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Substance Use Behaviors among College Students in the Food Service Industry

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Title: Substance Use Behaviors among College Students in the Food Service Industry
Language: English
Authors: Margaret Caruso (ORCID 0000-0003-4823-8467), Dennis Hoyer (ORCID 0000-0003-2548-7874), Lauren Clinton, Christopher J. Correia
Source: Journal of American College Health. 2024 72(8):2520-2527.
Availability: Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 8
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Food Service, Undergraduate Students, Employment Level, Substance Abuse, Coping, Drinking, Drug Abuse, Predictor Variables, Marijuana, At Risk Persons, Mental Health, Stress Management, Student Behavior
Assessment and Survey Identifiers: Positive and Negative Affect Schedule
DOI: 10.1080/07448481.2022.2119396
ISSN: 0744-8481
1940-3208
Abstract: Objective: Food service employment is associated with substance use, risk of substance use disorders and various negative consequences. Previous research has not examined the substance use patterns of students employed in food service positions. Method: During Fall of 2018, 276 undergraduates completed an anonymous online survey regarding current employment status and substance use. Results: Compared to students employed in other positions, students in food service positions reported higher levels of drinking to cope with negative affect, negative urgency, workplace substance use, marijuana use, marijuana-related problems, and motives. Food service employment was also a significant predictor of marijuana use and related consequences. Conclusions: Students in food service positions, relative to other employment positions, report elevated substance use behavior, risk factors, and negative consequences. Food service employment also contributed variance to models accounting for marijuana use and related consequences. Prevention and intervention strategies should be investigated to mitigate risk for this population.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1448273
Database: ERIC
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  Value: <anid>AN0180828323;acl01nov.24;2024Nov14.03:52;v2.2.500</anid> <title id="AN0180828323-1">Substance use behaviors among college students in the food service industry </title> <p>Objective: Food service employment is associated with substance use, risk of substance use disorders and various negative consequences. Previous research has not examined the substance use patterns of students employed in food service positions. Method: During Fall of 2018, 276 undergraduates completed an anonymous online survey regarding current employment status and substance use. Results: Compared to students employed in other positions, students in food service positions reported higher levels of drinking to cope with negative affect, negative urgency, workplace substance use, marijuana use, marijuana-related problems, and motives. Food service employment was also a significant predictor of marijuana use and related consequences. Conclusions: Students in food service positions, relative to other employment positions, report elevated substance use behavior, risk factors, and negative consequences. Food service employment also contributed variance to models accounting for marijuana use and related consequences. Prevention and intervention strategies should be investigated to mitigate risk for this population.</p> <p>Keywords: Alcohol; college students; employment; mental health; other drugs</p> <hd id="AN0180828323-2">Introduction</hd> <p></p> <hd id="AN0180828323-3">College student employment</hd> <p>Current college students pay the highest cost of attendance in history, and projections suggest that such costs will continue to rise.[<reflink idref="bib1" id="ref1">1</reflink>] In combination with financial aid and family support, students often finance their education and related expenses through part- or full-time employment. The National Center for Education Statistics reported that during 2017, 81% of part-time and 43% of full-time undergraduate students were employed.[<reflink idref="bib2" id="ref2">2</reflink>] Several studies have documented the potential health and academic risks of employment among college students.[[<reflink idref="bib3" id="ref3">3</reflink>]] Regarding substance use, employment in general—and more specifically, increased hours working and earning—has been associated with increased use of alcohol, marijuana, and cigarettes.[[<reflink idref="bib5" id="ref4">5</reflink>], [<reflink idref="bib7" id="ref5">7</reflink>]] While employment may be a financial necessity for many, more research is needed to determine the risk factors and needs of employed students.</p> <hd id="AN0180828323-4">Employment in food service and substance use patterns</hd> <p>Food service workers represent a disproportionate number of heavy substance users and endorse one of the highest drinking rates of any occupation.[[<reflink idref="bib8" id="ref6">8</reflink>], [<reflink idref="bib10" id="ref7">10</reflink>]] More specifically, food service workers are more likely to engage in work-related substance use, report an increased frequency and variety of substances used, and experience negative alcohol and substance-related consequences.[<reflink idref="bib11" id="ref8">11</reflink>] For example, research has observed hazardous drinking patterns in more than 40% of sampled food service workers,[<reflink idref="bib12" id="ref9">12</reflink>] frequent heavy or binge drinking,[<reflink idref="bib13" id="ref10">13</reflink>] increased illicit substance use,[<reflink idref="bib8" id="ref11">8</reflink>],[<reflink idref="bib14" id="ref12">14</reflink>] and impairment while working and subsequent workplace problems.[<reflink idref="bib8" id="ref13">8</reflink>],[<reflink idref="bib15" id="ref14">15</reflink>] Additionally, food service workers experience heightened mortality rates directly related to substance-induced accidents,[<reflink idref="bib16" id="ref15">16</reflink>] cirrhosis of the liver,[<reflink idref="bib17" id="ref16">17</reflink>] and general alcohol-induced liver disease.[<reflink idref="bib18" id="ref17">18</reflink>]</p> <p>A number of practical and theoretical explanations for the increased risks associated with substance use among food service workers have been offered. One may be the age of individuals who tend to fill these positions. The Bureau of Labor Statistics reported that employees in the food and drink services industry have the second youngest median age (i.e., 28.8 years old) compared to all U.S workers in other industries ages 16 and older.[<reflink idref="bib19" id="ref18">19</reflink>] Furthermore, a quarter of employed students between the ages 16 and 29 hold food and personal services positions.[<reflink idref="bib20" id="ref19">20</reflink>] In a national sample of employed adults, Frone observed that food service employees between the ages of 18–30 more frequently endorsed using illicit substances in general, as well as substance-related impairment in the workplace, than their older counterparts.[<reflink idref="bib9" id="ref20">9</reflink>]</p> <p>The reported observations of substance use among teenagers and young adults in food service positions line up with a more general pattern, namely that regardless of occupational or educational status, young adults and college aged individual are at increased risk for substance misuse and related impairment. More specifically college aged individuals consistently exhibit the highest "past month" binge drinking and use of marijuana when compared to others from all other age groups.[<reflink idref="bib21" id="ref21">21</reflink>] However, there is limited research specifically exploring the substance use behavior of college students employed in the food service industry.</p> <p>Beyond the potential age-related explanation for the links between employment in food service positions and substance use, there are more theoretical models involving stress and coping that could contribute to our understanding of these elevated risks. For example, tension reduction theory postulates that substance use attenuates negative emotional states such as fear, anxiety, and stress.[[<reflink idref="bib22" id="ref22">22</reflink>], [<reflink idref="bib24" id="ref23">24</reflink>]] The short-term reductions in these aversive emotional states that substance use can provide serves to reinforce such use. Over time, this reinforcement effect leads to the development of an individual's beliefs and expectations about the role substance use plays in emotion regulation.[<reflink idref="bib25" id="ref24">25</reflink>] In turn, this gives rise to situation-specific motives that most proximally inform decisions regarding engagement in substance use behavior.[<reflink idref="bib26" id="ref25">26</reflink>]</p> <p>Research has directly linked job-related stress to substance use among employees and suggested that that working in restaurants and other food service positions can be particularly stressful.[[<reflink idref="bib27" id="ref26">27</reflink>], [<reflink idref="bib29" id="ref27">29</reflink>]] One study using a diverse sample of college students suggests that substance use may be used to ameliorate aversive psychological states specifically associated with work.[<reflink idref="bib7" id="ref28">7</reflink>] Finally, using substances to cope with negative emotions and experiences,[<reflink idref="bib31" id="ref29">31</reflink>] along with a number of other factors (e.g., certain demographics,[<reflink idref="bib32" id="ref30">32</reflink>],[<reflink idref="bib33" id="ref31">33</reflink>] Greek affiliation,[<reflink idref="bib34" id="ref32">34</reflink>] higher levels of negative affect or impulsivity,[<reflink idref="bib35" id="ref33">35</reflink>] lower levels of distress tolerance)[<reflink idref="bib36" id="ref34">36</reflink>], has been specifically linked to increased risk of elevated substance use and related negative consequences among college students. Therefore, food service workers who are in college may be vulnerable to work-related stress and may be at risk for misusing substances in an attempt to cope with the resulting emotional states.</p> <hd id="AN0180828323-5">Current study</hd> <p>The current exploratory study was designed to compare students employed in food service positions to those employed in other positions across a range of variables related to substance use consumption, negative consequences, and risk factors. Though previous studies have looked at these behaviors in samples with a range of ages, none have focused specifically on college students. In addition, whereas most studies have used single or a limited number of items to assess substance use behaviors, ours is the first to employ a large battery of psychometrically sound measures. Given the aforementioned tension reduction and motivational theories that inform this area of research, our battery includes measures that assess use of substances to cope with negative affect, along with other known psychologically-oriented risk factors such as impulsivity and distress tolerance. We hypothesized that students employed in food service positions (relative to those working in other types of positions) would report elevated use of alcohol and marijuana and related negative consequences, and that employment in food service position would add incremental validity to predictions of substance use after accounting for other demographic variables. We also hypothesized that students in food service positions (relative to those in other types of positions) would show elevations in the use of substances to cope with negative emotional states and other related psychological risk factors.</p> <hd id="AN0180828323-6">Method</hd> <p></p> <hd id="AN0180828323-7">Participants</hd> <p>Participants were college students at a large, public, Southeastern university located in a city, who were at least 18 years old and reported current part-time or full-time employment. The original sample of responders included 1,012 individuals, all of whom received 1 hour of extra credit in undergraduate psychology courses. After removing 736 participants who reported that they were not currently working, the final sample consisted of 276 currently employed (full or part-time) college students. The majority (65%) reported working less than 15 hours per week, with some working between 15 and 34 (30%) or at least 35 (5%). The largest proportion of the sample reported working in the food preparation and service industry (20.3%), followed by sales (18.5%), educational instruction and library (12.3%), community and social service (10.1%,) office and administrative support (10.1%). management (8.3%), personal care and service (8.3%), life, physical, and social science (8%), and arts, design, entertainment, sports, and media (7.6%). Of the remaining 14 occupation classifications, 12 were endorsed by between 4.7% and 0.4% of the sample, and 2 (architecture and engineering, construction and extraction) were not endorsed by any participants. The sample was comprised of primarily female (<emph>n</emph> = 217, 78.6%) Caucasian (<emph>n</emph> = 247, 89.5%) students, but also consisted of students who identified as African American (10.1%), Asian (4.0%), and American Indian or Alaska Native (1.1%) (percentages add up to greater than 100% of participants could select multiple options); 4.7% of the sample reported their ethnicity as Hispanic or Latino. A significant minority of students reported being members of a Greek sorority or fraternity (<emph>n</emph> = 109, 39.5%)</p> <hd id="AN0180828323-8">Measures</hd> <p></p> <hd id="AN0180828323-9">General information questionnaire</hd> <p>This measure assessed basic demographic information. Variables included age, gender, current year in college, participation in Greek life, race, ethnicity, and current residence status (i.e., on-campus or off-campus).</p> <hd id="AN0180828323-10">Employment survey</hd> <p>The employment survey included questions regarding current employment status and workplace substance-related outcomes. Items assessed the amount in which individuals work (i.e., "not currently working," "less than 15 hours per week," "15–34 hours per week," "35 or more hours per week") based on classifications provided by the United States Bureau of Labor Statistics[<reflink idref="bib37" id="ref35">37</reflink>]; current employment (yes or no) across 23 occupation classifications, as drawn from the United States Census (e.g., management occupations, food preparation and service occupations); and four items (yes or no) related to substance use in the workplace and at school (e.g., "consumed alcohol while at work," "attended work while high, intoxicated, or hung over").</p> <hd id="AN0180828323-11">Alcohol and marijuana consumption</hd> <p>To assess for use in the past 28 days, two separate questions asked participants to indicate the number of days within the past month that they used alcohol and marijuana. The Daily Drinking Questionnaire (DDQ) was also used to assess alcohol consumption over the past 28 days[<reflink idref="bib38" id="ref36">38</reflink>]; the DDQ presents participants with a grid representing the days of the week (i.e., Monday through Sunday, and then asks them to enter the number of standard drinks consumed drinking during each day of the week for a typical week. A total score representing total standard drinks consumed during a typical week was computed for each participant.</p> <hd id="AN0180828323-12">Alcohol use disorder identification test (AUDIT)</hd> <p>The AUDIT is a 10-item multiple choice questionnaire that is used to identify risk for alcohol-related problems.[<reflink idref="bib39" id="ref37">39</reflink>] Questions assessed for drinking behaviors (e.g., "How often do you have a drink containing alcohol?") and outcomes (e.g., "How often during the last year have you had a feeling of guilt or remorse after drinking?") that have been linked to problematic alcohol use. Items are scored on a Likert scale from 0 to 4, resulting in a maximum possible score of 40, with higher scores representing higher risk for problematic use. A high level of internal consistency was observed within our sample (α =.83).</p> <hd id="AN0180828323-13">Problem measures</hd> <p>The Rutgers Alcohol Problem Index (RAPI) is a 23-item scale used to assess for the frequency in which individuals experience problematic outcomes due to alcohol use.[<reflink idref="bib40" id="ref38">40</reflink>] Similarly, the Marijuana Problem Index (MPI) includes 23 items adapted from the RAPI, with the substitution of marijuana-specific language in place of alcohol-specific language.[<reflink idref="bib41" id="ref39">41</reflink>] The original version of the RAPI measures outcomes within the past year, but to gather consistent information on past month alcohol and marijuana use, the scales were adapted to assess problems within the past 28 days. Outcomes were measured on a scale from 0 to 4 (i.e., none, 1–2 times, 3–5 times, 6–10 times, 10 or more time), resulting in maximum possible scores of 92. Outcomes assessed in the RAPI and MPI include "Not able to do your homework or study for a test" and "Felt you had a problem with alcohol/marijuana." Responses on the RAPI and MPI yielded high levels of internal consistency in the current sample (α =.93 and.86, respectively).</p> <hd id="AN0180828323-14">Motives</hd> <p>Drinking motives were assessed using the Drinking Motives Questionnaire – Revised (DMQ-R),[<reflink idref="bib42" id="ref40">42</reflink>] a 20-item measure that assesses the frequency in which individuals drink for 4 specific motives. Self-report items are scored on a Likert scale from 1 ("Almost never/never") to 5 ("Almost always/always"), with items corresponding to coping (e.g., "to forget your worries"), enhancement (e.g., "because you like the feeling"), social (e.g., "because it helps you enjoy a party"), and conformity (e.g., "so you won't feel left out") motives. Marijuana motives were assessed with the Marijuana Motives Measure (MMM).[<reflink idref="bib43" id="ref41">43</reflink>] Items on the MMM include the 20 items from the DMQ-R that have been adapted for marijuana use, with an additional 5 items that assess for expansion motives, which refers to using for the purpose of increasing creativity and openness to experiences (e.g., "to understand things differently"). Adequate levels of internal consistency were identified for each of the four drinking motives subscales (α's ≥.82) and each of the five marijuana motives subscales (α's ≥.73) among our sample.</p> <hd id="AN0180828323-15">Distress tolerance scale (DTS)</hd> <p>Distress tolerance abilities were measured with the DTS,[<reflink idref="bib44" id="ref42">44</reflink>] a 15-item self-report measure. Statements such as "I can't handle feeling distressed or upset" and "When I feel distressed or upset, all I can think about is how bad I feel" are rated on a 5-point Likert scale, with a score of 1 representing "Strongly agree" and a score of 5 representing "Strongly disagree." A composite score of all 15 items is often used to measure overall distress tolerance abilities in research settings and was also used in this study; a high degree of internal consistency (α =.93) was found within our sample.[<reflink idref="bib45" id="ref43">45</reflink>]</p> <hd id="AN0180828323-16">UPPS-P impulsive behavior scale</hd> <p>The UPPS-P Impulsive Behavior Scale is a 59 item self-report measure used to assess the degree to which individuals endorse trait-like impulsivity facets of negative urgency (12 items, "I have trouble controlling my impulses"), lack of premeditation (11 times, "My thinking is usually careful and purposeful"), lack of perseverance (10 items, "I tend to give up easily"), sensation seeking (12 items, "I'll try anything once"), and positive urgency (14 items, "I tend to lose control when I am in a good mood").[<reflink idref="bib46" id="ref44">46</reflink>] Statements related to the five impulsivity factors are rated on a scale from 1 ("Agree strongly") to 4 ("Disagree strongly"). Several items are reverse scored, and all scales are scored such that higher scores indicate more impulsive behavior. Each of the scales yielded high levels of internal consistency (α's ≥.83) in the current sample.</p> <hd id="AN0180828323-17">Positive and negative affect scale</hd> <p>The PANAS consists of two 10-item scales, one measuring positive affect and the other measuring negative affect.[<reflink idref="bib47" id="ref45">47</reflink>] Each item consists of a single word describing of a positive ("Excited," "Proud") or negative ("Upset," "Guilty") emotions. Items are scored on a 5-point Likert scale ranging from 1 ("Very little or not at all") to 5 ("Extremely"), and both the positive and negative scales scores range from 10 to 50. Both the positive (α =.91) and negative (.89) scales yielded high levels of internal consistency in the current sample).</p> <hd id="AN0180828323-18">Procedure</hd> <p>Prior to data collection, the study protocol was approved by the university's Institutional Review Board (IRB). Participants were then recruited through the psychology department's Web-based psychological research program, and all data were collected during the fall 2018 semester. Informed consent was provided to all participants prior to administration of the anonymous online survey.</p> <hd id="AN0180828323-19">Data analysis</hd> <p>Series of independent t-tests, chi-square tests of independence, and regression analyses tested for risk factors associated with working in food service industry. Specifically, independent t-tests assessed differences between food service workers and other workers in drinking frequency and quantity, substance-related problems (i.e., RAPI and MPI scores), risk for problematic alcohol use (i.e., AUDIT scores), motives for use (i.e., DMQ and MMM scores), and impulsivity facets (i.e., UPPS-P scores). All t-tests and associated statistics were reported after first taking Levine's test for equality of variances into account. Chi-square tests of independence assessed for differences between food service workers and other workers in the endorsement of work-related substance use concerns (e.g., using illicit drugs, drinking alcohol while working). Hierarchical linear regression analyses tested for the statistical influence of job category (food service worker vs. all other occupations), quantified as an increase in variance accounted for, and a statistically significant coefficient, on marijuana use frequency and use-related problems. To control for variables typically linked to increased substance use, dummy coded variables to account gender (male = 0, female = 1), ethnicity (non-Caucasian = 0, Caucasian = 1) and Greek affiliation (no = 1, yes = 1) were included in the first step of each model, followed by the addition of job category in the second step.</p> <hd id="AN0180828323-20">Results</hd> <p></p> <hd id="AN0180828323-21">Employment</hd> <p>For the purpose of the current study, the sample was divided into those who reported working in the food service industry (<emph>n</emph> = 56) and those in other occupations (<emph>n</emph> = 226). Students in food service positions did not significantly differ from other students in terms of average age, gender, racial background, or membership in a campus Greek organization.</p> <hd id="AN0180828323-22">Substance use behavior</hd> <p>Students in food service positions were compared to those in other occupations across a number of variables related to alcohol and marijuana use, workplace behavior, and use-related risk factors of substance use. These results are depicted in Tables 1 and 2. The groups reported similar levels of alcohol consumption over the past 28 days and negative consequences on the AUDIT and RAPI. Food service workers reported higher levels of drinking to cope with negative affect (<emph>t</emph> = 2.28, <emph>p</emph> <.05; <emph>d</emph> =. 37). Observed differences on AUDIT scores and enhancement motives failed to reach statistical significance but were associated with small effects sizes (i.e., Cohen's D above.20). Food service workers reported higher levels of marijuana consumption over the past 28 days at a level that approached statistical significance (<emph>t</emph> = 2.08, <emph>p</emph> <. 10; <emph>d</emph> =.32). Food service workers reported higher levels of negative consequences on the MPI (<emph>t</emph> = 2.24, <emph>p</emph> <. 05; <emph>d</emph> =.50), and greater endorsement of coping (<emph>t</emph> = 2.10, <emph>p</emph> <. 05; <emph>d</emph> =.42), enhancement (<emph>t</emph> = 2.54, <emph>p</emph> <. 05; <emph>d</emph> =.44), and expansion (<emph>t</emph> = 2.50, <emph>p</emph> <.05; <emph>d</emph> =.49) motives Regarding workplace behavior, food service workers were also more likely to report using illicit drugs (<emph>X<sups>2</sups></emph>= 16.68, <emph>p</emph> <.001; φ =.30) and alcohol (<emph>X<sups>2</sups></emph>=7.15, <emph>p</emph> <.01; φ =.25) while working (Table 2). Although not statistically significant, the small effect size suggests a weak relationship between being a food service work and the likelihood of attending work while intoxicated, high, or hung over (<emph>p</emph> =. 16; φ =.21).</p> <p>Table 1. Summary of substance use and risk factor variables.</p> <p> <ephtml> <table><thead><tr><td /><td>Full sample (N = 276)</td><td>Food service (n = 56)</td><td>Other occupation (n = 220)</td><td><italic>p</italic></td><td><italic>d</italic></td></tr></thead><tbody valign="top"><tr><td>Alcohol use</td><td /><td /><td /><td /><td /></tr><tr><td>Recent use days</td><td char=".">4.52 (4.67)</td><td char=".">4.70 (4.70)</td><td char=".">4.47 (4.67)</td><td char=".">.75</td><td char=".">.05</td></tr><tr><td>Drinks per week</td><td char=".">5.61 (6.84)</td><td char=".">6.21 (7.84)</td><td char=".">5.45 (6.56)</td><td char=".">.46</td><td char=".">.11</td></tr><tr><td>AUDIT</td><td char=".">5.73 (5.10)</td><td char=".">6.79 (5.76)</td><td char=".">5.46 (4.90)</td><td char=".">.08</td><td char=".">.26</td></tr><tr><td>RAPI</td><td char=".">3.07 (6.18)</td><td char=".">3.79 (6.20)</td><td char=".">2.90 (6.18)</td><td char=".">.35</td><td char=".">.14</td></tr><tr><td>Social motives</td><td char=".">12.11 (5.85)</td><td char=".">12.95 (6.14)</td><td char=".">11.89 (5.77)</td><td char=".">.23</td><td char=".">.18</td></tr><tr><td>Enhancement motives</td><td char=".">10.28 (4.91)</td><td char=".">11.18 (5.23)</td><td char=".">10.05 (4.82)</td><td char=".">.13</td><td char=".">.23</td></tr><tr><td>Coping motives</td><td char=".">7.70 (3.68)</td><td char=".">8.84 (4.37)</td><td char=".">7.41 (3.44)</td><td char=".">.03</td><td char=".">.37</td></tr><tr><td>Conformity motives</td><td char=".">6.31 (2.59)</td><td char=".">6.29 (2.36)</td><td char=".">6.31 (2.64)</td><td char=".">.93</td><td char=".">.01</td></tr><tr><td>Marijuana use</td><td /><td /><td /><td /><td /></tr><tr><td>Recent use days</td><td char=".">2.20 (6.50)</td><td char=".">3.86 (8.65)</td><td char=".">1.77 (5.78)</td><td char=".">.09</td><td char=".">.32</td></tr><tr><td>MPI</td><td char=".">1.15 (3.66)</td><td char=".">2.59 (5.87)</td><td char=".">0.78 (2.74)</td><td char=".">.03</td><td char=".">.50</td></tr><tr><td>Social motives</td><td char=".">6.07 (2.95)</td><td char=".">6.66 (3.31)</td><td char=".">5.92 (2.83)</td><td char=".">.13</td><td char=".">.25</td></tr><tr><td>Enhancement motives</td><td char=".">7.87 (5.83)</td><td char=".">9.89 (6.97)</td><td char=".">7.35 (5.39)</td><td char=".">.01</td><td char=".">.44</td></tr><tr><td>Coping motives</td><td char=".">6.18 (3.27)</td><td char=".">7.27 (4.72)</td><td char=".">5.91 (2.73)</td><td char=".">.04</td><td char=".">.42</td></tr><tr><td>Conformity motives</td><td char=".">5.26 (1.12)</td><td char=".">5.27 (0.82)</td><td char=".">5.25 (1.19)</td><td char=".">.94</td><td char=".">.01</td></tr><tr><td>Expansion motives</td><td char=".">6.48 (4.03)</td><td char=".">8.02 (5.50)</td><td char=".">6.09 (3.46)</td><td char=".">.02</td><td char=".">.49</td></tr><tr><td>Risk factors</td><td /><td /><td /><td /><td /></tr><tr><td>Distress tolerance</td><td char=".">51.24 (12.97)</td><td char=".">49.29 (12.99)</td><td char=".">51.74 (12.95)</td><td char=".">.21</td><td>-.19</td></tr><tr><td>Negative urgency</td><td char=".">25.18 (7.07)</td><td char=".">27.04 (7.99)</td><td char=".">24.70 (6.75)</td><td char=".">.03</td><td char=".">.32</td></tr><tr><td>Lack of premeditation</td><td char=".">20.41 (5.23)</td><td char=".">21.34 (4.83)</td><td char=".">20.17 (5.31)</td><td char=".">.13</td><td char=".">.22</td></tr><tr><td>Lack of perseverance</td><td char=".">18.75 (4.83)</td><td char=".">19.79 (4.98)</td><td char=".">18.49 (4.76)</td><td char=".">.07</td><td char=".">.27</td></tr><tr><td>Sensation seeking</td><td char=".">32.03 (6.96)</td><td char=".">33.07 (5.66)</td><td char=".">31.77 (7.24)</td><td char=".">.15</td><td char=".">.19</td></tr><tr><td>Positive urgency</td><td char=".">23.74 (8.17)</td><td char=".">25.64 (9.45)</td><td char=".">23.25 (7.76)</td><td char=".">.05</td><td char=".">.29</td></tr><tr><td>Negative affect</td><td char=".">21.67 (7.47)</td><td char=".">23.11 (7.89)</td><td char=".">21.30 (7.33)</td><td char=".">.11</td><td char=".">.24</td></tr><tr><td>Positive affect</td><td char=".">32.50 (8.24)</td><td char=".">30.57 (8.66)</td><td char=".">32.99 (8.07)</td><td char=".">.05</td><td>-.30</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note: reported values are means and standard deviations</emph>.</p> <p>Table 2. Summary of work place behaviors.</p> <p> <ephtml> <table><thead><tr><td /><td>Full sample (N = 276)</td><td>Food service (n = 56)</td><td>Other occupation (n = 220)</td><td><italic>p</italic></td><td>φ</td></tr></thead><tbody valign="top"><tr><td>Work place behavior</td><td /><td /><td /><td /><td /></tr><tr><td>Consumed alcohol</td><td char=".">3.3% (9)</td><td char=".">8.9% (5)</td><td char=".">1.8% (4)**</td><td char=".">.01</td><td char=".">.25</td></tr><tr><td>Used illicit substance</td><td char=".">4.3% (12)</td><td char=".">14.3% (8)</td><td char=".">1.8% (4)***</td><td char="."><.001</td><td char=".">.30</td></tr><tr><td>Attended while intoxicated, high, or hungover</td><td char=".">10.9% (30)</td><td char=".">16.1% (9)</td><td char=".">9.5% (21)</td><td char=".">.16</td><td char=".">.21</td></tr><tr><td>Missed work due to intoxication</td><td char=".">5.8% (16)</td><td char=".">8.9% (5)</td><td char=".">5.0% (4)</td><td char=".">.59</td><td char=".">.08</td></tr></tbody></table> </ephtml> </p> <p>2 Note: reported values are percentages and frequencies; *<emph>p <.05</emph><sups>**</sups><emph>p <.01</emph><sups>***</sups><emph>p <.001</emph>.</p> <p>Based on group differences in marijuana-related variables, regression analyses were run to determine how employment in a food service occupation contributed to models of frequency of use and negative consequences. In both cases, demographic variables typically associated with elevated use (gender, racial background, Greek affiliation) were entered in as the initial step, and the employment variable was entered as the second step. As depicted in Table 3, adding the employment variable into the model at step 2 increased the amount of unique variance accounted for recent marijuana use days (<emph>F</emph> = 4.26, <emph>p</emph> <.05) and marijuana problems (<emph>F</emph> = 10.48, <emph>p</emph> <. 001). Based on interpretations of the unstandardized beta coefficients, being a food service worker (relative to other types of positions) was associated with approximately 2 more marijuana use days (<emph>p</emph> <.05) and 1.75 more marijuana-related problems per month (<emph>p</emph> <. 001).</p> <p>Table 3. Regression analyses accounting for marijuana use and marijuana problems.</p> <p> <ephtml> <table><thead><tr><td>Variable</td><td>Β</td><td><italic>SEB</italic></td><td>β</td><td><italic>T</italic></td><td><italic>R</italic>² change</td></tr></thead><tbody valign="top"><tr><td><italic>Recent marijuana use</italic></td></tr><tr><td> Step 1</td><td /><td /><td /><td /><td char=".">0.03<xref ref-type="table-fn" rid="tfn3">*</xref></td></tr><tr><td> Gender</td><td>−2.41</td><td char=".">0.99</td><td>−0.15</td><td>−2.47<xref ref-type="table-fn" rid="tfn3">*</xref></td><td /></tr><tr><td> Greek</td><td>−0.53</td><td char=".">0.84</td><td>−0.40</td><td>−0.63</td><td /></tr><tr><td> Race</td><td>−0.87</td><td char=".">1.28</td><td>−0.42</td><td>−0.69</td><td /></tr><tr><td> Step 2</td><td /><td /><td /><td /><td char=".">0.05<xref ref-type="table-fn" rid="tfn3">*</xref></td></tr><tr><td> Gender</td><td>−2.45</td><td char=".">0.98</td><td>−0.16</td><td>−2.50<xref ref-type="table-fn" rid="tfn3">*</xref></td><td /></tr><tr><td> Greek</td><td>−0.37</td><td char=".">0.84</td><td>−0.03</td><td>-.44</td><td /></tr><tr><td> Race</td><td>−0.92</td><td char=".">1.28</td><td>−0.04</td><td>−0.72</td><td /></tr><tr><td> Food service vs. other occupations</td><td char=".">1.98</td><td char=".">0.96</td><td char=".">.12</td><td char=".">2.06<xref ref-type="table-fn" rid="tfn3">*</xref></td><td /></tr><tr><td><italic>Marijuana problems</italic></td></tr><tr><td> Step 1</td><td /><td /><td /><td /><td char=".">.02<xref ref-type="table-fn" rid="tfn3">*</xref></td></tr><tr><td> Gender</td><td>−0.86</td><td char=".">0.56</td><td>−0.10</td><td>−1.53</td><td /></tr><tr><td> Greek</td><td>−0.52</td><td char=".">0.47</td><td>−0.07</td><td>−1.09</td><td /></tr><tr><td> Race</td><td>−0.55</td><td char=".">.73</td><td>−0.05</td><td>-.76</td><td /></tr><tr><td> Step 2</td><td /><td /><td /><td /><td char=".">.06<xref ref-type="table-fn" rid="tfn3">*</xref></td></tr><tr><td> Gender</td><td>−0.87</td><td char=".">0.55</td><td>−0.10</td><td>−1.58</td><td /></tr><tr><td> Greek</td><td>−0.38</td><td char=".">0.47</td><td>−0.05</td><td>−0.80</td><td /></tr><tr><td> Race</td><td>−0.58</td><td char=".">0.72</td><td>−0.05</td><td>−0.82</td><td /></tr><tr><td> Food service vs. other occupations</td><td char=".">1.73</td><td char=".">.54</td><td char=".">.19</td><td char=".">3.24***</td><td /></tr></tbody></table> </ephtml> </p> <p>3 <emph>p <.05</emph><sups>**</sups><emph>p <.01.</emph><sups>***</sups><emph>p <.001</emph>.</p> <hd id="AN0180828323-23">Additional risk factors</hd> <p>As depicted in Table 1, food service workers reported elevated levels of negative urgency (<emph>t</emph> = 2.22, <emph>p</emph> <.05; <emph>d</emph> =.32). Observed differences on several other variables approached statistical significance, with those in food service positions reporting higher levels of lack of perseverance (<emph>t</emph> = 1.96, <emph>p</emph> =.05; <emph>d</emph> =.27) and positive urgency (<emph>t</emph> = 1.81, <emph>p</emph> <. 10; <emph>d</emph> =. 29), and lower levels of lower level of positive affect (<emph>t</emph> = 1.97, <emph>p</emph> =.05; <emph>d</emph> = −.30). The observed differences between lack of premeditation (<emph>d</emph> =.22) and negative affect (<emph>d</emph> =.24) we consistent with small effect sizes despite the lack of statistical significance.</p> <hd id="AN0180828323-24">Discussion</hd> <p>College students are well-represented in the food service industry and at risk for elevated patterns of substance use and related negative consequences. However, research on students in food service positions is very limited, and to our knowledge this is the first study to directly examine a range of substance use behaviors and related risk factors in this population. In our sample, college-aged employees reported similar levels of alcohol consumption and related consequences across work settings. However, those in food service positions reported higher levels of drinking to cope—a strong predictor of negative alcohol-related consequences.[<reflink idref="bib48" id="ref46">48</reflink>] Regarding marijuana use, students in food service positions reported marginally higher levels of marijuana consumption, as well as significantly higher negative consequences and endorsement of coping, enhancement, and expansion motives. Food service workers were also more likely to report elevated levels of impulsivity and were more likely to consume alcohol or illicit substances while working. Finally, being employed in a food service position, relative to employment in other positions, contributed unique variance to models of marijuana use and related negative consequences. While the majority of these observed differences were relatively small in terms of effect size, they are consistent with previous research on the risks associated with food service employment. The findings have the potential to inform future research and intervention efforts.</p> <p>While students in food service positions were more likely to report increased use of marijuana in general, and use of both alcohol and marijuana specifically while working, the finding that food service workers did not show elevated levels of general alcohol consumption was contrary to our initial hypotheses. Previous research has suggested that the availability paradigm, or access to alcohol and illicit substances overall as well as in the workplace, may contribute to greater use and higher risk for consequences.[<reflink idref="bib9" id="ref47">9</reflink>] Interestingly, high rates of alcohol use having been reported among food service workers persists even for those employed in establishments that do not serve alcohol, or in at locations with strict policies against drinking while are work.[[<reflink idref="bib49" id="ref48">49</reflink>], [<reflink idref="bib51" id="ref49">51</reflink>]] In our sample, it is unclear how availability of alcohol or marijuana contributed to patterns of substance use, both in general and specifically while working. It may be that the students in our sample had sufficient access to alcohol, such that working in the food service industry did not contribute any additional risk. In addition, it is unclear the degree to which availability of marijuana, or any work-related policies related to marijuana use impacted the decision making of student in our sample. One recent study found that food service workers were more likely to report use of illicit drugs, and these users were less likely to be concerned about the potential for negative outcomes related to occupational, health, or other areas of functioning.[<reflink idref="bib52" id="ref50">52</reflink>] More research is needed to determine how the actual or perceived availability and acceptability of using alcohol or marijuana while working impacts the behavior of college-aged employees. This may be especially true as the legal landscape related to marijuana use continues to evolve.</p> <p>The increased endorsement of using both alcohol and marijuana to cope among food service workers, along with their increased endorsement of both positive and negative urgency, is particularly interesting within the context of tension reduction and motivational models of substance use.[<reflink idref="bib23" id="ref51">23</reflink>],[<reflink idref="bib25" id="ref52">25</reflink>],[<reflink idref="bib26" id="ref53">26</reflink>] Coping motives have been consistently linked to elevated risk of negative outcome related to both alcohol and marijuana.[<reflink idref="bib53" id="ref54">53</reflink>],[<reflink idref="bib54" id="ref55">54</reflink>] In addition, links between coping motives and negative urgency—or the tendency to act rashly when distressed—have been established among college student drinkers and adult marijuana users.[<reflink idref="bib53" id="ref56">53</reflink>],[[<reflink idref="bib55" id="ref57">55</reflink>], [<reflink idref="bib57" id="ref58">57</reflink>], [<reflink idref="bib59" id="ref59">59</reflink>]] When applied to work, these theories and previously reported findings would suggest that work-related stress could lead to increased use of substances to cope with the resulting negative affect, especially in individual who are high in negative urgency. As previously noted, employment in food service positions may lead to higher levels of work-related stress or work-school conflict.[<reflink idref="bib5" id="ref60">5</reflink>],[<reflink idref="bib7" id="ref61">7</reflink>] Relatedly, previous studies have raised the "alienation-stress" paradigm to suggest that employees use substances as a direct or indirect response to physical and psychosocial elements of work environments.[<reflink idref="bib27" id="ref62">27</reflink>] More research is needed to determine if the combination of college enrollment and stressors related to food service positions may intersect with motives for substance use and variety of variables related to impulsivity and emotion regulation.</p> <hd id="AN0180828323-25">Limitations</hd> <p>Our current findings, while novel and clinically important, are limited by several factors. While our study is informed by tension reduction theory and motivational models of substance use, we did not directly assess work-related stress to see how it related to substance use, coping motives, or negative urgency. However, our descriptive findings do lay the groundwork for more prospective studies that test how these variables interact in predicting risk among food service workers relative to other types of workers. Our sample size is comparatively small, which challenged our ability to further explore different roles and work schedules in the food service industry. It may be possible for in-group differences to exist, such as among bartenders, hostesses, and fast-food workers. Similarly, the number of hours spent working, or the specific hours (e.g., mornings, late evenings) might have an impact on the experience and consequences of employment. A larger sample would be needed to fully explore such differences.</p> <p>Moreover, the sample is predominately female, resulting in a limited ability to generalize findings across gender. Specifically, given that males students tend to report higher levels of alcohol use than females,[<reflink idref="bib33" id="ref63">33</reflink>] the lack of gender diversity might explain similarities in alcohol consumption, as well as in negative consequences across the RAPI and the AUDIT. Inclusion of a broader sample may have helped clarify if similarities across setting were overshadowed by gender. Relatedly, the present sample is predominately composited of White participants. While this is reflective of the university population sampled from, it may not be reflective of racial/ethnic norms of college food service workers overall. It is imperative for future research to examine substance misuse rates amongst college-aged food service workers who represent a more generalizable portion of the population.</p> <p>Given the number of statistical tests we conducted, the likelihood of a type 1 error is increased (e.g., reporting difference between food service and other types of workers that do not exist). Given the lack of research on substance use among college-aged food service workers and descriptive nature of our study, we viewed the possibility of type II errors (e.g., failing to detect and report differences that do exist) as more problematic if they reduced the likelihood of future research on potentially important findings. This potential concerns is underscored by the fact that across several variables (e.g., AUDIT, lack of perseverance), the effect sizes were above the standard threshold for a small but meaningful relationship, even though the findings did not reach conventional levels of statistical significance. Such a pattern can be attributed the relatively small sample size.</p> <p>Finally, our study is based on self-report, thus results may be influenced by incorrect perceptions of one's own use and motives, as well as the potential for social desirability bias. Based on our two limitations, replication and extension through a combination of self-report studies and field studies with larger sample sizes are needed and would likely yield important information about the use of substances in different work settings, as well as unique stressors that might impact substance use behavior among students in a variety of positions.</p> <hd id="AN0180828323-26">Future directions</hd> <p>Given these limitations, future research would benefit from exploring these findings in a larger, more diverse sample. This may help facilitate an understanding of how age (e.g., students under and over the legal drinking age), ethnicity and gender roles interact with various employment-related variables to increase or mitigate substance use behavior. As noted by Duke et al,[<reflink idref="bib60" id="ref64">60</reflink>] food service workers are a heterogenous group who have different roles, responsibilities, and occupational aspirations that impact their social networks and drinking practices. Social capital theory, which focusses on the formation and impact of dynamic social networks, could be used to explore how demographic variables interact with specific jobs (e.g., kitchen staff, hosts, waitstaff, bartenders, managers), job locations (e.g., on- vs. off-campus,), and work environments (e.g., establishments that do or not serve alcohol) interact to influence substance use behavior.[<reflink idref="bib60" id="ref65">60</reflink>]</p> <p>Additionally, prospective studies might examine possible interventions for workplace substance misuse that would be effective for college-aged employees, such as work-based assistance programs aimed toward decreasing the prevalence of illicit drug use and resulting consequences. Likewise, campus-based intervention research may explore the needs of students who work in environments with high engagement in substance use to assist in development of refusal skills and coping strategies. Through both greater understanding of substance use behaviors as well as possible intervention modalities, more can be done to reduce risk in this disproportionately affected, and understudied, population.</p> <hd id="AN0180828323-27">Conflict of interest disclosure</hd> <p>The authors have no conflicts of interest to report. The authors confirm that the research presented in this article met the ethical guidelines, including adherence to the legal requirements, of the United States of America and received approval from the Institutional Review Board of Auburn University.</p> <ref id="AN0180828323-28"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> The College Board. Trends in college pricing 2018. Available at: https://research.collegeboard.org/pdf/trends-college-pricing-2018-full-report.pdf. Published 2018. Accessed May 8, 2020.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> Institute of Education Services: National Center for Educational Statistics. College Student Employment. Available at: https://nces.ed.gov/programs/coe/indicator%5fssa.asp. Published 2019. Accessed May 4, 2020.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref3" type="bt">3</bibl> <bibtext> Logan J, Hughes T, Logan B. Overworked? An observation of the relationship between student employment and academic performance. J Coll Stud Ret. 2016; 18 (3): 250 – 262. doi: 10.1177/1521025115622777.</bibtext> </blist> <blist> <bibl id="bib4" type="bt">4</bibl> <bibtext> Park Y, Sprung J. Work-school conflict and health outcomes: beneficial resources for working college students. J Occup Health Psychol. 2013; 18 (4): 384 – 394. doi: 10.1037/a0033614.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref4" type="bt">5</bibl> <bibtext> Butler A, Dodge K, Faurote E. College student employment and drinking: a daily study of work stressors, alcohol expectancies, and alcohol consumption. J Occup Health Psychol. 2010; 15 (3): 291 – 303. doi: 10.1037/a0019822.</bibtext> </blist> <blist> <bibl id="bib6" type="bt">6</bibl> <bibtext> Bono R, Barnes A, Dick D, Kendler K. Drinking, cigarette smoking, and employment among American college freshmen at a four-year university. Subst Use Misuse. 2017; 52 (2): 182 – 193. doi: 10.1080/10826084.2016.1223136.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref5" type="bt">7</bibl> <bibtext> Oviatt D, Baumann M, Bennett J, Garva R. Undesirable effects of working while in college: work-school conflict, substance use, and health. J Psychol. 2017; 151 (5): 433 – 452. doi: 10.1080/00223980.2017.1314927.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref6" type="bt">8</bibl> <bibtext> Frone M. Prevalence and distribution of illicit drug use in the workforce and in the workplace: findings and implications from a U.S. national survey. J Appl Psychol. 2006; 91 (4): 856 – 869. doi: 10.1037/0021-9010.91.4.856.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref20" type="bt">9</bibl> <bibtext> Frone M. Prevalence and distribution of alcohol use and impairment in the workplace: A U.S. national survey. J Stud Alcohol. 2006; 67 (1): 147 – 156. doi: 10.15288/jsa.2006.67.147.</bibtext> </blist> <blist> <bibtext> Bush D, Lipari R. The CBHSQ Report: Substance Use and Substance Use Disorder, by Industry. Rockville, MD : Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality; 2015.</bibtext> </blist> <blist> <bibtext> Norström T, Sundin E, Muller D, Leifman H. Hazardous drinking among restaurant workers. Scand J Public Health. 2012; 40 (7): 591 – 595. doi: 10.1177/1403494812456634.</bibtext> </blist> <blist> <bibtext> Moore R, Cunradi C, Duke M. Dimensions of problem drinking among young/adult restaurant workers. Am J Drug Alcohol Abuse. 2009; 35 (5): 239333. doi: 10.1080/00952990903075042.</bibtext> </blist> <blist> <bibtext> Kjaerheim K, Mykletun R, Aasland O, Haldorsen T, Andersen A. Heavy drinking in the restaurant business: the role of social modelling and structures, factors of the workplace. Addiction 1995; 90 (11): 1487 – 1495. doi: 10.1111/j.1360-0443.1995.tb02811.x.</bibtext> </blist> <blist> <bibtext> Zhang Z, Snizek W. Occupation, job characteristics, and the use of alcohol and other drugs. Soc Behav Pers. 2003; 31 (4): 395 – 412. doi: 10.2224/sbp.2003.31.4.395.</bibtext> </blist> <blist> <bibtext> Nusbaumer M, Reiling D. Environmental influences on alcohol consumption practices of alcoholic beverage servers. Am J Drug Alcohol Abuse. 2002; 28 (4): 733 – 742. doi: 10.1081/ADA-120015879.</bibtext> </blist> <blist> <bibtext> Coggon D, Harris E, Brown T, Rice S, Palmer K. Occupation and mortality related to alcohol, drugs and sexual habits. Occup Med (Lond). 2010; 60 (5): 348 – 353. doi: 10.1093/occmed/kqq040.</bibtext> </blist> <blist> <bibtext> Olkinuora M. Alcoholism and occupation. Scand J Work Environ Health. 1984; 10 (6): 511 – 515. doi: 10.5271/sjweh.2292.</bibtext> </blist> <blist> <bibtext> Farid B, Lucas G, Williams R. Occupational risk factors in patients with alcoholic or non-alcoholic liver disease. Alcohol Alcohol. 1994; 29 (4): 459 – 463.</bibtext> </blist> <blist> <bibtext> U.S. Bureau of Labor Statistics. Labor force statistics from the current population survey. Washington (DC): Division of Labor Force Statistics. Available at: https://<ulink href="http://www.bls.gov/cps/cpsaat18b.htm">www.bls.gov/cps/cpsaat18b.htm</ulink>. Published 2020. Accessed April 30, 2020.</bibtext> </blist> <blist> <bibtext> Carnevale A, Smith N, Melton M, Price E. Learning While Earning: The New Normal. Washington (DC) : Georgetown University: Center on Education and the Workplace; 2015. Accessed April 30, 2020 at: https://1gyhoq479ufd3yna29x7ubjn-wpengine.netdna-ssl.com/wp-content/uploads/Working-Learners-Report.pdf</bibtext> </blist> <blist> <bibtext> Substance Abuse and Mental Health Services Administration. (2021). Key Substance Use and Mental Health Indicators in the United States: Results from the 2020 National Survey on Drug Use and Health (HHS Publication No. PEP21-07-01-003, NSDUH Series H-56). Rockville, MD : Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://<ulink href="http://www.samhsa.gov/data/">www.samhsa.gov/data/</ulink></bibtext> </blist> <blist> <bibtext> Cappell H, Greeley J. Alcohol and tension reduction: an update on research and theory. In: Blane HT, Leonard KE, eds. Psychological Theories of Drinking and Alcoholism. New York : Guilford Press; 1987 : 15 – 54.</bibtext> </blist> <blist> <bibtext> Conger JJ. Alcoholism: theory, problem and challenge. II. Reinforcement theory and the dynamics of alcoholism. Q J Stud Alcohol. 1956; 17 (2): 296 – 305.</bibtext> </blist> <blist> <bibtext> Wolkowicz NR, Peltier MR, Wemm S, MacLean RR. Subjective stress and alcohol use among young adult and adult drinkers: systematic review of studies using Intensive Longitudinal Designs. Drug Alcohol Depend Rep. 2022; 3 : 100039. doi: 10.1016/j.dadr.2022.100039.</bibtext> </blist> <blist> <bibtext> Cooper ML, Frone MR, Russell M, Mudar P. Drinking to regulate positive and negative emotions: a motivational model of alcohol use. J Pers Soc Psychol. 1995; 69 (5): 990 – 1005. doi: 10.1037//0022-3514.69.5.990.</bibtext> </blist> <blist> <bibtext> Cox WM, Klinger E. A motivational model of alcohol use. J Abnorm Psychol. 1988; 97 (2): 168 – 180. doi: 10.1037/0021-843X.97.2.168.</bibtext> </blist> <blist> <bibtext> Frone MR. Work stress and alcohol use. Alcohol Res Health. 1999; 23 (4): 284 – 291.</bibtext> </blist> <blist> <bibtext> Hight SK, Park J-Y. Role stress and alcohol use on restaurant server's job satisfaction: Which comes first? Int J Hosp Manag. 2019; 76 : 231 – 239. doi: 10.1016/j.ijhm.2018.05.012.</bibtext> </blist> <blist> <bibtext> Shigihara AM. Health behaviors in the service sector: substance use among restaurant employees. J Soc Behav Health Sci. 2020; 14 (1): 37 – 52. doi: 10.5590/JSBHS.2020.14.1.04.</bibtext> </blist> <blist> <bibtext> Gatta ML. Balancing trays and smiles: what restaurant servers teach us about hard work in the service economy. In: Bolton S, Houlihan M, eds. Work Matters: Critical Reflections on Contemporary Work. Basingstoke, United Kingdom : Palgrave Macmillan; 2009 : 114 – 128.</bibtext> </blist> <blist> <bibtext> Cooper ML, Kuntsche E, Levitt A, Barber LL, Wolf S. Motivational models of substance use: a review of theory and research on motives for using alcohol, marijuana, and tobacco. In: Sher KJ, ed. The Oxford Handbook of Substance Use and Substance Use Disorders. Vol. 1. New York, NY: Oxford Library of Psychology, Oxford University Press; 2016 : 375 – 421.</bibtext> </blist> <blist> <bibtext> Iwamoto DK, Grivel M, Cheng A, Clinton L, Kaya A. Asian American women and alcohol-related problems: The role of multidimensional feminine norms. J Immigr Minor Health. 2016; 18 (2): 360 – 368. doi: 10.1007/s10903-015-0159-3.</bibtext> </blist> <blist> <bibtext> Merrill JE, Carey KB. Drinking over the lifespan: focus on college ages. Alcohol Res: Curr Rev. 2016; 38 (1): 103 – 114.</bibtext> </blist> <blist> <bibtext> Park A, Sher KJ, Krull JL. Risky drinking in college changes as fraternity/sorority affiliation changes: a person-environment perspective. Psychol Addict Behav. 2008; 22 (2): 219 – 229. doi: 10.1037/0893-164X.22.2.219.</bibtext> </blist> <blist> <bibtext> Magid V, Colder CR. The UPPS Impulsive Behavior Scale: Factor structure and associations with college drinking. Pers Individ Dif. 2007; 43 (7): 1927 – 1937. doi: 10.1016/j.paid.2007.06.013.</bibtext> </blist> <blist> <bibtext> Zvolensky MJ, Vujanovic AA, Bernstein A, Leyro T. Distress tolerance: theory, measurement, and relations to psychopathology. Curr Dir Psychol Sci. 2010; 19 (6): 406 – 410. doi: 10.1177/0963721410388642.</bibtext> </blist> <blist> <bibtext> United States Bureau of Labor Statistics. How the government measures unemployment. United States Department of Labor. Available at: https://<ulink href="http://www.bls.gov/cps/cps%5fhtgm.htm">www.bls.gov/cps/cps%5fhtgm.htm</ulink>. Updated October 8, 2015. Accessed July 8, 2022.</bibtext> </blist> <blist> <bibtext> Collins RL, Parks GA, Marlatt GA. Social determinants of alcohol consumption: The effects of social interaction and model status on the self-administration of alcohol. J Consult Clin Psychol. 1985; 53 (2): 189 – 200. doi: 10.1037/0022-006X.53.2.189.</bibtext> </blist> <blist> <bibtext> Saunders JB, Aasland OG, Babor TF, De La Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption–II. Addiction. 1993; 88 (6): 791 – 804. doi: 10.1111/j.1360-0443.1993.tb02093.x.</bibtext> </blist> <blist> <bibtext> White HR, Labouvie EW. Towards the assessment of adolescent problem drinking. J Stud Alcohol. 1989; 50 (1): 30 – 37. doi: 10.15288/jsa.1989.50.30.</bibtext> </blist> <blist> <bibtext> Simons JS, Carey KB. Risk and vulnerability for marijuana use problems: the role of affect dysregulation. Psychol Addict Behav. 2002; 16 (1): 72 – 75. doi: 10.1037/0893-164X.16.1.72.</bibtext> </blist> <blist> <bibtext> Cooper ML. Motivations for alcohol use among adolescents: development and validation of a four-factor model. Psychol Assess. 1994; 6 (2): 117 – 128. doi: 10.1037/1040-3590.6.2.117.</bibtext> </blist> <blist> <bibtext> Simons J, Correia CJ, Carey KB, Borsari BE. Validating a five-factor marijuana motives measure: relations with use, problems, and alcohol motives. J Couns Psychol. 1998; 45 (3): 265 – 273. doi: 10.1037/0022-0167.45.3.265.</bibtext> </blist> <blist> <bibtext> Simons JS, Gaher RM. The distress tolerance scale: development and validation of a self-report measure. Motiv Emot. 2005; 29 (2): 83 – 102. doi: 10.1007/s11031-005-7955-3.</bibtext> </blist> <blist> <bibtext> Kaiser AJ, Milich R, Lynam DR, Charnigo RJ. Negative Urgency, Distress Tolerance, and substance abuse among college students. Addict Behav. 2012; 37 (10): 1075 – 1083. doi: 10.1016/j.addbeh.2012.04.017.</bibtext> </blist> <blist> <bibtext> Lynam D, Smith G, Whiteside S, Cyders M. The UPPS-P: Assessing Five Personality Pathways to Impulsive Behavior. West Lafayette, IN : Purdue University; 2006</bibtext> </blist> <blist> <bibtext> Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: The PANAS Scales. J Pers Soc Psychol. 1988; 54 (6): 1063 – 1070. doi: 10.1037/0022-3514.54.6.1063.</bibtext> </blist> <blist> <bibtext> Carey K, Correia C. Drinking motives predict alcohol-related problems in college students. J Stud Alcohol. 1997; 58 (1): 100 – 105. doi: 10.15288/jsa.1997.58.100.</bibtext> </blist> <blist> <bibtext> Michailids MP, Elwkai ME. Factors contributing to occupational stress experienced by individuals employed in the fast food industry. Work. 2003; 21 (2): 125 – 140.</bibtext> </blist> <blist> <bibtext> Moore RS, Ames GM, Cunradi CB, Duke MR. Alcohol policy comprehension, compliance, and consequences among young adult restaurant workers. J Workplace Behav Health. 2012; 27 (3): 181 – 195. doi: 10.1080/15555240.2012.701183.</bibtext> </blist> <blist> <bibtext> Moore RS, Cunradi CB, Duke MR, Ames GM. Dimensions of problem drinking among young adult restaurant workers. Am J Drug Alcohol Abuse. 2009; 35 (5): 329 – 333. doi: 10.1080/00952990903075042.</bibtext> </blist> <blist> <bibtext> Kaminski K, Kitterlin-Lynch M, Cain L, Beckman E. Drug use and its perceived consequences: A comparison of foodservice and non-foodservice employees. Int J Hosp Manag. 2019; 77 : 238 – 244. doi: 10.1016/j.ijhm.2018.07.003.</bibtext> </blist> <blist> <bibtext> Hoyer D, Correia CJ. Relations among motives, negative urgency, and mindfulness skills in college drinkers. Addict Behav. 2020; 101 : 106135. doi: 10.1016/j.addbeh.2019.106135.</bibtext> </blist> <blist> <bibtext> Schultz NR, Bassett DT, Messina BG, Correia CJ. Differential role of cannabis use motives in predicting impairment across three measures. J Stud Alcohol Drugs. 2019; 80 (1): 26 – 31. doi: 10.15288/jsad.2019.80.26.</bibtext> </blist> <blist> <bibtext> Cyders MA, Smith GT. Mood-based rash action and its components: Positive and negative urgency. Pers Individ Dif. 2007; 43 (4): 839 – 850. doi: 10.1016/j.paid.2007.02.008.</bibtext> </blist> <blist> <bibtext> Adams ZW, Kaiser AJ, Lynam DR, Charnigo RJ, Milich R. Drinking motives as mediators of the impulsivity-substance use relation: pathways for negative urgency, lack of premeditation, and sensation seeking. Addict Behav. 2012; 37 (7): 848 – 855. doi: 10.1016/j.addbeh.2012.03.016.</bibtext> </blist> <blist> <bibtext> Jones KA, Chryssanthakis A, Groom MJ. Impulsivity and drinking motives predict problem behaviours relating to alcohol use in University students. Addict Behav. 2014; 39 (1): 289 – 296. doi: 10.1016/j.addbeh.2013.10.024.</bibtext> </blist> <blist> <bibtext> Simons JS, Gaher RM, Oliver MNI, Bush JA, Palmer MA. An experience sampling study of associations between affect and alcohol use and problems among college students. J Stud Alcohol. 2005; 66 (4): 459 – 469. doi: 10.15288/jsa.2005.66.459.</bibtext> </blist> <blist> <bibtext> Sofis MJ, Budney AJ, Stanger C, Knapp AA, Borodovsky JT. Greater delay discounting and cannabis coping motives are associated with more frequent cannabis use in a large sample of adult cannabis users. Drug Alcohol Depend. 2020; 207 : 107820. doi: 10.1016/j.drugalcdep.2019.107820.</bibtext> </blist> <blist> <bibtext> Duke MR, Ames GM, Moore RS, Cunradi CB. Divergent drinking patterns of restaurant workers: the influence of social networks and job position. J Workplace Behav Health. 2013; 28 (1): 30 – 45. doi: 10.1080/15555240.2013.755447.</bibtext> </blist> </ref> <aug> <p>By Margaret Caruso; Dennis Hoyer; Lauren Clinton and Christopher J. Correia</p> <p>Reported by Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib10" firstref="ref7"></nolink> <nolink nlid="nl2" bibid="bib11" firstref="ref8"></nolink> <nolink nlid="nl3" bibid="bib12" firstref="ref9"></nolink> <nolink nlid="nl4" bibid="bib13" firstref="ref10"></nolink> <nolink nlid="nl5" bibid="bib14" firstref="ref12"></nolink> <nolink nlid="nl6" bibid="bib15" firstref="ref14"></nolink> <nolink nlid="nl7" bibid="bib16" firstref="ref15"></nolink> <nolink nlid="nl8" bibid="bib17" firstref="ref16"></nolink> <nolink nlid="nl9" bibid="bib18" firstref="ref17"></nolink> <nolink nlid="nl10" bibid="bib19" firstref="ref18"></nolink> <nolink nlid="nl11" bibid="bib20" firstref="ref19"></nolink> <nolink nlid="nl12" bibid="bib21" firstref="ref21"></nolink> <nolink nlid="nl13" bibid="bib22" firstref="ref22"></nolink> <nolink nlid="nl14" bibid="bib24" firstref="ref23"></nolink> <nolink nlid="nl15" bibid="bib25" firstref="ref24"></nolink> <nolink nlid="nl16" bibid="bib26" firstref="ref25"></nolink> <nolink nlid="nl17" bibid="bib27" firstref="ref26"></nolink> <nolink nlid="nl18" bibid="bib29" firstref="ref27"></nolink> <nolink nlid="nl19" bibid="bib31" firstref="ref29"></nolink> <nolink nlid="nl20" bibid="bib32" firstref="ref30"></nolink> <nolink nlid="nl21" bibid="bib33" firstref="ref31"></nolink> <nolink nlid="nl22" bibid="bib34" firstref="ref32"></nolink> <nolink nlid="nl23" bibid="bib35" firstref="ref33"></nolink> <nolink nlid="nl24" bibid="bib36" firstref="ref34"></nolink> <nolink nlid="nl25" bibid="bib37" firstref="ref35"></nolink> <nolink nlid="nl26" bibid="bib38" firstref="ref36"></nolink> <nolink nlid="nl27" bibid="bib39" firstref="ref37"></nolink> <nolink nlid="nl28" bibid="bib40" firstref="ref38"></nolink> <nolink nlid="nl29" bibid="bib41" firstref="ref39"></nolink> <nolink nlid="nl30" bibid="bib42" firstref="ref40"></nolink> <nolink nlid="nl31" bibid="bib43" firstref="ref41"></nolink> <nolink nlid="nl32" bibid="bib44" firstref="ref42"></nolink> <nolink nlid="nl33" bibid="bib45" firstref="ref43"></nolink> <nolink nlid="nl34" bibid="bib46" firstref="ref44"></nolink> <nolink nlid="nl35" bibid="bib47" firstref="ref45"></nolink> <nolink nlid="nl36" bibid="bib48" firstref="ref46"></nolink> <nolink nlid="nl37" bibid="bib49" firstref="ref48"></nolink> <nolink nlid="nl38" bibid="bib51" firstref="ref49"></nolink> <nolink nlid="nl39" bibid="bib52" firstref="ref50"></nolink> <nolink nlid="nl40" bibid="bib23" firstref="ref51"></nolink> <nolink nlid="nl41" bibid="bib53" firstref="ref54"></nolink> <nolink nlid="nl42" bibid="bib54" firstref="ref55"></nolink> <nolink nlid="nl43" bibid="bib55" firstref="ref57"></nolink> <nolink nlid="nl44" bibid="bib57" firstref="ref58"></nolink> <nolink nlid="nl45" bibid="bib59" firstref="ref59"></nolink> <nolink nlid="nl46" bibid="bib60" firstref="ref64"></nolink>
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  Data: Substance Use Behaviors among College Students in the Food Service Industry
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  Data: <searchLink fieldCode="AR" term="%22Margaret+Caruso%22">Margaret Caruso</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4823-8467">0000-0003-4823-8467</externalLink>)<br /><searchLink fieldCode="AR" term="%22Dennis+Hoyer%22">Dennis Hoyer</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2548-7874">0000-0003-2548-7874</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lauren+Clinton%22">Lauren Clinton</searchLink><br /><searchLink fieldCode="AR" term="%22Christopher+J%2E+Correia%22">Christopher J. Correia</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+American+College+Health%22"><i>Journal of American College Health</i></searchLink>. 2024 72(8):2520-2527.
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  Data: Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: 8
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  Group: Date
  Data: 2024
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Label: Descriptors
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  Data: <searchLink fieldCode="DE" term="%22Food+Service%22">Food Service</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Employment+Level%22">Employment Level</searchLink><br /><searchLink fieldCode="DE" term="%22Substance+Abuse%22">Substance Abuse</searchLink><br /><searchLink fieldCode="DE" term="%22Coping%22">Coping</searchLink><br /><searchLink fieldCode="DE" term="%22Drinking%22">Drinking</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+Abuse%22">Drug Abuse</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Marijuana%22">Marijuana</searchLink><br /><searchLink fieldCode="DE" term="%22At+Risk+Persons%22">At Risk Persons</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+Health%22">Mental Health</searchLink><br /><searchLink fieldCode="DE" term="%22Stress+Management%22">Stress Management</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Positive+and+Negative+Affect+Schedule%22">Positive and Negative Affect Schedule</searchLink>
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  Data: 10.1080/07448481.2022.2119396
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  Data: 0744-8481<br />1940-3208
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objective: Food service employment is associated with substance use, risk of substance use disorders and various negative consequences. Previous research has not examined the substance use patterns of students employed in food service positions. Method: During Fall of 2018, 276 undergraduates completed an anonymous online survey regarding current employment status and substance use. Results: Compared to students employed in other positions, students in food service positions reported higher levels of drinking to cope with negative affect, negative urgency, workplace substance use, marijuana use, marijuana-related problems, and motives. Food service employment was also a significant predictor of marijuana use and related consequences. Conclusions: Students in food service positions, relative to other employment positions, report elevated substance use behavior, risk factors, and negative consequences. Food service employment also contributed variance to models accounting for marijuana use and related consequences. Prevention and intervention strategies should be investigated to mitigate risk for this population.
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  Data: 2024
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  Data: EJ1448273
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        PageCount: 8
        StartPage: 2520
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      – SubjectFull: Food Service
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Employment Level
        Type: general
      – SubjectFull: Substance Abuse
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      – SubjectFull: Student Behavior
        Type: general
      – SubjectFull: Positive and Negative Affect Schedule
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      – TitleFull: Substance Use Behaviors among College Students in the Food Service Industry
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              Value: 8
          Titles:
            – TitleFull: Journal of American College Health
              Type: main
ResultId 1