of variance accounted for by this variable.
3. Results Associations between the predictor and criterion variables are presented in Table 1. IU was significantly correlated with negative affectivity (r = .58, p b .01), anxiety sensitivity (r = .52, p b .01), DMQ-R Coping (r = .31, p b .01), and DMQ-R Conformity (r = .30, p b .01). DMQ-R Social and DMQ-R Enhancement were both significantly negatively associated with gender and positively associated with marijuana use status and alcohol consumption. DMQ-R Coping was significantly associated with marijuana use status (r = .17, p b .01), alcohol consumption (r = .33, p b .01), negative affectivity (r = .37, p b .01), and anxiety sensitivity (r = .33, p b .01). DMQ-R Conformity was significantly associated with negative affectivity (r = .18, p b .01) and anxiety sensitivity (r = .21, p b .01). Lastly, all of the drinking motives were significantly associated with one another (range = .11 to .75). Results of the regression analyses are presented in Table 2. In terms of social drinking motives, step one of the model accounted for 24.8% of the variance, and alcohol consumption (β = .47, t = 8.63, p b .01) was the only significant predictor. The second step of the model was not significant. In terms of enhancement drinking motives, step one of the model accounted for 29.8% of unique variance, and marijuana use status (β = .16, t = 3.02, p b .01) and alcohol consumption (β = .48, t = 9.06, p b .01) were the only significant predictors. The second step of the model was not significant. In terms of coping drinking motives, step one of the model accounted for 29.1% of unique variance. Alcohol consumption (β = .30, t = 5.80, p b .01), negative affectivity (β = .28, t = 4.97, p b .01), and anxiety sensitivity (β = .17, t = 3.07, p b .01), were significant predictors at this step. Step two accounted for 1.5% of unique variance, and intolerance of uncertainty (β = .16, t =2.57, p b .05) was a significant predictor. In terms of conformity drinking motives, step one of the model accounted for 7.9% of unique variance. Gender (β = -.13, t = − 2.20, p b .05) and anxiety sensitivity (β = .20, t = 3.15, p b .01) were the only significant predictors at step one. Step two accounted for 4.7% of unique variance and intolerance of uncertainty (β = .28, t = 3.98, p b .01) was a significant predictor.
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Table 1 Descriptive data and intercorrelations among predictor and criterion variables.
1. Gender 2. Smoking Status 3. Marijuana Use 4. Alcohol Consumption 5. PANAS-NA 6. ASI-3 7. IUS 8. DMQR-Social 9. DMQR-Enhance 10. DMQR-Coping 11. DMQR-Conform
1
2
3
4
5
6
7
8
9
10
11
Range
M
SD
– – – – – – – – – – –
.00 – – – – – – – – – –
−.17** .19** – – – – – – – – –
−.27** .04 .28** –
.18** .11* .02 .03 – – – – – – –
.08 .15** .10* .05 .48** – – – – – –
.08 −.06 −.06 .01 .57** .52** – – – – –
−.11* −.02 .21** .47** .06 .06 .06 – – – –
−.13** .00 .29** .49** .07 .02 −.01 .75** – – –
.00 .05 .17** .33** .37** .33** .31** .49** .45** – –
−.07 −.04 .01 −.02 .18** .21** .30** .27** .11* .40** –
– – – 0–20 10–45 0–68 27–131 5–25 5–25 5–25 5–24
– – – 4.99 20.75 14.99 66.53 15.84 14.55 9.95 7.83
– – – 3.71 6.75 10.68 20.32 5.26 5.46 4.41 3.59
* p b .05, ** p b .01. Note: Gender: 1 = male, 2 = female = 2; Smoking Status: 1 = yes, 2 = no; Marijuana Use: lifetime marijuana use, Yes = 1, No = 2; Alcohol Consumption: frequency X quantity; PANAS-NA: Positive and Negative Affect Schedule- Negative Affect subscale (Watson et al., 1988) ASI-3: Anxiety Sensitivity Index-3 (Taylor et al., 2007); IUS: Intolerance of Uncertainty Scale (Freeston et al., 1994); AUDIT: Alcohol Use and Disorders Identification Test (Babor et al., 1992); DMQR-Social: Drinking Motives Questionnaire Revised-Social Motives (Cooper, 1994); DMQR-Enhance: Drinking Motives Questionnaire Revised-Enhancement Motives (Cooper, 1994); DMQR-Coping: Drinking Motives Questionnaire Revised-Coping Motives (Cooper, 1994); DMQR-Conform: Drinking Motives Questionnaire Revised-Conformity Motives (Cooper, 1994).
4. Discussion The goal of the current study was to examine the role of IU in terms of drinking motives among college students. Consistent with prediction, greater levels of IU were associated with coping (1.5% of unique variance) and conformity (4.7% unique variance) drinking
Table 2 Intolerance of uncertainty predicting alcohol Use and drinking motives. ΔR2
t (each predictor)
Criterion Variable: DMQR-Social Step 1 .25 Gender .76 Smoking Status −1.12 Marijuana Use 1.75 Alcohol Consumption 8.63 PANAS-NA .95 ASI −.21 Step 2 .00 IUS .60 Criterion Variable: DMQR-Enhancement Step 1 .30 Gender .08 Smoking Status −1.41 Marijuana Use 3.02 Alcohol Consumption 9.06 PANAS-NA 1.13 ASI −.73 Step 2 .00 IUS −.51 Criterion Variable: DMQR-Coping Step 1 .29 Gender .45 Smoking Status −.46 Marijuana Use 1.73 Alcohol Consumption 5.80 PANAS-NA 4.97 ASI 3.07 Step 2 .02 IUS 2.57 Criterion Variable: DMQR-Conformity Step 1 .08 Gender −2.20 Smoking Status −.32 Marijuana Use .25 Alcohol Consumption −.43 PANAS-NA 1.55 ASI 3.15 Step 2 .05 IUS 3.98
β
sr2
.04 −.06 .09 .47 .06 −.01
.00 .00 .04 .19 .00 .00
.04
.00
.00 −.07 .16 .48 .06 −.04
.00 .00 .02 .20 .00 .00
−.03
.00
.02 −.02 .09 .30 .28 .17
.00 .00 .01 .08 .06 .03
.16
.02
−.13 −.02 .02 −.03 .10 .20
.01 .00 .00 .00 .02 .03
.28
.05
** = p b .01, * = p b .05. Note. β = standardized beta weight; sr 2 = squared semi-partial correlation.
p .00** .45 .25 .08 .00** .34 .84 .55 .55 .00** .94 .16 .00** .00** .26 .47 .61 .61 .00** .65 .65 .09 .00** .00** .00** .01* .01* .00** .03* .75 .80 .67 .12 .00** .00** .00**
motives. These significant effects were above and beyond the variance accounted for by gender, smoking status, marijuana use status, alcohol consumption, negative affectivity, and anxiety sensitivity. These results suggest that individuals who are unable to withstand uncertainty are motivated to drink alcohol as a way to manage or avoid negative emotional states and social rejection. Also consistent with prediction, intolerance of uncertainty was not significantly predictive of social and enhancement drinking motives. Thus, it appears that individuals who are unable to withstand uncertainty are more likely to drink to avoid negative states as opposed to drinking to enhance positive states. Individuals with high IU may use alcohol as a way to cope with or dampen the arousal or negative affectivity related to uncertain events or social situations. These results are consistent with previous work that has demonstrated the relationship between other anxiety-related risk factors (i.e., anxiety sensitivity) and coping and conformity drinking motives (Howell, Leyro, Hogan, Buckner & Zvolensky, 2010; Stewart & Zeitlin, 1995). Moreover, these findings are particularly important given that such negative reinforcement motives are directly linked to higher levels of alcohol use and more drinking-related problems, particularly among college students (Carpenter & Hasin, 1999; Cooper et al., 1995; Park & Levenson, 2002). Although not directly tested in the current study, the findings also point to the possibility that individuals with high IU may are increased risk for developing alcohol-related problems. Though promising, there are several limitations that warrant consideration. First, the sample is relatively homogeneous in terms of gender and race. Further studies are needed to explore the role of IU in alcohol use motives in more diverse college student samples. Second, no assessments for the presence of psychopathology were conducted. Thus, it is unclear what proportion of the current sample met criteria for an anxiety or alcohol use disorder. It will be important for future studies to examine how patterns of associations between IU and drinking motives differ based on alcohol use disorder and anxiety disorder, particularly GAD, diagnostic status. Third, self-report measures were utilized as the primary assessment methodology, which does not fully protect against reporting errors and may be influenced by shared method variance. Thus, future studies could build on the present work by utilizing a multi-method assessment approach to address this concern. For example, it may be beneficial to assess or manipulate IU behaviourally, via an experimental task such as a gambling task that has been used in previous IU research (Ladouceur et al., 2000). Finally, the present crosssectional design does not permit causal-oriented hypothesis testing. Longitudinal studies are needed to better understand how IU impacts drinking motives and drinking behavior, including attempts to cut down or stop drinking, over time.
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4.1. Conclusions The results of this study suggest that IU is associated with drinking to manage or avoid negative affect, which could potentially lead to more problematic drinking behavior. Thus, interventions aimed at reducing IU may be helpful in reducing problematic alcohol consumption among college students who report negative reinforcement drinking motives. Role of funding sources There was no funding for this study. Contributors KMK and ACM designed the study and wrote the protocol, conducted literature searches, and conducted the statistical analyses. EMO collected the data, conducted literature searches and drafted the Method and References sections. KMK and ACM wrote the first draft of the manuscript and EMO provided significant input in re-drafting. All authors contributed to and have approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgment Access to REDCap for data collection was supported by a Center for Clinical and Translational Science and Training Grant (UL1-RR026314) awarded to the University of Cincinnati.
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