Identifying and Profiling Scholastic Cheaters_ Their Personality, Cognitive Ability, and Motivation

Identifying and Profiling Scholastic Cheaters:Their Personality,Cognitive Ability,and Motivation

Kevin M.Williams,Craig Nathanson,and Delroy L.Paulhus

University of British Columbia

Despite much research,skepticism remains over the possibility of profiling scholastic cheaters.However,several relevant predictor variables and newer diagnostic tools have been overlooked.We remedy this deficit with a series of three studies.Study 1was a large-scale survey of a broad range of personality predictors of self-reported cheating.Significant predictors included the Dark Triad (Machiavellianism,narcissism,psy-chopathy)as well as low agreeableness and low conscientiousness.Only psychopathy remained significant in a multiple regression.Study 2replicated this pattern using a naturalistic,behavioral indicator of cheating,namely,plagiarism as indexed by the Internet service Turn-It-In.Poor verbal ability was also an independent predictor.Study 3examined possible motivational mediators of the association between psychopathy and cheating.Unrestrained achievement and moral inhibition were successful mediators whereas fear of punish-ment was not.Practical implications for researchers and educators are discussed.Keywords:antisocial,psychopathy,plagiarism,scholastic cheating

Student cheating remains a disconcerting problem for educators.In a typical survey,two thirds of college students report having cheated at some point during their schooling (e.g.,Stern &Hav-licek,1986;Cizek,1999).If anything,the problem appears to have worsened in recent years (Josephson Institute of Ethics,2008)with lifetime cheating rates as high as 80%in some student samples (Robinson,Amburgey,Swank,&Faulker,2004).One contributor,the escalating access to the Internet has greatly facilitated plagia-rism—especially among computer-savvy students (Ma,Wan,&Lu,2008;Underwood &Szabo,2003).

Some investigators argue that situational factors are paramount in the explanation of cheating behavior (see Murdock,Miller,&Goetzinger,2007).Other researchers have sought to profile pre-dispositions,that is,identify the best individual difference predic-tors of cheating.To date,the predictors garnering the most support are poor scholastic attitudes and poor academic preparation (e.g.,Cizek,1999;Whitley &Keith-Spiegel,2002).Those same reviews were pessimistic about the value of personality and cognitive ability measures in predicting cheating.

The present report comprises three studies designed to challenge that pessimism.Our challenge is based on two weaknesses in previous research:First is the omission of key personality predic-tors.Second is the failure to exploit objective measures of cheating in a meaningful setting.Before detailing our research,a brief review of that earlier research is warranted.

Measurement of Scholastic Cheating

In their taxonomy of academic dishonesty,Whitley and Keith-Spiegel (2002)listed copying,plagiarism,facilitation,misrepre-sentation,and sabotage.For each variety of cheating,specific methods are in common use for measurement and detection.In scholastic settings,there is a clear trend favoring the use of high-tech to replace traditional low-tech methods (Cizek,1999).In research settings,a third category of cheating assessment may be added to this list—laboratory cheating.1Each of these approaches to cheating measurement involves advantages and disadvantages.In the case of multiple-choice exams,college instructors have traditionally employed low-tech methods such as direct observa-tion of exam copying or passing answer keys.In the case of plagiarism,instructors have often relied on their ability to detect a familiar source or writing quality unlikely to have been generated by the student.Such methods are rarely used in empirical research.As new technologies such as the Internet,cellular phones,and personal digital assistants (PDAs)became available,so too did new methods for engaging in scholastic cheating.Fortunately,the instructor’s arsenal of cheating detection methods has also bene-fited from technological innovation.Of particular importance is the availability of new computer software.

For example,software for the detection of multiple-choice an-swer copying includes several commercially available programs;others—notably,Signum (Harpp,Hogan,&Jennings,1996)and S-Check (Wesolowsky,2000)—are freely available from their authors.These programs conduct a pairwise comparison of stu-dents’responses to multiple-choice tests to search for excessive overlap in the answer patterns.For each possible pair of students,an index of similarity is calculated:Those with suspiciously high overlap (i.e.,those that are identified as obvious outliers among the distribution of similarity scores)are flagged as potential cheating pairs (Frary &Tideman,1997;Harpp &Hogan,1993;Harpp et al.,1996;Wesolowsky,2000).The validity of these methods is cor-1

Although many such measures are available (Nicol &Paunonen,2002),they will not be detailed here.This form of cheating is not scholastic in the sense of being motivated by higher grades.

Kevin M.Williams,Craig Nathanson,and Delroy L.Paulhus,Depart-ment of Psychology,University of British Columbia.

Correspondence concerning this article should be addressed to Delroy L.Paulhus,Department of Psychology,3519Kenny Building,University of British Columbia,Vancouver,BC,Canada V6T 1Z4.E-mail:dpaulhus@psych.ubc.ca

Journal of Experimental Psychology:Applied ?2010American Psychological Association 2010,Vol.16,No.3,293–3071076-898X/10/$12.00DOI:10.1037/a0020773

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roborated by the fact that flagged pairs of students are almost invariably found to have been seated adjacent to each other (Nathanson,Paulhus,&Williams,2006).

For the detection of essay plagiarism,another category of an-ticheating software is available.The most widely used program, Turn-It-In,is accessed via a commercial website(iParadigms, LLC,2004).It is now the standard plagiarism screen for major academic institutions across the globe(Dahl,2007;Jones,2008). The program algorithm compares the text of a submitted paper against the continually updated entries in its comprehensive data-base.Items in this database range from previously submitted student papers to academic and professional articles,as well as current and previous Internet web pages.The program notes strings of(at least)seven consecutive words that match previous papers and calculates an overall percentage score of plagiarized text.The output includes a copy of the essay with a different color code for each source and the exact citation.

The Turn-It-In program operates on the same principle as the more crude method of inserting essay text into an Internet search engine such as Google(McCullough&Holmberg,2005).In either case,instructors are able to assess plagiarism rates more objec-tively and efficiently than could be achieved with instructor judg-ment alone.Drawbacks include the fact that some programs are costly;others are complicated to use.Some,including Turn-It-In, have triggered legal challenges.

Self-reports.To estimate cheating rates and their correlates in large samples,the most efficient method is to collect self-reports (e.g.,Robinson et al.,2004;Underwood&Szabo,2003).In the same survey,one could inquire about a wide variety of cheating behaviors.Questions could also cover a substantial time period (e.g.,how many times did you cheat during high-school?).Be-cause cumulative self-reports are more reliable than single,or even multiple behavioral measures,they have more statistical power for evaluating individual difference correlates.This traditional survey technique is also the least expensive and labor-intensive(Paulhus &Vazire,2007).

The obvious concern is the credibility of self-reports(Paulhus, 1991).Questions about a specific recent test(“Did you cheat on the psychology midterm exam?”)are of dubious value because students may fear repercussions for admitting the offense.Ques-tions about past cheating(e.g.,during high-school)may be of more value because of the time interval and the lack of possible reper-cussions.It is interesting that high values such as the80%lifetime cheating rate found by Robinson et al.(2004)suggest that impres-sion management is not a serious concern in anonymous surveys of cheating.

Summary.Low-tech methods for cheating measurement have rarely been used in research.Self-report and behavioral measures are widely used but each has pros and cons.Depending on the purpose of the research,either one may be appropriate.In the research presented below,we exploited both methods.

Research on Demographic Predictors Research on demographic predictors of cheating has also raised complexities.One consistent finding is that men are more likely than women to report having cheated(e.g.,Jensen,Arnett,Feld-man,&Cauffman,2001;Lobel&Levanon,1988;Newstead, Franklyn-Stokes,&Armstead,1996;Szabo&Underwood,2004).Yet concrete measures do not confirm such a sex difference (Culwin,2006;McCabe,Trevino,&Butterfield,2001;Nathanson et al.,2006;Whitley,Nelson,&Jones,1999).It is unclear whether this difference is the result of men overreporting their actual cheating,women underreporting,or both.

Differences in cheating across college majors have been re-ported in a handful of studies.Business students report higher rates than nonbusiness students(McCabe,Butterfield,&Trevino, 2006).Students in science and engineering report higher levels of cheating than those with arts majors(Marsden,Carroll,&Neill, 2005;Newstead et al.,1996).Given the higher rate of males in science and engineering,however,it is not clear whether gender or major is the ultimate source.Whitley and colleagues(1999)argue that major is more important:In a meta-analysis,they showed that women in science and engineering cheat virtually as much as their male counterparts.

Even fewer studies have examined cultural differences in scho-lastic cheating.Hayes and Introna(2005)reported that,compared to students from the United Kingdom,East Asian students held more tolerant attitudes toward scholastic cheating.However, Nathanson and colleagues(2006)found no behavioral differences between East Asian and European students in behavioral indicators of cheating.Altogether,then,the literature gives little indication of demographic differences in actual cheating behavior.

Research on Personality Predictors Comprehensive reviews of research on cheating predictors have downplayed the value of personality predictors(Cizek,1999; Whitley&Keith-Spiegel,2002).However,a number of personal-ity variables have not yet been given sufficient attention.The reason may simply be that standard measures of these variables have only recently become widely used.Among the overlooked variables are several with obvious relevance to cheating:narcis-sism,psychopathy,and the Big Five personality dimensions of Agreeableness,Conscientiousness,and Openness to Experience. For possible inclusion in our research,we will address each in some detail.

The Dark Triad.The constructs of narcissism,Machiavel-lianism,and psychopathy are commonly referred to as the Dark Triad of personality(Paulhus&Williams,2002).Narcissists are characterized by grandiosity,entitlement,and a sense of superior-ity over others(Raskin&Terry,1988).Such individuals are arrogant,self-centered,self-enhancing(Morf&Rhodewalt,2001) and ultimately,interpersonally aversive(Paulhus,1998).Most relevant to cheating,we suspect,is the sense of entitlement (Emmons,1987).Narcissists feel entitled to recognition for their intellectual superiority even when their academic accomplish-ments are mediocre.Therefore,attaining the plaudits they deserve may require cheating.

Individuals high in Machiavellianism are characterized by cyn-icism,amorality,and a belief in the utility of manipulating others (Christie&Geis,1970).A wealth of evidence confirms that these individuals exploit a range of duplicitous tactics to achieve their goals(see Jones&Paulhus,2009;McHoskey,2001).All these tendencies increase the likelihood of indulging in scholastic cheat-ing.However,the few studies exploring this possibility have revealed only weak links,at best(Cizek,1999;Flynn,Reichard,& Slane,1987).

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Psychopathy is characterized by the four key features of erratic lifestyle,manipulation,callousness,and antisocial tendencies (Hare,2003;Williams,Paulhus,&Hare,2007).All four suggest that psychopaths are more likely to cheat than are nonpsychopaths. Psychopathy is strongly and consistently associated with a wide range of misconduct in nonoffenders(alcohol and drug abuse, bullying,antiauthority abuse,driving offenses,criminal behavior; Williams&Paulhus,2004).We predict that this link will extend to scholastic cheating.To date,only one study has investigated the relation between psychopathy and a behavioral cheating behavior (Nathanson et al.,2006):Cheating was predictable from two self-report measures—the Self-Report Psychopathy scale (Paulhus,Neumann,&Hare,in press)and the Psychopathic Per-sonality Inventory(Lilienfeld&Andrews,1996).

Note that our use of the term psychopathy does not imply clinical or forensic levels.Accumulating research suggests that the construct tapped by self-report psychopathy questionnaires is con-ceptually identical to that tapped by interview methods in clinical/ forensic samples(Lebreton,Binning,&Adorno,2005).Of course, the mean scores in college students are substantially lower than those in clinical/forensic samples(Forth,Brown,Hart,&Hare, 1996;Paulhus,Nathanson,&Williams,in press).Nonetheless, roughly3%still qualified for a clinical diagnosis of psychopathy. Terms such as“nonoffender psychopathy”or“subclinical psy-chopathy”are avoided in this paper,in order to minimize the assumption that nonoffender/subclinical psychopathy is qualita-tively different from clinical/forensic psychopathy.

The Big Five.The Big Five personality traits—Extraversion, Agreeableness,Conscientiousness,Emotional Stability,and Open-ness to Experience—are now widely viewed as the fundamental dimensions of personality(Goldberg,1994;Costa&McCrae, 1992).Extraversion is characterized as the tendency to be sociable, talkative,energetic,and sensation-seeking.Agreeableness in-volves cooperating with others,and maintaining harmony.Con-scientiousness entails ambition,responsibility,and orderliness. Emotionally stable individuals are anxiety-free,well-adjusted,and resilient to stress.Finally,openness entails independent thinking, along with esthetic and intellectual interests.

Given the consensus on their importance,it is surprising how few studies of scholastic cheating have included the Big Five traits. Of the five,only extraversion and stability(vs.neuroticism)have received any attention.Those two factors were studied in depth by Eysenck(e.g.,Eysenck,1970)long before the Big Five became prominent as an organizational unit.

It is unfortunate the studies on extraversion and cheating have yielded equivocal results.Cizek(1999)reported that,in three out of four studies,extraversion showed a small significant positive correlation with cheating.However,Jackson and colleagues re-cently obtained a negative,albeit weak,association between ex-traversion and cheating(Jackson,Levine,Furnham,&Burr,2002). Similarly,studies of stability have shown weak(though consis-tently positive)correlations with cheating(Cizek,1999;Jackson et al.,2002).

The three other Big Five factors have yet to be studied in the context of cheating.Low agreeableness(i.e.,disagreeableness) seems especially relevant to cheating,given that its central features include confrontation and lack of cooperation(Costa&McCrae, 1992).Current understanding of openness to experience suggests no obvious association with cheating.

The Big Five variable with the closest conceptual connection to cheating is(low)conscientiousness.This trait seems particularly relevant given its contribution to academic preparedness,the broader concept noted earlier.The published research is minimal but some argue that dishonesty has clear conceptual links with conscientiousness(e.g.,Emler,1999;Murphy,2000).In a study conducted before the Big Five labels became popular,Hethering-ton and Feldman(1964)showed that students low in trait respon-sibility were found to be more likely to cheat.Prudence,another construct related to conscientiousness,has been linked(negatively) to self-reported cheating(Kisamore,Stone,&Jawahar,2007).A wealth of research in industrial settings has shown that those scoring low on conscientious-related traits engage in a persistent pattern of dishonest behaviors such as theft,absenteeism,and bogus claims of worker compensation(Hogan&Hogan,1989). Such behaviors may be seen as the workplace equivalent of aca-demic cheating.

Overview of the Present Research

Three studies were conducted to investigate possible links be-tween scholastic cheating and the overlooked personality variables noted above.Study1examined the role of three demographic and eight personality predictors—including the Dark Triad and the Big Five—in a large-scale survey of self-reported cheating behavior. Study2sought to replicate these findings using a behavioral indicator of plagiarism,namely,scores recorded by the Turn-It-In program.Also included was a measure of verbal ability to control for potential overlap between psychopathy and cognitive abilities. In Study3,motivational mechanisms underlying the personality-misconduct link were evaluated via mediation analysis.

Study1:Predictors of Scholastic Cheating

The primary goal of Study1was to fill in the above-mentioned gaps in the research on personality correlates of scholastic cheat-ing.Based on the literature reviewed above,scholastic cheating should be associated with all of the Dark Triad variables(Hypoth-esis1.1)with psychopathy as the strongest predictor(Hypothesis 1.2).Of the Big Five,low scores on agreeableness and conscien-tiousness should predict cheating(Hypothesis1.3).Based on the above research,the self-reported cheating rates should be higher in male than in female students(Hypothesis1.4)but no ethnic dif-ferences are expected(Hypothesis1.5).

Method

Participants.Two-hundred and49students in second-year undergraduate psychology classes at the University of British Columbia participated in the study for course credit.70%were female;the majority of students were of either European(41.4%) or East Asian(32.5%)ethnicity.

Measures and procedure.Participants enrolled by respond-ing to an advertisement to participate in a study examining“Per-sonality and Background Factors.”They picked up a take-home questionnaire package that included several personality scales,as well as a variety of misconduct scales embedded in a large-scale survey.Instructions on the cover page cautioned against including any personally identifying information(e.g.,name,student num-

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ber).Given the sensitive nature of some of the questionnaire items, this procedure was necessary to encourage honest and accurate responses.Students returned their unmarked and sealed question-naire package in a bin outside the lab;inside,they signed in to receive their credit.

Personality questionnaires.Questionnaires were selected for conceptual relevance and reputable psychometric properties,as detailed below.Unless otherwise specified below,all items were presented in Likert format:1?“Strongly disagree”to5?“Strongly agree.”

Narcissism was assessed with the Narcissistic Personality In-ventory(NPI;Raskin&Terry,1988).The NPI contains40forced-choice items such as“I like to be the center of attention.”versus “I like to blend in with the crowd.”Currently considered the standard measure of subclinical narcissism,the NPI has well-established psychometric properties(Morf&Rhodewalt,2001). One point was assigned for each narcissistic response. Machiavellianism was assessed with the20-item Mach-IV (Christie&Geis,1970).Items include“Most people are basically good and kind”and“It is hard to get ahead without cutting corners here and there.”The Mach-IV is the most widely used measure of Machiavellianism,and is psychometrically robust(for the latest review,see Jones&Paulhus,2009).In this dataset,items were scored on a6-point Likert scale ranging from?3(disagree strongly)to?3(agree strongly).

Psychopathy was measured using the64-item Self-Report Psy-chopathy scale(SRP-III;Paulhus et al.,in press).The SRP is patterned after the Psychopathy Checklist-Revised(PCL-R;Hare, 2003),the current gold standard for assessing psychopathy in forensic and clinical settings.The SRP has generated coherent results in psychometric studies covering areas such as concurrent and convergent/discriminant validity(Hicklin&Widiger,2005), including correlations with measures of general misconduct (Camilleri,Quinsey,&Tapscott,2009;Williams et al.,2007). Example items include“I have attacked someone with the goal of hurting them”and“I like to have sex with people I hardly know.”Total scores on this measure tend to behave similarly to Lilienfeld and Andrew’s(1996)Psychopathic Personality Inventory(e.g., Nathanson et al.,2006).

The44-item Big Five Inventory(BFI;John&Srivastava,1999) was used to assess the Big Five factors of personality.Example items(and the Big Five trait they assess)include“is talkative”(extraversion),“is considerate and kind to almost everyone”(agreeableness),“is a reliable worker”(conscientiousness),“re-mains calm in tense situations”(stability),and“has an active imagination”(openness).Substantial evidence has accumulated for the validity of all five factors(John&Srivastava,1999). Scholastic cheating.The two items used to assess cheating were:“I have cheated on school tests”and“I have handed in a school essay that I copied from someone else.”Both specifically referred to high-school to preclude concerns about admitting to cheating at our university.A cheating index was calculated as the mean of these two items.To preclude item overlap,the item with similar content(“Only losers don’t cheat on tests”)was removed from the psychopathy scale.

Results and Discussion

High-school cheating rates were estimated by coding any stu-dent with a nonzero score on the two-item index as a cheater.A substantial73%of students admitted to cheating at least once in high school.That value approximated the median of those values cited in the literature(64%;Cizek,1999).The reported rate for plagiarism was38.8%.Apparently,cheating tendencies among college students continue at disturbingly high levels. Demographics.Hypotheses regarding demographics were supported.Consistent with Hypothesis1.4,males reported higher cheating rates than females:t(243)?3.37,p?.01;d?.35.This difference has been remarkably consistent across a spate of studies (Cizek,1999).Given that the pattern of personality analyses was similar across gender,however,we only report results for the pooled sample.Consistent with Hypothesis1.5,no ethnic differ-ences were found.

Personality predictors.For purposes other than estimating high-school rates,self-reported cheating was indexed with a con-tinuous measure—the mean of the two self-report items.The item mean was2.12(SD?.99)on a5-point scale.Reliability of the composite was.73.Analyses with the individual cheating items showed similar though weaker patterns.

Note from Table1that the alpha reliability estimates for the personality scales were sound,ranging from.78to.89.Also displayed in Table1are the correlations among the Big Five and

Table1

Study1:Intercorrelations and Descriptive Statistics for Personality Measures and Self-Reported Cheating

123456789

Dark Triad

1.Psychopathy(.89).53?.44?.18??.48??.33?.19?.08.58?[.66]

2.Machiavellianism(.78).26??.09?.50??.36??.09?.01.39?[.46]

3.Narcissism(.87).48??.29?.12.24?.23?.20?[.24] Big Five

4.Extraversion(.86).0

5.21?.35?.24?.09[.11]

5.Agreeableness(.81).31?.1

6.02?.23?[?.27]

6.Conscientiousness(.82).25?.12?.28?[?.33]

7.Stability(.83)?.02.08[.10]

8.Openness(.78).07[.08] Cheating criterion

9.Self-reported cheating(.73)

Note.N?228.Values in parentheses are alpha reliabilities.Values in square brackets are disattenuated for unreliability in the criterion.

?Indicates significance at p?.05,two-tailed.

296WILLIAMS,NATHANSON,AND PAULHUS

Dark Traid personality variables:The pattern is similar to that found in previous studies(e.g.,Hicklin&Widiger,2005;Paulhus &Williams,2002;Williams&Paulhus,2004).

Of special interest are the correlations of the personality variables with scholastic cheating.Consistent with Hypothesis 1.1,each of the Dark Triad variables exhibited significant positive associations with scholastic cheating.Consistent with Hypothesis1.2,psychopathy showed the strongest correlation (.58)followed by Machiavellianism(.39)and narcissism(.20; all p?.01).There are plausible mechanisms for each of these personality influences.

Narcissists are known for their arrogance and sense of entitle-ment(Emmons,1987).Expecting to achieve more than others, they often underperform(Wallace&Baumeister,2002).Such ego-threat can lead narcissists to behave in an antisocial fashion (Twenge&Campbell,2003).Cheating may be necessary to reaf-firm their self-perceived superiority.As far as we know,there is no previous evidence confirming this association empirically. Given their manipulative tendencies,it is not surprising to find that Machiavellian individuals have cheated in academic settings. More surprising,however,is that this association has seen little to no empirical support in previous research(Cizek,1999;Flynn et al.,1987).Those failures may be attributed in part to weakness in methodology.For example,the Flynn et al.(1987)study used an inferior measure of Machiavellianism,artificially dichotomized students into high-and low-Machiavellian groups,and used a contrived cheating measure.Our improved methodology may have provided a more powerful test of the expected duplicity of Machi-avellians.

Regressions.Given the statistical overlap among the person-ality constructs,multiple regression analysis was conducted to determine the unique contribution of the relevant predictors.Re-sults indicated that,after controlling for the other predictors,only psychopathy,??.50,t(220)? 6.71;p?.01,remained a significant predictor of scholastic cheating.

The Big Five.Consistent with Hypothesis 1.3were the significant negative correlations with conscientiousness(?.28) and agreeableness(?.23;all p?.01).Aspects of low consci-entiousness such as irresponsibility,disorganization,and im-pulsivity likely contribute to cheating behavior(Hogan& Hogan,1989).Because they end up less prepared and have poorer study skills,they find themselves in desperate straits (Hogan&Hogan,1989).

The uncooperativeness inherent in disagreeableness presents a plausible explanation for its association with cheating.Along with conscientiousness,however,agreeableness lost significance in a regression with the Dark Triad members.Presumably,the direct relevance of the Dark Triad to antisocial behavior confers the advantage to those three variables in predicting this narrow crite-rion.

Unsuccessful cheating predictors.The remaining Big Five predictors—emotional stability,extraversion,and openness—failed to predict self-reported cheating.The results with extraversion and emotional stability are consistent with the previous reviews(Cizek, 1999;Jackson et al.,2002;Whitley&Keith-Spiegel,2002).The only previous study of openness to experience also failed to produce significant results(Nathanson et al.,2006).

Study2:Objective Measurement of Scholastic

Cheating

Our use of self-report measures in Study1was appropriate for exploring new predictors in a large sample survey.However,the limitations of self-report are well-known(e.g.,Paulhus,1991). Although the maximization of anonymity helps minimize impres-sion management,other response biases such as self-deception may magnify associations via common method variance.Along with sexual behavior,scholastic cheating constitutes a sensitive self-disclosure that is vulnerable to underreporting or flat denial among college students.Alternatives such as peer-evaluations have considerable value in some measurement contexts(Paulhus &Vazire,2007),but are difficult to apply to scholastic cheating. To provide a behavioral measure of essay plagiarism,the Internet-based computer program Turn-It-In(iParadigms,LLC, 2004)was used in Study2.As reviewed above,this program compares a submitted paper against the constantly updated entries in its extensive database.Items in the database range from previ-ously submitted student papers to academic and professional arti-cles,as well as current and previous Internet web pages.By examining strings of consecutive words,each paper receives a percentage score that indicates how much of the paper directly matches sources in the databank.

One previous behavioral study reported a link between person-ality and multiple-choice answer copying(Nathanson et al.,2006), but personality predictors of plagiarism have yet to be studied. Although both are forms of scholastic cheating,multiple-choice answer copying and plagiarism may not have the same personality correlates(Marsden et al.,2005).Consider,for example,that multiple-choice answer copying is typically spontaneous and un-planned whereas plagiarism is more deliberate and effortful.Ac-cordingly,personality traits such as psychopathy and low consci-entiousness(given their connection with poor impulse-control) would be more relevant to answer-copying than to plagiarism. Nonetheless,we hypothesize that psychopathy will again be the principal predictor of plagiarism.

The role of cognitive ability.The association between(poor) cognitive ability and cheating has been studied extensively.It appears that students with poorer academic skills tend to cheat more—perhaps to compensate for their shortcomings.It is worth examining the evidence for this argument,which has recently been summarized by three major reviews.

Whitley and Keith-Spiegel(2002)were pessimistic about any link between cognitive ability and cheating but Cizek(1999)concluded that there is a negative association.The most comprehensive review was recently conducted by Paulhus,Nathanson,and Williams(in press).Only behavioral indicators of cheating were considered but measures of ability included various IQ tests,SAT scores,and other aptitude tests.The results were quite consistent across13studies:in every case,cheating rates were higher in students with lower cogni-tive ability.The mean effect size was?.26.

The possibility that psychopathic individuals have poorer cog-nitive ability suggests an alternative explanation for their higher cheating rates.Psychopaths may just be compensating for their low ability.The empirical literature,however,does not support the premise.In several studies,self-report psychopathy scores have been found to be uncorrelated with measures of general intelli-gence and knowledge in students(Nathanson et al.,2006;Paulhus

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&Williams,2002),community members(Ishikawa,Raine,Lencz, Bihrle,&Lacasse,2001),and patient/offender samples(Crocker et al.,2005).

On occasion,psychopathy is occasionally found to be negatively correlated with verbal intelligence(e.g.,Nathanson et al.,2006). Given the potential for overlap,it behooves us to disentangle their roles with respect to scholastic cheating.Accordingly,we included a measure of verbal intelligence in Study2.Our decision to measure verbal(as opposed to some other component of)intelli-gence was its relevance to plagiarism.

Summary.Study2would extend Study1by turning to a behavioral measure of scholastic cheating,namely,plagiarism scores from https://www.wendangku.net/doc/95261719.html,ing the same set of personality predic-tors as in Study1,Study2also evaluated the contribution of cognitive ability.

We expect the Turn-It-In plagiarism rate to be lower than that of self-reported cheating(Hypothesis2.1).Based on previous behav-ioral research,there should be no sex differences(Hypothesis2.2) or ethnic differences in behavioral cheating rates(Hypothesis2.3). Among the personality variables,we predict that the Dark Triad will be significant predictors of behavioral cheating(Hypothesis 2.4),with psychopathy as the strongest personality predictor(Hy-pothesis 2.5).Based on Study1,low agreeableness and low conscientiousness should also predict plagiarism(Hypothesis2.6). Poor verbal ability will also be related to plagiarism independently of psychopathy(Hypothesis2.7).

Method

Participants.We solicited participants from two sections of introductory psychology that had an essay requirement.Of the114 students enrolled in these sections,107agreed to participate in a personality survey.2Seventy-two(67.3%)of them were female, and the majority of students were of either East Asian(41.0%)or European(43.0%)ethnicity.

Measures and procedure.Participants completed a battery of personality scales through an Internet webpage:It prevented stu-dents from reporting any personally identifying information(e.g., name,student number).Instead,students created a random8-digit student ID,which was used to obtain their credit at a predeter-mined location upon completing the survey.

Personality and verbal ability scales.The personality ques-tionnaires included on the webpage were identical to those used in Study1:the Self-Report Psychopathy Scale(SRP-III),Narcissistic Personality Inventory(NPI),Mach-IV,and Big Five Inventory (BFI).One minor difference is that,in contrast to Study1,the Mach IV scale responses were collected on5-point(Disagree to Agree)items.

The verbal ability test was based on the Quick Word Test (QWT;Borgatta&Corsini,1964),a100-item power vocabulary test.In the past,the QWT has shown strong convergent validity with other standard intelligence tests such as the Wechsler Adult Intelligence Scales(see Bass,1974).Internal consistency estimates on the full test average.91.The QWT items were updated and the revision,renamed the UBC Word test,has been normed and validated(Nathanson&Paulhus,2007).Each item is five letters in length and respondents must select the best synonym from four choices.Administration time was set to a maximum of eight minutes.To control for variation in the number attempted,scores were calculated as the ratio of correct answers to questions an-swered.

Behavioral cheating measure.Plagiarism scores were based on two essays assigned to the students by their course instructor. The first paper required students to summarize a research project whereas the second paper addressed a personal life experience. Shortly before the essays were assigned,students were given an essay outline that informed students that their papers would be scrutinized by Turn-It-In.The outline also pointed students to various university websites describing Turn-It-In,proper APA format guidelines,and the definition of plagiarism.

As detailed earlier,Turn-It-In examines student essays for pla-giarism by comparing each one to an extensive database of written works.This process results in each paper receiving a percentage score that indicates how much of the paper directly matches sources in the databank.The output displays the percentage of overlapping text,which is then categorized and color-coded based on the original text source.

Because Turn-It-In also flagged legitimate overlapping text such as quotes and citations,it was necessary to have research assistants further scrutinize the results(this drawback has been rectified in more recent versions of the program).Discounting instances of legitimate overlap yielded a genuine proportion plagiarized(the plagiarism index).Two research assistants showed100%agree-ment on the plagiarism index.Note that the Turn-It-In algorithm has since been improved to discount legitimate text citations.

Results and Discussion

Reliability.Note from Table2that reliability estimates for the personality scales ranged from.71to.88.The reliability for UBC-Word test was calculated with an odd-even estimate(.90):This method is considered appropriate for a speeded test(Crocker& Algina,1986).A reliability estimate for the Turn-It-In index was derived from the correlation of plagiarism scores from the two essays (r?.41).The reliability estimate for the composite was.57. Operationalizing cheating.Plagiarism was defined as any nonzero percentage detected by Turn-It-In(after screening).The mean plagiarism rate was23%(SD?22.5).A total of16students (15.0%)plagiarized on at least one of their essays.To reduce skewness,plagiarism scores were transformed into a dichotomous variable.Students who plagiarized on at least one essay were assigned a score of1;all others were assigned a zero.Agreeement between our two raters was100%.Similar procedures have been used previously to deal with the highly skewed distributions com-mon in cheating studies(e.g.,Daly&Horgan,2007).

The resulting proportion of cheaters was15%(SD?38). Consistent with Hypothesis2.1,rates of Turn-It-In plagiarism were much lower than the self-report cheating rates from Study1. Consistent with Hypotheses2.2and2.3,plagiarism rates did not differ according to ethnic background[European vs.East Asian; 2However,students were not specifically advised that Turn-It-In results would be used in our research.This procedure was critical to the study,and was approved by the course instructor as well as the ethical review boards at both the departmental and university level.The instructor was free to use the Turn-It-In results to penalize students at her discretion,but did not. Similar procedures have been used by other researchers of behavioral plagiarism(Daly&Horgan,2007).

298WILLIAMS,NATHANSON,AND PAULHUS

t (72)??.44,p ?.05;d ??.06]or gender:[t (105)??.24,p ?.05;d ??.03].

Predictors of cheating.Having established personality asso-ciations in Study 1,we used one-tailed tests of significance for the parallel Study 2tests.Note from Table 2that Dark Triad correlates of Turn-It-In plagiarism were all significant,supporting Hypoth-esis 2.4.The pattern of correlates was comparable to that with self-reported scholastic cheating in Study 1.Supporting Hypothe-sis 2.5,psychopathy was the strongest predictor.Hypothesis 2.6was partially supported in that agreeableness but not conscien-tiousness was a significant predictor.3

Consistent with Hypothesis 2.7,low verbal ability was also a significant predictor.To examine the possibility of poor verbal ability as an alternative explanation for the psychopathy-plagiarism link,partial correlations were conducted.Specifically,the correlation between psychopathy and plagiarism was recalcu-lated,controlling for verbal ability.This partial correlation (.21,p ?.01)was virtually identical to the original correlation (.22,p ?.01).The lack of a significant change may be traced to the fact that psychopathy and verbal ability were almost completely orthogonal (r ??.04,p ?.05).This orthogonality of psychopathy and cognitive ability is a consistent finding in both clinical samples (e.g.,Hare,2003)and nonclinical samples (Paulhus &Williams,2002).

Behavioral indicators.One major advance of Study 2was the use of a behavioral indicator of cheating.Nonetheless,personality correlates of cheating were similar in Studies 1and 2.This consistency suggests that both methods detect cheating in mean-ingful ways.The pattern of correlates echoed a previous study using a behavioral indicator of multiple-choice answer copying (Nathanson et al.,2006).

Together,Studies 1and 2have established a robust personality predictor of scholastic cheating,thereby addressing the skepticism of some commentators (e.g.,Whitley &Keith-Spiegel,2002).The impact of psychopathy was strong and consistent across self-report and behavioral assessments of scholastic cheating.An obvious next step is to explore the psychological mechanisms by which the psychopathy-scholastic cheating link operates.In Study 3,the motivational mediators of this link are explored,in an attempt to

understand why psychopathic individuals engage in scholastic cheating.

Study 3:Psychological Mediators of Scholastic

Cheating

To identify possible mediators,we searched the literature for motivations students have offered for engaging in or avoiding scholastic cheating (e.g.,Anderman,Griesenger,&Westerfield,1998;Cizek,1999;Rettinger,Jordan,&Peschiera,2004).Three categories appear repeatedly in the literature.One is a motivation for cheating,namely,unrestrained achievement motivation :That is,some students strive to attain academic success without regard to fairness.A common motivation reported for not cheating is fear of punishment :Most students are concerned with repercussions such as suspension or expulsion from school.Another deterrent to cheating may be labeled moral inhibition :That is,students who consider themselves honest and principled are less likely to cheat.The first of these three may be considered an approach or incentive motivation,whereas the final two are avoidance or deterrence motivations (i.e.,avoiding punishment and guilt,respectively).There is reason to believe that all three of these motivations are linked to psychopathy.First,unrestrained achievement maps onto the unmitigated agency quadrant of the interpersonal circumplex (i.e.,high dominance and low nurturance)—the same quadrant that houses psychopathy (Jones &Paulhus,2010;Salekin,Trobst,&Krioukova,2001).Second,insensitivity to punishment was asso-ciated with psychopathy as far back as the earliest laboratory research (Hare,1966).Finally,the impoverished moral identity in psychopaths is also evident from the scientific literature (O’Kane,Fawcett,&Blackburn,1996;Trevethan &Walker,1989).In short,their links to both psychopathy and cheating suggest that all three motivations (unrestrained achievement,fear of punishment,moral

3

Because the plagiarism scores were non-normal,we repeated the analyses involving demographic variables and psychopathy with chi-square tests of independence and Mann–Whitney tests,respectively.The same results were obtained.

Table 2

Study 2:Intercorrelations and Descriptive Statistics for Personality Measures and Plagiarism

1

2345678910Dark Triad

1.Psychopathy

(.88)

.49??.33??.03?.58???.39??.03?.04?.14.22?[.30]2.Machiavellianism (.77)

.23???.10?.45???.30???.08?.13.01.14?[.19]3.Narcissism (.81)

.36???.21???.06.19.17?.10.12?[.16]Big Five

4.Extraversion (.88)

.11.13.24??.19?.04.08[.11]5.Agreeableness (.77)

.22??.32??.22???.02?.20?[?.26]6.Conscientiousness (.78)

.22??.14.05?.06[?.08]7.Stability (.80)

.14.21??.03[?.04]8.Openness (.71)

.38???.07[?.09]9.Verbal ability (.90)

?.14?[?.19]

Cheating criterion

10.Turn-It-In plagiarism

(.57)

Note.N ?107.Values in parentheses are alpha reliabilities.Values in square brackets are disattenuated for unreliability in the criterion.?

p ?.05,one-tailed.??p ?.05,two-tailed.

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inhibition)are viable candidates to be mediators of psychopathic cheating.Their role will be evaluated statistically via mediation analysis.

The present study.The primary goal of Study3was to determine which of the three motivational factors(unrestrained achievement,fear of punishment,moral inhibition)could explain the psychopathy-cheating link.As a first step,a principal compo-nents analysis was conducted to organize and simplify a wide range of motivations for academic cheating.

Each of these motivational factors was then evaluated as a psychological mediator using the most recent analytic methods (see Chaplin,2007).Mediation was determined to occur if the link between psychopathy scores and cheating outcomes could be explained by an indirect path via one of the motivations.Essen-tially,the impact of the mediator corresponds to the product of(a) the path between the predictor and the mediator and(b)the path between the mediator and the outcome.Significance tests for mediation were conducted using the bootstrap procedures devel-oped by Shrout and Bolger(2002)and programmed by Preacher and Hayes(2004).

In sum,we hypothesize that psychopathy will correlate signif-icantly with each of the motivations for cheating(Hypothesis3.1). Each of the motivations for cheating will correlate significantly with cheating(Hypothesis 3.2).Each motivation will provide partial mediation of the link between psychopathy and cheating (Hypothesis3.3).

Method

Participants.Two-hundred and23students enrolled in under-graduate psychology classes participated for course credit.One-hundred and41(63.2%)were female,and the majority were of either East Asian(44.4%)or European(28.3%)ethnicity.Because gender and ethnic differences were minimal,the analyses were based on the pooled sample.

Measures and procedure.The data collection procedure was similar to Study2.Students participated by responding to an advertisement listed on the department’s Internet-based research participation system.They completed a battery of personality scales on a lab webpage.The procedures were designed to maxi-mize anonymity by advising participants not to report any person-ally identifying information(e.g.,name,student number).Instead, they selected a random8-digit student ID,which was later used to obtain a course credit of one percent.

Personality and cheating questionnaires.Unless otherwise specified,all items are scored with a five-point Likert scale(1?“Strongly disagree”to5?“Strongly agree”).Again,the Self-Report Psychopathy Scale(SRP-III;Paulhus et al.,in press)was used to assess psychopathy(alpha reliability?.89).

Cheating behavior was measured with admission items from the Self-Report Cheating Scale(Paulhus,Williams,&Nathanson, 2004).Twenty-six items assess misconduct behaviors such as “Brought hidden notes to a school test”and“Copied someone else’s answers on a school test without them knowing.”Eighteen of the items specifically assess cheating behaviors,whereas the remaining eight were fillers measuring general misconduct.When combined to generate an overall self-report cheating score,the alpha reliability of these18items was.85.

Potential mediators of cheating were measured using the moti-vation items of the Self-Report Cheating Scale(Paulhus et al., 2004).Based on results from previous studies and reviews(e.g., Cizek,1999),20items were generated.Respondents were asked to rate various factors that have influenced their decision to cheat(or refuse to cheat)on previous academic tasks,or might influence their decision to cheat(or refuse to cheat)in the future.Example items include“I needed to do it to get(or keep)a scholarship,”“I’m not concerned about the punishments involved if I am caught,”and“I pride myself in being a good and trustworthy person.”

Results

Factoring the motivations for cheating.To structure a man-ageable number of distinct motivations for cheating,a principal components analysis was conducted on the20common motiva-tions for cheating.Maximum Likelihood extraction generated sim-ilar results,but Principal Axis Factoring results were not as clear. Given the exploratory nature of this analysis,an oblique rotation (direct oblimin)was used.The first four eigenvalues were5.32, 1.91,1.44,and1.15.Parallel analysis indicated that a three-factor solution was appropriate.We used the interpolation tables pro-vided by Cota,Longman,Holden,Fekken,and Xinaris(1993): The minimal value for a third eigenvalue was1.41. Fortunately,three factors were interpretable:They corresponded substantially with the three common motivations for cheating found in the literature.Following common PCA practice,items with pattern matrix coefficients above.30were retained.The pattern matrix is displayed in Table3.Seven items loaded above .30on the first factor:They were combined to form a subscale with an alpha reliability of.71.These items concern the acceptability of cheating to gain some academic goal,for example,high grades, winning a scholarship,or receiving praise.Although most students seek these goals,only a subset feel that cheating is an appropriate strategy for obtaining these and other goals.It is this subset of individuals who are of particular relevance in this context.Ac-cordingly,the first factor was named“Unrestrained Achievement.”Four items loaded at least.30on the second factor and were combined to form a composite score.The reliability of this sub-scale was.51.High loading items dealt with concerns about detection by professors and teaching assistants,and punishment such as suspension or expulsion from the academic institute. Accordingly,the second factor was labeled“Fear of Punishment.”Nine items loaded at least.30on the third factor and were combined to form a composite score with an alpha reliability of .54.This factor involves personal beliefs about one’s own charac-ter and morals.Some students view themselves as honest individ-uals who stick to their principles.Presumably,such individuals would be less likely to engage in scholastic cheating.Conversely, individuals who neither value these attributes nor feel they possess them would be more likely to cheat.Other items referred to excuses about their cheating behavior(e.g.,test taking surround-ings make it too easy to cheat).Example items include“I pride myself in being a good and trustworthy person,”and“Being honest and moral is not a high priority for me”(reverse-scored).Accord-ingly,the third factor was named“Moral Inhibition.”

300WILLIAMS,NATHANSON,AND PAULHUS

Associations among the three motivations were generally small. The exception was a moderate negative correlation between Un-restrained Achievement and Moral Inhibition(r??.40,p?.01). Intercorrelations.Table4presents the intercorrelations among psychopathy,self-reported cheating and the potential me-diators.Psychopathy correlated significantly with cheating(r?.55;p?.01),after removing overlapping items.The significant correlations of psychopathy with all three motivations supports Hypothesis3.1.Hypothesis3.2was partially supported in that cheating correlated significantly with Moral Inhibition and Unre-strained Achievement but not with Fear of Punishment. Mediation analyses.Each of the cheating motivations was evaluated as a potential mediator of the psychopathy-cheating https://www.wendangku.net/doc/95261719.html,ing the bootstrap approach(Preacher&Hayes,2004;Shrout& Bolger,2002),5,000samples were drawn.This method is consid-ered more powerful than the traditional Sobel(1982)method, given that the sampling distribution of the indirect effect is typi-cally non-normal(Shrout&Bolger,2002).It also allows for the simultaneous evaluation of multiple mediators.The latter is im-portant for our data because the mediators are intercorrelated. Figure1displays the overall mediation model:The impact of psychopathy on cheating can be seen to drop from.55to.32after

Table3

Study3:Pattern Matrix Loadings From Principal Components Analysis of Motivations

for Cheating

Unrestrained achievement Fear of punishment Moral inhibition Unrestrained achievement

Cheat to get a scholarship.73.03.26 Cheat to pass a course.71?.12.09 Cheat because exam difficult.66.08?.09 Cheat because of social pressure.65.02?.05 Cheat to compete.64?.01?.18 Cheat to get a high grade.62.07?.26 Fear of punishment

Punishment is severe.03.72?.05

Too many TAs.19.63?.16 Punishments are empty threats.38?.39?.23

Not concerned about punishment.29?.38?.18 Moral inhibition

Cheat because I can?.04?.09?.68 Cheat because no one will know.18?.17?.64 Don’t cheat cause I’m a good person.21?.06.58 Cheat because I’m not honest/moral?.02?.37?.57 Cheat without thinking.15.15?.53 Cheat because everyone does it.27.12?.51 Note.N?223.Factor extraction was followed by a direct oblimin rotation.Bold entries are the highest loading for each item.

Table4

Study3:Intercorrelations and Descriptive Statistics for Psychopathy,Self-Reported Cheating and the

Potential Mediators

12345 1.Psychopathy(.89).23??.20??.49?.55?

Motivation for cheating

2.Unrestrained achievement(.71)?.02?.40?.39?

3.Fear of Punishment(.51).01?.10

4.Moral Inhibition(.54)?.61?

Cheating criterion

5.Self-reported cheating(.85) Item mean 2.11 2.42 2.30 3.31 1.95 Standard deviation.42.85.62.73.54 Note.N?223.In the text,hypothesized correlations are couched as one-tailed tests.All items were measured on5-point scales.

?Indicates significance at p?.01(two-tailed).

Figure1.Analysis of three mediatiors of the relation between psychop-athy and cheating.All values represent standardized regression coefficients (betas).The lower path indicates the total effect of psychopathy on cheat-ing with the indirect effect in parentheses.??denotes statistical significance at p?.01,two-tailed.

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the introduction of the three mediators.Analysis revealed with 95%confidence that the total indirect effect(i.e.,the difference between the total and direct effects)of psychopathy on cheating was significant with a point estimate of.23and a95%confidence interval of.11to.35.Hence,the overall mediation was significant. Nonetheless,the direct impact(.32)remained significant(p?.05) indicating that the three motivations provided only partial media-tion of the association of psychopathy with cheating.

In support of Hypothesis3.3,two of the motivations appeared to be successful and unique mediators:(1)for unrestricted achieve-ment,the95%CI of.03to.09around the point estimate of.06did not include zero and(2)for moral inhibition,the95%CI(.13;.33) around the point estimate of.24did not include zero.By contrast, the95%CI(-.22;.28)for the point estimate of fear of punishment (.003)did include zero.

General Discussion

The impetus for the three studies reported here was the wide-spread skepticism about the value of individual differences in predicting scholastic cheating(Cizek,1999;Whitley&Keith-Spiegel,2002).Those two reviews—fully comprehensive at the time—were published before the advent of several highly relevant personality measures.

Study1addressed this limitation by measuring the Big Five and Dark Triad traits in a large-scale study of self-reported scholastic cheating.Study2revealed a similar pattern using a behavioral criterion and a control for intellectual ability.Although traits such as Machiavellianism,narcissism,disagreeableness,and(low)con-scientiousness showed some degree of association,psychopathy was the strongest and most consistent predictor.Indeed,psychop-athy stood out as a significant predictor in all three studies reported here.Poor verbal ability also predicted cheating but did not ac-count for the impact of psychopathy.

This robust link between psychopathy and scholastic cheating is consistent with a body of research linking psychopathy to a broad range of misconduct in both offenders and nonoffenders.In of-fender samples,psychopathy is a notoriously strong correlate of criminal behavior and recidivism(see Hare,2003).In nonoffender samples(e.g.,students),psychopathy is typically measured via self-report,but exhibits a similar pattern of results.For example, Williams,Paulhus,Nathanson,and colleagues(Nathanson et al., 2006;Williams&Paulhus,2004;Williams et al.,2007)have repeatedly demonstrated associations between psychopathy and a wide range of misconduct indicators,including concrete behaviors. This malevolent personality can be traced to an especially volatile combination of manipulativeness,callous affect,erratic impulsive-ness,and antisocial tendencies.Only subsets of this synergistic combination are found in related constructs such as disagreeable-ness.

These broader implications of the psychopathy-cheating link parallel Blankenship and Whitley’s(2000)supposition about an underlying cheating personality:This notion arose from their dem-onstration that scholastic cheaters were also likely to engage in a wide variety of antisocial behavior including drug use and vio-lence.The present findings complement that research and further promote the view of psychopathy as perhaps the single most destructive personality syndrome.Furthermore,these results pro-vide further evidence for the viability of psychopathy as a con-struct with conceptual similarity(if not equivalence)in offender and nonoffender samples(Lebreton et al.,2005).

Other Individual Difference Predictors of Cheating Whereas psychopathy demonstrated strong and replicable asso-ciations with cheating,other personality predictors were less ef-fective.The identification of weak or null predictors also contrib-utes to our understanding of cheating behavior.Weak or moderated predictors require further study whereas consistently null predictors can safely be excluded from further research. Narcissism and Machiavellianism.Of the two remaining Dark Triad constructs,Machiavellianism did show some associa-tions with cheating—although they were fewer and weaker than those with psychopathy.Although often predicted,the empirical association of Machiavellianism with actual cheating behavior has proved to be surprisingly weak(Christie&Geis,1970;Cizek, 1999;Flynn et al.,1987).We found interesting that association remained even after controlling for psychopathy,narcissism,con-scientiousness,and https://www.wendangku.net/doc/95261719.html,cking the impulsive tendency of psychopaths,Machiavellians may be more deliberate in their mischief and more attentive to possible negative consequences (Jones&Paulhus,2009).

Finally,narcissism was the least successful predictor of cheating among the Triad constructs.Regression analyses demonstrated that any cheating behavior initially attributed to narcissism could be explained by its overlap with psychopathy and Machiavellianism. These results fit with previous research.For example,narcissists’performance motivation is strongly influenced by ego involvement (Wallace&Baumeister,2002).Specifically,narcissists’perfor-mance motivation is enhanced if an opportunity for self-enhancement—such as the publicizing of task results—presents itself.A public posting of grades might have inspired narcissists to cheat.Apparently,their sense of entitlement and need for recog-nition was insufficient to provoke cheating in our studies.

The Big Five.We offered hypotheses regarding two of the Big Five factors.One was that conscientious students would cheat less.Although this hypothesis was in fact confirmed in Study1, the association disappeared when other predictors were included in the regression equation.Even conscientiousness failed to work in Study2.

The rationale for the original hypothesis was that conscientious students tend to be better prepared academically and,therefore, have less need to cheat(Hogan&Hogan,1989).Note however, that conscientiousness also has a strong ambition component (Costa&McCrae,1998).This desire to excel may motivate some conscientious individuals to cut corners,no matter how well-prepared they are.In short,conscientiousness combines two com-ponents that work in opposite directions:The result was a minimal net effect on cheating.Future research should take advantage of measures that disentangle these two components(e.g.,Jackson, Paunonen,Fraboni,&Goffin,1996).

Similarly,initial associations between disagreeableness and cheating were eliminated after accounting for overlap with the Triad constructs and conscientiousness.These results are most likely attributable to the sizable overlap between agreeableness and the Triad constructs.Of the Big Five traits,only agreeableness overlaps with each of the Triad,and typically to a substantial degree(Paulhus&Williams,2002).It appears that disagreeable-

302WILLIAMS,NATHANSON,AND PAULHUS

ness alone is not sufficient:Only when it operates in combination with other unsavory attributes(as in psychopathy)does cheating occur.Finally,the openness,stability,and extraversion scales were consistently unrelated to cheating behavior.

Low verbal ability.Another hypothesis concerned the asso-ciation of poor verbal ability with cheating.Several reviews (Cizek,1999;Paulhus et al.,in press)have concluded that the ability-cheating link is a robust one(see also Daly&Horgan, 2007).The underlying principle is that students with poor cogni-tive ability are less well prepared for tests and essays and therefore choose to compensate by cheating.With respect to plagiarism,we assumed that this link should be even clearer when verbal ability is isolated from more global conceptions of cognitive ability. The hypothesis was tested and confirmed in Study2with a small but significant effect of verbal ability on plagiarism.We believe that link between cheating and intelligence is indirect: Cheating is a method for coping with perceived inadequacies.If we are right,further research may show that those with poor math ability are more likely to cheat on math tests.An appropriate experimental manipulation may confirm this person x situation notion.

Sex differences.The pattern of sex differences in cheating found in Studies1and3mimicked those of previous research (McCabe et al.,2001;Whitley et al.,1999):That is,self-reported rates of cheating were higher in males than in females.However, this sex difference disappeared in Study2when cheating was measured in a more concrete fashion.To date,explanations for the sex difference in self-reported cheating styles have been elusive and largely speculative(Cizek,1999).Results involving objective cheating rates further support the notion that there is no real sex difference in cheating.Given the confound with academic major, however,our data cannot tease apart the contributions of gender and major.

Explaining the Psychopathy-Cheating Link

Once the unique association between psychopathy and scholas-tic cheating had been confirmed in Studies1and2,we explored the motivational mediators of this link in Study3.Our mediation analyses provided a means for quantifying the explanatory power of these three motivations for cheating.

An unrestrained achievement motivation partially explained this association.Incentives such as high grades and scholarships seem to activate dishonesty in these individuals.Callous disregard for others and lack of impulse control encourage cheating as a means for achieving success.Indeed,such mechanisms are activated by psychopathic individuals as methods for achieving all of their life goals—academic or otherwise(Hare,2003).It is notable that the achievement goals shared by most college students trigger cheat-ing in psychopaths alone.

Also confirmed was a second mediator of psychopathic cheat-ing—a deficit in moral inhibition.The finding is consistent with previous demonstrations of links between psychopathy and moral-ity deficits(Williams et al.,2009).Even if temptations to cheat are activated,most students avoid acting on them because it compro-mises their self-image.As the final roadblock to cheating,this moral identity may be seen as the ultimate deterrent(Acquino& Douglas,2003).Psychopaths,however,not only admit to such deficits,they may well devalue society’s notion of integrity.In sum,there are both internal(intrinsic)and external(incentive) factors involved in the thought process underlying psychopathic cheating.

Our expectations about the mediating impact of a third motiva-tion—fear of punishment—were not fulfilled.This failure can be traced to a lack of association between fear and cheating.We caution that this finding not be taken to suggest that fear of punishment has no impact:Indeed,there is a wealth of evidence to suggest that punishment does in fact deter students from cheating (Cizek,1999).Rather than fear per se,it may be that perceived likelihood of being turned in by a peer is the psychological mediator(McCabe et al.,2006).

Limitations

Our use of a behavioral criterion in Study2addressed the limitations of self-report methods,but may have also introduced other limitations.For example,the eligibility requirements neces-sary for students in Study2led to a relatively small sample size, which hampered our ability to confirm significant associations.As expected,the effect sizes(correlations with cheating)were lower with a behavioral criterion compared to the self-report.For exam-ple,the.58correlation of psychopathy in Study1fell to.22in Study2.Disattenuation of the criterion variables,however,helped reduce this difference.Note that common self-report variance in Study1suggests another possible explanation for the high corre-lation:It may be that psychopaths are more willing to admit their cheating.

Another aspect of Study2impaired its power to find significant correlates.The low frequency of plagiarists identified in this dataset(i.e.,roughly7%to15%)restricted the range in the dependent variable and produced a highly skewed measure of cheating(see Cohen,Cohen,West,&Aiken,2002).These rates may seem low compared to previous estimates based on self-report (Newstead et al.,1996),which are upward of two thirds of students (Robinson et al.,2004;Stern&Havlicek,1986).Indeed,our own self-report estimate in Study1was73%.

Such self-report measures,however,cover a wider scope and time:Ours,for example,asked whether the student had cheated at any time in high school.Such self-reports often subsume all varieties of cheating(e.g.,answer copying,plagiarism,using hid-den notes,etc.).In contrast,our Turn-It-In coverage was restricted to two discrete opportunities to plagiarize essays in one university course:Hence our rates—about7%—represent typical rates of cheating per opportunity(Lavin,1965).

This fact highlights one of the trade-offs involved in using Turn-It-In and similar programs.These programs capture natural-istic cheating behavior,as opposed to other behavioral methodol-ogies which,though typically inducing higher frequencies of cheating,require contrived entrapment scenarios,or are otherwise unrealistic(e.g.,Hoff,1940;Leveque&Walker,1970).Further-more,the essays used in the Study2course were designed to minimally susceptible to cheating:Students were instructed to write about personal experiences rather than a traditional literature review or other essay style that could be plagiarized much more readily.These instructions undoubtedly reduced rates of plagia-rism even further.This handicap makes the cheating correlations reported in this study conservative estimates.In that light,our confirmation of significant associations is especially noteworthy.

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Causal inferences.In general,one may be more confident in inferring causality if(a)the measurement of independent variables temporally precedes that of dependent variables,(b)it is empiri-cally demonstrated that changes in the independent variable lead to changes in the dependent variable,on average,(c)changes in the dependent variable do not lead to changes in the independent variable,or(d)other potential causal variables are ruled out (Cohen et al.,2002).

As with all correlational studies,causal inferences in the present studies must be qualified.As a general rule,however,it is reason-able to assume that the trait variables studied here temporally precede other variables(see review by Bouchard&Loehlin, 2001).Moreover,the plagiarism measure was collected after the personality measures were collected.It is difficult to argue that cheating tendencies make people less conscientious or intelligent. However,caution is warranted in conclusions about the medi-ation analyses conducted in Study 3.The variables were not collected in any distinct temporal order.Those mediators—interpreted as motivations—could be construed as either justifica-tions(which occurred after the cheating behavior)instead of motivations(which occur before the cheating behavior). However,justifications tend to reduce feelings of guilt.There-fore,in the psychopathy-cheating context,it is unlikely that these mediators are justifications because psychopathic individuals ex-perience little guilt(Hare,2003).Future studies that can establish precise temporal measurement of these mediators may permit a clearer explication of this dynamic process.

Future Directions and Recommendations

Behavioral indicators.Our findings have implications for re-searchers of cheating behavior and educators in general.Both groups can benefit from the use of concrete,objective criteria such as the Turn-It-In program used here.Researchers are justifiably concerned about the biases inherent in self-report measures—especially those that assess socially undesirable behaviors such as cheating(Paulhus, 1991).Individuals who admit to cheating may also admit to undesir-able personalities:Spurious correlations are the result.Software indi-ces are more objective,unobtrusive,and can be used to capture cheating at naturalistic rates in naturalistic settings. Nonetheless,the similarity of the results obtained from self-report(Studies1and3)and computer-based criteria(Study2) suggests that both methods have their place as cheating indicators. Such convergence and replication substantiates our claims about the personality correlates of self-reported cheating.

Given the option,behavioral outcomes tend to be more convinc-ing to many behavioral scientists.The success of our research with programs such as Turn-It-In and S-Check suggests that behavioral indicators of other forms of misconduct would be ideal in future studies.However,the logistics of using such measures may prove difficult,if not impossible,among nonoffender samples.Forensic measures such as criminal records are unworkable,given that most students and community members have no offenses.Obtaining ethical approval and student consent for the use of such measures would also be complicated.Some researchers have been creative in their efforts to obtain behavioral indicators of misconduct,includ-ing the collection of official university records and workplace reports(e.g.,Gustafson&Ritzer,1995).Again,use of these measures entails several trade-offs compared to self-report mea-sures(e.g.,sample size,time considerations).

Beyond the Big Five.In future research,we recommend the exploration of several other individual difference variables.As noted earlier,Lee and Ashton(2005)have recently expanded the Five-Factor Model of personality to include a sixth factor—Honesty-Humility(H-H)—as part of their HEXACO model of fundamental personality traits.H-H captures characteristics such as“sincerity,fairness,and modesty versus slyness,pretentious-ness,and greed”(Lee&Ashton,2005;p.1573).H-H demon-strates strong negative correlations with each of the Dark Triad (Lee&Ashton,2005)as well as self-reported scholastic cheating (Marcus,Lee,&Ashton,2007).Future research may determine the independent contributions of H-H and the Triad constructs in predicting scholastic cheating.

Implications for educators—contending with cheating. Educators have to deal with cheating at both the abstract and practical levels.First,they must continually revisit the meaning of the construct as interpreted by students and test administrators (Chambliss et al.,2010;Harris,2001;Murdock&Stephens,2007). They are also on the front lines in contending with cheating and, when it occurs,about documenting the offense(Whitley&Keith-Spiegel,2002).The present research supports the interpretation of a high Turn-It-In score as cheating by linking it to individual difference variables,namely,psychopathy and poor ability,which have previously been linked with cheating.The use of such soft-ware can help overcome some of the problems with traditional techniques.When suspected for other reasons,confirmation of plagiarism via computer software is an invaluable tool.In fact, simply publicizing the fact that such techniques are in use should reduce the prevalence of cheating on any given exam. Effecting improvements in students’cognitive ability and char-acter is a more challenging goal:To the extent such changes are even possible,they seem beyond the mandate of the typical edu-cator.Psychopathic individuals are notoriously unresponsive to treatment interventions applied by highly trained clinicians,and sometimes become even more dangerous following treatment (Rice,Harris,&Cormier,1992).Instead,a preventative approach to cheating is more likely to be fruitful.There is no shortage of useful techniques for preventing cheating,such as alternate exam forms,clear warnings about the use of cheating detection pro-grams,banning cell-phones and other electronic devices,random or assigned seating arrangements,and assigning essays that in-volve writing about personal experiences that could not be easily plagiarized from external sources(Cizek,1999;Gulli,Kohler,& Patriquin,2007;Whitley&Keith-Spiegel,2002).

More generally,educators should benefit from awareness that the most probable cheaters are those low in scholastic prepared-ness and high in psychopathy.Attention to the first group requires redoubling efforts to prevent students from falling behind.Another approach may be to reduce the degree of competitiveness among the students.By creating an environment where relative achieve-ment is de-emphasized,the disadvantaged students would feel less threatened and less likely to resort to cheating.Such thinking is hardly new among educators but it might help to acknowledge that scholastic unpreparedness has its roots in basic traits.

Dealing with those high in psychopathy,on the other hand, raises more fundamental pedagogical issues.The fact that cheating is just one in their history of antisocial behaviors suggests that

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psychopaths top the“most likely to be expelled”list.Yet early diagnosis and surveillance of such individuals is problematic.It seems unlikely that school boards and university senates would approve of mass prescreening of students for psychopathy.Any attempt to determine probability-of-expulsion in advance suggests an unsavory“guilty until proven innocent”approach.

Even if prescreening were to be approved,there is no estab-lished cutoff score for psychopathy in nonoffender populations. Although some researchers have argued that psychopaths form a distinct group in student samples(Harris,Rice,&Quinsey,1994), recent evidence has supported a normal distribution of psychopa-thy scores—even among offenders(Edens,Marcus,Lilienfeld,& Poythress,2006;Lilienfeld&Andrews,1996;Nathanson et al., 2006).Either way,the diagnosis of psychopathy in a nonoffender population is a comparatively more subjective endeavor than that in a clinical or forensic context.Even if scores were kept confi-dential,labeling could be extremely harmful to the student.The surveillance of high scoring individuals would be highly problem-atic ethically and practically.Indeed,it is possible that such labels might translate into self-fulfilling prophecies.Furthermore,our examination of potential mediators,combined with the results of several forensic studies(see Hare,2003),suggests that threats of punishment are likely to go unheeded by psychopathic individuals. On the whole,our character analysis suggests that the only way to eliminate cheating among psychopaths is to make it impossible. Overall,these cheating reduction strategies may be grouped into two main categories:Altering teaching philosophy and modifying test administration techniques.The former,which includes reducing the competitive nature of the classroom environment,may be most ef-fective for reducing cheating stemming from cognitive ability deficits. The latter,which includes the use of alternate test forms,should be most beneficial in eliminating cheating by psychopathic individuals. Ideally,a combination of philosophical and methodological ap-proaches may be most effective in abolishing cheating.

Conclusions

Our challenge to previous skepticism about profiling scholastic justified cheaters appears to have paid off.This series of studies on key personality variables eventuated in the isolation of subclinical psychopathy as a powerful predictor.The replication of this asso-ciation across three studies was essential for confirmation.The association held up whether self-report or computer-scored behav-ioral indices of cheating were used as operationalizations.Asso-ciations also held up when the Big Five personality variables were partialed out.Had we studied Machiavellianism,narcissism,agree-ableness,conscientiousness or verbal ability on their own,each would have yielded a significant link:The unique role of psychop-athy would not have been so apparent.

In addition,our comparative analyses of the Turn-It-In scores with self-report cheating provide mutual support for the validity of each method Although behavioral and self-report measures both have inadequacies,the converging pattern of correlates with psy-chological variables raises confidence in both approaches.

Our conclusions may apply to misconduct in other nonoffender samples.In the business world,for example,it may be that psychopaths commit other acts of misconduct—such as fraud or assault—in order to achieve goals such as promotions,wealth,or power.Although many strive to attain such goals,psychopathic individuals are most likely to believe that such devious and ag-gressive tactics are acceptable as means to ambitious ends.It is also possible that psychopathic individuals’self-image as tough, deceitful and callous explains their general tendencies toward misconduct.Indeed the dynamics uncovered here may apply to all psychopathic misconduct.A frank analysis may eventuate in suc-cessful strategies for preventing,or reducing such behavior.

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Received August29,2007

Revision received June28,2010

Accepted June29,2010Ⅲ

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IDENTIFYING AND PROFILING SCHOLASTIC CHEATERS

脐带干细胞综述

脐带间充质干细胞的研究进展 间充质干细胞（mesenchymal stem cells,MSC S ）是来源于发育早期中胚层 的一类多能干细胞[1-5]，MSC S 由于它的自我更新和多项分化潜能，而具有巨大的 治疗价值 ,日益受到关注。MSC S 有以下特点：(1)多向分化潜能，在适当的诱导条件下可分化为肌细胞[2]、成骨细胞[3、4]、脂肪细胞、神经细胞[9]、肝细胞[6]、心肌细胞[10]和表皮细胞[11, 12]；(2)通过分泌可溶性因子和转分化促进创面愈合；(3) 免疫调控功能，骨髓源（bone marrow ）MSC S 表达MHC-I类分子，不表达MHC-II 类分子，不表达CD80、CD86、CD40等协同刺激分子，体外抑制混合淋巴细胞反应，体内诱导免疫耐受[11, 15]，在预防和治疗移植物抗宿主病、诱导器官移植免疫耐受等领域有较好的应用前景；(4)连续传代培养和冷冻保存后仍具有多向分化潜能，可作为理想的种子细胞用于组织工程和细胞替代治疗。1974年Friedenstein [16] 首先证明了骨髓中存在MSC S ，以后的研究证明MSC S 不仅存在于骨髓中，也存在 于其他一些组织与器官的间质中：如外周血[17]，脐血[5]，松质骨[1, 18]，脂肪组织[1]，滑膜[18]和脐带。在所有这些来源中，脐血(umbilical cord blood)和脐带(umbilical cord)是MSC S 最理想的来源，因为它们可以通过非侵入性手段容易获 得，并且病毒污染的风险低，还可冷冻保存后行自体移植。然而，脐血MSC的培养成功率不高[19, 23-24]，Shetty 的研究认为只有6%，而脐带MSC的培养成功率可 达100%[25]。另外从脐血中分离MSC S ，就浪费了其中的造血干/祖细胞(hematopoietic stem cells/hematopoietic progenitor cells,HSCs/HPCs) [26, 27]，因此，脐带MSC S (umbilical cord mesenchymal stem cells, UC-MSC S )就成 为重要来源。 一．概述 人脐带约40 g, 它的长度约60–65 cm, 足月脐带的平均直径约1.5 cm[28, 29]。脐带被覆着鳞状上皮，叫脐带上皮，是单层或复层结构，这层上皮由羊膜延续过来[30, 31]。脐带的内部是两根动脉和一根静脉，血管之间是粘液样的结缔组织，叫做沃顿胶质，充当血管外膜的功能。脐带中无毛细血管和淋巴系统。沃顿胶质的网状系统是糖蛋白微纤维和胶原纤维。沃顿胶质中最多的葡萄糖胺聚糖是透明质酸，它是包绕在成纤维样细胞和胶原纤维周围的并维持脐带形状的水合凝胶，使脐带免受挤压。沃顿胶质的基质细胞是成纤维样细胞[32]，这种中间丝蛋白表达于间充质来源的细胞如成纤维细胞的，而不表达于平滑肌细胞。共表达波形蛋白和索蛋白提示这些细胞本质上肌纤维母细胞。 脐带基质细胞也是一种具有多能干细胞特点的细胞，具有多项分化潜能，其 形态和生物学特点与骨髓源性MSC S 相似[5, 20, 21, 38, 46]，但脐带MSC S 更原始，是介 于成体干细胞和胚胎干细胞之间的一种干细胞，表达Oct-4, Sox-2和Nanog等多

二、分析天平的基本操作

模块二滴定分析基本操作任务一分析天平的基本操作 一、分析天平的分类 分析天平是定量分析中最常用的准确称量物质的仪器。分析天平分类：等臂（双盘）分析天平、不等臂（单盘）分析天平、电子天平。 二、电子天平的介绍 1、工作原理：电磁平衡原理，秤盘通过支架连杆支架作用于线圈上，重力方向向下。线圈内有电流通过时，根据电磁基本理论，通电的导线在磁场中将产生一个向上作用的电磁力，与秤盘重力方向相反大小相同，与之相平衡，而通过导线的电流与被称物体的质量成正比。 2、性能特点：a.使用寿命长，性能稳定，灵敏度高，体积小，操作方便 b.称 量速度快、精度高 c.具有自动校准、累计称量、超载显示、自动去皮等功能 3、称量的一般程序 水平调节——打扫——预热——开启显示器——校准——称量——结束工作 ①水平调节检查水平仪，调节水平调节脚，使水泡位于水平仪中心。 ②打扫打扫天平秤盘 ③预热通电预热30min以上 ④开启显示器按ON键，显示器亮，显示屏出现0.0000g ⑤校准按“校准”键 ⑥称量被称物置于秤盘中间进行称量 ⑦称量结束工作取下被称物，核对零点，关闭天平，进行使用登记 4、基本称量方法 ①直接称量法将称量物直接放在天平盘上直接称量物体的质量。例如，称量 小烧杯的质量，容量器皿校正中称量某容量瓶的质量，重量分析实验中称量某坩埚的质量等，都使用这种称量法。 ②固定质量称量法

用于称量某一固定质量的试剂(如基准物质)或试样。适于称量不易吸潮、在空气中能稳定存在的粉末状或小颗粒样品。 A、去皮将干燥的容器置于秤盘上，待显示平衡后按“去皮”键扣除皮重并显示零点 B、加样打开天平门，用药匙将试样抖入容器内，使之达到所需质量。 固定质量称量法注意：若不慎加入试剂超过指定质量，用牛角匙取出多余试剂，直至试剂质量符合指定要求为止。严格要求时，取出的多余试剂应弃去，不要放回原试剂瓶中。操作时不能将试剂散落于天平盘等容器以外的地方，称好的试剂必须定量地由表面皿等容器直接转入接受容器，此即所谓“定量转移”。 ③递减称量法（减量法） 用于称量一定质量范围的样品或试剂。样品易吸水、易氧化或易与二氧化碳等反应时，可选择此法。。 称量步骤：试样的保存——取出盛试样的称量瓶——称出称量瓶质量——敲样——再称出其质量——样品质量——连续称样——称量工作结束 A、试样保存待称样品放于洁净的干燥容器（称量瓶）中，置于干燥器中保存 B、取出称量瓶左手戴手套取出称量瓶或者用折叠成约1cm的纸取出 C、称出称量瓶质量称出称量瓶质量，记录数据 D、敲样将称量瓶取出，在接收容器的上方倾斜瓶身，用称量瓶盖轻敲瓶口上部使试样慢慢落入容器中，瓶盖始终不要离开接受器上方。当倾出的试样接近所需量时，一边继续用瓶盖轻敲瓶口，一边逐渐将瓶身竖直，使粘附在瓶口上的试样落回称量瓶，然后盖好瓶盖，准确称其质量。两次质量之差，即为试样的质量。按上述方法连续递减，可称量多份试样。

精神分裂症的病因及发病机理

精神分裂症的病因及发病机理 精神分裂症病因：尚未明，近百年来的研究结果也仅发现一些可能的致病因素。（一）生物学因素1．遗传遗传因素是精神分裂症最可能的一种素质因素。国内家系调查资料表明：精神分裂症患者亲属中的患病率比一般居民高6.2倍，血缘关系愈近，患病率也愈高。双生子研究表明：遗传信息几乎相同的单卵双生子的同病率远较遗传信息不完全相同 的双卵双生子为高，综合近年来11项研究资料：单卵双生子同病率（56.7%），是双卵双生子同病率（12.7%）的4.5倍，是一般人口患难与共病率的35-60倍。说明遗传因素在本病发生中具有重要作用，寄养子研究也证明遗传因素是本症发病的主要因素，而环境因素的重要性较小。以往的研究证明疾病并不按类型进行遗传，目前认为多基因遗传方式的可能性最大，也有人认为是常染色体单基因遗传或多源性遗传。Shields发现病情愈轻，病因愈复杂，愈属多源性遗传。高发家系的前瞻性研究与分子遗传的研究相结合，可能阐明一些问题。国内有报道用人类原癌基因Ha-ras-1为探针，对精神病患者基因组进行限止性片段长度多态性的分析，结果提示11号染色体上可能存在着精神分裂症与双相情感性精神病有关的DNA序列。2．性格特征：约40%患者的病前性格具有孤僻、冷淡、敏感、多疑、富于幻想等特征，即内向

型性格。3．其它：精神分裂症发病与年龄有一定关系，多发生于青壮年，约1/2患者于20～30岁发病。发病年龄与临床类型有关，偏执型发病较晚，有资料提示偏执型平均发病年龄为35岁，其它型为23岁。80年代国内12地区调查资料：女性总患病率（7.07%。）与时点患病率（5.91%。）明显高于男性（4.33%。与3.68%。）。Kretschmer在描述性格与精神分裂症关系时指出：61%患者为瘦长型和运动家型，12.8%为肥胖型，11.3%发育不良型。在躯体疾病或分娩之后发生精神分裂症是很常见的现象，可能是心理性生理性应激的非特异性影响。部分患者在脑外伤后或感染性疾病后发病；有报告在精神分裂症患者的脑脊液中发现病毒性物质；月经期内病情加重等躯体因素都可能是诱发因素，但在精神分裂症发病机理中的价值有待进一步证实。（二）心理社会因素1．环境因素①家庭中父母的性格，言行、举止和教育方式（如放纵、溺爱、过严）等都会影响子女的心身健康或导致个性偏离常态。②家庭成员间的关系及其精神交流的紊乱。③生活不安定、居住拥挤、职业不固定、人际关系不良、噪音干扰、环境污染等均对发病有一定作用。农村精神分裂症发病率明显低于城市。2．心理因素一般认为生活事件可发诱发精神分裂症。诸如失学、失恋、学习紧张、家庭纠纷、夫妻不和、意处事故等均对发病有一定影响，但这些事件的性质均无特殊性。因此，心理因素也仅属诱发因

脐带血造血干细胞库管理办法(试行)

脐带血造血干细胞库管理办法（试行） 第一章总则 第一条为合理利用我国脐带血造血干细胞资源，促进脐带血造血干细胞移植高新技术的发展，确保脐带血 造血干细胞应用的安全性和有效性，特制定本管理办法。 第二条脐带血造血干细胞库是指以人体造血干细胞移植为目的，具有采集、处理、保存和提供造血干细胞 的能力，并具有相当研究实力的特殊血站。 任何单位和个人不得以营利为目的进行脐带血采供活动。 第三条本办法所指脐带血为与孕妇和新生儿血容量和血循环无关的，由新生儿脐带扎断后的远端所采集的 胎盘血。 第四条对脐带血造血干细胞库实行全国统一规划，统一布局，统一标准，统一规范和统一管理制度。 第二章设置审批 第五条国务院卫生行政部门根据我国人口分布、卫生资源、临床造血干细胞移植需要等实际情况，制订我 国脐带血造血干细胞库设置的总体布局和发展规划。 第六条脐带血造血干细胞库的设置必须经国务院卫生行政部门批准。 第七条国务院卫生行政部门成立由有关方面专家组成的脐带血造血干细胞库专家委员会（以下简称专家委

员会），负责对脐带血造血干细胞库设置的申请、验收和考评提出论证意见。专家委员会负责制订脐带血 造血干细胞库建设、操作、运行等技术标准。 第八条脐带血造血干细胞库设置的申请者除符合国家规划和布局要求，具备设置一般血站基本条件之外， 还需具备下列条件： （一）具有基本的血液学研究基础和造血干细胞研究能力； （二）具有符合储存不低于1 万份脐带血的高清洁度的空间和冷冻设备的设计规划； （三）具有血细胞生物学、HLA 配型、相关病原体检测、遗传学和冷冻生物学、专供脐带血处理等符合GMP、 GLP 标准的实验室、资料保存室； （四）具有流式细胞仪、程控冷冻仪、PCR 仪和细胞冷冻及相关检测及计算机网络管理等仪器设备； （五）具有独立开展实验血液学、免疫学、造血细胞培养、检测、HLA 配型、病原体检测、冷冻生物学、 管理、质量控制和监测、仪器操作、资料保管和共享等方面的技术、管理和服务人员； （六）具有安全可靠的脐带血来源保证； （七）具备多渠道筹集建设资金运转经费的能力。 第九条设置脐带血造血干细胞库应向所在地省级卫生行政部门提交设置可行性研究报告，内容包括：

电子天平使用说明书.

电子天平使用说明书 使用方法 ◎准备 1、将天平安放在稳定及水平的工作台上,避免振动、气流、阳光直射和剧烈的温度波动; 2、安装称盘; 3、接通电源前请确认当地交流电压是否与天平所附的电源适配器所需电压一致; 4、为获得准确的称量结果,在进行称量前天平应接通电源预热30分钟。 ◎电源 1. 天平随机附配交流电源适配器,输入220+22-33V ~ 50Hz 输出9V 300mA 2. 天平选用电池供电时可打开天平底部的电池盖按极性指示装入电池即可,建议使用9伏碱性电池,可连续工作约12小时。 当天平电池供电时,显示屏左上角电量指示框显示段数表明电池的状态(显示3段:电池充足,显示0段:电池耗尽,当电池电量将耗尽时,最后一个显示段闪烁。 ◎开机 在称盘空载情况下按<开/关>键,天平依次进入自检显示(显示屏所有字段短时点亮、型号显示和零状态显示,当天平显示零状态时即可进行称量; 当遇到相关功能键设置有误无法恢复时,按<开/关>键重新开机即可恢复初始设置状态。

◎校准 为获得准确的称量结果,必须对天平进行校准以适应当地的重力加速度。校准应在天平预热结束后进行,遇到以下情况必须使用外部校准砝码对天平进行校准。 1. 首次使用天平称量之前; 2. 天平改变安放位置后。 校准方法与步骤: 1.准备好校准用的标准砝码并确保称盘空载; 2.按<去皮>键:天平显示零状态; 3.按<校准>键:天平显示闪烁的CAL—XXX,(XXX一般为100、200或其它数字,提醒使用相对应的100g、200g或其它规格的标准砝码 4.将标准砝码放到称盘中心位置,天平显示CAL-XXX,等待几秒钟后,显示标准砝码的量值。此时移去砝码,天平显示零状态,则表示校准结束,可以进行称量。如天平不零状态,应重复进行一次校准工作。 ◎称量 天平经校准后即可进行称量,称量时必须等显示器左下角的“○”标志熄灭后才可读数,称量过程中被称物必须轻拿轻放,并确保不使天平超载,以免损坏天平的传感器。 ◎清零或去皮 清零:当天平空载时,如显示不在零状态,可按<去皮>键,使天平显示零状态。此时才可进行正常称量。

分析天平使用说明书

TG-328分析天平使用说明书 一、分析天平结构及作用原理： 1.该分析天平，是属于双盘等臂式，横梁采用铜镍合金制成，上面装有玛瑙刀三把，中间为固定的支点刀，两边可调整的承重刀。 好仪器，好资料，尽在沧州建仪（https://www.wendangku.net/doc/95261719.html,）。欢迎查询。 打造中国建仪销售第一品牌，树立沧州产品全新形象 2.支点刀位于支点刀垫上，支点刀垫固定在天平立柱上端。 3.横梁停动装置为双层折翼式，在天平开启时，横梁上的承重刀必须比支点刀先接角触，为了避免刀锋损坏和保证横梁位置的再现性，开启天平求轻稳，避免冲击，摇晃。 4.横梁的左右两端悬挂承重挂钩，左承重挂钩上装有砝码承重架，该二零碎件分别挂在小刀刃上，另有秤盘各一件分别挂在承重挂钩上。 5.整个天平固定在大理石的基座板上，底板前下部装有二只可供调整水平位置的螺旋脚，后面装有一只固定脚，天平木框前面有一扇可供启闭及随意停止在上下位置的玻璃门，右侧有一扇玻璃移门。 6.秤盘上节中间的阻尼装置，是用铝合金板制成，固定在中柱上。是利用空气阻力来减少横梁的摆动时间，达到静止迅速，从而提高工作效率。

7.光学报影装置，固定在底板上前方，可直接读出0.1-10毫克以内的重量值。 8.天平外框左侧装有机械加码装置，通过三档增减砝码的指示旋钮来变换自10毫克-199.99克砝码以内所需重量值。 二、分析天平主要技术指标： 规格型号技术参数：秤盘尺寸 TG328A200g/0.1mg80mm TG328B200g/0.1mg80mm1 TG628A200g/1mg80mm 三、分析天平性能特点： 1.TG系列双盘机械天平，采用空气阻尼，光电读数，具有称量准确，读数简便，价格实惠。 2.专供实验室，学校，工矿等作精密称量分析用。 四、天平的安装方法： a．安装前的准备工作安装前的准备工作安装前的准备工作安装前的准备工作 1.安装选择：天平必须放在牢固的台上，不准有震动，气流存在，室内气温要求干燥明亮，温度最好保持在20℃±2℃左右，避免阳光晒射单面受热和气温潮湿，反之影响天平的灵敏度和正确性。

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电子精密天平秤的使用方法及注意事项(正式版)

电子精密天平秤的使用方法及注意事项 刘维彬电子精密天平秤是定量分析工作中不可缺少的重要仪器，充分了解仪器性能及熟练掌握其使用方法，是获得可靠分析结果的保证。精密天平的种类很多，有普通精密天平、半自动/全自动加码电光投影阻尼精密天平及电子精密天平等。下面就电子精密天平的使用方法及注意事项做一介绍。 操作方法: 1．检查并调整天平至水平位置。 2．事先检查电源电压是否匹配（必要时配置稳压器），按仪器要求通电预热至所需时间。 3．预热足够时间后打开天平开关，天平则自动进行灵敏度及零点调节。待稳定标志显示后，可进行正式称量。 4．称量时将洁净称量瓶或称量纸置于称盘上，关上侧门，轻按一下去皮键，天平将自动校对零点，然后逐渐加入待称物质，直到所需重量为止。 5．称量结束应及时除去称量瓶（纸），关上侧门，切断电源，并做好使用情况登记。 注意事项: 1.天平应放置在牢固平稳水泥台或木台上，室内要求清洁、干燥及较恒定的温度，同时应避免光线直接照射到天平上。 2.称量时应从侧门取放物质，读数时应关闭箱门以免空气流动引起天平摆动。前门仅在检修或清除残留物质时使用。 3.电子精密天平若长时间不使用，则应定时通电预热，每周一次，每次预热

2h，以确保仪器始终处于良好使用状态。 4.天平箱内应放置吸潮剂(如硅胶)，当吸潮剂吸水变色，应立即高温烘烤更换，以确保吸湿性能。 5.挥发性、腐蚀性、强酸强碱类物质应盛于带盖称量瓶内称量，防止腐蚀天平。 6.称量重量不得过天平的最大载荷。 7.经常对电子天平进行自校或定期外校，保证其处于最佳状态。 8.天平发生故障，不得擅自修理，应立即报告测试中心质量负责人。 9.天平放妥后不宜经常搬动。必须搬动时，移动天平位置后，应由市计量部门校正计量合格后，方可使用。

精神分裂症的病因是什么

精神分裂症的病因是什么 精神分裂症是一种精神方面的疾病，青壮年发生的概率高，一般 在16～40岁间，没有正常器官的疾病出现，为一种功能性精神病。 精神分裂症大部分的患者是由于在日常的生活和工作当中受到的压力 过大，而患者没有一个良好的疏导的方式所导致。患者在出现该情况 不仅影响本人的正常社会生活，且对家庭和社会也造成很严重的影响。 精神分裂症常见的致病因素： 1、环境因素：工作环境比如经济水平低低收入人群、无职业的人群中，精神分裂症的患病率明显高于经济水平高的职业人群的患病率。还有实际的生活环境生活中的不如意不开心也会诱发该病。 2、心理因素：生活工作中的不开心不满意，导致情绪上的失控，心里长期受到压抑没有办法和没有正确的途径去发泄，如恋爱失败， 婚姻破裂，学习、工作中不愉快都会成为本病的原因。 3、遗传因素：家族中长辈或者亲属中曾经有过这样的病人，后代会出现精神分裂症的机会比正常人要高。 4、精神影响：人的心里与社会要各个方面都有着不可缺少的联系，对社会环境不适应，自己无法融入到社会中去，自己与社会环境不相

适应，精神和心情就会受到一定的影响，大脑控制着人的精神世界， 有可能促发精神分裂症。 5、身体方面：细菌感染、出现中毒情况、大脑外伤、肿瘤、身体的代谢及营养不良等均可能导致使精神分裂症，身体受到外界环境的 影响受到一定程度的伤害，心里受到打击，无法承受伤害造成的痛苦，可能会出现精神的问题。 对于精神分裂症一定要配合治疗，接受全面正确的治疗，最好的 疗法就是中医疗法加心理疗法。早发现并及时治疗并且科学合理的治疗，不要相信迷信，要去正规的医院接受合理的治疗，接受正确的治 疗按照医生的要求对症下药，配合医生和家人，给病人创造一个良好 的治疗环境，对于该病的康复和痊愈会起到意想不到的效果。

卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规范(试行)

卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规 范(试行)》的通知 【法规类别】采供血机构和血液管理 【发文字号】卫办医政发[2009]189号 【失效依据】国家卫生计生委办公厅关于印发造血干细胞移植技术管理规范(2017年版)等15个“限制临床应用”医疗技术管理规范和质量控制指标的通知 【发布部门】卫生部(已撤销) 【发布日期】2009.11.13 【实施日期】2009.11.13 【时效性】失效 【效力级别】部门规范性文件 卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规范（试行）》的通知 （卫办医政发〔2009〕189号） 各省、自治区、直辖市卫生厅局，新疆生产建设兵团卫生局： 为贯彻落实《医疗技术临床应用管理办法》，做好脐带血造血干细胞治疗技术审核和临床应用管理，保障医疗质量和医疗安全，我部组织制定了《脐带血造血干细胞治疗技术管理规范（试行）》。现印发给你们，请遵照执行。 二〇〇九年十一月十三日

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电子天平的使用方法 一、概述 分析天平是定量分析操作中最主要最常用的仪器，常规的分析操作都要使用天平，天平的称量误差直接影响分析结果。因此，必须了解常见天平的结构，学会正确的称量方法。我们用到的天平有以下二类：普通的托盘天平和电子天平。 普通的托盘天平是采用杠杆平衡原理，使用前须先调节调平螺丝调平。称量误差较大，一般用于对质量精度要求不太高的场合。调节1g以上质量使 用砝码，以下使用游标。砝码不能用手去拿，要用镊子夹。 电子天平是最新一代的天平，它是根据电磁力平衡原理，直接称量，全量程不需要砝码，放上被测物质后，在几秒钟内达到平衡，直接显示读数，具有称量速度快，精度高的特点。它的支撑点采取弹簧片代替机械天平的的玛瑙刀口，用差动变压器取代升降枢装置，用数字显示代替指针刻度。因此具有体积小、使用寿命长、性能稳定、操作简便和灵敏度高的特点。此外，电子天平还具有自动校正、自动去皮、超载显示、故障报警等功能。以及具有质量电信号如何输出功能，且可与打印机计算机联用，进一步扩展其功能，如统计称量的最大值、最小值、平均值和标准偏差等。由于电子天平具有机械天平无法比拟的优点，尽管其价格偏高，但也越来越广泛的应用于各个领域，并逐步取代机械天平。 称量时，要根据不同的称量对象和不同的天平，应当根据实际情况选用合适的称量方法操作。一般称量使用普通托盘天平即可，对于质量精度要求高的样品和基准物质应使用电子天平来称量。电子天平的称量： 二、称量前的检查 1、取下天平罩，叠好，放于天平后。 2、检查天平盘内是否干净，必要的话予以清扫。 3、检查天平是否水平，若不水平，调节底座螺丝，使气泡位于水平仪中心。 4、检查硅胶是否变色失效，若是，应及时更换。 三、开机 关好天平门，轻按ON/OFF键，LTD指示灯全亮，松开手，天平先显示型号，稍后显示为0.0000g，即可开始使用。 四、电子天平的一般使用方法 电子天平的使用方法较半自动电光天平来说大为简化，无需加减砝码，调节质量。复杂的操作由程序代替。下面简单介绍电子天平的两种快捷称量方法： 1、直接称量 在LTD指示灯显示为0.0000g时，打开天平侧门，将被测物小心置于秤盘上，关闭天平门，待数字不再变动后即得被测物的质量。打开天平门，取出被测物，关闭天平门。2、去皮称量 将容器至于秤盘上，关闭天平门，待天平稳定后按TAR键清零，LTD指示灯显示重量为0.0000g，取出容器，变动容器中物质的量，将容器放回托盘，不关闭天平门粗略读数，看质量变动是否达到要求，若在所需范围之内，则关闭天平门，读出质量变动的准确值。

我的精神分裂症形成和发展史

出生前背景 母亲是地道、淳朴、专一，文化程度不高的农村主妇，父亲是当地的混混，好色成性，道德观念淡薄，无责任感，为非作歹，攻击性强，专横，常聚众斗殴，浪荡无比。他的放荡从和母亲接姻前持续到今。从母亲断断断断续的回忆中我恍知我没呱呱落地前就已有不寻常的经历，失职的母亲怀着我和父亲怄气经常绝食威胁，奢望唤醒父亲的为父为夫的责任感。可怜的女人，痴痴的等待，身心俱损终换不来一时的真爱。他从不掩饰自己的劣迹，而是将其当作显示自己无限魅力和能耐的招牌加以渲染，毫无顾忌在当众谈论。 童年背景 除父母，还有两兄，我是幼女，相比较受宠爱。 爷爷 奶奶，传统的封建妇女，极重男轻女，从未给过我好脸色。爷爷、奶奶在家中居从属地位，对我没产生至关重要的影响。 儿时家里很穷，主要靠母亲支撑维系家族。她非常辛苦，在纺织厂，三班制。歇工还要步行到七八公里外的田地里劳作。很难照顾到我们的感受，她所能做的就是竭尽所能维系家庭的完整，让我们能生存下去。与此同时，她还要忍受父亲周而复始的背叛，虐待、暴打。生活不如意加之贫困无比，让她难免脾气暴躁，我是她时常爆发时的接纳对象。如此妇女，受封建思想灌输至深，永远铭记自己要恪守妇道，她始终如一的忠诚与父亲，永不离弃他，爱护他，疼爱他（她比父亲年长些，父亲相貌俊秀，而母亲姿色平平）。我可怜而鄙视她，丈夫如果某天一改往日作贱她的口吻，她会像孩子似的受宠若惊的心花怒放。 父亲霸道无比，家里人人惧怕他，他无比自恋。除了母亲，伤害最深的是大哥，每天无缘无故的遭受父亲的暴打。他性情多变，无法揣摩，吃饭时一家人欢声笑语，吃完饭看看大哥不顺眼他操起皮鞭就抽。看到大哥在皮鞭下嚎哭，新的皮鞭疤痕烙在旧疤痕上，我和二哥感到恐惧，怜悯大哥，然而我们是无助的，谁也不能阻挡皮鞭的落下。尽管如此，父亲当时在我心目中是高大的，令人崇拜的，对我产生的正负影响也是最强烈的。他多才多艺，知识渊博，开明，前卫，聪明，而母亲相比之下平庸很多，她每天只是起早贪黑的工作，思想保守，愚昧，无任何才华而言。 童年，虽说不是幸福的，但也算不上痛苦。 童年转青春期阶段 邻居是一个恶老太婆，和当时大多传统村妇一样，没知识、没修养也没教养。她确实很恶，不允许她看不顺眼的小孩从她家旁边的小巷经过，她不喜欢我。每次我冒险经过她都会如同恶狗样在我刚出现在她视野中就开始狂吠，连同我的老祖宗也一起骂，持续到我再次从原路返回，躲到家里，她的吠声还要延续十分钟。 被爱妄想出现在五年级，应该更早些。我喜欢上一个家境优越的的男生，尽管那时他已经有“女朋友”。从爱上他那刻起我就很明确他也是爱我的，他和同桌说话其实余光是在看我，尽管没有任何证实，我非常明确他就是偷偷看我的。即使在上课，即使他没有和同桌说话，我感觉他在狠狠的想着我。他回答老师的提问也暗示着对我的爱意。比如他的回答里有“她”，那就是暗示他说的是我。或是我读书看到书上的“他”字样，心便狂喜的乱跳，认为这是我暗恋对象给我的暗示，他一直在我身边！ 妄想形成初期就有泛化倾向，我似乎对自己相貌无限自信，觉得自己是最美的，一上街满街的男孩都为我的美貌所折服，他们都不由自主的盯着我看，我的一举一动都被他们密切关注着，一出门便有那么多双眼睛注视着我。

脐带血干细胞检测

脐带血干细胞检测 对每份脐血干细胞进行下列检测： ①母体血样做梅毒、HIV和CMV等病原体检测，这一检测使脐血干细胞适合于其它家庭成员应用。如任何一种病原体测试阳性，需重复测定。 ②每份脐血干细胞样本同时检测确定没有微生物污染。 ③细胞活性检测、有核细胞数、CD34+细胞数、集落形成试验等。CD34是分子量115KD 的糖蛋白分子，使用特定单克隆抗体（抗-CD34）确定，脐血祖细胞的大部分，包括体外培养产生造血集落的细胞都包含在表达CD34抗原的细胞群中。 ④HLA组织配型、ABO血型。 一、采血方式及其优点 再生缘生物科技公司采用最严谨的封闭式血袋收集法，避免在收集脐带血液时可能遭受微生物污染的发生，且以最少之操作步骤，收集最大量之脐带血液方式，在产房内即可完成。 二、脐带血处理与保存 脐带血收集于血袋，经专人运送至再生缘生物科技公司之无菌细胞分离实验室后，由专业的技术人员于完全无菌的环境下，依标准操作程序将血液进行分离，收集具有细胞核的细胞，其中含有丰富的血液干细胞，经加入冷冻保护剂和适当品管检测后，并进行以最适合

血液干细胞的冷冻降温程序方式，进行细胞冷冻程序，达到避免细胞受到冷冻过程之伤害。完成后，冷冻细胞立刻保存于摄氏零下196度的液态氮槽中。所有操作程序记录和细胞保存相关数据，均由计算机条形码系统追踪确认，完全符合国际脐带血库之标准操作程序和品管要求。 母亲血液之检测 为确保所操作和保存的脐带血液细胞，符合国际血液操作规范，并提供客户最大的保障，对于产妇血液必须同时进行一些病毒传染病的检测，以确保没有下列病毒，如艾滋病毒(HIV)、C型肝炎病毒(HCV)、人类T细胞淋巴病毒(HTLV)和梅毒(syphilis)，同时对于B型肝炎病毒(HBV)和巨细胞病毒(CMV)加以侦测和纪录，作为将来可能应用脐带血细胞时之必要参考数据并符合卫生医疗之要求。 脐带血细胞之品管 对于所保存之脐带血细胞均进行多项操作流程监控和品管检测，如微生物污染检测、血液细胞浓度、细胞存活率、细胞活性测定等，每一步骤均有详细之纪录，在操作方法和使用仪器方面均定期进行验证和校验，以符合国际医疗标准。 三、实验室、贮存处所介绍 再生缘生物科技公司拥有符合美国联邦标准(FED-STD-209E)和中华民国优良药品制造标准（一区、二区、三区）的生物安全实验室和无菌操作设备，在专业的技术人员依标准操作程序下进行血液分离和保存步骤，保障客户珍贵样品和权益。 分离后之细胞将依浓度分装入4-6个冷冻管，计算机降温冷冻完成后，即由食品工业发展研究所国家细胞库专业液态氮库房人员，将冷冻细胞分别存放于二个不同的脐带血细胞专属液态氮槽中保存，在安全机制上更有保障。液态氮库房拥有五吨的液态氮供应系统，每一液氮槽均有自动充填装置和异常警报系统，和每日值勤人员监控，确保冷冻细胞处于最佳的冷冻状态。 四、安全管制措施 脐带血液经快递送达无菌细胞分离实验室后，每一步骤均有专业技术人员操作和监督，并将所有分析数值详细填于具有条形码管制之分析表格和计算机数据表中，利用条形码和读码系统确认样品之专一性，避免人为失误，且便于追溯和数据品管。 在冷冻细胞保存上