This article reports the first national assessment of patterns of drinking and gambling-related rulemaking on college campuses . Analyses relating school policies to known school rates of drinking or gambling identified potentially influential policies. These results can inform and encourage the development of guidelines, or "best practices," upon which schools can base future policy.The college policy information was collected from handbooks, Web sites and supplemental materials of 119 scientifically selected colleges included in the fourth (2001) Harvard School of Public Health College Alcohol Study (CAS). A coding instrument of 40 items measured the scope and focus of school alcohol and gambling policies. This instrument included items to measure the presence of specific policies and establish whether the policies were punitive or rehabilitative. A total of 11 coders followed a process of information extraction, coding and arbitration used successfully in other published studies to codify policy information.Although all schools had a student alcohol use policy, only 26 schools (22%) had a gambling policy. Punitive and restrictive alcohol policies were most prevalent; recovery-oriented policies were present at fewer than 30% of schools. Certain alcohol and gambling policies had significant relationships with student binge drinking rates.The relative lack of college recovery-oriented policies suggests that schools might be overlooking the value of rehabilitative measures in reducing addictive behaviors among students. Since there are few college gambling-related policies, schools might be missing an opportunity to inform students about the dangers of excessive gambling. Young people are at increased risk for alcohol- and gambling-related problems compared to their older counterparts -3. ColleThe problems associated with addictive behaviors on college campuses have been well documented  . However, science can contribute to the creation of successful policy. Recognizing the important role that science can play in the development and evaluation of public policy, the federal government recently released draft "regulatory science" guidelines . The OffThe purpose of this study is to encourage the development of science guided school policy. To accomplish this goal, we will examine the prevalence and characteristics of alcohol- and gambling-related policies, including policy provisions for student recovery, in a scientifically selected sample of U.S. colleges. We will not include illicit drug policies in this analysis because illicit drug use is illegal for both adults and young people; these illegal behaviors fall under the purview of state and federal law that supersedes college policy. Our intent is to examine college policies that focus on legal activities. Therefore, using college alcohol and gambling policies, binge drinking rates and gambling frequency as evidence, this report describes the epidemiology  and influence of these assorted policies.During 1989, the federal government initiated basic alcohol and substance abuse education requirements. Previously, there was not a regulatory mandate obligating institutions of higher learning to set alcohol or drug use policy or bring students' attention to these rules if they existed. Schools also were not required to disseminate substance use policy information to parents or other interested parties. This situation changed with the passage of the federal Drug-Free Schools and Communities Act (DFSCA) of 1989.The DFSCA applies to all U.S. colleges. The act specifies that "as a condition of receiving funds or any other form of financial assistance under any Federal program, an institution of higher education (IHE) must certify that it has adopted and implemented a drug [and alcohol] prevention program...". Thus, aThe overall impact of mandated drug and alcohol programs is still unknown; as we noted before, there is some evidence that risky and addictive behaviors on college campuses are still prevalent despite targeted efforts by administrators to reduce student substance abuse ,6. SeverInconsistent policy content among institutions can create a problematic state of affairs. Although DFSCA directives aim to increase awareness of the potential dangers of alcohol and drug use among students, numerous studies continue to identify high levels of alcohol abuse on U.S. college campuses in recent years ,12-14,6.Even though individual colleges have adopted different strategies for reducing the problems associated with excessive alcohol consumption, the extent and effect of these efforts are largely unknown. One approach, perhaps in response to DFSCA, has been to develop and enforce policies on student substance abuse and recovery. Although recent psychosocial programs attempting to reduce student drinking behaviors have failed to reduce binge drinking , officiaStudents who seek help for alcohol or other substance use problems are faced with a multitude of school-provided and external treatment options. Addiction recovery programs are diverse, ranging from formal treatment programs  to less formal self-help options,  . Regardlenforcement  of alcohol policies aimed at combating underage drinking did result in decreased alcohol consumption among students. Beneficial effects resulting from the enforcement of existing rules, however, can be difficult to interpret. For example, in that study, it is unclear whether the enforcement of rules encouraged lower levels of drinking or entry to treatment for intemperate drinking or, alternatively, simply forced problematic drinkers to withdraw from school.Binge drinking, the consumption of five or more alcoholic drinks (four or more for women) on at least one occasion at one to two week intervals , has beeSome research suggests that gambling on college campuses is commonplace. A study of student gambling at six colleges in five different states  showed that of 1,771 surveyed students, 23% reported that they gambled at least weekly (ranging from 11% in Texas to 39% in Nevada) . In thatFor comparison, the National Gambling Impact Study Commission (NGISC) considered the adult rates of lifetime pathological gambling from four sources . The lowOther research contradicts the findings that college students are at elevated risk for problem gambling compared to the general adult population. For example, a recently published longitudinal study of students at the University of Missouri-Columbia showed markedly lower prevalence rates than the studies summarized above . In thisDespite the frequency with which college students engage in gambling activities, some evidence suggests that administrators are unaware of the dangers associated with excessive gambling among students; in addition, colleges do not have adequate policies addressing gambling . This siThis study is the first to identify patterns of drinking and gambling-related rulemaking on college campuses . By relating school policies to known school rates of drinking or gambling ,6 we canGiven the paucity of empirical college-based policy research, this study will fill an important gap in knowledge. To fill this void, this research will test a variety of addiction-related hypotheses that have not yet been examined empirically. Based upon the extant literature, this study will test the following four primary hypotheses:• Because there are few requirements guiding the creation of school substance use and gambling policies, the content and clarity of these policies will be heterogeneous across schools and modes of policy distribution ;• College alcohol policies currently devote relatively little attention to student recovery;restrictive alcohol use policies will experience higher levels of binge drinking among students than schools with prohibitive and recovery-oriented alcohol policies;• Due to differences in enforcement, awareness of the dangers of excessive alcohol consumption, educational programs and types of students, schools with either no or only • Absent a federal mandate that requires gambling-related regulations or education on college campuses, gambling policies will be less prevalent than alcohol use policies.United States College and University Addiction and Recovery Policies. The study qualified for exemption under 46 CFR §102(f) and the assurance identification number is M1240-01.The purpose of this study is to identify and assess alcohol and gambling policies among U.S. colleges. To ensure a representative national sample of colleges, we examined the scientifically selected sample of public and private American colleges that was used in a recent series of Harvard studies . The deAt the beginning of the project, we submitted an e-mail request for a hard copy of their student handbook to each school's admissions office. Each e-mail specified that we were interested in collecting school alcohol and gambling policies and requested that our inquiry be forwarded to the most appropriate school official. We gathered e-mail addresses for admissions offices from each school's official Web site. Using each school's main telephone number to initiate contact, investigators contacted schools that did not respond within thirty days to our e-mail request and verbally requested a handbook and any other existing alcohol and gambling policy materials. Typically, the person answering the call referred us to admissions offices, deans' offices, or student services offices for further assistance; we identified ourselves as calling from Harvard Medical School only when asked.To be eligible for inclusion in this study, each college policy had to meet the following five eligibility criteria:1. the policy had to prohibit, govern, or otherwise attempt to regulate alcohol use or gambling among students at a U.S. college or university;2. the policy had to be in effect ;3. the policy had to be readily available to the public, either in electronic or hard copy;4. the policy had to be written in English;5. the policy had to be available for review by project investigators no later than July 31, 2003.Our primary source of alcohol and gambling policies was each school's student handbook.  The student handbook is a centralized forum for regulatory information and is a primary source of official school policies for students and parents, as well as the public. In addition, the concept of a student handbook is widespread, making handbooks a common information source across many schools. Many institutions distribute student handbooks to all incoming freshmen; therefore, most students are familiar and comfortable with accessing the handbook. Student handbooks also are widely available to the public.When available, we used electronic versions  of each school's handbook; otherwise, we used a hard copy. Some schools, particularly large universities with many departments and/or divisions, did not have a single handbook that they distributed to all students. In these cases, we retrieved the school's policies from other official documents . Many schools also posted policy information  on their Web sites; we analyzed this information as a secondary source. We conducted an exhaustive search of each school's Web site using each site's integrated search engine and used keywords such as "alcohol," "drinking," "alcohol policy," "gambling," "wagering," "betting," "gambling policy," "substance use policy," "college (university) regulations," and "college (university) policies" to identify relevant sections of each Web site. Several sites did not include a search function; in such cases, we conducted a comprehensive visual search of the site. We also examined supplemental materials provided by schools  for comparison against handbooks and Web-based materials. We conducted a visual search of all hard-copy handbooks and supplemental policy materials and extracted all relevant information from these sources.We systematically archived all of the Web-based and other electronic regulatory sources  from each school on a computer. We filed hard copy materials, such as student handbooks and policy manuals, by school and kept these documents on site.Investigators developed a coding instrument by studying alcohol and gambling policies from a variety of U.S. schools outside the current sample and identifying the underlying characteristics of the policies. These characteristics were reduced to 40 items that reflected the scope and focus of school alcohol and gambling policies. The items were converted into a coding instrument that included 25 variables for alcohol policy and 15 variables for gambling policy. This instrument included items to measure the presence of specific policies and establish whether the policies were punitive or rehabilitative. All variables used a nominal scale that included common characteristics of each school policy; response choices varied slightly with the focus of each variable. All of the variables were arranged on a six-page coding form.To simplify coding and allow for within-school comparisons between different formats of policy dissemination (e.g. school handbook vs. school Web site), we separated each school's policy materials into three categories: (1) student handbooks (electronic or paper); (2) Web-based materials; and (3) supplementary materials (paper); a potential 357 documents required coding . However, because not every school had documents available in all three coding categories, the final document count was 164. Specifically, at the end of our data collection process, we had collected 73 student handbooks, 70 Web-based policies, and 21 supplementary documents.We assigned 11 coders the job of evaluating each school's alcohol and gambling policies. Each coder read a selection of policies and extracted relevant information in accordance with the coding form. The coding process proceeded as follows:1. Each policy document was assigned to two of eleven eligible DOA coders randomly. Each assigned coder independently abstracted information from each assigned policy document and recorded this information on separate coding forms.2. For each document, one member of the research team, designated as the "arbiter," compared the two coding forms and marked discrepant items.3. The arbiter returned the marked coding forms to their respective coders and requested that coders reconsider their answers to the items in question. Upon reconsideration, coders were free to change their answers or keep their original answers.4. Coders resubmitted their recoded documents to the arbiter who compared the discrepant items again. Discrepancies that remained were noted and resolved by the arbiter.5. Once all discrepancies had been resolved, the policy assessments on the coding forms were entered into an SPSS database using a procedure that screened entries for out-of-range values and discrepancies in branching among items.6. We assessed data entry reliability by selecting 10% of the cases in our database and rechecking each data entry point. Of the 680 items entered in these 17 randomly selected cases, there were no observed data entry errors.Shaffer and his associates have used a similar process of information extraction, coding and arbitration successfully in other published studies ,32.Our analysis of college alcohol and gambling policies generated several types of results. First, we describe the results of our coding procedure, the final sample of schools and available policy information. Next, we examine the policy evidence across information sources by analyzing the consistency between the information provided by handbooks and Web materials. We then present the prevalence of individual policy items and the results of a factor analysis that explored the underlying dimensions of the policy variables. Finally, we analyze the relationships between policies and student drinking and gambling rates using information collected in the most recent Harvard School of Public Health College Alcohol Study (CAS) .We assessed inter-coder reliability by comparing the total number of discrepant coded items to the total number of coded items. As described previously, each policy was assigned to two of eleven eligible DOA coders randomly. The participation of eleven coders yielded 55 possible coding-pair combinations; each of these pairings coded at least one policy. Specifically, the number of policies coded by each coder-pair ranged from a minimum of one (n = 6) to a maximum of six (n = 3). Coders had up to two opportunities to code each document: (a) an initial round of coding; and (b) a second round of coding to reconsider any discrepant items identified by the arbiter after the initial round of coding. The arbiter made the final coding decision on 345 out of a total of 4,100 possible items. The coding process yielded a study-wide inter-coder reliability rate of 91.6%.After thirty days had passed from our initial e-mail request, 46 of 119 schools had responded by sending hard copy materials. Eighteen of these 46 colleges sent materials completely unrelated to our request for school alcohol policies . Fourteen schools sent student handbooks, and another 14 schools sent other alcohol and/or gambling related  materials. Seventy-three schools did not respond to our request within thirty days. Subsequent to our follow-up telephone requests, we received student handbooks and supplemental materials from an additional 22 schools. This recruitment procedure resulted in 50 schools actively providing policy information for this study; for the remainder, policy information was obtained through other investigative procedures as described earlier .This study sought information on alcohol and gambling policy from a representative sample of 119 colleges across the U.S. We utilized three distinct common sources of information on school alcohol policy: student handbooks, school Web sites (non-handbook related) and supplementary materials . We collected a total of 164 policy-related documents from three sources: 73 policy documents from handbooks, 70 documents from school Web sites, and 21 from supplementary materials. Table We aggregated and analyzed policy information across sources because a preliminary examination revealed content differences among handbooks, Web sites  and suppTo determine the added contribution of supplemental materials , we created another set of recompiled variables following the previously outlined procedure. These variables reflected the total number of policies identified for the three schools with all three types of sources . We summed the policies reflected by the recompiled variables and then subtracted the policies contributed by handbooks and Web sources; this procedure revealed that supplemental materials contributed 4 of 30 (13.3%) policy items.Although school Web sites provide a substantial amount of alcohol policy information that is not contained in the primary document customarily provided to students , the overall added contribution of the school Web site in presenting policy information varied among schools. For example, one school's Web site contained an additional eight alcohol regulations that were not included in the handbook; however, several schools' sites contained no additional information. In addition, the type of information that was presented only on Web sites also varied: while most information pertained mainly to secondary alcohol policies , some schools chose to present vital alcohol policy information  on their Web site only (n = 2). Thus, although handbooks and Web sites are both important sources of alcohol policy information and supplements contribute little additional information, consistency across sources varies. The following analyses assess the agreement of information found in multiple sources.As mentioned earlier, of the 117 colleges for which we had information, all 117 (100%) had a written policy on student alcohol consumption and 26 schools (22%) had a student gambling policy. Because all schools had a written alcohol policy (and relatively few schools had a gambling policy), the following analyses focus on alcohol policies.Determining concordance between handbook and Web sources is important because administrators might be unaware of inconsistencies between official school documents. In addition, contradictory information can mislead students and potential applicants. We assessed the concordance between sources of college alcohol policy materials by determining the level of agreement  between handbooks and Web materials; that is, we compared the content of each type of document to identify differences in the presentation of each school's policy information between sources. We did not extend this particular analysis to include supplemental materials because, as we noted before, only a small number of schools (n = 3) had all three types of sources.Twenty-eight schools had both a handbook and Web materials; for each of these 28 schools we determined the absence or presence of the 25 alcohol policy variables in each source. We predetermined that a concordance rate of 85% would indicate a high level of agreement between documents. To be considered in agreement, complementary information had to be found in (or absent from) both sources; in cases where this requirement was not satisfied, the policies were considered in disagreement. Using these criteria, we determined that three policy variables  were mentioned often and were present in both handbooks and on Web sites, and consequently, showed high agreement. Either type of information resource seldom mentioned ten policy variables , therefore, also exhibiting high agreement. The remaining 12 policy variables  were often mentioned, but not consistently by both sources, indicating low agreement.Table and Web sites in nearly all cases.Policy variables that were rarely mentioned in handbooks and Web materials appear in Table Table As noted earlier, the coding process revealed that all 117 colleges  in this sample had a written policy on student alcohol consumption, but only 26 (22%) had a published policy that addressed gambling. The small number of schools with gambling policies precludes confident analysis of the dimensional composition of our gambling variables; therefore, we applied the factor analysis that follows only to alcohol policy variables.Three policy variables represented a multi-dimensional measurement strategy to yield detailed policy information. Consequently, we collapsed these three redundant policy items into the primary or gate items from which they originated . This resulted in 22 alcohol policy variables in all remaining analyses. These dependent variables all measured different aspects of school alcohol policies . To empirically examine the underlying dimensions reflected by our variables, we conducted an exploratory factor analysis. This procedure employed an initial factor extraction  and then an orthogonal rotation to simple structure. We selected the Varimax rotation to maximize the variance of loadings within factors and minimize the covariance across factors. The orthogonal solution identified eight policy clusters with Eigenvalues greater than 1.0 that explained 72.36% of the total variation. This explained variance lies within the 50–75% useful range suggested by Overall and Klett (1972). ConsequTable School policy and the law) contained only one item that loaded ≥ 0.50 and explained 4.83% of the total variance. Many schools deferred to local law entirely and did not publish other policies that were unique to the school. Factor 1 identifies this deference policy as a unique dimension. Factor 2  expands on deference to local law and presents additional school policies that prohibit alcohol for underage and legal age students. These items accounted for 5.43% of the total variance. Factor 3 includes policies that extend restrictions to include drinking by students of legal age . Items in Factor 3 explained 6.65% of the total variance. Factors 1, 2 and 3 include alcohol policies that focus on the legal status  of students; in addition, for those of legal age, these policies range from no school specific policies to prohibitions for students who are old enough to drink legally.The eight factors are ordered according to the number of policies measuring the overall domain; that is, factors containing general, or "blanket," policy items are listed first, followed by factors containing more specific policy items. Factor 1  provides specific guidance about where on-campus students can drink and how much alcohol is available ; these items accounted for 9.13% of the total variance. Factor 5 policies  accounted for 7.20% of the total variance and focus primarily on restrictions for on- and off-campus events. Factor 6  accounted for 13.50% of the total variance and includes policies that regulate off-campus activities .Factors 4 through 6 include policy variables directed to alcohol use on-campus and off-campus. Factor 4  recognize that students can have alcohol related problems that require recovery, and that these problems can exist before entering college or develop during college; these items accounted for 20.59% of the total variance in the data. Finally, Factor 8  accounted for 5.03% of the total variance and includes policies that reflect how the school participates in the recovery process . One item  failed to load ≥ 0.50 on any factor and was excluded from the final analysis.Different from the first 6 factors, factors 7 and 8 focus on student recovery. Factor 7 policies  to 5.4% .College alcohol policies varied widely. Table We conducted several analyses to determine the nature of relationships between student alcohol consumption, gambling behavior and policy content. As the factor analysis above illustrates and the relative prevalence of policies confirms, college alcohol-related policies are primarily intended to prevent, reduce or restrict alcohol use among students on college campuses. To test the relationships between alcohol policies and student drinking behaviour, we compared the mean binge drinking rates of students at schools with and without each policy variable. We obtained the mean binge drinking rates of the schools in our sample from the dataset used in Wechsler et al.'s Harvard School of Public Health College Alcohol Study (CAS). BecauseSchools that had either no policy restrictions or a prohibition policy for on-campus alcohol use by students ≥ 21 had lower mean past-month student binge drinking rates  compared to schools that employed an intermediate level of restrictive policies (47%) . Schools that allowed or did not mention alcohol use at on-campus sanctioned events for students ≥ 21 had a higher mean binge drinking rate  than schools that prohibited legal drinking at events (33%) . Schools that offered alcohol-free housing had a higher mean student binge drinking rate of 49% compared to schools that did not mention alcohol-free housing which had a binge rate of 42% . Two other alcohol policy variables evidenced significant relationships with student binge drinking behaviors, but these policies lacked widespread implementation at a large number of schools. Schools that specifically allowed a leave of absence for a student to participate in recovery activities (n = 2) evidenced a higher mean binge drinking rate (69%) than schools that did not mention such a policy . Keeping the small number of schools in mind, it is worth noting that schools that prohibited off-campus alcohol consumption for students ≥ 21 (n = 4) had a lower mean binge rate (10%) than schools without this provision .There were not enough schools with gambling policies to permit a detailed analysis of the relationship between policies and student gambling behavior; therefore instead of conducting an analysis of the relationship between gambling behavior and individual policy variables, we only were able to assess gambling behavior based on whether schools had a gambling policy. Using prevalence data from LaBrie et al.'s (2003)  recent sLong ago, Pigou  noted thSchools that restricted or prohibited on-campus alcohol use for students over 21 evidenced similar mean past-year student gambling participation rates , and schools with no restrictive policy evidenced a higher student gambling participation rate (46%) . Schools that did not mention or allowed alcohol at on-campus events for legal drinkers exhibited a higher mean gambling participation rate  than schools that prohibited alcohol at on-campus events (35%) . Similarly, schools that did not limit the quantity of alcohol available at events showed higher past-year gambling participation among students (42%) compared to schools with no such provision (37%) . Schools that had off-campus alcohol restrictions for legal-aged drinkers had a gambling rate of 38% while schools that did not had a mean gambling rate of 42% .Two other alcohol policy variables evidenced significant relationships with student gambling behaviors, but these policies were not widely implemented throughout the sample. Schools that did not expressly prohibit alcohol consumption for underage drinkers (n = 3) evidenced a mean past-year student gambling rate of 51%, while schools that prohibited underage drinking (n = 116) had a gambling rate of 41% . Schools that banned all alcohol consumption, whether on- or off-campus (n = 4) evidenced a lower gambling rate (30%) than schools that allowed at least some drinking  .and a policy prohibiting on-campus legal-aged drinking (n = 9) had a mean binge drinking rate of 29% – much lower than schools with just an alcohol policy , a gambling policy  or neither  . Schools with both a gambling policy and a policy prohibiting alcohol at on-campus events (n = 6) had a significantly lower mean binge rate (22%) than schools with just an alcohol policy , a gambling policy  or neither  . Schools that prohibited alcohol at on-campus events also evidenced significantly lower past-year student gambling rates than schools without such prohibitions: 30% versus 38% or higher .In addition to the direct relationships between policy variables and binge drinking and gambling, three alcohol policy variables evidenced unexpected interaction or intensification effects when gambling policies also were present. Schools that had both a policy prohibiting or restricting gambling activity among students Using written  and Web based sources, this study examined the nature and extent of alcohol and gambling-related policies among a representative sample of U.S. colleges. Every school in this representative sample had at least one alcohol use policy; however, few schools  had at least one gambling policy available. The relative rarity of gambling-related policies on college campuses represents a lost opportunity by school administrators to (a) prevent or limit disordered gambling among students and (b) facilitate recovery for students in need of gambling treatment. A recent study showed that, while not as prevalent as previously thought, gambling on college campuses is still quite common, with 42% of students having gambled in the past year and 2.6% gambling weekly or more . The freAll the schools in our sample recognized the need for some type of alcohol policy; however, the presence of more targeted policies varied considerably. Although this variation might reflect different policymaking strategies across institutions, it also could result from a variety of other influences, including the lack of federal standards guiding the creation of alcohol policy on college campuses. The absence of policy guidelines leaves administrators with a wide range of options about how to best address student substance use and abuse. Some administrators might prefer to match policy to their perception of local needs, while others might welcome policy guidelines. Both of these circumstances encourage additional research designed to help guide administrators to identify effective policies .Alcohol policies ranged from comprehensive restrictions and prohibition to liberal acceptance of student alcohol use. Policies encouraging recovery among students with alcohol use disorders were decidedly absent from our sample. For example, only 57.3% of schools expressed in writing that they made referrals to alcohol recovery services; all other recovery-oriented policy provisions were in place at fewer than 30% of schools, with two-thirds of these policies in effect at fewer than 10% of schools. Examination of the mean prevalence of the eight policy factors provides additional support for this finding. The mean prevalence of recovery recognition policies was 6.5% . Although recovery facilitation policies were more common, with a mean prevalence of 42.8% , this rate simply reflects that many schools report making referrals to outside treatment facilities. In contrast, the prevalence of prohibition policies was 92.3% . This limited of consideration for student recovery and emphasis on punitive and prohibitive measures might reflect an underlying institutional bias against accommodating students with special needs and an unsupportive atmosphere for those who are at most risk for developing alcohol problems. The higher prevalence of policies that direct referrals to outside treatment resources might indicate an eagerness among administrators to export students with addiction problems to non-school affiliated assistance. Alternatively, placing little emphasis on recovery might simply represent a lack of understanding about addictive behaviors and addiction recovery among school administrators.Even though the results of this study indicate that schools with recovery policies can evidence higher rates of binge drinking, this rate might reflect a pre-existing campus problem  rather than be a result of recovery policy implementation. Future policy research needs to examine whether a better balance between punishment and treatment policies will yield improved student health services, less substance misuse and, consequently, a better campus life for all students.As hypothesized, there were considerable and important differences between the information that was available in handbooks and on the Web. This observation is not surprising because there are few requirements guiding the creation of school substance use and gambling policies and no standards requiring consistency among sources. Also, the factor analysis illustrated that alcohol policies currently concentrate primarily upon prevention and punishment, and devote relatively limited attention to student recovery. Finally, as we expected, schools with no policy restrictions on alcohol consumption or restrictive alcohol policies often experienced higher levels of binge drinking among students than schools with prohibitive alcohol policies. Nevertheless, alcohol policies were associated inconsistently with student binge drinking rates; few policy variables exerted influence on patterns of student drinking. In some cases, policies designed to reduce student alcohol consumption showed an opposite effect.The results of this policy analysis suggest diverse and perhaps ambivalent tolerance toward alcohol use among U.S. colleges that has led to a deep underlying problem: there is a lack of model policy guidelines to assist colleges in (a) preventing addictive behaviors among students and (b) providing assistance to students already struggling with addiction. Optimally, if available, such guidelines would provide school administrators with "best practice" model policies that address the many aspects of addiction among students  and would outline strategies for implementing and enforcing such policies. In the absence of an explicit regulatory framework , schools are left to regulate addictive behaviors based upon the local attitudes and expectations of communities and implicit moral values held by school administrators. This circumstance can lead colleges to install policies intended to have immediate and drastic results  while neglecting policies that would promote recovery and provide lasting benefit to students. The absence of evidence-based policy leaves school administrators in a position of promulgating policy that might have effects that are contrary to their intentions. For example, the Boston Globe reported on October 30, 2002 that, "Forty-seven Massachusetts colleges will sign onto a statewide campaign today designed to punish students who abuse alcohol and to cut down on the rate of binge drinking on campuses by providing alcohol-awareness training for students, athletes, and Greek system members". This tyThe prevalence of alcohol-related problems at U.S. colleges highlights the need for comprehensive student policies addressing all aspects of alcohol use. Further, for policy to be effective students need to be aware of and understand school requirements; this requires that students know how to access policy information. Because schools currently are not required to disseminate alcohol policies in any particular form or through any specific medium, the availability of existing policy information can vary substantially among schools. Though most commonly printed in student handbooks, substance use policies also appear in policy manuals, pamphlets and, increasingly, on school Web sites. One recent study of college Web-based alcohol policy information  found thTables This study reveals that to gain a complete understanding of the components of a school's alcohol policy, it is necessary to consult both the handbook and the school Web site whenever possible. However, schools do not alert students and parents to this fact, and it is unreasonable for school administrators to expect inquiring persons to conduct complex searches for information that is considered to be freely available in the public domain.The results of the factor analysis provide a stark portrait of the current composition of college policies on potentially addictive behaviors. This analysis reveals that six of eight factors contained prohibitive and/or punitive policy variables. Although the factor analysis merely revealed the underlying psychometric properties of our instrument, the prevalence of specific policy variables across schools provides additional support for this finding. Whereas the results suggest that prohibition-oriented policies have been effective in reducing binge drinking and gambling under certain conditions, the relative scarcity of recovery-oriented policies prevents us from properly comparing the efficacy of these two strategies.The analysis of policy variables and binge drinking rates revealed a variety of relationships among policy variables and student drinking behaviors. Specifically, four policy variables related to student binge drinking  a policy prohibiting alcohol at on-campus events and (b) a prohibitive gambling policy also had small enrollment ; four of these six schools were state-operated. Underlying characteristics of students who seek out small state schools might be associated with the reduced binge rates reported among these institutions. These results suggest that, despite the role for shared policy guidelines, schools will benefit from analyzing the composition of their student body and tailoring new and modified alcohol policies to students' specific characteristics. Although competing explanations prevent the establishment of concrete cause-and-effect relationships in this study, the observed interaction effects between alcohol and gambling policies provide significant impetus for future research into effective policy strategy on college campuses.The interaction effects observed among alcohol policy variables and the presence of gambling policy on binge drinking behavior and past-year student gambling behavior presents an interesting and unanticipated finding. Because schools that have prohibitive alcohol policies From an observer's perspective, it appears that the many policy inconsistencies – and policy presentation inconsistencies – observed in this study reflect reactive policymaking strategies that are not guided by empirical evidence. The evidence suggests that effective school alcohol and drug policies, and student awareness of these policies, are important for many reasons. For example, college-aged individuals in recovery are extremely vulnerable to relapse; in addition to the generally high rate of relapse during the first year of recovery ,48, thisIt is especially important for school administrators to address risky drinking behaviors among students who do not currently have a drinking problem. Research has shown that addictive disorders originate with risk factors that always include exposure to potential objects of addiction ,50,52. MSeveral methodological limitations to this study should be noted. First, this study relied solely upon written policy materials. Although we conducted an exhaustive search of the Internet and requested hard materials from schools, it is possible that we failed to identify some publicly available policy materials that could have provided additional information about schools in our sample. In addition, we identified our policy variables by examining existing policies and identifying relevant regulatory components; however, others attempting to replicate this study might identify and measure different aspects of policy and, consequently, obtain different results. Further, this study considered official alcohol policy content across a sample of U.S. colleges; however, assessing official policy provides no data on whether or how schools enforce their stated policies. It is possible, and in many cases even likely, that schools rely on informal rules and established precedents to govern alcohol use or gambling violations. Due to the complex nature of the relationships between school administrators, students, parents and legal authorities, many schools likely assess alcohol or gambling violations on a case-by-case basis; consequently, practice policy might be very different from the formal rules described by official school documentation.This study has shown that there are many opportunities and perhaps an obligation to scientifically investigate the complex relationships between college alcohol and gambling policies and addictive behaviors. Future research, for example, should focus on policy enforcement and informal policies adopted by school administrators to provide a better understanding of current college practices regarding alcohol use and abuse. In addition, as schools begin to reevaluate and amend their substance abuse policies, longitudinal research could provide insight into the effects of policy revision on student behaviors. In addition, to advance our understanding of policy effects on intemperate patterns of behavior, future college-based research will need to examine the influence of policies on more specific behaviors. New research should deconstruct the macro indices  of binge drinking to determine whether policies can impact college violence, crime, driving under the influence, etc.College alcohol and gambling policy data holds important potential for future research. For example, for students with alcohol or gambling related disorders attending colleges with policies that interfere with treatment or fail to support recovery, the rate of relapse is likely to be higher than under a more treatment favorable public policy context. Similarly, research can demonstrate that policies can influence the likelihood of early identification and intervention: under some unsympathetic regimes, students with addiction problems will not come forward for assistance or adhere to a prescribed treatment program. Finally, new research needs to show that without supportive policies to guide college staff responses to treatment seeking students, this population will miss both the college experience and the opportunity to build a healthy foundation for their future.In this study, we analyzed a representative sample of U.S. colleges to determine the attentiveness of school policies toward students with addictive disorders and their recovery. The results encourage the development and implementation of reporting tools  that could prove valuable as both a resource for parents of at-risk students and a vehicle to raise public awareness. Identifying trends in collegiate policymaking as well as distinguishing strong and weak policies will allow us to begin to develop evidence based guidelines, or "best practices," upon which schools can base the development of future policy.The author(s) declare that they have no competing interests.HS conceived the study, was its principal architect, and was responsible for its overall conduct and exposition. AD was responsible for the data acquisition, adjudicated the reviewer ratings, and contributed to the drafting of the manuscript. RL was responsible for the statistical design, execution, and exposition. RK provided direct assistance to AD and participated in the preparation of the manuscript. DL contributed to the study structure, data analyses, and manuscript preparation. All the authors were members of the team that critically reviewed and coded the college policies. All authors read and approved the final manuscript.


Infection of plants by necrotizing pathogens can lead to the rapid and localized induction of a complex set of defense responses resulting in a restriction of pathogen growth and spread. Subsequently, an increase of plant resistance against a broad spectrum of pathogens is observed systemically. This plant immunity is known as Systemic Acquired Resistance. To identify components of the transduction pathway, we cloned and analysed the expression pattern of several mRNAs accumulating in cucumber plants after induction of Systemic Acquired Resistance.N-Acetylglucosaminyltranferase III and a putative pathogenesis related protein. The time course of accumulation of the three corresponding mRNAs was analysed by northern blotting in plants treated by BTH or in plants infected by Colletotrichum lagenarium.We tested on cucumber different compounds known to induce systemic acquired resistance. Among these, BTH thiadiazole-7-carbothioic acid S-methyl ester) proved to be very effective. mRNA RT-PCR differential display was used to identify mRNA sequences induced 24 hours after the application of 10 μM BTH to cucumber plants. A cDNA library constructed from cucumber plants sprayed with 10 μM BTH was screened to get corresponding full length cDNAs. Among the identified cDNAs were those coding for a putative ras-related GTP-binding protein, a putative beta-1,4-N-acetylglucosaminyltranferase III have been reported to be components of signal transduction pathways in mammals and plants.The mRNA RT-PCR differential display technique allowed the identification of three genes possibly involved in Systemic Acquired Resistance in cucumber. Pathogenesis-related proteins are known to be involved in plant defence against pathogens. GTP-binding protein and  Infection of plants by necrotizing pathogens can lead to the induction of a complex set of defense responses resulting in a restriction of pathogen growth and spread. The infected leaves develop a hypersensitive response (HR), i.e., rapid, localized cell death occurring at the sites of pathogen entry . ConcomiArabidopsis thaliana [Salicylic acid was identified as an important signal in the SAR transduction pathway. It was shown to accumulate during the onset of SAR in cucumber , tobaccothaliana . Exogenothaliana . Plants thaliana ,8.A. thaliana mutants has revealed that the NPR1 protein  is required for SAR induction and acts downstream of salicylic acid in the SAR pathway. Plants carrying mutations in this gene fail to express several PR genes and display enhanced susceptibility to infection [PR-1 gene [Arabidopsis thaliana [Analysis of nfection ,10. The R-1 gene -13. The R-1 gene , while cR-1 gene . Other cthaliana . They inthaliana .PR genes include 2,6-dichloroisonicotinic acid (INA), benzothiadiazole-7-carbothioic acid S-methyl ester (BTH) and L-α-amino butyric acid (ABA) [Besides pathogens, SAR is also induced by exogenously applied chemicals. In addition to salicylic acid, well-known chemical inducers of id (ABA) -23. SAR id (ABA)  that invid (ABA) . Local aid (ABA) -28.The aim of the present work was to identify and clone mRNAs accumulating after induction of SAR in cucumber plants. These sequences could correspond to proteins potentially involved in the signal transduction pathway leading to SAR or to proteins responsible for the state of resistance. In a first set of experiments, potential SAR inducing chemicals were tested in order to set up a reproducible system of activation of this resistance in cucumber. The mRNA RT-PCR differential display method  was then2. Control plants were infiltrated with water. In a parallel experiment, four-week-old cucumber plants (with two true leaves) were sprayed with 5 mM salicylic acid, 50 mM L-α-amino butyric acid, 0.78 mM 2-thiouracil, 1 mM thiamine, 20 mM BaCl2 or 1 mM BTH. Control plants were sprayed with water or left untreated. Total RNAs were extracted from treated leaves 6 h, 24 h or 48 h after treatment. Induction of PR-8 gene was assayed by Northern blotting followed by hybridization with a cucumber PR-8 cDNA probe. PR-8 cucumber gene encodes an acidic chitinase which accumulates after tobacco necrosis virus (TNV) infection or salicylic acid induction and is considered as a SAR molecular marker [The SAR inducing activity of different chemicals has already been documented in one or several plant species -23. To er marker .PR-8 gene could be due to wounding during infiltration, the effect of wounding alone was evaluated by making a cut from the midvein to the outer edge of the cotyledons. A strong signal was obtained after wounding which could be explained by induction of the acidic chitinase itself or of an isoform. Therefore infiltration did not prove to be an appropriate method for applying SAR inducers in cucumber, because it probably induced a wound response.In infiltration experiments (results not shown), control plants showed positive hybridization signals. To check whether this activation of the 2 induced slightly PR-8 expression (results not shown). RNA from control plants did not show any hybridization signal indicating that spraying itself did not induce PR-8 expression. BTH, which is an analogue of salicylic acid, showed the strongest PR-8 induction. But cucumber plants treated with 1 mM BTH showed a reduced growth . As BTH was shown to be a very efficient activator of disease resistance in different plant species [When applied by spraying, BTH, L-α-amino butyric acid and 2-thiouracil strongly induced PR-8 mRNA accumulation, while SA treatment led to a lower induction level Fig. . Thiamin species -23, we tColletotrichum lagenarium and salicylic acid treatment was shown to induce resistance against this pathogen [C. lagenarium. Two weeks after inoculation, the plants were scored for spreading lesions, i.e. lesions showing a larger size than the initial inoculated area. As shown in figure C. lagenarium showed large spreading lesions and thus extensive fungal growth. Treatment of plants with BTH prior to C. lagenarium inoculation resulted in a markedly decreased lesion formation  were respectively 86% and 83.5%. In BTH treated plants, 38 % (10 μM BTH) or 12 % (50 μM BTH) of inoculated sites developed spreading lesions . In the remaining case (dd2), no signal could be observed on the slot blots. This absence of hybridization signal could be due to a lack of sensitivity of the slot blot hybridization procedure.Plants were sprayed with 10 μM BTH or water. Sampling was performed 24 h after treatment in order to point out early-induced differences in gene expression. RT-PCR products were separated on polyacrylamide gels. Bands that appeared on the display of RNA only from BTH treated plants, or only from water treated plants were likely to correspond to differentially expressed mRNAs. Twelve differentially expressed bands were identified Table . Their sA. thaliana. It will be referred to as CRG (cucumber RAS-related GTP-binding protein). The cDNA dd4 matched to a translation releasing factor 2. It will be referred to as CTR (cucumber translation releasing factor 2). The cDNA dd6 matched to a putative β-1,4-N-Acetylglucosaminyltranferase III from A. thaliana. This protein was named CGT (cucumber acetylglucosaminyltransferase III). The cDNA dd11 matched to a putative pathogenesis related protein from A. thaliana and, with slightly less homology, to a pathogenesis related protein from barley induced by fungal infection [The dd3, dd4, dd5, dd6, dd7 and dd11 cDNA fragments were sequenced. Blast analysis did not lead to identification of any homology with known sequences. This is not surprising as mRNA differential display generates fragments corresponding to 3'untranslated regions for which homologies are difficult to find. Two of the six fragments were proved to be part of the same gene (dd5 and dd7). A cDNA library was constructed from cucumber plants sprayed with 10 μM BTH (leaves were sampled 24 h after treatment). The library was screened with the five differentially expressed fragments. Hits were obtained for four of these probes . Full length cDNAs corresponding to dd4, dd6 and dd11 were obtained. Homology between cloned cDNA and sequences in databases is presented in table nfection . It willPR-8, CPR, CRG and CGT genes in cucumber, the two first leaves of four-week old plants were sprayed with 10 μM BTH. In another batch of plants, the first leaf was inoculated with C. lagenarium. Total RNA was extracted from treated leaves or upper untreated leaves at various times after treatment. Accumulation of the PR-8, CPR, CRG and CGT mRNAs was assayed by Northern blotting followed by hybridization with the corresponding cDNA probes  and by inoculation with C. lagenarium (with a maximum at 72 h) in the leaves submitted to the treatment. A systemic induction could also be observed in untreated leaves from C. lagenarium inoculated plants (as from 72 h after infection).nts fig. . NeverthCRG gene was too low to allow us to show an induction of the expression (data not shown).The expression level of the PR-8 and CPR genes was only observed in the cut leaf 24 h after wounding. No expression was observed later nor in the uncut upper leaf. The CGT and CRG genes were not induced by wounding (results not shown).Expression of the same genes was analyzed in wounded cucumber plants. A cut was made from the midvein to the outer edge of the first leaf. Total RNA was extracted from the cut leaf or the upper leaf, 24 and 48 h after wounding. An induction of the expression of Pseudomonas putida BTP1 suspension, a plant growth-promoting rhizobacteria known to promote induced systemic resistance in cucumber [PR-8, CPR, CGT and CRG did not show any induction of expression in these conditions (results not shown).Expression of these genes was also analyzed in cucumber plants showing rhizobacteria-induced systemic resistance. Plants were grown in compost drenched with a cucumber . Total RPR-8 gene, which encodes an acidic chitinase from cucumber, was used as an indicator of the activation of the defense response. The accumulation of this acidic chitinase after tobacco necrosis virus infection or salicylic acid induction correlates with induced resistance [PR-8 gene expression. The protective effects of BTH on cucumber were confirmed in challenge experiments with C. lagenarium. Spraying cucumber plants with BTH (10 μM or 50 μM) allowed effective local and systemic protection against C. lagenarium. BTH was recently identified as a safe, reliable and non phytotoxic plant protection agent by scientists at Novartis. Exogenous application of BTH to tobacco, A. thaliana, wheat and cucumber has been shown to activate a number of SAR associated genes leading to enhanced plant protection against various pathogens [We tested here two different techniques and several compounds to induce SAR in cucumber. The expression of sistance . Among tathogens -22,28.N-acetylglucosaminyltranferase III (CGT) and a putative pathogenesis related protein (CPR). Expression of PR-8, CPR and CGT genes was shown to be induced by 10 μM BTH treatment as well as C. lagenarium infection. The response to BTH was observed earlier (5 h after treatment) than the one developed after pathogen inoculation (72 h after infection). However, systemic expression of these genes was only observed in C. lagenarium infected plants.Identifying SAR induced genes could provide clues to elucidate the signal transduction pathway leading to plant defense responses. We used RT-PCR differential display in BTH-treated cucumber plants to detect SAR associated mRNAs. We have identified four BTH-inducible genes: a putative ras-related GTP binding protein (CRG), a putative translation releasing factor 2 (CTR), a putative β-1,4-N-Acetylglucosaminyltranferase III catalyses the addition of N-acetylglucosamine to the β-mannoside of the tri-mannose core in N-glycans, resulting in the suppression of further processing and elongation. In mammals, N-acetylglucosaminyltransferase III expression is associated with differentiation, cell adhesion and tumor progression [2O2-induced activation of protein kinase C [N-linked glycans were shown to be widely distributed in plants and highly expressed at the cell surface, which might suggest a putative function in cell/cell communication [N-Acetylglucosaminyltranferase has never been described in the context of a plant-pathogen interaction. Several cDNAs or gene encoding enzymes involved in the biosynthesis of complex N-linked glycans have been cloned from plants. They include N-acetylglucosaminyltranferase I cDNAs from A. thaliana, potato and tobacco [N-acetylglucosaminyltransferase II cDNA from A. thaliana [N-acetylglucosaminyltranferases are involved in important mechanisms, notably signaling pathways and therefore seem of high interest. The putative PR protein, which has been first identified in barley after fungal infection [Small GTP-binding proteins form a large family of nucleotide triphosphatases whose activity is related to the binding, hydrolysis and release of guanosine triphosphate . MAP kingression ,44. It wkinase C ,46. N-linication . To our  tobacco , N-acetythaliana  and defethaliana . GTP-binnfection  has no kPR-8 and CPR genes were induced by wounding but not systemically. PR-8 and CPR genes were not induced by P. putida BTP1 treatment, which triggers induced systemic resistance (ISR) in cucumber. ISR is phenotypically similar to SAR but the mechanisms of this resistance were shown to be different: although this was not tested with P. putida BTP1, in other experimental systems ISR was shown to be dependent on NPR/NIM1 function, but does not involve salicylic acid, nor PR protein accumulation [A. thaliana was independent of PR genes expression [CGT and CRG expression, as these genes were not induced by P. putida BTP1.Only mulation . Our respression . In the C. lagenarium. Using RT-PCR differential display, we identified four BTH-inducible genes, including a putative ras-related GTP binding protein (CRG), a translation releasing factor 2 (CTR), a putative β-1,4-N-acetylglucosaminyltranferase III (CGT) and a putative pathogenesis related protein (CPR). Genes expression studies confirmed the local induction of CGT and CPR after BTH treatment or C. lagenarium infection and their systemic induction in response to C. lagenarium infection. Moreover CPR was locally induced by wounding. The significant level of expression of CGT and CPR genes during defense responses suggests a potential role for the gene products in the SAR pathway or in the state of resistance in cucumber.Among different SAR inducers tested on cucumber, BTH proved to be very efficient. Applied by spraying, BTH induced PR-8 mRNA accumulation and allowed effective local and systemic protection against Cucumis sativus cv. Marketer) were grown in compost at 22°C with a 16 h light photoperiod.Cucumber plants . Chemicals were dissolved in water and the pH adjusted to 6.6 with NaOH except for thiamine, BaClPseudomonas putida BTP1 suspension (4.108 CFU/ml in 0.85% NaCl). Control seeds were soaked in 0.85% NaCl. Cucumber seeds were sown in 10 cm-pots containing sterilized potting soil previously mixed with a P. putida BTP1 inoculum to a final concentration of 3.107 CFU/g or with an equal volume of sterile water for control plants. Cucumber were germinated at 25°C with a 16 h light photoperiod. Six and 12 days after sowing, 20 ml of a bacterial suspension at 108 CFU/ml were added as a drench to the roots. Control plants were watered with 20 ml of 0.85% NaCl.Prior to planting, disinfected cucumber seeds were soaked for 10 min in a C. lagenarium (106 spores/ml). In challenge experiments, inoculation was performed 5 (or 7) days after chemical treatment on the second or third leaf.Plants were placed in a humidity chamber 48 hours before infection experiments. The first true leaf was inoculated with 10 drops (10 μl) of a conidial suspension of 32P PR-8, CPR, CGT or CRG cDNA probe .The extraction of total RNA from cucumber leaves (5 plants per treatment) was performed using a phenol/SDS method . Norther35S dATP, separated by electrophoresis on denaturing 6% polyacrylamide gels and visualized by autoradiography. PCR reactions showing differentially displayed bands were repeated twice on two different RNA samples in order to reduce the number of false-positives.The mRNA differential display was performed using the differential display kit from Eurogentec (Belgium) and following the instructions of the supplier. PCR products were labeled with α-2O followed by boiling during 10 min, then precipitated and suspended in 10 μl of H2O. A second PCR amplification was performed on 4 μl of DNA following the same protocol than for the differential display itself. Products were cloned in pGEM-T vector (Promega) and manually sequenced by the dideoxy sequencing method. Available public databases (i.e. EMBL) were searched for homology with our sequences using the GCG software package .Differentially displayed bands were excised and eluted during 30 min in 100 μl of H32P labeled RT-PCR corresponding products from either BTH or H2O treated plants.PCR amplified DNA from four to ten clones of each differentially displayed band was blotted on a positively charged nylon membrane using a filtration manifold and following the instructions of the supplier (Hoefer). Blots were hybridized with the 32P labeled cDNA probes. cDNA sequencing was performed at Genome Express, France. Available public databases (i.e. EMBL) were searched for homology with our sequences using the GCG software package .mRNA from cucumber plants sprayed with 10 μM BTH (leaves were sampled 24 h after treatment) were purified with the PolyATractmRNA Isolation System III from Promega. The cDNA library was performed with the SMART cDNA Library Construction Kit from Clontech following the instructions of the supplier for cDNA synthesis by primer extension. The library was screened with CB carried out the plants treatments, the molecular biology studies and the database research and drafted the manuscript. MO supplied the pathogen and participated in the challenge and ISR induction experiments. JD and PT participated in the design and coordination of the study. All authors read and approved the manuscript.PR-8 mRNA accumulation in cucumber leaves in response to different concentrations of BTH. Total RNA was extracted from cucumber leaves 24 h and 48 h after spraying with water, 10 μM BTH, 30 μM BTH, 100 μM BTH or from untreated leaves (UT). RNA was fractionated by electrophoresis on agarose gel. Northern blot was probed with α-32P labeled PR-8 cDNA. Loading of equal amounts of RNA was confirmed by ethidium bromide (Et Br) staining.Click here for file


In this study, we analyzed TL-3 efficacy using a highly pathogenic FIV-C isolate, which causes a severe acute phase immunodeficiency syndrome, with high early mortality rates.The protease inhibitor, TL-3, demonstrated broad efficacy p ≤ 0.05) higher viral RNA loads as compared to asymptomatic animals. A marked and progressive increase in CD8+ T lymphocytes in animals surviving acute phase infection was noted, which was not evident in symptomatic animals (p ≤ 0.05). Average viral loads were lower in TL-3 treated animals and of the 6 animals requiring euthanasia, four were from the untreated cohort. At eight weeks post infection, half of the TL-3 treated animals and only one of six untreated animals had viral loads below detection limits. Analysis of protease genes in TL-3 treated animals with higher than average viral loads revealed sequence variations relative to wild type protease. In particular, one mutant, D105G, imparted 5-fold resistance against TL-3 relative to wild type protease.Twenty cats were infected with uncloned FIV-C and half were treated with TL-3 while the other half were left untreated. Two uninfected cats were used as controls. The general health and the immunological and virological status of the animals was monitored for eight weeks following infection. All infected animals became viremic independent of TL-3 treatment and seven of 20 FIV-C infected animals developed severe immunodepletive disease in conjunction with significantly (The findings indicate that the protease inhibitor, TL-3, when administered orally as a monotherapy, did not prevent viremia in cats infected with high dose FIV-C. However, the modest lowering of viral loads with TL-3 treatment, the greater survival rate in symptomatic animals of the treated cohort, and the lower average viral load in TL-3 treated animals at eight weeks post infection is indicative of a therapeutic effect of the compound on virus infection. Infected cats exhibit similar disease patterns as human immunodeficiency virus (HIV) infected patients by developing multiple immuno-depletive symptoms collectively referred to as acquired immunodeficiency syndrome (AIDS). As with HIV, differences in virulence among the different FIV subgroups are evident -4. Thus,in vitro with similar effectiveness -L-alanyl-L-valyl]amino])  treatmenUninfected and FIV-infected animals were intermittently scheduled for analyses of evoked potentials in conjunction with the blood sampling, including testing for both auditory and visual evoked potentials as previously described . Once reAnimals were examined daily and in case of health concerns further therapy/diagnostics were initiated. Animals with abnormal weight, or on antibiotics were placed on supplemental feeding with moist food and Nutrical. Dehydrated animals received subcutaneous fluid therapy. More affected animals received supportive care and medications, consisting of BID administration of antibiotics (Baytril), BID subcutaneous fluid therapy, BID temperature evaluation, BID application of antibiotic ophthalmic ointment supportive care. Any animals that required extensive supportive care  were euthanized. Euthanasia of research animals was conducted with strict adherence to NIH Office of Laboratory Animal Welfare protocols.Blood samples  were collected weekly during the first month of the study and then every two weeks thereafter, as described . SamplesPlasma was separated from blood by centrifugation at 3000 rpm for 5 minutes at room temperature. Blood cells were resuspended in 3 ml PBS and PBMC were separated from buffy coats by density gradient centrifugation using Ficoll-Hypaque Plus . PBMC were washed once in PBS and twice in PBS/2% FBS for flow cytometry analyses.Statistical p values for the FIV-C viral load were determined by the Student's two-tailed t-test . Statistical p values for the weekly total CD4 and CD8 cell counts were also determined by the Student's two-tailed t-test .1κ FITC and PE  were used as isotype controls. Cells were fixed with 2% PFA prior to analysis performed on a FACScan flow cytometer (Beckton Dickenson Immunocytometry Systems) using the Cell Quest Software program.Two-color flow cytometry analysis was performed on cells stained with mouse α-feline CD4 FITC and mouse α-feline CD8 PE . Anti-mouse IgG9 copies RNA /280 μl plasma), corresponding to the 1.2 kb KAN gene , was used to normalize plasma volumes between samples and to correct for sample loss from viral RNA extraction and cDNA synthesis. An on-column DNase/ RNase free (Qiagen) incubation step for 10 minutes at room temperature was added to remove residual cellular DNA. Complimentary DNA (cDNA) was generated in a 20 μl total reaction using 13 μl of sample RNA, 0.5 μl (2 μM stock) each of KAN and FIV specific reverse primers (sequences below) and StrataScript reverse transcriptase, following the manufacturer's protocol . After incubation, each cDNA sample was diluted in water to 30 μl and stored at -80°C for use in real-time PCR.Plasma for weeks 0, 2, 4, 6 , 6.5 , and 8, were isolated from whole blood by centrifugation and stored at -20°C. Viral RNA was extracted using the QiaAmp Viral RNA Isolation Kit  according to manufacturer's instructions with slight modifications: Plasma samples (280 μl) were lysed in buffer AVL  (Qiagen) for 10 minutes at room temperature in the presence of carrier RNA (10 μg/ml) and an external Kanamycin (KAN) RNA spike. Equal amounts of the external RNA spike  , forward, reverse primers and probe mix (7.5 μl), and cDNA target (5 μl). The mixture was incubated at 50°C for 2 minutes, 95°C for 10 minutes, then cycled at 95°C for 15 seconds and 60°C for 60 seconds 55 times, using the ABI Prism 7700 Sequence Detection System . Data were analyzed using the ABI 7700 Sequence Detection Software. Forward and reverse primers  used in real-time PCR were made at IDT, , while the fluorescein-dabsyl Amplifluor UniPrimer  was purchased from Serologicals . The primer sequences used for real-time PCR are as follows:FIV reverse-transcriptase forward: 5'-ACTGAACCTGACCGTACAGATAAATTACAGGAA GAACCCCCATA-3'FIV reverse-transcriptase reverse: 5'-TGTTAATGGATGTAATTCA TAACCCATC-3'KAN forward: 5'-ACTGAACCTGACCGTACACGCTCAGGCGCAATCAC-3'KAN reverse: 5'-CCAGCCATTACGCTCGTCAT-3'8 to 5 × 102 copies per well) of dsDNA plasmids of known copy number , against the cycle threshold (Ct) determined for that value. The pET28 vector (Novagen) was used as the target plasmid for the KAN gene, while a plasmid containing the molecular clone of FIV-C was used for the FIV reverse-transcriptase gene. Calculated values for each plasma sample represent relative copy numbers for the purposes of evaluation between individual samples.To determine the relative copy numbers of KAN and FIV from plasma samples, a linear standard curve was generated by plotting 10-fold dilutions (5 × 10Complementary DNA (cDNA) was synthesized from isolated plasma viral RNA of infected cats. The cDNA pool was used as a template for PCR reactions using 5' primer MFIVCPL5' (5'-GATTTATAAATCATATG GCATATAATAAAGTGGGTACCACTACAACATTAG-3'), which adds an NdeI restriction site, methionine, and alkaline to the N-terminal of the protease and 3' primer MFIVCPL33' (5'-CTGAGATCTGAGCAAGCTTTTACATTACTAATCT AATATTAAATTTAACCATG TTATC-3'), which adds a stop codon and a Hind III restriction site to the C-terminus of the protease. The amplified PCR product was gel purified and cloned into pCR-TOPOII vector  for sequencing. Selected DNA of mutants, N55D, H72R, D105G, and M107R were digested with Nde I/Hind III and ligated into pET21a expression vector (Novagen). The mutant FIV-C proteases were expressed in Rosetta pLysS cells (Novagen) and purified as previously described .2)-Val-Gln-Ser-Lys-Gly-Arg-NH2. The concentration was determined by active-site titration with inhibitor TL-3. Inhibitor constant (Ki) of TL-3 against mutant FIV-C protease was analyzed as described [Enzyme kinetics of FIV-C protease were assayed on the flourogenic substrate Arg-Ala-Leu-Thr-Lys(Abz)-Val-Gln/Phe(NOescribed .None of the authors have commercial interests or direct association with a company that is marketing TL-3. J.H.E. is a co-author of a patent application regarding use of protease inhibitors like TL-3 reported here, containing small P3 residues, as inhibitors of HIV and FIV.S.R. and C.H.S contributed equally to this work and carried out all tissue culture analyses, purification and characterization of cell populations isolated from PBMC, statistical analyses, and preparation of results for publication. Quantitative PCR analyses was carried out by D.A.S. K.J.C. was responsible for all in vivo animal work, including TL-3 administration and oversight of veterinary care for the animals. S.H-R. carried out measurements of brainstem auditory evoked potential changes. S.H., B.E.T, and J.H.E. acted as mentors for the various facets of the project, oversaw the writing of the manuscript, and provided space and funding to carry out the work.


The knowledge of factors accurately predicting the long lasting sick leaves is sparse, but information on medical condition is believed to be necessary to identify persons at risk. Based on the current practice, with identifying sick-listed individuals at risk of long-lasting sick leaves, the objectives of this study were to inquire the diagnostic accuracy of length of sick leaves predicted in the Norwegian National Insurance Offices, and to compare their predictions with the self-predictions of the sick-listed.Based on medical certificates, two National Insurance medical consultants and two National Insurance officers predicted, at day 14, the length of sick leave in 993 consecutive cases of sick leave, resulting from musculoskeletal or mental disorders, in this 1-year follow-up study. Two months later they reassessed 322 cases based on extended medical certificates. Self-predictions were obtained in 152 sick-listed subjects when their sick leave passed 14 days. Diagnostic accuracy of the predictions was analysed by ROC area, sensitivity, specificity, likelihood ratio, and positive predictive value was included in the analyses of predictive validity.The sick-listed identified sick leave lasting 12 weeks or longer with an ROC area of 80.9% (95% CI 73.7–86.8), while the corresponding estimates for medical consultants and officers had ROC areas of 55.6% (95% CI 45.6–65.6%) and 56.0% (95% CI 46.6–65.4%), respectively. The predictions of sick-listed males were significantly better than those of female subjects, and older subjects predicted somewhat better than younger subjects. Neither formal medical competence, nor additional medical information, noticeably improved the diagnostic accuracy based on medical certificates.This study demonstrates that the accuracy of a prognosis based on medical documentation in sickness absence forms, is lower than that of one based on direct communication with the sick-listed themselves. The increasing rate of sick leave experienced in most Western countries challenges insurance companies, employers, and public authorities to identify measures to reduce burdens at the individual, workplace and societal levels.To reduce the expenses of sick leave and the risk of expulsion from work, the Norwegian government introduced legislation in 1993 that anticipated early and more vigorous interventions of the Norwegian National Insurance Scheme , 2000, uThe selection process is currently based on information in medical sickness certificates supplied by access to the register of previous sickness benefits. A medical sickness certificate  is required if sick leave exceeds 3 days, and after 8 weeks an extended medical certificate is mandatory  .Based on the current practice with identifying sick-listed individuals at risk of long-lasting sick leaves, the objectives of this study were to inquire diagnostic accuracy of predictions within the NIOs, and to compare their predictions with the self-predictions of the sick-listed.In October and November 1997 and March and April 1998, newly sick-listed persons with musculoskeletal or mental disorders   were incA total of 495 randomly selected persons received a questionnaire on the expected length of their ongoing sick leave period. The answer categories were: less than 4 weeks, 4 to 7 weeks, 8 to 11 weeks, 12 to 15 weeks, 16 to 25 weeks, 26 to 51 weeks, and at least 1 year. Some 152 persons (30.7%), called the responder group, returned the questionnaire with this question filled in.Based on SC1s available after 14 days of sick leave, two NIO officers without formal medical competence, but experienced in working with sick-listed persons, and two experienced physicians working part time as insurance medical officers , assessed the expected length in each of the 993 ongoing sick leave cases. In 496 randomly chosen cases, the NIO assessors had additional access to information on sick leave periods during the previous 3 years. Of potentially 1986 assessments in each profession, the officers and medical consultants had 18 and 25 missing assessments, respectively.SC2s became available in 322 of the 459 cases where sick leave exceeded 8 weeks, and the NIO assessors reassessed these cases.Reproducibility of assessments by medical consultants were analysed in 20 cases reassessed by the two NIO medical consultants, and assessed by another eight of their colleagues.The reference standard lengths of individual sick leaves within 1 year were collected from the National Sickness Benefit Register. Sick leaves interrupted by only 1–2 days without sickness benefits, typically on weekends, were registered as a single period. The observed length of sick leave thus comprised the total period of continuous full-time or part-time absence due to sickness within 1 year.The diagnostic accuracy of predicted lengths was compared on the basis of sensitivity, specificity, likelihood ratio and the area under the receiver operating characteristics curves (ROC area) ,7. The nThe predictive validity is presented as sensitivity, specificity, positive predictive value (PPV) and likelihood ratio at different thresholds, cut-offs, in predicted length . ReliabiThe Regional Ethical Committee approved the protocol, and the Norwegian Data Inspectorate licensed the necessary register of sick-listed subjects.The mean observed continuous sickness absence was 100.8 days (median 48 days). Sick leaves in females lasted a mean of 105.1 days, compared to 94.6 days in men . The mean length among persons with musculoskeletal disorders was 90.2 days in 335 males and 108.6 days in 489 females. The mean length among persons with mental disorders was 120.6 days in 56 males and 90.0 days in 113 females.The mean length of the sick leave in the responder group was 107.4 days , compared to 92.4 days in the 343 non-responders. Stratified analysis revealed longer mean sick leaves among responders 40 years and younger, of 109.3 days (95% CI 81.4–134.5 days), compared to the 79.3 days (95% CI 65.6–93.1 days) in non-responders. Stratification on gender or musculoskeletal or mental disorders did not reveal any significant differences in the length of sick leave between responders and non-responders.All assessors, including the sick-listed themselves, systematically overestimated the length of short sick leaves (lasting 4–11 weeks) and underestimated the length of long sick leaves , and sick leaves lasting 26 weeks or longer with a ROC area of 75.5% (95% CI 67.9–82.1%). Sick-listed persons with mental disorders or with neck, or shoulder and arm disorders, were most accurate in their assessment Figure . This waThe sick-listed subjects predicted their sick leaves with higher sensitivity and PPV than the NIO assessors Tables , 4. MaleDuration of at least 8 weeks was the preferable cut-off in predicted length, to identify sick leaves lasting at least 12 weeks Table . A prediThe sensitivity of identifying sick leaves lasting at least 26 weeks was generally low when medical consultants and officers predicted on the basis of SC1s. Table . The senAccording to the results, the effects of the different predictive strategies can be illustrated by considering a program designed to intervene in all cases where the subject is expected to be sick-listed for more than 12 weeks at 14 days of sick leave. Out of every 1000 sick-listed persons, 333 will be sick-listed for more than 12 weeks according to the prevalence in this study. The random selection of 333 persons will include 111 true positives, while 333 persons selected by officers will include 133 of the 333 persons that will be sick-listed at least 12 weeks. The evaluation of 1000 sick-listed individuals thus increases the number of true positives by 22 in a selection of 333 sick-listed persons. The alternative strategy of asking the sick-listed themselves will include 210 true positives in a selection of 333 persons.Agreement between medical consultants in their initial prediction of sick leaves lasting at least 12 weeks, was fair, with a kappa of 0.31 (95% CI 0.20–0.43). The corresponding kappa value between officers was 0.05 (95% CI -0.05–0.14).In the prediction of sick leaves lasting at least 12 weeks based on the SC2, agreement was moderate between medical consultants  and fair between officers . The corresponding agreements in the prediction of sick leaves lasting at least 26 weeks were moderate between medical consultants  and fair between insurance officers .The differences in diagnostic accuracy, between the two participating medical consultants and their eight colleagues in the reproducibility group, were not significant.The results of the present study question any practical value of using information in medical sickness certificates in predicting the length of sick leave, as is the current practice in Norwegian NIOs. Instead, the sick-listed themselves predicted their length of sick leaves far more accurately, but this information is not routinely sought.The officers in the present study were selected from experienced officers who had shown an interest in the field of sick leave. This might introduce a bias of overestimating the officers' general ability to predict the length of sick leaves. The performances of the two medical consultants were representative of eight of their colleagues who participated in the reproducibility part of the study. We therefore consider the diagnostic accuracy of the assessors to be representative of their professional groups, or at least not underestimated due to bias. Although the diagnostic accuracy varied within each group, the main conclusion of better predictive ability among the sick-listed, was challenged neither by comparing with the mean length predicted by assessors, nor by comparing with the best-performing NIO assessor.The distributions of gender and diagnosis among the 993 persons included in the study were comparable with those in the National Sickness Benefits Register. The findings of longer sick leaves in women with musculoskeletal disorders, and longer sick leaves in men with mental disorders, are consistent with the Register and other studies -13.The low responder rate among the sick-listed introduced a possible selection bias, although we could not identify any selection bias in gender, age, diagnosis or occupation . If therIf the lengths of sick leaves were predominantly related to loss of function caused by sickness, in line with the legislation, we would expect that the medical consultants' professional competence would favour them in predictions of the lengths of sick leaves. The differences we observed between medical consultants and officers in mean ROC area, were however minor. Furthermore, we could not demonstrate any significant differences in diagnostic accuracy between medical consultants and officers when aggregate information on disease, treatment, function related to work, and prognoses were available in the SC2. The improvement in ROC area with this aggregated information was minor, with the area just reaching 70%, which is considered borderline useful for some purposes , and is The Norwegian NIO is obliged by legislation to perform early intervention on the sick-listed in an effort to reduce the length of sick leave and the risk of expulsions from work. Limited resources and the large number of sick-listed individuals make selection desirable before any intervention is initiated. An alternative to selection on the basis of medical certificates is to communicate directly with the sick-listed themselves. This selection for intervention by NIOs might be seen as screening. The aim is to reach – at an acceptable cost – as many as possible of those that might profit from intervention. The potential individual gain by intervention will be greater when longer lasting sick leaves can be anticipated, and greater the sooner individual intervention programs are established.The marginal predictive ability and modest agreement between NIO assessors questions the use of resources in selection based on information from medical certificates. The predictions of medical consultants tend to be better than those of officers, but not to an extent that makes it more meaningful to use medical consultants in the selection process, rather than officers.With limited resources for intervention, it might be more cost effective to identify those whose sick listing will last longer than 26 weeks instead of 12 weeks. Based on self-reporting, eight out of ten would be true positives, and one fourth of the individuals would be reached. To reach the same number of true positives at 14 days of sick leave, the ratio of true positives would be reversed from eight out of ten, to two or three out of ten, if the selection were based on medical certificates.In the search for tests predicting long-lasting sick leaves, such as The Örebro Musculoskeletal Pain Questionnaire , the preSick-listed individuals predicted their length of sick leave far more accurately than did NIO medical consultants and officers based on information from sickness certificates and the history of past sick leaves. The predictions of sick-listed males were better than those of females, and older persons predicted better than younger persons. The availability of more information, as through the SC2, had only a minor effect on the predictive ability of the medical consultants and officers. Neither reliability nor validity of their predictions was satisfactory.This study demonstrates the need to re-consider the diagnostic usefulness of documentation on sickness absences, and supports a change in strategy from collecting more medical information to more direct communication with the sick-listed themselves, for effective and early interventions to prevent long sick leaves and expulsions from work.The author N.F. is part-time employed as National Insurance medical consultant.NF was in charge of designing and running the study, and performed most of the analyses and the writing of this manuscript. RJ actively supervised all parts of the study, and OHF contributed to planning and writing. All authors read and approved the final version of the manuscript.The pre-publication history for this paper can be accessed here: