Law School Stress

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Law School Stress: Moving from Narratives to Measurement Andrea M. Flynn,* Yan Li,** and Bernadette Sánchez*** I. INTRODUCTION For decades, law students and legal professionals have unduly suffered from psychological disorders, suicidal ideation, and substance abuse. 1 Law school stressors have been extensively described by members of the legal community, and they provide rich and compelling depictions of the problems in law school. However, scientific studies explaining how and why psychological distress occurs are lacking. Even less is known scientifically about how to practically address these problems and law students continue to suffer. The legal community, operating alone, has been unable to significantly alleviate law students’ distress. Thus, a partnership between the social sciences, particularly psychology, and the legal community may offer a new opportunity to develop creative ways to address these issues. While legal professionals know a great deal about the environments in which they train and work, psychologists offer complementary tools to address this problem. Specifically, psychologists can provide expertise in research methods, statistics, and mental health issues. This study was conducted to use theoretically and statistically

* Associate Professor of Psychology, Concordia University Chicago. ** Associate Professor of Psychology, DePaul University. *** Professor of Psychology, DePaul University. 1. See Robert Kellner, Roger J. Wiggins, & Dorothy Pathak, Distress in Medical and Law Students, 27 COMP. PSYCHOL. 220 (1986); Lawrence S. Krieger, What We’re Not Telling Law Students, and Lawyers, What They Really Need to Know: Some Thoughts-in-Action Toward Revitalizing the Profession from Its Roots, 13 J.L. & HEALTH 1, 3–7 (1998); Lekan Oguntoyinbo, Battling Mental Illness in the Legal Profession, DIVERSITY & THE BAR 18, 18–21 (2015); Jerome M. Organ, David B. Jaffe & Katherine M. Bender, Helping Law Students Get the Help They Need: An Analysis of Data Regarding Law Students’ Reluctance to Seek Help and Policy Recommendations for a Variety of Stakeholders, THE BAR EXAM’R. at 8 (2015); Stephen B. Shanfield & G. Andrew H. Benjamin, Psychiatric Distress in Law Students, 35 J. LEGAL EDUC. 65 (1985); Matthew M. Dammeyer & Narina Nunez, Anxiety and Depression Among Law Students: Current Knowledge and Future Directions, 23 L. HUM. BEHAV. 55, 58 (1999); Connie J. A. Beck, Bruce D. Sales, & Bruce D. Sales, Lawyer Distress: Alcohol-Related Problems and Other Psychological Concerns Among a Sample of Practicing Lawyers, 10 J.L. & HEALTH 1, 1–11 (1995); G. Andrew H. Benjamin, Elaine J. Darling, & Bruce Sales, The Prevalence of Depression, Alcohol Abuse, and Cocaine Abuse Among United States Lawyers, 13 INT. J.L. & PSYCHIATRY 233, 233–36 (1990); Susan Swaim Daicoff, Lawyer, Know Thyself: A Psychological Analysis of Personality Strengths and Weaknesses (2004); William W. Eaton, et al., Occupations and the Prevalence of Major Depressive Disorder, 32 J. OCCUPATIONAL MED. 1079 (1990); Amiram Elwork & G. Andrew H. Benjamin, Lawyers in Distress, 23 J. PSYCHOL & L., 206 (1995); Colin James, Lawyers’ Wellbeing and Professional Legal Education, EURO. J. LEG. EDUC.1, 3–4 (2008); Lawrence S. Krieger & Kennon M. Sheldon, What Makes Lawyers Happy? A Data-Driven Prescription to Redefine Professional Success, 83 GEO. WASH. L. REV. 557, 586–87 (2015).

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sound research methods widely used in the social sciences to develop a tool law schools can use to evaluate their programs to transform concern for students into measurable action points. The resulting tool, the Law School Stressor Measure (LSSM) has a variety of practical and empirical uses. Background information, the rationale, method for development, and evaluation of the psychometric properties of the LSSM are described in this Paper. A. Background The authors of this study, research psychologists, stumbled upon the literature describing law students’ psychological distress. After carefully evaluating the empirical and anecdotal literature, we sought to better understand this phenomenon. To do so, we conducted an exploratory, qualitative study of graduating law students by asking this simple question: Looking back, what would you say was very stressful about your law school experience? (If many things were very stressful or different times were stressful for different reasons, please list all.). Here are a few of the responses we received: “I have nervous tics for the first time in my life. I need pills to fall asleep, pills to wake up, pills to stop panic attacks, and pills to stop wanting to die.” One student recounted the following: “I have had physical symptoms of stress every semester at finals. The first semester I broke out in full body hives. This semester I’ve been through two bottles of Pepto Bismol in two weeks and I still feel like I’m going to throw up.” A different respondent reported: “I was prescribed anti-anxiety medication and I suffered severe health consequences centered around the stress of final exams. Nothing else I experienced in law school, or in any other part of my life, has been remotely comparable to the stress of finals.” Our respondents provided a variety of similar responses. Collectively, the empirical and anecdotal literature, combined with the results of our own exploratory study, suggested to us that there must be some features of the law school environment that significantly and negatively impact students. However, a well-researched, psychometrically-sound measurement tool did not yet exist that would allow law students’ experiences to be systematically studied across programs. Consequently, we were unable to conduct a study directly linking law school stressors to students’ mental health symptoms. Therefore, our goal was to use our psychological research methods to develop the LSSM. We recognize that not all students will find law school stressful, nor will they experience the anxiety, depression, and substance use described by other researchers. This Paper, however, is devoted to describing the LSSM so that the most at-risk students can be identified and programs can be improved to promote students’ mental health.

B. Literature Review Legal professions are popular, with over 760,000 practicing lawyers in the


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U.S. and more than 119,000 law students. 2 It is noteworthy, however, that law students and lawyers are at risk for depression, anxiety, substance use, and suicidal ideation. 3 Although it is possible that legal professionals are more vulnerable to psychological problems prior to entering the profession, several studies suggest otherwise. 4 Moreover, lawyers’ increased susceptibility seems to start in law school because of the law school environment. To test this, researchers have examined students as they progressed through law school and with undergraduate comparison groups. 5 Results showed that law students had higher ratings of subjective well-being, positive affect and satisfaction with life compared to undergraduate students before law school. 6 However, students in their first and third years of law school showed significant declines in well-being, positive affect, life satisfaction, and significant increases in negative affect compared to their own pre-law school levels. 7 In another study, law students reported significant increases in health problems, negative affect, and depression, and decreases in positive affect and positive attitudes in their first year. 8 While these studies imply that the law school environment is responsible for students’ mental health problems, they do not measure the law school environment nor tie it to students’ symptoms. To do so, a psychometrically-sound, reliable, valid measurement tool of the law school environment is needed. This tool can also 2. Bureau of Labor Statistics, U.S. DEP’T OF LABOR OCCUPATIONAL OUTLOOK HANDBOOK, 2014–15 EDITION, LAWYERS (2014) [https://perma.cc/W8VX-DSXJ]; ABA Section of Legal Education Reports 2014 Law School Enrollment Data, AM. BAR ASS’N (Dec. 16, 2014) [https://perma.cc/59AU-WUNN]. 3. See supra note 1, 2. 4. Alan Reifman et al., Depression and Affect Among Law Students During Law School: A Longitudinal Study, 2 J. EMOTIONAL ABUSE 93, 97 (2000); Mary E. Pritchard & Daniel N. McIntosh, What Predicts Adjustment Among Law Students?, 143 J. SOC. PSYCHOL. 727, 731 (2003); Kennon M. Sheldon & Lawrence S. Krieger, Does Legal Education Have Undermining Effects on Law Students? Evaluating Changes in Motivation, Values, and Well-Being, 22 BEHAV. SCI. & L. 261, 267 (2004); Kennon M. Sheldon & Lawrence S. Krieger, Understanding the Negative Effects of Legal Education on Law Students: A Longitudinal Test and Extension of Self-Determination Theory, 33 PERSONALITY & SOC. PSYCHOL. BULL. 883, 887 (2007). 5. See Reifman et al., supra note 4; Pritchard & McIntosh, supra note 4; Sheldon & Krieger, Does Legal Education Have Undermining Effects on Law Students?, supra note 4. 6. See Sheldon & Krieger, Does Legal Education Have Undermining Effects on Law Students?, supra note 4, at 261. In a classic study, Sheldon and Krieger conducted a longitudinal study, first assessing law students’ well-being before starting law school and comparing their participants’ scores to those of an undergraduate comparison group. Surprisingly, before law school, law students were actually higher on subjective well-being than the undergraduate comparison group. However, by the end of the first year of law school, law students’ subjective well-being dropped significantly. Further, at the end of first year, law students were more depressed and experienced more physical illness than before starting law school. These changes were still evident when the same students were assessed again in their second and third years of law school. Sheldon and Krieger found similar results assessing law students at another law school, providing further evidence of their results. Sheldon and Krieger used the Self-Determination Theory (SDT) as their guiding framework, and therefore also assessed factors such as intrinsic motivation. Sheldon and Krieger define intrinsic motivation as one’s own desire to perform a task because he/she finds it interesting, important, and meaningful. In contrast, extrinsic motivation is when one is driven to perform in order to reach some external goal, such as a grade or payment. Sheldon and Krieger found that students’ intrinsic motivation dropped significantly over the course of students’ first year. Because the current student assesses stressors, SDT and related factors were not incorporated. 7. See Sheldon & Krieger, Does Legal Education Have Undermining Effects on Law Students?, supra note 4, at 280; Sheldon & Krieger, Understanding the Negative Effects of Legal Education on Law Students, supra note 4, at 889–90. 8. See Pritchard & McIntosh, supra note 4, at 734.


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be used by law schools to identify at-risk students. C. Proposed Stressors in Law School Non-empirical, anecdotal literature describes the stressors in law school. 9 Although these stressors may be present in other academic environments, academic literature has not yet investigated their impact on law students. The present study draws on the non-empirical literature, which was also used to develop the Law School Stressor Measure (LSSM). The main stressors identified in the non-empirical literature include: workload, job insecurity, grading, course structure and the Socratic Method, inadequate mentoring, and peer problems. The strenuous workload in law school is commonly criticized. 10 Due to the workload, law students may be unable to engage in healthy behaviors, like getting enough sleep and exercising. 11 Intense time demands may impair relationships and cause social isolation. 12 When students do engage in leisure, they feel guilty about not studying and experience preoccupation with their academic responsibilities. 13 Law students report experiencing stressors about their grades and jobs. 9. G. Andrew H. Benjamin et al., The Role of Legal Education in Producing Psychological Distress Among Law Students and Lawyers, AM. B. FOUND. RES. J., 225 (1986); Ann L. Iijima, Lessons Learned: Legal Education and Law School Dysfunction, 48 J. Legal. Educ. 524 (1998); Daniel M. McIntosh et al., Stress and Health in 1st-Year Law Students: Women Fare Worse, 24 J. APPLIED SOC. PSYCHOL. 1474 (1994); Suzanne C. Segestrom, Perceptions of Stress and Control in the First Semester of Law School, 32 WILLAMETTE L. REV. 593 (1996); Richard Sheehy & John J. Horan, Effects of Stress Inoculation Training for 1st-Year Students, 11 INT. J. STRESS MGMT. 41, 42–43 (2004); Peter Kutulakis, Stress and Competence: From Law Student to Professional, 21 CAP. U. L. REV. 835 (1992). It is not possible to document all of the criticisms that have been lodged against law schools. However, our review identified several main areas including workload, job insecurity, grading, course structure and the Socratic Method, inadequate mentoring, and peer problems. There have been a number of important pieces written by the legal community describing criticisms and problems within the legal educational system. While there are a number of important benefits to these pieces, they do not involve data collected in objective, systematic ways. For instance, Iijima’s essay provides thoughtful, reflective observations of the law school environment. However, Iijima does not provide evidence based on systematic, quantitative data. Other works involve methodological flaws that make connecting law school stressors and psychological outcomes difficult. For instance, McIntosh et al., used empirical methods to study female law students’ experiences. However, the stressor measures used are confounded because they simultaneously ask about the stressor and the outcome of the stressor. For example, McIntosh et al., used this item: “I worry about lining up a job for the summer.” Here, the item asks about the stressor (finding a summer job) while also assessing the psychological outcome (worrying about it). Other items used in that study reflect subjectivity, a direct contrast to psychological literature emphasizing the assessment of the stressor free from appraisals. One item used by McIntosh et al., is: “When I’m speaking in class, I feel that other students are forming negative impressions of me.” Here, students are not providing objective information about the stressor, but about their impressions of how other students perceive them. Taken as a whole, it is not possible to draw conclusions about the law school environment and how it affects students. 10. James R. Elkins, The Quest for Meaning: Narrative Accounts of Legal Education, 38 J. LEGAL EDUC. 577 (1988); see Iijima, supra note 9, at 527; Gerald F. Hess, Heads and Hearts: The Teaching and Learning Environment in Law School, 52 J. LEGAL EDUC. 76 (2002); Kutulakis, supra note 9, at 837; Bridget A. Maloney, Distress Among the Legal Profession: What Law Schools Can Do About It, 15 NOTRE DAME J.L. ETHICS & PUB. POL’Y. 314 (2001). 11. See Iijima, supra note 9, at 529; Kutulakis, supra note 9, at 837; Lawrence S. Krieger, What We’re Not Telling Law Students, and Lawyers, That They Really Need to Know: Some Thoughts-in-action Toward Revitalizing the Profession From Its Roots, 13 J. L. & HEALTH 8; Maloney, supra note 10, at 314. 12. See Elkins, supra note 10, at 586; Hess, supra note 10, at 77–78; Maloney supra note 10, at 318. 13. See Elkins, supra note 10, at 586.


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The job market for attorneys is highly competitive and there are not enough jobs for all lawyers. 14 Law students believe that their grades, particularly in their first year, will determine their career trajectory. 15 In fact, students with top grades are more likely to be selected for their school’s law review or interviews with illustrious firms. 16 Students’ debt may amplify these concerns.17 Consequently, many law students may feel pressure to earn exceptional grades in order to find a job. However, grading practices within law school have been criticized, for reasons that are described next. The grading practices in law schools may negatively impact students. 18 Grade curving is common and involves setting a class mean, requiring a mandatory percentage the class receiving each letter grade, or capping how many students can receive each letter grade. 19 Instead of meeting objective standards, students must outperform their peers. These practices create competition, not collaboration or collegiality, among students. 20 Simultaneously, professors’ expectations are unclear. 21 Many law classes have few or one assessments, such as one exam. 22 Therefore, students cannot change their study strategies until their grade is already determined. Many law professors teach with dialectical methods, including the Socratic Method. 23 The Socratic Method typically involves selecting students, often randomly, in class to deconstruct a case or issue to identify weaknesses

14. American Bar Association Task Force on the Future of Legal Education, Draft Report and Recommendations AMERICAN BAR ASSOCIATION, at 34 (2013) [https://perma.cc/6KX7-5TKB]. See Elkins, supra note 7, at 586; Mitu Gulati, Richard Sander, & Robert Socloskie, The Happy Charade: An Empirical Examination of the Third Year of Law School, 51 J. LEGAL EDUC. 238 (2001); Kutulakis, supra note 9, at 838; Krieger, supra note 11, at 6, 19. In 2013, The American Bar Association’s Task Force on the Future of Legal Education presented a preliminary document outlining some of the chief concerns facing legal education. The concerns centered around whether law school is too expensive, resulting in large student loans, and inadequate employment opportunities upon completion of law school. Among many other recommendations, the ABA emphasized the need for law schools to critically examine their programs and cultures, and instead innovate to better prepare graduates for the changing needs of the workforce. 15. See Elkins, supra note 10, at 590; Iijima, supra note 9, at 527; Hess, supra note 10, at 78; Maloney, supra note 10, at 327–28; Krieger & Sheldon, supra note 4, at 576. 16. See Elkins, supra note 10, at 592; Gulati et al., supra note 14, at 239. 17. See Krieger & Sheldon, supra note 4, at 578. 18. See Iijima, supra note 9, at 527; Hess, supra note 10, at 78; Krieger, supra note 11, at 12; Maloney, supra note 10, at 308, 313, 327; Robert P. Schuwerk, The Law Professor as Fiduciary: What Duties Do We Owe to Our Students?, 45 S. TEX. L. REV., 789 (2004). 19. Nancy H. Kaufman, A Survey of Law Schools’ Grading Practices, 44 J. LEGAL EDUC. 417, 421 (1994). 20. See Elkins, supra note 10, at 590; Iijima, supra note 9, at 527; Hess, supra note 10, at 78; Krieger, supra note 11, at 11, 19. 21. See Iijima, supra note 9, at 528; Hess, supra note 10, at 78; Maloney supra note 10, at 325–26; Schuwerk, supra note 18, at 778–79. 22. See Maloney supra note 10, at 325–26; Schuwerk supra note 18, at 778–79. 23. Patricia Mell, Taking Socrates’ Pulse: Does the Socratic Method Have Continuing Vitality in 2002?, 81 MICH. B. J. 46 (2002). Mell describes the most common concerns about the Socratic Method, while also suggesting that the practice is benefits students by allowing them to deconstruct the assumptions of various arguments as well as how it can improve learning outcomes in large law school classes. Mell suggests that the Socratic Method can be alienating for students, but particularly female or racial/ethnic minority students. Mell cites surveys that report that use of the Socratic Method, at least in its most traditional form, has declined. See Iijima, supra note 9, at 528; Hess, supra note 10, at 81.


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in the student’s reasoning and preparation. 24 However, many students find this anxiety-provoking or humiliating. 25 The Socratic Method may be especially detrimental for women and students of color. 26 Law students are also faced with the challenging of adapting their academic strategies and professionalism for law school and their careers. 27 However, many students do not know how to succeed in law school nor the legal profession, and do not have a mentor. 28 Students may also perceive professors as intimidating or inaccessible, possibly because some law professors do not believe mentoring students is part of their job. 29 Therefore, students may be unable to access necessary career and professional development information. Problems with classmates has been identified as a stressor experienced by law students. In an informal survey, Traiger and Weddle found that 47% of law students had experienced at least one incident of peer mistreatment in the past six months. 30 Examples of peer mistreatment include mocking, criticism, making comments about one’s personal life, playing practical jokes on others, bullying on social media, and name calling. 31 Peer mistreatment may be heightened for students based on their sexual orientation, sex, and race/ethnicity. 32 Students’ use of licit and illicit substances to enhance academic performance may also increase tension between peers. 33 The exact impact of peer mistreatment is unknown, but it may negatively impact students. For instance, Pritchard and McIntosh found socially isolated law students experienced more mental health problems than those with more social support. 34

24. See Mell, supra note 23, at 46. 25. See Hess, supra note 10, at 81; Kutulakis, supra note 9, at 836–37; Maloney supra note 10, at 324– 25. 26. Katherine S. Mangan, Lani Guinier Starts Campaign to Curb Use of the Socratic Method, 43 CHRON. HIGHER EDUC., A13 (1997); Elizabeth Mertz, Wamucii Njogu, & Susan Gooding, What Difference Does Difference Make? The Challenge for Legal Education, 48 J. LEGAL EDUC. 1, 2–4, 17–18 (1998). 27. Kutulakis, supra note 9, at 840; see Maloney, supra note 10, at 325–326. 28. Kutulakis, supra note 9, at 840; see Maloney, supra note 10, at 315; Maloney, supra note 10, at 315; Schuwerk, supra note 18, at 759. 29. See Maloney, supra note 10, at 315; Schuwerk, supra note 18, at 759. Schuwerk argues that there is a fundamental flaw in the reasoning among many law professors in the U.S. in that they do not perceive that their students will not necessarily follow academic career paths. Schuwerk suggests that students need increased mentoring in pursuing applied careers, including the practice of law. Further, according to Schuwerk, many law professors perceive the law professor-law student relationship as inherently hierarchical, with thereby implying that the needs of the professors trump those of students. Schuwerk proposes that law professors believe that transmitting academic information sufficiently fulfills their duties to their students. Instead, Schuwerk states that law students need additional guidance and socialization into the world of practicing attorneys. Without buy-in from law professors, students are missing an inherently important part of their legal training. 30. Jeff Traiger & Daniel B. Weddle, Cruel Curriculum: Peer on Peer Abuse in Law Schools, 22 TEMP. POL. & CIV. RTS. L. REV. 301 (2013). 31. See Traiger & Weddle, supra note 12, at 314–17. 32. See Traiger & Weddle, supra note 12, at 317–18; Morrison Torrey, Jennifer Ries, & Elaine Spiliopoulos, What Every First-Year Female Law Student Should Know, 7 COLUM. J. GENDER & L. 267 (1997). 33. See Oguntoyinbo, supra note 1, at 21. 34. See Pritchard & McIntosh supra note 4, at 737.


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This literature, while descriptive, is non-empirical and does not objectively measure the law school environment. 35 Thus, we used the anecdotal literature as a basis for developing items for the LSSM. In addition to the anecdotal literature, this study relied on psychological theories of stress, described next, to create and ground items. D. Theoretical Models of Stress Experiencing stressors is associated 36 with immune suppression 37 illdisease, 39 and psychological symptoms. 40 However, methodological limitations make firmly establishing a causal relationship between experiencing stressors and psychological symptoms difficult. 41 In order to study the relationship between stressors and psychological symptoms, researchers must carefully consider psychological theories of stress and associated measurement practices. There are two primary epistemologies for conceptualizing stress, which have important implications for how stressors are measured. 42 ness, 38

35. See Sheldon and Krieger, Does Legal Education Have Undermining Effects on Law Students?, supra note 4. As also explained by Sheldon and Krieger, even though declines in mental health co-occur with law school, it does not mean that law school causes these changes or that law school stressors can predict which students will experience mental health issues. 36. Many studies examining the relationship between the experience of stressors and physical and mental health outcomes are correlational in nature, therefore suggesting associations, rather than causal relationships. In order to determine a causal relationship between two variables, an experimental method using random assignment and manipulation under the control of the researcher is necessary. By nature, randomly assigning participants to experience stressors has ethical and practical limitations. See BETH MORLING, RESEARCH METHODS IN PSYCHOLOGY: EVALUATING A WORLD OF INFORMATION 275, 282 (2nd ed. 2015). Further, experimental manipulations of stress may not resemble how stressors are experienced in the “real-world.” Consequently, the majority of studies measure the relationships between stressors and other variables as they naturally occur. In addition, stress measurement is difficult and there are a number of criticisms of the existing stressor measures. The following offer a more thorough review of these critiques. See Kathryn E. Grant et al., Stressors and Child and Adolescent Psychopathology: Measurement Issues and Prospective Effects, 33 J. OF CLINICAL. CHILD AND ADOLESCENT. PSYCHOL. 412, 418–21 (2004); Scott M. Monroe et al., Prediction of Psychological Symptoms Under High-Risk Psychosocial Circumstances: Life Events, Social Support, and Symptom Specificity, 92 J. OF ABNORMAL PSYCHOL. 338 (1983). 37. Suzanne C. Segerstrom & Gregory E. Miller, Psychological Stress and the Human Immune System: A Meta-Analytic Study of 30 Years of Inquiry, 130 PSYCHOL. BULL. 601 (2004). 38. Sheldon Cohen & Gail M. Williamson, Stress and Infectious Disease in Humans, 109 PSYCHOL. BULL. 5 (1991); Sheldon Cohen, William J. Doyle & David P. Skoner, Psychological Stress, Cytokine Production, and Severity of Upper Respiratory Illness, 61 PSYCHOL. MED. 175 (1999). 39. See Cohen & Williamson, supra note 38. 40. See Grant et al., supra note 36; Monroe et al., supra note 36. 41. See Grant et al., supra note 36, at 412–25; Grant et al., Stressors and Child and Adolescent Psychopathology: Moving from Markers to Mechanisms of Risk, 129 PSYCHOL. BULL. 447 (2003); Constance Hammen, Stress and Depression, 1 ANN. REV. CLINICAL. PSYCHOL. 293 (2005); Kenneth S. Kendler et al., Life Dimensions of Loss, Humiliation, Entrapment, and Danger in the Prediction of Onsets of Major Depression and Generalized Anxiety, 60 ARCHIVES. GEN. PSYCHIATRY 795 (2003); Richard S. Lazarus, Theory-Based Stress Measurement, 1 PSYCHOL. INQUIRY (1990). 42. See Lazarus, supra note 41, at 4–5. In general, Lazarus theorizes that stress is not merely a byproduct of some type of adversity, but is instead intrinsically related to: a) how the person thinks about the stressor, and b) what resources the individual believes he/she has at his/her disposal to cope with them. Critics of this model, including researchers who subscribe to the stimulus-response model, take issue with these assumptions. For example, some stressors, such as natural disasters, are expected to be stressful regardless of how one appraises them. Further, the assumption that distress is produced by how one thinks about the stressors and not the stressor itself essentially places the burden of the distress on the individual experiencing it. In an extreme


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In the stimulus-response model, stressors are defined as events that “commonly produce psychological or physical distress in the organism.” 43 In this model, researchers attempt to understand the direct effects of environmental stressors on individuals. Therefore, stressor measures using this model are aimed at assessing the stressor only. 44 For example, researchers may ask participants the frequency of occurrence of specified events. Other processes, like perceptions of the stressor, reactivity, and coping strategies, are measured separately to identify their independent effects. An alternate theory, the transactional model, suggests stress is inherently related to individuals’ appraisals of stressors. 45 In other words, events are not stressful, but cause stress because of the individual’s perceptions of them. For instance, participants may be asked: How much of a hassle was this (specific factor) for you today? 46 This item assesses how troubling the event was, not whether the event was experienced. Therefore, it is impossible to know how much of the impact of the stressor was due to the stressor itself or one’s interpretation. The simultaneous assessment of stressors and responses is problematic in the law school literature. For instance, McIntosh and colleagues included items such as “I get anxious when I think I’m about to be called on in class.” 47 Because this item assesses both the symptom (getting anxious) and the stressor (being called on in class), it is unclear whether the law school environment caused anxiety in students. The stimulus-response model was used in this study to determine how law school stressors typically impact individuals experiencing them. We acknowledge that numerous psychological processes are involved in the lived stress experience. However, by measuring stressors separately from other processes, their direct impact can be assessed. Further, several other measures of stressors in specific academic environments have been developed. 48Therefore, example, someone experiencing racial discrimination would be expected to feel stressed, regardless of how he/she appraised the discrimination. Another criticism of Lazarus’s model is that secondary processes, including appraisals, should be studied separately from other components of the relationship. For example, many researchers using the stimulus-response model will assess (a) the extent to which an individual has experienced a stressor, (b) cognitive or other psychological processes associated with experiencing the stressor, and (c) the impacts of the stressors separately from one another to reduce measurement confounding. 43. Stevan E. Hobfoll, Ralf Schwarzer & Kyum Koo Chon, Disentangling the Stress Labyrinth: Interpreting the Meaning of the Term Stress as it is Studied in Health Context, 11 ANXIETY STRESS AND COPING 183 (1998); Thomas Holmes & Richard Rahe, The Social Readjustment Rating Scale., J. PSYCHOSOMATIC RES. 213 (1967). Other theoretical models of stress exist and are more fully described by Hobfoll et al. However, these two models capture the essential differences in ways of conceptualizing stress. The stimulus-response model was first introduced by Holmes and Rahe (1967), and assumes that the frequency of common stressors can be assessed separately from the impact of those stressors. To date, there are no empirical studies examining the objective features of the law school environment. Thus, it is not possible to draw conclusions about how the law school environment affects students. 44. See Grant et al., supra note 41, at 447; Hobfoll et al., supra note 43, at 183. 45. See Lazarus, supra note 41, at 3–4. 46. Anita DeLongis, Susan Folkman & Richard Lazarus, The Impact of Daily Stress on Health and Mood: Psychological and Social Resources as Mediators, 54 J. PERSONALITY AND SOC. PSYCHOL. 495 (1988). 47. See McIntosh et al., supra note 9, at 1498; Pritchard & McIntosh supra note 4, at 732–33. 48. A number of field-specific stressor measures have been developed outside of law school, aiming to


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the current investigation utilizes the stimulus-response model of stressors in order to develop a measure of stressors unique to the law school environment. E. The Current Investigation It is unclear how law school affects students because a psychometrically and theoretically-sound measure of law school stressors does not exist. Thus, the goal of this study was to develop the Law School Stressor Measure (LSSM) and present its psychometric properties. In Study 1, we used principal components analysis (PCA) to select items that loaded on each factor. 49 Next, gender and ethnicity effects on LSSM scores were examined. We also evaluated the LSSM’s discriminant and predictive validity and the test-retest reliability. In Study 2, a random subset of Study 1 participants completed the LSSM to establish test-retest reliability. II. STUDY 1 METHODOLOGY Study 1 investigated the factor structure of the 82-item version of the LSSM with current first, second and third year law students. Effects of race/ethnicity and gender were also examined. To evaluate the LSSM’s validity, we examined whether the LSSM was (a) predictive of GPA, suggesting that students experiencing more law school stressors struggle more academically and (b) significantly but weakly associated with general life stressors because law school stressors should be related, yet distinct from, stressors in other areas of students’ lives.

assess the particular stress unique to specific academic environments. These include the following: Nancy Cahir & Robin D. Morris, The Psychology Student Stress Questionnaire, 47 J. CLINICAL PSYCHOL. 414 (1991); Jenny Firth, Levels and Sources of Stress in Medical Students, 292 BRIT. MED. J. 1178 (1986); Sarah Reed & Peter R. Giacobbi, The Stress and Coping Responses of Certified Graduate Athletic Training Students, 39 J. ATHLETIC TRAINING 193 (2004); Shannon M. Suldo et al., Development and Initial Validation of the Coping with Academic Demands Scale: How Students in Accelerated High School Curricula Cope with School-related Stressors, 33 J. PSYCHOEDUCATIONAL ASSESSMENT 339 (2015), Jiandong Sun et al., Educational Stress Scale for Adolescents: Development, Validity, and Reliability with Chinese Students, 29 J. PSYCHOEDUCATIONAL ASSESSMENT 534 (2011). Thus, there is a precedent for developing and using stressor measures for specific educational settings. 49. MARJORIE A. PETT, NANCY R. LACKEY & JOHN J. SULLIVAN, MAKING SENSE OF FACTOR ANALYSIS: THE USE OF FACTOR ANALYSIS FOR INSTRUMENT DEVELOPMENT IN HEALTH CARE RESEARCH 2, 88–91, (2003). In this study, a factor analysis was conducted in order to better understand how specific items on the Law School Stressor Measure were (a) interrelated, and (b) could be reduced to a smaller set to increase the feasibility and applicability of this measure in future research. Because the specific number of underlying factors was unknown prior to analyses (since this is the first study of its kind), an exploratory factor analysis was conducted (as opposed to a confirmatory factor analysis). The two most commonly used forms of exploratory factor analysis are principal components analysis and principal axis factoring. Principal components analysis (PCA) extracts the total variance of all items and can easily identify redundant items, and thus is often used in item reduction. Because this study aims to develop a measure with a reasonable length that can be easily administered, PCA was first used to achieve a shorter scale that could capture substantial item variances. PAF extracts the common variance among items and is used to better understand the factor structure. We conducted a PAF to double check the factor structure obtained from the PCA results and confirmed the same factor structure.


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A. Participants Participants were recruited from two law schools (Schools A and B) in a large, Midwestern city. At that time, School A was ranked in the top 100 law schools in the U.S., and School B was ranked in the top 20. 50 Juris Doctor (J.D.) students participated in Study 1 in their spring semester. All measures and procedures were approved by the authors’ university’s institutional review board. Participants received an email from a law school administrator describing the study with instructions. Participants were told they would receive a $25 gift card to their university’s book store upon completion. Participants consented to releasing their transcripts. A total of 322 participants completed the LSSM and 316 participants completed the full study. Of the 316 participants who completed the full study, 307 (97%) completed the study online and 9 (3%) used paper measures. There were no significant differences in background characteristics based on how participants completed the study. Demographically, the sample resembled the J.D. population at each respective law school. Of the 316 participants (Table 1) who completed the study, the majority were White/European American (70%) and female (58%). Participants ranged from 21 to 43 years of age, with a mean of 26.61 (SD = 3.16). 51 B. Measures Academic Achievement. Semester grade point average (GPA) was collected from participants’ transcripts at the end of the semester. Most law course grades are determined by one examination administrated at the end of the semester. 52 Thus, GPA was used to evaluate the predictive validity of the LSSM. GPAs can range from 0.0 to 4.0 (4.0 = A, 3.67 = A-, etc.). Brief Symptom Inventory. 53 The BSI is a normed, 53-item self-report measure of psychological symptoms in individuals aged 13 years or older. Participants are asked to rate how distressed they have been by each of the 53 symptoms over the past 7 days on a 5-point Likert rating scale: 0 = not at all, 1 50. America’s Best Graduate Schools 2008: Complete Guide to Law Schools, U.S. NEWS AND WORLD REPORT (2008) http://www.usnews.com/usnews/edu/grad/rankings/law/lawindex_brief.php [https://perma.cc/DBM6-DBDF]. 51. See Morling supra note 36, at 555. In statistics, a mean represents an average of the values used in the analysis. The standard deviation is an average of how different each score is from the mean. The standard deviation can be used to interpret the variability within the data since a mean can be affected by extreme scores, outliers or variability in general. 52. See Maloney, supra note 10, at 325–26. 53. The BSI is a widely-used assessment of psychological symptom and has been normed using large samples of adult (psychiatric) inpatient and adult nonpatient populations. Thus, comparisons direct comparisons between law students’ psychological symptoms and the larger adult population in the U.S. are possible. All scoring in this study was based on the BSI manual. Leonard R. Derogatis, Brief Symptom Inventory: Administration, Scoring and Procedures Manual (1993). An introduction to the BSI was written prior to the publication of the official scoring manual. Leonard R. Derogatis & Nick Melisaratos, The Brief Symptom Inventory: An Introductory Report 13 PSYCHOL. MED. 595 (1983).


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= a little bit, 2 = moderately, 3 = quite a bit, and 4 = extremely. The BSI includes twelve dimensions, including three global indices and nine symptom subscales. In this study, we used the Positive Symptom Distress Index (PSDI) to measure of overall psychological distress. PSDI scores were calculated and converted to T scores (based on norms in adult, nonpatient populations) using the instructions in the BSI manual. According to Derogatis, T scores values indicating a clinical diagnosis for a psychological disorder have not yet been established. 54 However, a T score of 60 indicates that participant is in the 84th percentile and a T score of 70 indicates that the participant is in the 98th percentile for that dimension. Demographics. Participants self-reported their race/ethnicity, gender, institution, age, and year in school. Law School Stressor Measure (LSSM). The LSSM was developed and refined based on existing anecdotal literature on law student stressors, a qualitative analysis of graduating law students’ self-reported law school stressors, and feedback from stress assessment experts. 55 LSSM items were developed using the stimulus-response model as a theoretical orientation. 56 Thus, each item assessed one objective stressor experienced by students in the law school setting and not other psychological processes, like appraisals. The LSSM asks participants to rate the frequency of the occurrences of stressors during the students’ current academic term using this scale: 0 = never (0% of the time), 1 = infrequently (25% of the time), 2 = sometimes (50% of the time), 3 = often (75% of the time), 4 = always (100% of the time). The initial version of the LSSM included 150 items. Team members dropped 68 items because they were redundant or less relevant. The remaining 82 items were subjected to exploratory PCA. Social Readjustment Rating Scale-Revised. 57 The SRRS-R measures general life stressors and was used to establish the LSSM’s discriminant validity. The SRRS-R includes 51 events such as “Divorce” and “Change in residence.” Participants rate the frequency they experienced each event in the past

54. See Derogatis, supra note 53. 55. Andrea M. Flynn, Katie J. Kizer, & Bernadette Sánchez, Accounts from the Field: Law Students’ Stress in Their Own Words, under review. This manuscript is currently under review and describes qualitative analyses of graduating law students’ self-reported stressors. The respondents were all third-year law students reflecting on what was stressful about law school. Our analyses showed that students’ responses generally fell into one of these categories: law school-life balance; adjustment to law school; inadequate financial resources; problems with faculty and administration; the physical setting of their law school; questioning in class and the Socratic Method; grading and competition for grades; the law school curriculum; careers and job searching; and the bar examination. These results were used to generate items for the LSSM. 56. See Grant et al., supra note 41, at 447, Hobfoll et al., supra note 43, at 183. 57. Charles J. Hobson et al., Stressful Life Events: A Revision and Update of the Social Readjustment Rating Scale, 5 INT’L. J. OF STRESS MGMT 1, 1–23 (1998); Charles J. Hobson & Linda Delunas, National Norms and Life Event Frequencies for the Revised Social Readjustment Rating Scale, 8 INT’L. J. OF STRESS MGMT 310 (2001).


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12 months. The frequency of each endorsed event is multiplied by the standardized “stressfulness” weight for that item. 58 Weighted items are summed to calculate SRRS-R scores. C. Procedure Participants consented to the study, then completed the LSSM, SRRS-R, and demographic measure in the middle of their spring semester. Students’ GPAs were obtained at the end of the semester. Participants completing paper versions of study measures did so privately at their law school. Procedures for completion using paper measures were otherwise equivalent. Participants’ responses were coded with a unique, randomly assigned identification number to match Study 1 and Study 2 responses. III. STUDY 1 RESULTS A. Exploratory PCA 59 An exploratory factor analysis with PCA was run to examine the relevance of items to factors and the factor structure. Tests of factorability were examined before conducting the analysis. The Bartlett’s test of sphericity was (χ2 (3321) = 12884.21, p < .000), and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy was .875. Individual MSA values ranged from .75 to .94, with one item below .70 (.63) but still in the acceptable range. Therefore, common variance between items was strong. The scree plot and analysis of variance reflected a 5-factor solution. Preserving 5 factors, a PCA with Promax Rotation was repeated, deleting items for any of these three reasons: loading on more than one factor, loadings below |.40|, or lack of conceptual fit. A total of 30 items were deleted at this stage, leaving 52 items, loading on five factors. The structure matrix, including items loading above |.40|, is listed in Table 2. Of the 52 items, 27 are reverse scored (lower scores reflect higher frequency). LSSM subscale scores are calculated

58. See Hobson et al., supra note 57, at 7; Hobson & Delunas, surpa note 57, at 310. 59. See Pett et al., supra note 49. The LSSM was developed and evaluated using the guidelines specified in the widely-used text written by Pett, et al. More specifically, items were developed using legal scholarship on law school stressors, academic literature on stress and stress measurement, and experts in the field of stress research. According to Pett et al., exploratory factor analysis involves the following steps once the items are developed: (1) assess the correlation matrix, (2) extract the factors, (3) rotate the factors, (4) refine the solution, (5) interpret the findings, and report the results. In this study, we tested the correlation matrix by using Bartlett’s test of sphericity and Kaiser-Meyer-Olkin Measure of Sampling Adequacy. To extract the factors, we used a scree plot. The scree plot suggested five underlying factors. We then rotated the matrix. Rotation is used to find the simplest factor structure possible, specifically by maximizing high loadings and minimizing low loadings. In this study, we elected to use Promax rotation, which is an oblique rotation, since our factors were correlated. We further refined our solution by deleting items if they loaded on more than one factor, had low factor loadings, or did not appear to be meaningfully or theoretically related to the factor. The remainder of the results in this study explain our interpretation of our findings, particularly whether the LSSM showed evidence of reliability and validity.


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by summing participants’ responses on that factor’s items, then dividing by the number of items of that subscale. LSSM composite scores are calculated by adding all 52 items and dividing by 52. Higher LSSM scores indicate higher stressor frequency. Next, labels were given to each factor. A Principle Axis Factoring (PAF) was conducted to examine the factor structure of these 52 items, resulting in a very similar factor structure. 60 These five factors (see Table 3) account for a moderate amount of variance (41.14%) of the 52 items. The interfactor correlations of the LSSM subscales are all statistically significant and low in magnitude (see Table 4), suggesting the factors assess related, yet distinct, stressors. The effects of race/ethnicity and gender on the LSSM composite were examined using Analysis of Variance (ANOVA). 61 No significant differences were found for gender, F (2, 317) = 2.867, p > .05, nor race/ethnicity F (4, 317) = 1.839, p > .05. A Multivariate Analysis of Variance (MANOVA)62 was used to evaluate whether there were significant differences in the five subscales of the LSSM due to gender and race/ethnicity. There was not a significant effect for gender (Wilks’ Λ = .95, F (10, 606) = 1.496, p > .05), nor the interaction between race/ethnicity and gender (Wilks’ Λ = .08, F (20, 1224) = 1.212, p > .05). However, significant racial/ethnicity differences were found (Wilks’ Λ = .87, F (20, 1006) = 2.175, p < .01). Univariate tests showed that significant racial/ethnic differences were only found for the LSW factor (F (4, 311) = 3.39, p ≤ .01). Post-hoc Tukey tests (Table 4) showed Indian/other participants scored significantly lower than Hispanic/Latino/a participants (p < .05) on the LSW. No other significant pairwise comparisons were found. Since the difference in these groups represented only one significant univariate test and may be due to small sample sizes, it was determined that race/ethnicity did not need to controlled for in subsequent analyses. B. Predictive Validity Participants completed the LSSM during the academic semester. Law students’ grades are often determined by a single assessment at the end of the semester. 63 Thus, GPAs calculated at the end of the semester represent a future event and were used to evaluate the predictive validity of the LSSM. Two re-

60. The results of the PAF were very similar to the results of the PCA, providing evidence for the obtained factor loadings and structures. 61. An ANOVA is used when researchers are evaluating whether differences exist between 2 or more groups on a continuous outcome measure. See Morling, surpa note 36, at 479. 62. A MANOVA is used when groups of 2 or more are being compared on at least 2 dependent variables that are likely to be related. See ARTHUR ARON, ELAINE N. ARON, & ELLIOT J. COUPS, STATISTICS FOR PSYCHOLOGY 644 (4th ed. 2006). 63. See Maloney, supra note 10, at 325–26.


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gressions were conducted using the LSSM composite and subscales as predictors of GPA. 64 A simple linear regression was calculated to predict GPA based on LSSM composite scores. A significant regression showed that higher stressors predicted lower GPAs (F (1, 317), = 41.08, p < .001, β = -.38), with an R2 of .12. Before conducting regression analyses with the LSSM subscales, we determined they were not affected by multicollinearity. The multiple linear regression analysis using the LSSM subscales to predict GPA was statistically significant (see Table 5). Four LSSM subscales significantly predicted GPA, including IS, GR, PR, and CD with higher levels of stressors predicting lower GPAs. Predictive validity of the LSSM was evaluated by examining how well the LSSM composite and subscales as predictors of the BSI PSDI. Results showed three LSSM subscales (IS, LSW, PR, see Table 7) significantly predicted PSDI scores, accounting for 22% of variance in students’ PSDI scores. The LSSM composite was also a significant predictor (see Table 8), accounting for 18% of variance in PSDI scores. C. Discriminant Validity 65 A correlation was used to evaluate whether the LSSM measures a distinct construct from the SRRS-R. Although both measure stressors, the LSSM is intended to measure law school stressors only; other stressors are beyond the scope of the LSSM. The SRRS-R measures stressors in other areas of students’ lives, like the death of a family member. Consistent with our prediction, we found significant, but weak (r = .12-.26), correlations between the LSSM and SRRS-R (see Table 3), providing evidence of the LSSM’s discriminant validity. IV. STUDY 2 METHODOLOGY Test-retest reliability of the LSSM was examined in Study 2 using a randomly selected subsample of participants from Study 1. We predicted that LSSM scores from Study 1 would be strongly correlated with LSSM scores in Study 2.

64. SUSAN A. NOLAN & THOMAS E. HEINZEN, ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES 370–71 (2d ed. 2014). According to Nolan and Heinzen, regressions are used to test how well an independent variable predicts a dependent variable (the outcome variable). In this case, we were interested in examining if, and to what extent, law school stressors predict GPA and psychological symptoms. 65. See Morling, supra note 36, at 145–46. According to Morling, discriminant validity is established by examining how a variable of interest is different from other variables. For instance, in this study, we were interested in understanding the effects of law school stressors only. We wanted to ensure that we were only measuring law school stressors, and not other stressors students might experience in other areas of their lives (such as a breakup). In doing so, we can examine whether law school stressors predict outcomes that are of interest to students, faculty and administrators, such as GPAs and students’ mental health.


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A. Participants A total of 80 Study 1 (Time 1) participants were randomly selected for participation in Study 2 (Time 2), and 69 participants (83.1% of those selected) completed the Study 2 (22% of the Study 1 participants). Study 2 participants were slightly more likely to be female, White or African American, and from School B (see Table 1). Participants completed Study 2 an average of 21.78 (SD = 10.08) days after Study 1. B. Procedure The online data collection tool was used to randomly select participants for Study 2 following completion of Study 1. All Study 2 participants completed the LSSM using the same IRB-approved website that was used in Study 1. After completion, participants were issued a $20 gift card to their university’s book store. C. Measures Law School Stressor Measure (LSSM). The LSSM used in Study 1 was administered in Study 2. V. STUDY 2 RESULTS Correlation coefficients between Study 1 (Time 1) and Study 2 (Time 2) for the LSSM were statistically significant and ranged from .71 to .90 (see Table 6). 66 The LSSM at Study 2 was also internally consistent. Cronbach’s alpha was .92 for the LSSM composite and ranged from .76 to .89 for the subscales. 67 VI. DISCUSSION The purpose of this study was to develop and evaluate the LSSM so it can be used in additional law school settings. Our results show the LSSM is a valid, reliable, internally consistent tool. Our findings were generally consistent with our predictions, with some slight differences from our expectations in terms of our PCA results. One of the most important findings from this study is that one-third of the sample experienced significant psychological distress. Furthermore, stressors 66. See id. at 129. According to Morling, psychological measures should show adequate test-retest reliability, or consistency, across reasonable periods of time. Significant, large correlations between the two administrations of the LSSM provide evidence that the LSSM is stable and consistent. 67. See id. at 129, 134–35. Internal reliability refers to how consistent a scale is across the items of the scale. Id. Internal reliability provides further evidence of a scale’s reliability. The most commonly used test of internal reliability is Cronbach’s alpha. The minimum requirement for most measures used in psychological science is .70. Id. In this study, the Cronbach’s alphas far exceeded this minimum requirement, suggesting the LSSM is internally consistent.


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related to instrumental support, law school workload, and peers were directly and significantly predictive of students’ psychological symptoms. Taken as a whole, law school stressors also had a significant impact on students, with a 99.9% probability that the relationship between law school stress and students’ psychological distress was not due to chance or error. Thus, law schools would benefit greatly from using the LSSM to determine the level of stressors in their law schools and finding ways to reduce them. This study also showed evidence of the predictive validity of the LSSM in terms of students’ GPAs. Specifically, the LSSM composite and four of five LSSM factors (IS, GR, PR, and CD) significantly predicted GPA. Thus, students who report stress within the law school environment are struggling academically. Surprisingly, LSW did not predict GPA, possibly because the workload for law students is universally strenuous. 68 The LSSM shows other strong psychometric properties. As predicted, the LSSM displayed discriminant validity by correlating weakly with other life stressors. Thus, the LSSM measures objective properties of law school stressors, and not problems outside of law school. Except for one minor difference, perhaps because of small sample sizes, the LSSM seems to provide similar results for students regardless of sex and race/ethnicity. The LSSM is reliable, as demonstrated by significant T1 to T2 correlations and robust Cronbach’s alphas. There are limitations to this study. Future studies should examine the LSSM at schools with more diverse rankings and in additional geographical areas. Further, although this study had adequate sample-to-item ratios, a larger sample would be helpful. Finally, we do not address the complex ways that stressors, appraisals, and coping, among other processes, impact students. The results of this study show that the LSSM is a parsimonious tool to assess how students experience law school. Future studies can test whether law school stressors cause students’ psychological symptoms and the role of other psychological processes. In addition to using the LSSM for research, law schools can use it to identify at-risk students, evaluate programs, tailor stress-reduction initiatives and improve conditions in their law schools. In fact, the authors of this study invite interested law administrators, professors and students as collaborators in future studies aimed at helping reduce law students’ psychological distress. We believe a close alliance between the psychological and legal communities is essential for improving students’ quality of life. We hope this study represents the first of many studies that use scientific methodologies to promote law students’ well-being.

68. See Iijima, supra note 9, at 527; Hess, supra note 10; Kutulakis, supra note 12, at 837; Maloney, supra note 10, at 314.


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Table 1 Participant Demographics Full study (N = 322)

LSSM only (N =316)

Study 2 (N = 69)

Institution School A

49%

49%

41%

School B

51%

51%

59%

First-year

33%

33%

32%

Second-year

37%

37%

39%

Third-year

29%

30%

29%

Missing

2%