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tnubh 12,456 Ø Ø Ø FAQ | Register Now | Sign In HOME PHYSICAL SCIENCES PHYSICS SPACE CHEMISTRY APPLIED PHYSICS AEROSPACE OPTICS EARTH SCIENCES ENVIRONMENT ENERGY ATMOSPHERIC PALEONTOLOGY GEOLOGY OCEANOGRAPHY LIFE SCIENCES GENETICS & MOLECULAR BIOLOGY EVOLUTION MICROBIOLOGY ECOLOGY & ZOOLOGY IMMUNOLOGY NEUROSCIENCE MEDICINE CANCER RESEARCH PUBLIC HEALTH PHARMACOLOGY CLINICAL RESEARCH AGING VISION SOCIAL SCIENCES ANTHROPOLOGY ARCHAEOLOGY PSYCHOLOGY SCIENCE EDUCATION & POLICY SCIENCE HISTORY PHILOSOPHY & ETHICS CULTURE TECHNOLOGY MATHEMATICS SCIENCE & SOCIETY SPORTS SCIENCE RANDOM THOUGHTS HUMOR VIDEO CONTRIBUTORS HOME > MICROBIOLOGY > SCIENCE 2.0 Fake Banner Want To Consume Cow Feces? Have Some Raw Milk By Hank Campbell | February 18th 2015 01:22 PM | Print | E-mail User pic. Hank Campbell Would you like some Campylobacter or E. Coli today? Raw milk in 26 U.S. states is now the best place to get it, since most readers of Science 2.0 are not going to have the opportunity to buy chicken from a street vendor in China. That raw milk is risky and has no benefit is not news. In 2012 the CDC showed it again but clamoring for raw milk got even louder. It is in the news again, as part of the naturalistic fallacy that infects mostly the anti-science hippie left and a minority of people on the libertarian 'government can't regulate what diseases I should give my children' right. Like with vaccines and polio, or riding a bicycle on the freeway, just because you might have the right to do something stupid does not mean you should, and raw milk isn't better for you, it is worse. It is that simple. But it is getting more popular. So it is not so much the 979 illnesses (that we know about) that concerns me, it is that the trend is going up rather than down. The fact is that if you drink raw milk your risk of getting sick is 150X pasteurized milk and there is zero nutritional benefit to it - it is just simply getting more popular because of diet fads linked to more 'natural' ways of living, and that is why the raw milk outbreaks were 4X higher since 2007 than they were 20 years ago. And look at the ages impacted most: Percentage of patients affected by outbreaks associated with nonpasteurized milk, by age and etiologic agent, United States, 2007–2012. Small kids and people ages 20-49? What is going on there? In kids it makes sense, they have dumb parents, but among older people it is another flavor of the Hipster Doofus demographic, the sub-literates who quote Proust and their reasons for vaccine denial whenever the opportunity presents itself: Link Except raw milk proponents are not just in San Francisco or Portland. That 81 percent of outbreaks happened in states where raw milk is legal makes sense. What makes no sense is the response of raw milk believers to the latest foodborne disease warning - sell more of it and make it legal in more places. Obviously that makes sense to people selling 18th century food myths, and that same logic is why we should have sold more DDT in the 1970s, more ozone-killing CFCs in the 1980s and why everyone agreed that producing more CO2 emissions in the 1990s would be the best way to prevent global warming. And you should always eat raw chicken, since processing food is bad. Except it isn't bad, anyone who has milked a cow (where it becomes really obvious) or seen a commercial dairy operation knows exactly how raw milk spreads disease: Cows do not care what else they are doing while they are being milked, they don't take potty breaks. And cows get diseases, just like people do. The cow could have bovine tuberculosis or mastitis. I can't imagine why raw milk is all over my news feeds again this week but American Council on Science and Health takes the prize for most across-the-board awareness today, taking down raw milk, homeopaths, anti-vaccine beliefs, anti-GMO hysteria and Fox News in only 3 blurbs: The takeaway: Homeopathic vaccines won't prevent Campylobacter bacteria so it is better to side with science. Citation: Elisabeth A. Mungai, Casey Barton Behravesh, L. Hannah Gould, 'Increased Outbreaks Associated with Nonpasteurized Milk, United States, 2007–2012', Emerg Infect Dis Volume 21, Number 1—January 2015 DOI: 10.3201/eid2101.140447 Science 2.0 MORE ARTICLES Model That Claimed Only Lockdown Works To Prevent Coronavirus Spread Was Flawed, Shows New Look College Enrollment Will Go Down This Decade, And That's Probably A Good Thing Medical Misuse Needs A Real Definition All Articles ABOUT I founded Science 2.0® in 2006 and since then it has become the world's largest independent science communications site, with over 300,000,000 direct... View Profile RELATED ARTICLES Raw Milk Not Worth The Risk- Study Home Cheese Makers Take Note: Consider Kefir For Making Feta Does Raw Milk Reduce Lactose Intolerance? 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Donate with PayPal button We are a nonprofit science journalism group operating under Section 501(c)(3) of the Internal Revenue Code that's educated over 300 million people. You can help with a tax-deductible donation today and 100 percent of your gift will go toward our programs, no salaries or offices. Popular NowNew CommentsEvents Model That Claimed Only Lockdown Works To Prevent Coronavirus Spread Was Flawed, Shows New Look Why Haven't Crocodiles Evolved Much Since The Age Of The Dinosaurs? Longitudinal Study Shows Vaping Is Not As Harmful As Smoking R0 And Why We'll Need 70 Percent Vaccination To Stop COVID-19 Bitter Or Sweet? It's Not Just Preference, Tongues Have Evolved In Different Areas 13 Ways To Get Better COVID-19 Restriction Uptake Hot TopicsLinks Current Topic: Is BPA Safe Or Not? The best writers in science tackle science's hottest topics. 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aqbuc NCBINCBI Logo Skip to main content Skip to navigation Resources How To About NCBI Accesskeys PMC US National Library of Medicine National Institutes of Health Search database PMC Search term Search Advanced Journal listHelp COVID-19 is an emerging, rapidly evolving situation. Get the latest public health information from CDC: https://www.coronavirus.gov Get the latest research information from NIH: https://www.nih.gov/coronavirus Find NCBI SARS-CoV-2 literature, sequence, and clinical content: https://www.ncbi.nlm.nih.gov/sars-cov-2/ Journal ListHHS Author ManuscriptsPMC4979577 Logo of nihpa J Subst Use. Author manuscript; available in PMC 2017 Jan 1. Published in final edited form as: J Subst Use. 2016; 21(4): 395–399. Published online 2015 Sep 18. doi: 10.3109/14659891.2015.1040089 PMCID: PMC4979577 NIHMSID: NIHMS760791 PMID: 27524938 Mood Symptoms in Steroid Users: The Unexamined Role of Concurrent Stimulant Use Pilar M. Sanjuan, Ph.D. Pilar M. Sanjuan, Fellow: The University of New Mexico, Center on Alcoholism, Substance Abuse, and Addictions, 2650 Yale Boulevard, SE, MSC11-6280, Albuquerque, NM 87106, USA; James L. Langenbucher, Ph.D., Associate Professor James L. Langenbucher, Rutgers, The State University of New Jersey, Center of Alcohol Studies, 607 Allison Road, Piscataway, NJ 08854, USA; Tom Hildebrandt, PsyD, Associate Professor Tom Hildebrandt, Mt Sinai School of Medicine, One Gustave L Levy Place, Box 1230, New York, NY 10029, USA; Author information Copyright and License information Disclaimer The publisher's final edited version of this article is available at J Subst Use See other articles in PMC that cite the published article. Go to: INTRODUCTION Appearance and performance enhancing drugs (APEDs) include a range of illicit, prescription, and over-the-counter preparations used to increase lean body-mass in order to attain idealized physiques and improve athletic performance (Thomas Hildebrandt, Langenbucher, Carr, & Sanjuan, 2007). Most APED users are polydrug users engaging in “stacking,” taking several drugs from different categories concurrently and sequentially over 8-10 week time blocks (Dodge & Hoagland, 2011). This study focuses on two APED categories: Anabolic-Androgenic Steroids (referred to simply as “steroids” in this article) and Thermogenic and Ergogenic Drugs (stimulants). Substances in the steroids group include numerous synthetic testosterone derivatives varying in half-lives and metabolite ratios. Stimulants used in this capacity include fat-burning and energy-boosting drugs (Coffey, Steiner, Baker, & Allison, 2004; Maglione et al., 2005; Shekelle PG, Hardy ML, Morton SC, & et al, 2003; Sjöqvist, Garle, & Rane, 2008). Common stimulants include liothyronine (thyroid hormone), clenbuterol (illicit in the U.S.), synephrine, ephedra, ephedrine, theophylline, and caffeine (Thomas Hildebrandt, Harty, & Langenbucher, 2012; Thomas Hildebrandt et al., 2007). When used as medically indicated, these stimulants have less dramatic mood effects than stimulants better associated with misuse (e.g. methamphetamine.) Prevalence Prevalence rates of steroid use range from 1.5% of 12th graders (Johnston, O’Malley, Bachman, & Schulenberg, 2012), 6.4% of adult males, 13.4% of athletes, to 18.4% among recreational sports people (Sagoe, Molde, Andreassen, Torsheim, & Pallesen, 2014). The prevalence of APED stimulant use is more complicated as these include common substances (e.g. caffeine) as well as prescription-only medications. Rates of stimulant use are higher among athletes using of other types of APEDs (Buckman, Farris, & Yusko, 2013) ranging from 28% to 56% compared to non-APED users. Other research has found rates ranging from 25% for ephedrine (Kanayama, Gruber, Pope, Jr., Borowiecki, & Hudson, 2001) to 58% for ephedrine, pseudoephedrine, or amphetamine (Bents, Tokish, & Goldberg, 2004) among athletes and 7% for non-prescription weight loss products in the general population (Blanck H, Khan L, & Serdula MK, 2001). Mood Effects There is widespread popular belief that the use of steroids routinely results in powerful episodes of anger and violence termed “roid rage” (Chantal, Soubranne, & Brunel, 2009). However, researchers in this field agree that such negative mood effects are more likely to be rare and difficult to predict (Thomas Hildebrandt et al., 2007; Kanayama, Hudson, & Pope, 2009; Pope HG, Jr, Kouri EM, & Hudson JI, 2000; Rubinow & Schmidt, 1996; Yates, Perry, MacIndoe, Holman, & Ellingrod, 1999). Prior research has found adverse psychological effects of steroids including anger, aggressiveness, depression, and mania (Daly et al., 2003; Pagonis, Angelopoulos, Koukoulis, & Hadjichristodoulou, 2006; Su T et al., 1993; Yates, Perry, & Murray, 1992). Positive effects may include enhanced self-esteem, vigor, libido, perceived power, and concentration (Tom Hildebrandt, Langenbucher, Carr, Sanjuan, & Park, 2006). However, many studies have failed to find any psychoactive effects associated with steroid use (Bagatell, Heiman, Matsumoto, Rivier, & Bremner, 1994; Bahrke, Wright, Strauss, & Catlin, 1992; Malone, Dimeff, Lombardo, & Sample, 1995; Midgley, Heather, & Davies, 2001; O’Connor, Archer, & Wu, 2004; Tricker et al., 1996; Yates et al., 1999), supporting the idea that steroid mood effects are idiosyncratic. An understanding of the variables associated with APED-related mood disturbance is critical for identifying high risk individuals and for developing treatments. Most research on APED-induced mood effects focuses solely on steroids and does not examine concurrently used drugs (e.g. stimulants). This study was designed to assess the effects of stimulant use on mood effects as a potential variable underlying the idiosyncratic nature of steroid-associated negative mood effects. We also tried to minimize retrospective memory errors by only assessing current mood. In accordance with research finding mood effects associated with steroid use, we hypothesized that current steroid and stimulant use each would be associated with (1) increased vigor, mania, anxiety, depression, anger, fatigue, and confusion and (2) decreased positive affect. Go to: METHODS Links from internet websites that primarily focused on bodybuilding, weightlifting, or using steroids, and also from search engines, led to our internet-accessible survey, which was located on the Rutgers University website. These links were identified as leading to a “Rutgers survey on training practices and mood.” All participants initially followed this link to a Rutgers Institutional Review Board-approved consent form and clicked on second link at the bottom of this page to indicate consent. The entire protocol of the study was approved by the Rutgers Institutional Review Board. Participants Participants were 122 male weightlifters and bodybuilders, mean age of 32 (19-57, SD = 8.68), who anonymously followed the consent link. Females were targeted as well as males, but only males reached a sample size that could be analyzed. Participants did not need to have used APEDs to enroll, but, because the survey was linked to some websites with steroid-related content, many had used them. Participants did not receive any financial compensation for completing the survey. Eight participants who completed the survey were excluding for missing data. There were no other exclusion criteria. Measures The questionnaire began with demographic questions and then presented the following mood scales, each adapted to query the past 24-hours. Participants rated current moods prior to reporting current drug use. Questions about weight-training were interwoven between mood questionnaires. Anger The Revised State-Trait Anger Expression Inventory (STAXI-2:Spielberger, 1998) State-Anger scale assesses the intensity of anger at a particular time, and has been used extensively in research on health and anger. It has 3 subscales: Feelings, Verbal, and Physical. Mania The Self-Report Manic Inventory (SRMI; Shugar, Schertzer, Toner, & di Gasbarro, 1992) has been found more sensitive than other measures to euthymic and hypomanic fluctuations (Cooke, Krüger, & Shugar, 1996). Mood The Profile of Mood States – Brief (POMS-B; McNair & Heuchert, 2005), the only authorized short version of the POMS, has six factors: tension/anxiety, depression/dejection, anger/hostility, vigor/activity, fatigue/inertia, and confusion/bewilderment. Positive Mood The Automatic Thoughts Questionnaire – Positive (ATQ-P; Ingram & Wisnicki, 1988), measures the occurrence of positive self-relevant cognitions. The Marlowe-Crowne Social Desirability Scale (M-CSDS; Crowne & Marlowe, 1960) and the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) were included as covariates, to control for the desire to look good and trait affect. Mood scales were followed by sections developed specifically for this study assessing current steroid and stimulant use, dietary and sleep habits, use of other medications, and prior physical or psychiatric diagnoses. The entry question to the steroids section was, “Have you ever used anabolic steroids?” For participants who answered “yes,” this was followed by further questions about specific drugs used and patterns of use. The entry question to the stimulants section was “Have you ever used fat burners or endurance boosters such as Xenadrine or T3?” For participants answering “yes,” this was again followed by further questions about drugs and patterns of use. Data Analysis The main goal was to identify mood effects associated with steroids and stimulants. Because steroids have a long half-life and most stimulants have a comparatively short half-life, participants were considered currently on steroids if they had used them in the past 14 days and as currently on stimulants if they had used them in the past 24 hours. Analyses consisted of 2 × 2 analyses of covariance (ANCOVA) for drug use status (current steroid by current stimulant) for each mood scale. We controlled for social desirability, trait affect, age, marital status, employment, income, exercise recency, and prior night’s sleep. In addition, effect sizes were examined (Cohen’s d) for steroid and stimulant use on mood as compared to normative population scores for the POMS-B (Yeun & Shin-Park, 2006), ATQ (Ingram, Kendall, Siegle, Guarino, & McLaughlin, 1995), and STAXI (Spielberger, 1998). Go to: RESULTS Demographics Of 236 individuals who clicked the survey link, 225 consented, 135 completed the survey, 130 were male, and 122 had complete data for these analyses. Eight-four percent of participants resided in the United States, 45% were married, 75% were employed full-time, 40% had a college degree, and another 16% held graduate degrees. The majority of the participants were Caucasian (93%). Sixty-two percent of participants identified their training goal as a bodybuilding, while 36% identified it as weight-lifting. Participants averaged 97 (SD = 14.3, Range = 63-141) kilograms with a body mass index of 30 (SD = 3.8, Range 22-44) and fat-free mass index (FFMI – determined by height, weight, and self-reported body fat percentage (Kouri et al., 1995b) of 25 (SD = 3.2, Range 18-36). They were experienced APED users: 87% (N=106) reporting lifetime use of steroids for an average 3.6 years (SD = 4.28) and 80% (N=97) reporting lifetime use of stimulants for an average 3.5 years (SD = 4.1). Thirty-one percent (N=38) of the sample was not currently taking steroids or stimulants, 30% (N=37) were currently taking only steroids, 18% (N=22) were currently taking only stimulants, and 21% (N=25) were currently taking both steroids and stimulants. Internal Consistency Internal consistency for the measures in our sample was good and ranged from 0.77 to 0.94 as follows, for the STAXI-2: α=0.94, SRMI: α=0.85, POMS: α=0.90, ATQ-P: α=0.94, M-CSDS: α=0.77 and PANAS: α=0.83.. ANCOVAs The overall F-tests for all ANCOVA models were significant (p<.001), with significant main effects (p<.025) for stimulant use on Tension/Anxiety and for steroid use on Vigor/Activity. Participants using stimulants scored higher on Tension/Anxiety than those not using stimulants and participants using steroids scored lower on Vigor/Activity than non-users. No interaction effects were found for stimulants by steroids, but these were included in the models in Table 1. Table1 Mood Scales by APED Use Mood Measure Stimulants Steroids Overall Model APED Users vs. Norm No Yes No Yes F d SRMI - Mania 9.6(6.4) 10.9(5.8) 11.0(6.6) 9.0(5.7) 3.98c N/A POMS-B Tension/Anxiety 2.9(3.0)a 3.4(3.8)a 3.0(3.1) 3.1(3.2) 11.27c .74c Depression/Dejection 2.1(3.0) 2.5(4.5) 2.0(3.1) 2.3(4.1) 15.62c .42b Anger/Hostility 3.3(3.6) 2.7(3.9) 3.0(3.2) 3.1(4.2) 6.94c .61c Vigor/Activity 9.0(4.2) 10.5(5.0) 10.5(4.2)a 8.6(4.7)a 9.34c .07 Fatigue/Inertia 4.8(3.5) 4.2(4.5) 4.4(4.0) 4.7(3.9) 3.42c .83c Confusion/ Bewilderment 3.2(2.2) 3.7(2.8) 3.3(2.5) 3.3(2.4) 6.05c .54c ATQ - Positive Affect 110(13.8) 113(17.8) 113(13.1) 109(17.2) 19.46c 1.81c STAXI-2 Anger Feelings 7.5(2.7) 7.2(2.8) 7.2(2.5) 7.6(3.0) 4.49c −.08 Anger Verbal 7.4(2.7) 7.1(3.4 7.6(3.7) 7.0(2.9) 2.90c −.20 Anger Physical 6.0(2.8) 5.5(1.9) 5.9(2.2) 5.8(2.8) 3.87c .08 Total Anger 21(7.8) 19.8(7.4) 20.7(7.4) 20.3(7.9) 4.26c −.08 Note. F = F-value, ap<.025, bp<.01, cp<.001, APED = Appearance and performance enhancing drug, SRMI = The Self-Report Manic Inventory, POMS-B = The Profile of Mood States- Brief, ATQ = The Automatic Thoughts Questionnaire, STAXI-2 = The Revised State-Trait Anger Expression Inventory. In order to correct for multiple comparisons, alpha was set at p<.025 (N=122). Means and standard deviations listed above are raw. Social desirability, trait affect, age, marital status, employment, income, recency of exercise, and hours of last sleep correlated with dependent variables and were included as covariates in the analyses. Other potential covariates measured did not have sufficient variance in the sample to account for variance in the final models, and so were not included. Cohen’s d was calculated for the effect sizes in the final column, “APED Users vs. Norm,” where only participants taking stimulants, steroids, or both (N=85, which did not include participants not using either type of substance) were compared to normative samples in the literature (Ingram et al., 1995; Spielberger, 1998; Yeun and Shin-Park, 2006). A positive direction means that the norm was higher than our APED using subsample and negative direction means the APED subsample was higher. Effect Size Analyses Cohen’s d was calculated to examine effect sizes for differences between mood means for the APED-using subsample (steroid or stimulant use) and normal populations (Ingram et al., 1995; Spielberger, 1998; Yeun & Shin-Park, 2006). The APED-using subsample in this study had significantly lower scores (Table 1: last column) than norms for all POMS-B negative mood scales, higher than normal ATQ-P positive affect scores, and were not different than norms for vigor/activity or any STAXI anger scales. The magnitudes of the differences in effect size between the APED users and the general population were not different across POMS-B mood subscales, Q(5)=.021, p>.99, nor anger (STAXI) subscales, Q(2)=2.99, p=.23.The grand mean effect size for POMS-B mood was .54, indicating that the APED-using subsample was on average a half standard deviation below the normal population on measures of mood disturbance. For the anger (STAXI) scales the grand mean effect size was .07, thus not different than the general population. Go to: DISCUSSION Steroid users reported less vigor/activity than non-users, and stimulant users reported higher levels of tension/anxiety compared to non-users. Otherwise, for most mood measures there were no differences between steroid and/or stimulant users and non-users. These findings support the idea that mood effects of steroids are idiosyncratic and not commonplace. Results are consistent with previous research that has also failed to find steroid specific effects (Bagatell et al., 1994; Bahrke et al., 1992; Malone et al., 1995; Midgley et al., 2001; O’Connor et al., 2004; Pope HG et al., 2000; Tricker et al., 1996; Yates et al., 1999). The effect of stimulant use on tension/anxiety was consistent with the central nervous system arousal side-effect profiles of these substances (Maglione et al., 2005; Pearce & Himsworth, 1982; Shekelle PG et al., 2003). The higher tension/anxiety in stimulant users may account for some prior reports of mood disturbance in steroid users. Also supporting the idiosyncratic nature of negative APED mood effects, the APED-using subsample scored in normal or below normal ranges on the mood and anger subscales. Indeed, APED users scored lower on all negative mood scales and higher on positive thoughts than the normative samples, but no differently than the norm for anger. It is possible that characteristics of these athletes (e.g. consistent exercise and dietary regimens, goal-directed motivation) were protective against adverse moods. Limitations and Strengths The sample demographics may not be representative of the bodybuilding/weightlifting population, though consistent with previous research in this area. If some subsample of APED users were more likely to experience anger or aggression with APEDs, (e.g. inmates, violent criminals) they may have been missed by web-based recruitment. Additionally, dose was not assessed and the sample was not large enough to sort out mood effects associated with different types of steroids/stimulants. Finally, the entry question for the stimulants section only gave two examples (Xenadrine and T3) in addition to specifying “fat burners and endurance boosters”, and some people may have been using other substances that would fall under this category, but not have thought they applied here if they were not listed as examples. Additionally, we included many preparations in this section that contain high doses of caffeine, but there may have been other ways not on our list in which participants were using high dose caffeine. By utilizing internet technology to assess bodybuilders and weightlifters anonymously about current APED use and mood state this study builds upon prior self-report research that queried over longer retrospective recall periods (Choi & Pope, 1994; Cooper, Noakes, Dunne, Lambert, & Rochford, 1996; Lefavi, Reeve, & Newland, 1990; Parrott, Choi, & Davies, 1994; Pope & Katz, 1988, 1994) as well as other APED research (Choi, Parrott, & Cowan, 1990; Kouri, Lukas, Pope, & Oliva, 1995; Moss, Panzak, & Tarter, 1992; Perry et al., 2003). This prior research was by necessity limited by the error inherent in longer retrospective recall periods. Additionally, we were able to assess participants from across the United States and around the world, and thus our results do not reflect only local trends. And finally, we were able to recruit participants who might have been unwilling or unable to visit a laboratory setting for face-to-face assessment. Conclusions This study was designed to examine the role of stimulants used in addition to steroids among bodybuilders and weightlifters utilizing a current use and current mood focused cross-sectional internet-based survey of bodybuilders and weightlifters. No adverse mood effects were significantly associated with steroid use, while anxiety/tension was significantly associated with stimulant use. The findings from this study regarding stimulant use suggest these substances are not benign. Their use with steroids may account for some adverse moods, particularly increased anxiety and tension, often associated with steroids. Future natural observation research on steroid mood effects needs to assess and control for stimulant use among APED users. The roles of each of these classes of stimulants in mood changes should be differentiated. Physicians and mental health professionals might also take care to assess the use and psychoactive effects of stimulants in patients having potential APED-related problems. Idiosyncratic negative effects of APEDs on mood may be associated more with stimulant use than with steroid use, despite the congressional and general public focus on steroids in the United States. Go to: Acknowledgments Funded by grants NIDA K02-00390 (Langenbucher), NIAAA, T32 AA07569 (McCrady), and NIAAA T32 AA018108-02 (McCrady). Go to: References Bagatell CJ, Heiman JR, Matsumoto AM, Rivier JE, Bremner WJ. Metabolic and behavioral effects of high-dose, exogenous testosterone in healthy men. The Journal of Clinical Endocrinology & Metabolism. 1994;79(2):561–567. doi:10.1210/jcem.79.2.8045977. [PubMed] [Google Scholar] Bahrke MS, Wright JE, Strauss RH, Catlin DH. Psychological moods and subjectively perceived behavioral and somatic changes accompanying anabolic-androgenic steroid use. 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