Student assistance program outcomes for students at risk for suicide.

Evidence Based Practice and Policy Reports

Student Assistance Program Outcomes for Students at Risk for Suicide

The Journal of School Nursing 2014, Vol. 30(3) 173-186 ª The Author(s) 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1059840514525968 jsn.sagepub.com

Virginia Sue Biddle, PhD, RN, CPNP, PMHNP-BC1, John Kern III, PhD2, David A. Brent, MD3, Mary Ann Thurkettle, PhD, RN4, Kathryn R. Puskar, DrPH, RN, CS, FAAN5, and L. Kathleen Sekula, PhD, APRN, FAAN6

Abstract Pennsylvania’s response to adolescent suicide is its Student Assistance Program (SAP). SAP has been funded for 27 years although no statewide outcome studies using case-level data have been conducted. This study used logistic regression to examine drug-/alcohol-related behaviors and suspensions of suicidal students who participated in SAP. Of the 46 services, 10 best predicted (p < .01) that these undesirable outcomes would cease. Although no study subjects died by suicide, 42 of 374,626 referred students did die by suicide. Suicidal students who did not participate had double the rate of suicide of suicidal participants of SAP. Students referred for other reasons also killed themselves. Further work must be done to assess all referred students for suicide risk, examine educational outcomes, monitor substance-related crimes and overdoses, and examine school-related factors postmortem. Evidence from this study can be used by researchers to plan future studies and by Pennsylvania’s school nurses when planning services. Keywords emergency care, crisis intervention, mental health, safety, injury, prevention, screening, risk identification, high school, self-injury, program, development, evaluation, quantitative research

School nurses and nurse practitioners are in a prime position to identify and aid high school students at risk for suicide, a devastating public health problem in the United States. Suicide is the third leading cause of death for youth 15 through 19 years of age and the second leading cause of death for Caucasian youth in the same age-group (Centers for Disease Control and Prevention, 2012b). Two behavioral risk factors for suicide that may be monitored by school personnel are substance use/abuse and being suspended from school (Fergusson, Beautrais, & Horwood, 2003; Foley, Goldston, Costello, & Angold, 2006; Swahn & Bossarte, 2007; Thompson, Eggert, Randell, & Pike, 2001; Windle, 2004). Substance use is problematic because of its disruptive effects on the ability to regulate oneself psychologically and its adverse impact on social adjustment (Tarter, Kirisci, Reynolds, & Mezzich, 2004). In other words, it can cause impaired judgment and disinhibition (Campbell & Rohrbaugh, 2006; Makhija & Sher, 2007). Students who possess, use, sell, or are under the influence of drugs or alcohol may be suspended from school or school-related activities as punishment. Suspensions are problematic because they remove adolescents from the usual school support network.

Pennsylvania’s solution to suicide and substance use/ abuse is its Student Assistance Program (SAP), named in 1991 as the program to satisfy its Act 211 requirement to identify, intervene, and refer for appropriate services students having mental health and drug and alcohol problems (Commonwealth Student Assistance Program Interagency Committee, 2004a). A SAP must exist in each of Pennsylvania’s 619 high, 572 middle, and 1,917 elementary school

1

Department of Psychiatry and Human Behavior, Thomas Jefferson University, Philadelphia, PA, USA 2 Department of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA, USA 3 Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh, Pittsburgh, PA, USA 4 Department of Nursing, Slippery Rock University, Slippery Rock, PA, USA 5 School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA 6 School of Nursing, Duquesne University, Pittsburgh, PA, USA Corresponding Author: Virginia Sue Biddle, PhD, RN, CPNP, PMHNP-BC, Department of Psychiatry and Human Behavior, Division of Child and Adolescent Psychiatry, Suite 210, 833 Chestnut Street, Philadelphia, PA 19107, USA. Email: [email protected]

Downloaded from jsn.sagepub.com at MCMASTER UNIV LIBRARY on March 11, 2015

174

The Journal of School Nursing 30(3)

Table 1. Calculation of Potential Years of Life Lost for Youth 15–19 Years of Age Who Died by Suicide in Pennsylvania for Years 2000 through 2010. Age at Death in Years 15 16 17 18 19

Number of Suicides

Years of Potential Life Lost per Suicidea (Based on Age 65 Years)

73 100 114 148 189 672c

65 65 65 65 65

15 ¼ 50 16 ¼ 49 17 ¼ 48 18 ¼ 47 19 ¼ 46

Total Years of Potential Life Lostb 73 50 49 100 48 114 47 148 46 189

¼ 3,650 ¼ 4,900 ¼ 5,472 ¼ 6,956 ¼ 8,694 31,971

a

‘‘Years of Potential Life Lost per Suicide’’ is calculated by subtracting the ‘‘Age at Death in Years’’ from age 65 (Pennsylvania Department of Health, 2013). ‘‘Total Years of Potential Life Lost’’ is determined by multiplying ‘‘Years of Potential Life Lost per Suicide’’ by the ‘‘Number of Suicides.’’ c In all, 672 youth died by suicide out of a total population of 9,989,424 aged 15 through 19 years (for years 2000 through 2010). The rate of suicide for this group was 6.7 (rate ¼ [672/9,989,424] 100,000). b

buildings and cyber and charter schools (Commonwealth Student Assistance Program Interagency Committee, Departments of Education, Health, and Public Welfare, 2011; EducationBug.org, 2013). The primary goal of the SAP is to help students overcome barriers to student success in each school district (Commonwealth Student Assistance Program Interagency Committee, 2004b). Although the SAP has existed for 27 years, no studies have examined statewide outcomes for individual participants. Therefore, the purpose of this study was to examine relationships between participation in Pennsylvania’s SAP; violation of school drug and alcohol policies due to use/abuse, possession, or distribution of drugs/alcohol; and suspensions from school or school activities for students at risk for suicide. It examined the incidence of suicide for students referred to the SAP as well. This study was part of a larger study that also examined reasons for referral, attendance, performance, and promotion and graduation (Biddle, 2009).

Background and Significance of the Problem The rate of suicide in the United States was 7.56 per 100,000 for 15- through 19-year-old adolescents for years 2000 through 2009 (National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, 2010). Pennsylvania’s rate for the same period was near the national rate at 7.08—a staggering 31,971 lost years of life for its youth (Table 1). Since any incident of suicide is unacceptable, Healthy People 2020: Understanding and Improving Health targets suicide attempts of adolescents (U.S. Department of Health and Human Services, 2012). Objective Mental Health Mental Disorders-2 (MHMD-2) is to reduce suicide attempts from a baseline of 1.9 per 100 adolescents (for 2009) to 1.7, a 10% reduction based on Youth Risk Behavior Surveillance System data. The National Strategy for Suicide Prevention highlights the importance of school prevention efforts that target youth

suicide (U.S. Department of Health and Human Services Office of the Surgeon General and National Action Alliance for Suicide Prevention, 2012). Objective 5.2 of the strategy is to encourage community-based settings, including schools, to provide education and implement effective programs that promote wellness and prevent suicide and related behaviors. The strategy states that schools can ensure that students at risk for suicide have access and are encouraged to use counseling. In Pennsylvania, this is done via the SAP.

Literature Review Prior research has demonstrated that a relationship exists between suicidal ideation and attempts and the two educational outcomes of interest in this study—drug and alcohol use/abuse and suspensions from school. A retrospective analysis of survey data from 13,110 students in Grades 7 through 12 collected via the National Longitudinal Study of Adolescent Health showed that alcohol, marijuana, and illicit drug use predicted suicide attempts (Borowsky, Ireland, & Resnick, 2001). A study using Youth Risk Behavior Survey data gathered from 13,639 high school students revealed that initiation of preteen alcohol use was also associated with suicidal ideation and attempts (Swahn & Bossarte, 2007). Relationships between onset/current use of substances, illicit drug use, problems controlling drug use, and suicide risk have been found for students at risk for dropping out of high school (Cho, Hallfors, & Iritani, 2007; Walsh & Eggert, 2007). Relationships have also been found between alcohol/drug, cigarette, illicit drug use, and youth suicide in Michigan, western North Carolina, rural Tennessee, and the United States as a whole (Dunn, Goodrow, Givens, & Austin, 2008; Epstein & Spirito, 2009; Foley et al., 2006; Perkins & Hartless, 2002; Swahn et al., 2012). Limitations of these studies included selfreported data, low response rates, inability to infer causality, lack of medical verification of suicide attempts, ideation rather than attempts, and high levels of suicidal ideation required for inclusion.


Biddle et al.

175

Relationships have also been identified between suicidality and school suspensions, the other educational outcome of interest. Risk of suicidal ideation and suicide attempts has been correlated with school suspensions for students younger than 15 years of age (Fergusson et al., 2003). In the Great Smoky Mountains study (Foley et al., 2006), functional impairment, measured using school suspensions and other domains related to school and family, was associated with suicidality. Psychological autopsies, used to identify factors that may be related to a suicide by gathering and synthesizing information via structured interviews of family and friends, forensic reports, and health care records and other documents (Isometsa, 2001), showed that suicide victims were more likely to have been suspended and to have experienced other school difficulties compared to controls (Gould, Fisher, Parides, Flory, & Shaffer, 1996). The SAP was created and piloted during 1984 as a process for early identification of youth having problems in school due to drug or alcohol use (Commonwealth Student Assistance Program Interagency Committee, 2004a; Newman, Henry, DiRenzo, & Stecher, 1988). Intervention strategies for suicidal students were added during the 1986–1987 school year (Commonwealth Student Assistance Program Interagency Committee, 2004a). The SAP in each school is implemented by a professionally trained core team that may include nurses and nurse practitioners, counselors, teachers, an administrator, a school district representative, and liaisons from county mental health and drug and alcohol systems (Commonwealth Student Assistance Program Interagency Committee, 2004b). Team members identify student psychosocial problems, determine if they are within school responsibility, and suggest interventions (Commonwealth Student Assistance Program Interagency Committee, 1991, 2004a). When a problem is beyond the array of services provided at school, teams assist in accessing services within the community. Few evaluations of SAPs have been conducted. A survey concerning the SAP in the Owen J. Roberts School District revealed that 92% of high school students believed that student assistance services should be provided (TaylorMearhoff, 1990). In all, 66% reported that they would refer a troubled friend, 39% reported knowing someone who had been helped, 11% reported that they had been helped, and 38% were referred for treatment during the 1989–1990 school year. Seventy-eight percent of faculty reported knowing someone who had been helped. No educational outcomes were examined. Sample size and study limitations were not discussed. A retrospective analysis of SAP data for one urban school district in Pennsylvania was conducted for school years 1998–1999 through 2000–2001 (Fertman, Tarasevich, & Hepler, 2003). It showed that referrals increased since the 1995–1996 school year, that students were consistently linked to behavioral health care at a higher rate than reported nationally based on the Report of the Surgeon General’s

Conference on Children’s Mental Health (U.S. Public Health Service, 2000), and that a majority complied with recommendations. Suspensions also decreased. Violations of school drug and alcohol policies, an outcome of importance in this study, were not examined. Neither study of the SAP focused on students at risk for suicide.

Purpose The purpose of this study was to examine relationships between participation of students at risk for suicide in Pennsylvania’s SAP and educational outcomes, including (1) possession, distribution, and use or abuse of substances (referred to as drug and alcohol policy violations) and (2) suspensions from school and school-related activities (referred to as suspensions). These outcomes were measured at the time of referral to the SAP and at closure of a student’s case (the student no longer needed services, graduated, transferred to a different school, dropped out, or the school year ended). Incidence of suicide was also examined. We asked the following questions: ‘‘Which services, if any, were associated with drug and alcohol policy violations and/or suspensions for students at risk for suicide?’’ and ‘‘What was the incidence of suicide for students referred to the SAP?’’

Conceptual Framework The protection-risk model was the guiding framework for this study. It proposes that risk factors (family history of alcoholism, poor school work, etc.) increase the likelihood of problematic behavior and negative outcomes and that protective factors (value on health, high controls against deviant behavior, etc.) moderate the impact of risk factors, decreasing the likelihood of problematic behaviors (Jessor, 1991; Jessor, Turbin, & Costa, 2003). Risk factors may be noticed by school personnel, parents, peers, and community agency staff who may refer students to the SAP (Pennsylvania Department of Education, 1997). Students may also refer themselves. They may learn about SAP through school websites or brochures (Commonwealth of Pennsylvania Departments of Education, Health, and Public Welfare, 2004; North Allegheny School District, 2013). Reasons for concern include talking about suicide, wanting to die, having no reason to live, or being a burden (Suicide Prevention Resource Center, n.d.). Risk factors may lead to risky behaviors and lifestyles that result in health/life-compromising outcomes. Suicidal ideation or attempt, the reason subjects were referred to the SAP, are examples of risk behaviors/lifestyles that contribute to health/life-compromising outcomes in the protection-risk model (Jessor, 1991; Jessor et al., 2003). These outcomes include suspensions and drug and alcohol policy violations and death by suicide. Interventions recommended by SAP team members target risk factors, protective factors, and behaviors/lifestyles in an effort to improve outcomes and prevent suicide.


176


Method An inferential, retrospective, secondary regression analysis was conducted. The study was approved by the Institutional Review Board of Duquesne University, the educational institution under which it was conducted.

Data Analyses were performed on SAP data for school years 1997–1998 through 2005–2006. It is maintained by the Pennsylvania Department of Education (DOE) in an online database accessed via a web-based application referred to as SAP Online. The data were requested from the Chief of Safe Schools of the Pennsylvania DOE. The DOE’s consultant removed all personal and school information from the data prior to e-mailing it in Microsoft Access files.

Population Characteristics The SAP population included 347,626 cases of all high school students referred to the SAP during school years 1997–1998 through 2005–2006. The students were 13 through 21 years of age and attended 9th through 12th grades. The population was divided into the SAP population referred for suicide risk (n ¼ 18,445) and the SAP population referred for reasons other than suicide risk (n ¼ 329,181). This study focused on the first of these—students referred for suicidal ideation, gesture, or attempt (also referred to as suicide risk and risk for suicide). Suicide refers to a fatality that results from suicidal behavior (act of self-injury) associated with at least some intent to die (Posner, Oquendo, Gould, Stanley, & Davies, 2007). Suicidal ideation refers to active thoughts about killing oneself or passive thoughts about wanting to die. Suicide gesture, which is no longer recommended for use due to its pejorative nature (Posner et al., 2007), describes violence that is suicidal by nature and self-directed with little or no intent to die. It may be a way to communicate that something is wrong, prepare for an attempt, or manipulate or control others (Centers for Disease Control and Prevention, 2012a; Crosby, Ortega, & Melanson, 2011). For purposes of this study, gestures are classified as suicidal ideation as recommended by Posner, Oquendo, Gould, Stanley, and Davies (2007). Suicide attempt is potentially a self-injurious behavior with at least some intent to die as a result.

Sample Characteristics A sample was included in each of the two logistic regression analyses in this study. Samples refer to randomly selected cases of suicidal students drawn from the SAP population referred for suicide risk. The first sample included 2,037 cases in which subjects (individual students within each sample) were identified as having violated drug and alcohol policies. The second sample included 2,016 cases in which subjects were identified as having been suspended from

school. For the 4,053 cases in both samples combined, only 2,112 were unique since many students had both violated drug and alcohol policies and been suspended from school. With respect to the 2,112 students who comprised the unique cases, two thirds (66.5%) were female and one third (33.5%) were male. Student ethnicity was primarily White (81.7%), African American (7.9%), and Hispanic (6.6%). The ethnicity of a small percentage of students was multiracial (1.4%), Asian or Pacific Islander (1%), Asian Indian (1%), and American Indian or Alaskan Native or Aleut (0.1%). The cases included approximately 6% more Whites (total of 75.5%) and 8% fewer African Americans (total of 16%) compared to the Pennsylvania public school student population for 2004–2005, the final year of this study. Population data were obtained from the Annie E. Casey Foundation (2013). Pennsylvania has 19 urban and 48 rural counties, with 235 of its 500 school districts located in rural counties (Center for Rural Pennsylvania, n.d.-a). Students attending rural schools comprise one fourth (26%) of Pennsylvania’s public school student population (Center for Rural Pennsylvania, n.d.-b). One fourth of students (27.2%) whose unique cases were included in this study also attended rural schools. The remainder of the students attended urban schools. SAP participation was highest for Grade 9 and lowest for Grade 12. Two percent of subjects were gifted, while one fourth (26.2%) attended special education classes. Few (0.9%) were legally emancipated.

Measures Outcome variables. Two variables of interest, drug and alcohol policy violations and suspensions, were designated as educational outcomes (Table 2). These dependent variables were measured and recorded at the time of referral and again at closure of a student’s case. They were recorded as ‘‘improved’’ only if they stopped occurring (equaled zero). Suicides, the worst possible mental health outcome for students referred to the SAP, were also examined. Independent variables. Dichotomous independent variables (also referred to as explanatory or predictor variables by Hosmer and Lemeshow, 2000a) included 54 services recommended to students by SAP team members, with 19 services offered in schools (school services) and 35 services offered by agencies in communities (community-agency services; Table 2). The variety of services is needed because every strategy is not appropriate for every school, and different approaches are needed for different students (Centers for Disease Control and Prevention, 2001). As a result, services are not the same across students and schools, and some schools and communities may have more effective services than others. Demographic and personal variables, which were potential confounding variables in this study, included age, gender,


Biddle et al.

177

Table 2. SAP Variables Used in the Study. Type of Variable

Variable Name

Values

Dependent, dichotomous

Drug and alcohol policy violations

Dependent, dichotomous

Suspensions

Independent, dichotomous

Referred for suicidal ideation or attempt

0 ¼ violations have continued or worsened since referral to the SAP, and 1 ¼ no violations have occurred since referral to the SAPa 0 ¼ suspensions have continued or increased since referral to the SAP, and 1 ¼ no suspensions have occurred since referral to the SAPa 0 ¼ student was not referred to the SAP for this reason, and 1 ¼ student was referred to the SAP for this reason 0 ¼ student did not participate in the service, and 1 ¼ student did participate in the service



School services: Academic supports, Alternative school placement, Conflict resolution, Crisis intervention, Dropout prevention program, Drug and alcohol aftercare/support group, Drug and alcohol education/prevention group, Mental/behavioral health aftercare/support group, Mental health special issues group (divorce, grief, loss, etc.), Mentoring, Multidisciplinary team evaluation, No services recommended. One-to-one counseling with guidance counselor, school psychologist, etc. One-to-one follow-up with team member or other school personnel, Other, Other in-school group, School-based juvenile probation, Services by/from school social worker, Team intervention, and Teen parenting/pregnancy program. Community-agency services: Academic support, Other community services, Outpatient drug/alcohol treatment, Juvenile probation, Mental health treatment—Behavioral health rehab services, Inpatient mental health treatment, Outpatient mental health treatment, Mental health treatment—Partial program, No services recommended, Other social services agencies (e.g., children, youth, & family services), Referral to in-school support/aftercare services, Screening/assessment by licensed drug and alcohol provider, Screening/assessment by licensed mental health provider, and Screening/assessment by behavior specialist (e.g., combined drug and alcohol, mental health, violence, etc.). 0 ¼ service was not recommended, and Additional community agency services: 1 ¼ service was recommended Assessment by behavioral specialist, Assessment by drug and alcohol provider, Assessment by other social services agency, Continue existing drug and alcohol services, Continue existing mental health services, Children and youth services, Domestic violence center, Faith-based organization, Juvenile probation, Other community services, Rape action center, and Team recommended other. Downloaded from jsn.sagepub.com at MCMASTER UNIV LIBRARY on March 11, 2015

(continued)

178


Table 2. (continued) Type of Variable

Variable Name

Values

One-to-one follow-up and outpatient mental health treatment, Independent, Counseling and outpatient mental health treatment, dichotomous interaction effect Crisis intervention and outpatient mental health treatment, and Inpatient mental health treatment and outpatient mental health treatment Demographic and Gender Non-White ethnicity personal, White ethnicity dichotomous Unknown ethnicity (includes Black/African American, Hispanic, Asian or Pacific Islander, Asian Indian, Asian, multiracial, other, and Hispanic ethnicities) Gifted student Special education student Legally emancipated Rural/urban status of county Demographic and Age personal, ordinal Grade Month referred to the SAP

Number of times referred to the SAP during the current school year

Total # of referral reasons per case

0 ¼ student did not receive both services, and 1 ¼ student did receive both services

0¼ 0¼ 0¼ 0¼

male and 1 ¼ female no and 1 ¼ yes no and 1 ¼ yes no and 1 ¼ yes

0 ¼ No and 1 ¼ Yes 0 ¼ No and 1 ¼ Yes 0 ¼ No and 1 ¼ Yes 0 ¼ Urban, 1 ¼ Rural 13 through 21 years 9 through 12 1 ¼ Carried over from previous school year (n ¼ 0) 2 ¼ August (n ¼ 19) 3 ¼ September (n ¼ 335) 4 ¼ October (n ¼ 312) 5 ¼ November (n ¼ 262) 6 ¼ December (n ¼ 227) 7 ¼ January (n ¼ 204) 8 ¼ February (n ¼ 200) 9 ¼ March (n ¼ 220) 10 ¼ April (n ¼ 161) 11 ¼ May (n ¼ 104) 12 ¼ June (n ¼ 28) Missing ¼ 40 n ¼ 2,112 1 (n ¼ 1,651) 2 (n ¼ 313) 3 (n ¼ 78) 4 (n ¼ 70) n ¼ 2,112 0 (n ¼ 650) 1 (n ¼ 557) 2 (n ¼ 370) 3 (n ¼ 230) 4 (n ¼ 135) 5 (n ¼ 89) 6 (n ¼ 42) 7 (n ¼ 21) 8 (n ¼ 13) 9 (n ¼ 4) 11 (n ¼ 1) n ¼ 2,112

Note. SAP ¼ Student Assistance Program; SS ¼ school service, CAS ¼ community-agency service, TR ¼ SAP team recommendation. a Outcomes that show improvement.

grade, gifted, attended special education classes (for students with low intelligence quotients), ethnicity, legal emancipation, attendance at school in a rural or urban county, month that the student was referred to the SAP, and number of times referred during the particular school year (Table 2). They were controlled by including them in analyses as independent variables (Kleinbaum & Klein, 2002).

Analysis This inferential study used retrospective SAP data in combination with logistic regression models. Backward elimination was chosen as the method of variable selection because it is useful when the outcome has not been studied previously, when important independent variables are not known, and when associations between the independent


Biddle et al.

179

variables and outcomes are not well understood (Hosmer & Lemeshow, 2000b). Furthermore, it provides a fast and effective means for screening large numbers of variables and fitting a number of logistic regression equations. Separate regressions were conducted using SPSS 16.0. We examined the relationships between one of the two dichotomous-dependent variables (drug/alcohol violations, suspensions) and the independent variables (services) by implementing two separate logistic regression analyses— drug and alcohol policy violations versus services and suspensions versus services. Analyses were completed for unique cases. Associations between dichotomous independent variables and outcomes were determined based on slope coefficients (B) in the regression models. If the slope was positive (þ), the outcome was likely to improve in the presence of the independent variable. If the slope was negative (), the outcome was likely to improve in the absence of the independent variable. All sample sizes exceeded power analysis requirements (p < .05, two-tailed test, effect size of .20, n 318 cases; Kramer & Chmura, 1987). Based on goodness-of-fit tests (Cox and Snell R2, Nagelkerke R2, and chi-square), we concluded that independent variables (services and control variables) enabled us to make better predictions about the outcomes than we could have made without them. Post hoc analyses were also performed to examine suicides. We compared the incidence of suicide for students referred for suicide risk to that of students referred for other reasons. Within these groups, we compared incidence for participants—students referred to the SAP who participated in recommended services—to nonparticipants—students referred to the SAP who did not participate in recommended services. Reasons for not participating included refusal to participate, not being able to obtain parental permission, and already receiving treatment.

Results Many services in which subjects participated were statistically significant independent variables that predicted drug and alcohol policy violations and/or suspensions, the two educational outcomes of interest in this study.

Educational Outcomes All services contained in the final logistic regression model (Table 3) for drug and alcohol policy violations versus services had positive slope coefficients, meaning that all of them predicted that violations were likely to cease for subjects that received the particular service. Due to the large number of services, only those that were significant at p < .01 are listed. These include ‘‘alternative school placement,’’ ‘‘assessment by licensed drug and alcohol provider,’’ ‘‘children and youth services,’’ ‘‘faith organization,’’ ‘‘one-to-one counseling,’’

‘‘assessment by behavior specialist,’’ ‘‘crisis intervention,’’ and ‘‘drug and alcohol education/prevention group.’’ All services contained in the final logistic regression model for suspensions and services (Table 4) had positive slope coefficients (B)—all predicted that subjects would no longer be suspended from school after participating in the SAP. Services that were significantly associated with suspensions that stopped for students at risk for suicide at p < .01 included ‘‘assessment by licensed drug and alcohol provider,’’ ‘‘juvenile probation,’’ and ‘‘crisis intervention and outpatient mental health treatment,’’ all of which were received by students. All statistically significant services are summarized in Table 5.

Demographic and Personal Variables Several demographic and personal variables that were statistically significant in predicting drug and alcohol policy violations and suspensions varied across the models (Tables 3 and 4). Only ‘‘month’’ predicted outcomes in both models, having a positive (þ) slope coefficient (B). The later the month of the school year (August through June) in which the student was referred to the SAP, the more likely it was that drug and alcohol policy violations and suspensions would cease. The greater the number of services that a student received, the greater the likelihood that drug- and alcoholrelated behaviors would stop. The greater the number of times that a student was referred, the more likely that suspensions would cease. These relationships are associative, and not causal, as they are based on observational data.

Nonparticipants in the SAP Population Referred for Suicide Risk Post hoc analyses were completed to examine differences in educational outcomes between participants and nonparticipants in the SAP population referred for suicide risk. Reasons for not participating and whether services were received elsewhere are unknown. Among SAP participants, 85% (n ¼ 9,908) stopped being suspended from school compared to 83% (n ¼ 547) of SAP nonparticipants, and 98% (n ¼ 11,086) of participants stopped their drug- and alcohol-related behaviors compared to 97% (n ¼ 623) of nonparticipants.

Suicides Post hoc analyses were also completed for deaths by suicide of participants and nonparticipants in the SAP population (Table 6). None of the 2,112 students who comprised the unique cases included in this study died by suicide. Fortytwo others did die by suicide. These students were not included in the sample of unique cases because they were nonparticipants or both educational outcomes of interest in this study were not a problem for these students. Fisher’s exact tests were completed to compare suicide rates. Within the SAP population referred for suicide risk,


180


Table 3. Binary Logistic Regression Model for Services Predicting Drug and Alcohol Policy Violations (n ¼ 2,037). 95% CI for EXP(B) Independent Variable Alternative school placement (SS) Assessment by licensed drug & alcohol provider (TR) Children and youth services (TR) Constant Month Total # of services Faith organization (TR) One-to-one counseling (SS) Assessment by behavior specialist (TR) Crisis intervention (SS) Drug and alcohol education/prevention group (SS) One-to-one follow-up (SS) Age Juvenile probation (SS) Continue existing mental health services (TR)

B

Sig.

Odds Ratio, Exp(B)

Lower

Upper

3.024 2.83 2.062 23.213 0.362 0.461 2.968 1.596 1.726 1.356 1.896 1.055 0.363 1.94 0.941

.000 .000 .000 .000 .000 .000 .001 .001 .002 .002 .004 .012 .021 .026 .034

20.574 16.946 7.860 .000 1.436 1.585 19.446 4.931 5.616 3.882 6.657 2.872 1.438 6.96 2.563

5.939 6.223 2.625 — 1.178 1.274 3.129 1.858 1.854 1.674 1.830 1.256 1.055 1.258 1.076

71.265 46.145 23.537 — 1.751 1.973 120.877 13.092 17.011 9.005 24.212 6.570 1.960 38.501 6.109

Note. SS ¼ school service, TR ¼ team recommendation; CI ¼ confidence interval; four independent variables included in the model are significant at p < .05 but are not discussed in the article.

nonparticipants had a suicide rate that was double that of participants (129.25 compared to 65.20 suicides per 100,000 persons). The difference in rates was not statistically significant. Both of these groups, however, did have statistically significant higher rates of suicide compared to both participants (11.43 suicides per 100,000 persons) and nonparticipants (4.39 suicides per 100,000 persons) in the SAP population referred for reasons other than suicide risk (Table 6).

Discussion This study provided the only available evidence concerning Pennsylvania’s SAP and educational outcomes of suicidal students. It did so by identifying services that were significantly associated with the cessation of drug and alcohol policy violations and suspensions. The findings are important because school nurses and other SAP team members need to consider promising services when making recommendations for care and inquiring about student preferences. Post hoc analysis also determined that no subjects in this study experienced the worst possible mental health outcome—suicide. This and the other findings are important to stakeholders, including school personnel, since they have an implicit contract with parents to protect student safety (Substance Abuse and Mental Health Services Administration, 2012); state legislators and taxpayers, who need to know whether state funding is being spent on an effective SAP; and school nurses and other SAP team members, who need to ensure that effective care is being provided and that progress is being made toward the achievement of student goals.

Interventions Related to Cessation of Drug and Alcohol Policy Violations or Suspensions One of the responsibilities of school nurses and other SAP team members is to refer students at risk for suicide to helpful community providers and school services (Substance Abuse and Mental Health Services Administration, 2012). In this study, services that were associated with drug and alcohol policy violations that ceased included placement in an alternative school, assessment by a licensed drug and alcohol provider or behavior specialist, children and youth services that intervene in alleged cases of child abuse, counseling provided by faith organizations or school personnel, crisis intervention at school, and participation in a drug and alcohol educational/prevention group. Services that were associated with suspensions that stopped were assessment by a licensed drug and alcohol provider, juvenile probation in school, and crisis intervention and outpatient mental health treatment when the student has participated in both interventions. These services need to be given careful consideration when planning care. Many services, however, were not associated with improved educational outcomes. These included academic supports, behavioral health rehab, continuation of existing drug and alcohol or mental health services, drug/alcohol and mental health/behavioral aftercare/support groups, special issue groups, outpatient drug/alcohol treatment, inpatient mental health treatment, partial programs, assessment by a licensed mental health provider or social services agency, conflict resolution, domestic violence centers, mentoring, services from rape action centers or social workers, SAP team intervention, teen parenting/pregnancy


Biddle et al.

181

Table 4. Binary Logistic Regression Model for Services Predicting Suspensions (n ¼ 2,016). 95% CI for EXP(B) Independent Variable # of times referred during current school year Assessment by licensed drug & alcohol provider (TR) Month Non-White ethnicity Constant Crisis intervention (SS) and outpatient mental health treatment (CAS) Juvenile probation (SS) School located in rural PA county Assessment by behavior specialist (TR) SAP team intervention (SS) Grade Other community services (CAS) Alternative school placement (SS) Multidisciplinary team evaluation (SS) Dropout prevention (SS) Gender Gifted student Special education student Total # of services

B

Sig.

Odds Ratio, Exp (B)

Lower

Upper

0.443 1.051 0.134 0.595 4.763 0.479 1.393 0.369 0.572 0.593 0.142 0.502 0.67 0.565 0.97 0.286 1.391 0.277 0.06

.000 .000 .000 .001 .002 .006 .008 .013 .020 .021 .027 .027 .033 .038 .044 .045 .062 .064 .072

0.642 2.861 1.144 1.814 .009 1.615 4.027 1.446 1.772 .552 1.153 1.652 1.954 1.76 2.639 0.751 .249 1.319 1.061

0.548 1.872 1.081 1.292

0.753 4.374 1.211 2.546

1.149 1.448 1.081 1.092 0.334 1.016 1.058 1.056 1.033 1.027 0.567 0.058 0.984 0.995

2.271 11.199 1.935 2.874 0.913 1.308 2.579 3.616 2.999 6.782 0.994 1.073 1.768 1.133

Note. CI ¼ confidence interval; CAS ¼ community-agency service, SS ¼ school service, SAP ¼ Student Assistance Program; TR ¼ team recommendation; 12 independent variables included in the model are significant at p < .05 but are not discussed in the article.

Table 5. Services That Predicted That Drug and Alcohol Policy Violations or Suspensions Were Likely to Cease for Students at Risk for Suicide Who Participate in the SAP. Services That Predicted That Drug and Alcohol Policy Violations and Suspensions Were Likely to Cease SAP Outcomes

Most Likely to Cease

Likely to Cease

Drug and alcohol policy violations

Alternative school placement (SS)*** (20.6)a Assessment by licensed drug & alcohol provider (TR)*** (16.9)a Children & youth services (TR)*** (7.9)a

Suspensions

Assessment by licensed drug and alcohol provider (TR)*** (2.9)a

Faith organization (TR)** (19.4)a One-to-one counseling (SS)** (4.9)a Assessment by behavior specialist (TR)** (5.6)a Crisis intervention (SS)** (1.7)a Drug and alcohol education/prevention group (SS)** (6.7)a One-to-one follow-up (SS)* (2.9)a Juvenile probation (SS)* (7.0)a Continuing existing mental health services (TR)* (2.6)a Crisis intervention and outpatient mental health treatment (IEV)** (1.6)a Juvenile probation (SS)** (4.0)a Assessment by behavior specialist (TR)* (1.8)a Other community services (CAS) * (1.7)a Alternative school placement (SS)* (2.0)a Multidisciplinary team evaluation (SS)* (1.8)a Drop-out prevention (SS)* (2.6)a

Note. SAP ¼ Student Assistance Program; SS ¼ school service, CAS ¼ community-agency service, TR ¼ SAP team recommendation, IEV ¼ interaction effect variable (interaction term). a Indicates the odds ratio, the likelihood of change in drug and alcohol policy violations and suspensions related to participation in the service. All services listed predicted that violations or suspensions would cease. *p < .05. **p < .01. ***p ¼ .000.

programs, and referral to in-school support/aftercare services. If any of these services are selected, programs with proven track records need to be sought, and progress needs

to be monitored frequently to ensure that educational outcomes and school, social, and family functioning are improving.


182


Table 6. Suicide Rates for the SAP Population. Category

Number of Suicides

n

Total

Rate of Suicide per 100,000 Studentsa

9 6 —

13,803 4,642 —

— — 18,445

65.20b 129.25c —

SAP population referred for suicide risk Participants Nonparticipants Total SAP population referred for suicide risk SAP population referred for reasons other than suicide risk Participants Nonparticipants Total SAP population referred for reasons other than suicide risk Total SAP population

22 6 —

192,516 — 136,665 — — 329,181

—

—

347,626

11.43 4.39 — —

Note. SAP ¼ Student Assistance Program. a ‘‘Rate of Suicide per 100,000 Students’’ was calculated using the following formula: (Number of Suicides /n) 100,000. bStatistically significant higher suicide rate (65.20) compared to participants (p ¼ .0001, rate ¼ 11.43) and nonparticipants (p < .000001, rate ¼ 4.39) in the SAP population referred for reasons other than suicide (based on Fisher’s Exact test). c Statistically significant higher suicide rate (129.25) compared to participants (p < .000001, rate ¼ 11.43) and nonparticipants (p ¼ 0.00033) in the SAP population referred for reasons other than suicide (based on Fisher’s exact test).

Demographic and Personal Variables Subjects who received a greater number of services may have experienced cumulative positive effects, helping them to address suicide risk and substance-related issues stemming from multiple psychosocial needs. Perhaps outcomes improved for those referred during later months of the school year because they wanted to be promoted to the next grade or to graduate. They may also have realized that they would soon have a respite from their school-related problems. Being referred multiple times may indicate that students have serious psychiatric issues such as bipolar disorder that may require time to treat or symptoms that are not responding to treatment. Hence, they may have been less likely to stop being suspended. Number of referrals can serve as a warning sign that students may need an intensive or increased level of care. The unique cases that were part of the study included fewer African Americans compared to the Pennsylvania public school population (16%). The percentage of African American subjects at risk for suicide (7.9%) is closer to the rate of suicide attempts among African American youth based on the 1991–2001 Youth Risk Behavior Survey (8.65%; Sean & Marcus, 2003). Although the rate of suicide among African American adolescents aged 15 through 19 years has increased (rate of 4 for year 2010), it is still less than that for Caucasians of the same age (rate of 8.3 for year 2010).

Nonparticipants at Risk for Suicide Post hoc analyses were completed to examine differences in outcomes between participants and nonparticipants in the SAP population referred for suicide risk. Similar results were found for each group—almost all participants and nonparticipants stopped their drug- and alcohol-related behaviors, and over four fifths of both groups stopped being

suspended from school. One explanation is that the referral process itself may be therapeutic. This is supported by the finding of Thompson, Eggert, Randell, and Pike (2001) that even brief suicide risk assessments and crisis intervention can be beneficial for young people. However, whether students had problematic drug- and alcohol-related behaviors outside of school is unknown. Also, problematic behaviors may not always be detected or brought to the attention of school personnel.

Suicides Services in which subjects participated may have been effective in preventing suicide since no subjects died by suicide. However, this study did not address causal relationships. Forty-two students who were referred to the SAP still died by suicide. They constituted less than 1% of all 15- through 19-year-old Pennsylvanians who died by suicide during 1997 through 2006 (n ¼ 634; Pennsylvania Department of Health, n.d.), the years of this study. Clearly, the majority of youth who were suicidal during those years did not participate in the SAP and may not have been referred at all. Perhaps they were never identified as being at risk, were truant from school, had graduated, had dropped out of school, or attended a private school. The SAP referral process discriminates between the SAP population referred for suicide risk and the SAP population referred for reasons other than suicide risk. However, participants in the latter population fared no better when it came to suicide than nonparticipants in the same population, suggesting that a better job may need to be done of assessing students referred to the SAP for reasons other than suicide risk for exactly that—suicide risk. The best approach may be to assess all students in the SAP population for suicide risk, regardless of reasons for referral.


Biddle et al.

183

Difficulties and Limitations Due to the large number of independent variables that were statistically significant in the logistic regression models, consideration was given to using Bonferroni correction to ensure that the final models included the independent variables (services) that best predicted outcomes. In Bonferroni correction, the level of significance is divided by the number of hypothesis tests. In this study, the a level would have been zero due to the large number of variables. This would have eliminated a large number of statistically significant independent variables (services) from the models. Menard (2002) suggests relaxing the usual .05 criterion for statistical significance since, in exploratory research such as this, greater emphasis is placed on finding good independent variables (predictor or explanatory variables) rather than eliminating bad ones. For this study, variables were deemed significant at the .05 level and are indicated as such. Data such as psychiatric illnesses and level (severity) of suicide risk cannot be shared in the SAP database without child and parental/guardian consent. Level of risk is important because students at higher risk may require longer periods of treatment and recovery. They may also have lingering cognitive and functional issues that negatively impact educational outcomes. Variables such as parental support and socioeconomic status could not be measured or controlled for as this information was not contained in the database. SAP participation, as well as services obtained, could be impacted by these variables. Although the SAP database contains variables that represent referrals to the SAP during prior years of school, no method for linking cases across different school years existed. The assumption had to be made that all cases were for different students. An additional limitation was the inability to ensure that data had been entered correctly into the SAP database. This is the responsibility of SAP team personnel. Not all students at risk for suicide are referred to the SAP. During a pilot study, some school counselors stated in personal communications that they phone parents/guardians when they identify students at risk, as they should with all suicidal students (Biddle, 2009). Parents/guardians pick up the students and accept responsibility for obtaining appropriate care. Data concerning these students are not contained in the SAP database. The database also does not include academic outcomes for students never in need of referral. Outcomes cannot be compared without following up on nonparticipants or performing postmortem follow-up if students died. Outcomes also could not be compared with other evidencebased programs because no reports examining relationships between participation and educational outcomes were found.

Implications Although this study was exploratory in nature, it provided information concerning SAP services that moderate

relationships between risk for suicide and unacceptable drugand alcohol-related behaviors and suspensions of high school students. The results (Table 5) can be used by school nurses and nurse practitioners and other Pennsylvania SAP team members when recommending and referring students for services. Suicides can effectively be averted by developing positive connections and building protective factors, including support, good relationships, academic achievement, positive peer groups, coping skills, confidence, new knowledge, connectedness, and accessible health care (King, 2006; Mental and Behavioural Disorders Department of Mental Health, World Health Organization, 2000). Nurses and other SAP team members can consider protective factors of individual students, preferences for care, and results of this study as they recommend services—services that will develop connections, build protective factors, and address psychosocial risk factors.

Recommendations for Future Research Intervention studies of services designed to develop connections, build protective factors, and address suicide risk and related factors must be conducted to ensure that SAP team personnel are recommending effective services. Any ineffective services also need to be identified and replaced. Evidence showing program effectiveness may contribute to increased and timely referrals. Interventions aimed at identification of suicidal students, keeping suicidal students in school, and helping them to achieve need to be created and evaluated. Drug and alcohol policy violations and suspensions for suicidal students who participate in the SAP need to be compared to those students who do not participate in the SAP after being referred as well as those who do not need to be referred at all to the SAP. In addition, drug and alcohol crimes need to be monitored via the juvenile justice system, and drug and alcohol overdoses and suicide attempts need to be monitored via the public health system. The Home, Education, Activities, Drug use and abuse, Sexual behavior, and Suicidality and depression interview instrument could be incorporated into nursing assessments (Biddle, Sekula, Zoucha, & Puskar, 2010). Reliable and valid methods for assessing severity of risk—mild (in need of outpatient care in the future), moderate (in need of immediate outpatient care), or severe (in need of emergent care)— need to be developed. Psychological autopsies need to be performed for all adolescents who die by suicide. For the SAP, we need to focus on high school students referred and not referred. These examinations can help to elucidate factors we may not be cognizant of at this time. For example, for those 42 students who were referred but still died by suicide, what factors might we have overlooked? How were those students different from the others? A mandate would be a start to establishing a death review team for all teen suicides in Pennsylvania. The team would examine all


184


variables, among them SAP participation, graduation, and dropping out of school.

Summary

Authors’ Note This manuscript is based on doctoral dissertation Student Assistance Program Outcomes of Students at Risk for Suicide.

Declaration of Conflicting Interests

Pennsylvania’s SAP was created during the mid-1980s as a process for early identification of students with drug or alcohol problems. Interventions were added a few years later for students at risk for suicide. This study examined SAP cases by analyzing relationships between two educational outcomes—violations of school drug and alcohol policies and suspensions—and SAP participation by suicidal students. It also examined suicides of participants and nonparticipants. Findings provide the most current and only evidence regarding services that were associated with improved educational outcomes for suicidal students participating in Pennsylvania’s SAP. Services that showed promise for addressing drug- and alcohol-related behaviors included placement in an alternative school, assessment by a licensed drug and alcohol provider, children and youth services that intervene in alleged cases of child abuse, counseling provided by faith organizations, one-to-one counseling provided by school personnel, assessment by a behavior specialist, crisis intervention at school, and participation in a drug and alcohol educational/prevention group. Services that showed promise for addressing problems that lead to suspensions included assessment by a licensed drug and alcohol provider, juvenile probation in school, and crisis intervention and outpatient mental health treatment together. Findings can be used by Pennsylvania school nurses, nurse practitioners, and other SAP team members to select and monitor services—services that need to develop connectedness and build protective factors. Further evaluation of interventions must be completed, but the variation in services that is needed to meet the differing needs of students must not be compromised. Interventions that identify suicidal students, help them stay in school, and address risk and protective factors need to be developed. Educational outcomes of suicidal SAP participants need to be compared to those of nonparticipants. Drug and alcohol crimes need to be monitored via the juvenile justice system, and overdoses need to be monitored via the public health system. All students referred to the SAP need to be assessed for suicide risk, regardless of the reasons that they were referred, and reliable and valid methods for assessing suicide risk are needed. Psychological autopsies of completed teen suicides need to be conducted to elucidate currently unknown risk factors. We must continue to evaluate the SAP and ensure that effective interventions are provided. The vision of the SAP as an evidence-based program can be achieved through continued research and program refinement that helps SAP teams, including school nurses and nurse practitioners, protect the lives of Pennsylvania’s public high school students from suicide.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by grants from the National Association of Pediatric Nurse Practitioners Foundation; the National Association of Pediatric Nurse Practitioners, Delaware Valley Chapter; and Sigma Theta Tau International, Xi Chapter.

References Annie E. Casey Foundation. (2013). Data center. Kids count. Pennsylvania. Enrollment - Percent of students (pre-k - grade 12) by race and ethnicity. Retrieved from http://datacenter.kidscount. org/data/bystate/Rankings.aspx?order¼a&loct¼10&dtm¼5568 &state¼PA&tf¼515&ind¼2682&ch¼a&by¼a Biddle, V. S. (2009). Student assistance program outcomes of students at risk for suicide (academic performance, drug use, alcohol use). Dissertation Abstracts International: Section B: The Sciences and Engineering, 69, 4662. Biddle, V. S., Sekula, L. K., Zoucha, R., & Puskar, K. R. (2010). Identification of suicide risk among rural youth: Implications for the use of HEADSS. Journal of Pediatric Health Care. Retrieved from http://www.sciencedirect.com.proxy1.lib.tju. edu/science/article/pii/S0891524509000741 Borowsky, I. W., Ireland, M., & Resnick, M. I. (2001). Adolescent suicide attempts. Risks and protectors. Pediatrics, 107, 485–493. Campbell, W. H., & Rohrbaugh, R. M. (2006). The biopsychosocial formulation manual. A guide for mental health professionals. New York, NY: Routledge. Centers for Disease Control and Prevention. (2001). School health guidelines to prevent unintentional injuries and violence. [Guideline]. Morbidity & Mortality Weekly Report Recommendations & Reports, 50, 1–73. Centers for Disease Control and Prevention. (2012a). Definitions: Self-directed violence. Retrieved from http://www.cdc.gov/violenceprevention/suicide/definitions.html Centers for Disease Control and Prevention. (2012b). FastStats, adolescent health. Retrieved from http://www.cdc.gov/nchs/ fastats/adolescent_health.htm Center for Rural Pennsylvania. (n.d.-a). Demographics. Rural school districts. Retrieved from http://www.ruralpa2.org/ rural_muni_sd.cfm?countyname¼ALL&schooldistrict¼ALL& ruralurbanstatus¼ALL&orderby¼entity&submit¼Search Center for Rural Pennsylvania. (n.d.-b). Rural/urban PA. Retrieved from http://www.rural.palegislature.us/rural_urban.html Cho, H., Hallfors, D. D., & Iritani, B. J. (2007). Early initiation of substance use and subsequent risk factors related to suicide among urban high school students. Addictive Behaviors, 32, 1628–1639.


Biddle et al.

185

Commonwealth of Pennsylvania Departments of Education, Health, and Public Welfare. (2004). Are you worried about your child? The Students Assistance Program can help. A guide for parents and families. Retrieved from http://www.qvsd.org/ uploaded/District_Files/Publications/HighSchool/HSStudent AssistantancProgram.pdf Commonwealth Student Assistance Program Interagency Committee. (1991). Guidelines for student assistance program implementation. Retrieved from http://www.sap.state.pa.us/UploadedFiles/ SAP_Guidelines.pdf Commonwealth Student Assistance Program Interagency Committee. (2004a). History of secondary student assistance programs in Pennsylvania. Retrieved from http://www.sap.state.pa.us/ uploadedfiles/historyofsap.pdf Commonwealth Student Assistance Program Interagency Committee. (2004b). What is the student assistance program? Retrieved from www.sap.state.pa.us/uploadedfiles/whatisSAP.doc Commonwealth Student Assistance Program Interagency Committee, Departments of Education, Health, and Public Welfare. (2011). Commonwealth of Pennsylvania’s student assistance program frequently asked questions and best practices responses. Retrieved from http://www.sap.state.pa.us/uploadedfiles/SAP-QA-BestPractice6-17-2011.pdf Crosby, A. E., Ortega, L., & Melanson, C. (2011). Self-directed violence surveillance: Uniform definitions and recommended data elements. Version 1. Retrieved from http://www.cdc.gov/ violenceprevention/pdf/self-directed-violence-a.pdf Dunn, M. S., Goodrow, B., Givens, C., & Austin, S. (2008). Substance use behavior and suicide indicators among rural middle school students. Journal of School Health, 78, 26–31. Retrieved from http://onlinelibrary.wiley.com.proxy1.lib.tju.edu/doi/10. 1111/j.1746-1561.2007.00262.x/abstract EducationBug.org. (2013). Welcome to the Pennsylvania public school directory. Retrieved from http://pennsylvania.educationbug.org/public-schools/ Epstein, J. A., & Spirito, A. (2009). Risk factors for suicidality among a nationally representative sample of high school students. Suicide & Life-Threatening Behavior, 39, 241–251. Retrieved from http://www.atypon-link.com.proxy1.lib.tju. edu/GPI/doi/abs/10.1521/suli.2009.39.3.241 Fergusson, D. M., Beautrais, A. L., & Horwood, L. J. (2003). Vulnerability and resiliency to suicidal behaviours in young people. Psychological Medicine, 33, 61–73. Fertman, C. I., Tarasevich, S. L., & Hepler, N. A. (2003). Retrospective analysis of the student assistance program: Implications for practice and research. Harrisburg, PA: Pennsylvania Commission on Crime and Delinquency. Foley, D. L., Goldston, D. B., Costello, E. J., & Angold, A. (2006). Proximal psychiatric risk factors for suicidality in youth: The Great Smoky Mountains study. Archives of General Psychiatry, 63, 1017–1024. Gould, M. S., Fisher, P., Parides, M., Flory, M., & Shaffer, D. (1996). Psychosocial risk factors of child and adolescent completed suicide. Archives of General Psychiatry, 53, 1155–1162.

Hosmer, D. W., & Lemeshow, S. (2000a). Introduction to the logistic regression model. In N. A. C. Cressie, N. I. Fisher, I. M. Johnstone, J. B. Kadane, D. W. Scott, B. W. Silverman . . . D. G. Kendall (Series Eds.), Applied logistic regression (2nd ed., pp. 1–30). New York, NY: John Wiley. Hosmer, D. W., & Lemeshow, S. (2000b). Model-building strategies and methods for logistic regression. In N. A. C. Cressie, N. I. Fisher, I. M. Johnstone, J. B. Kadane, D. W. Scott, B. W. Silverman . . . D. G. Kendall (Series Eds.), Applied logistic regression (2nd ed., pp. 91–142). New York, NY: John Wiley. Isometsa, E. T. (2001). Psychological autopsy studies—A review. European Psychiatry: The Journal of the Association of European Psychiatrists, 16, 379–385. Jessor, R. (1991). Risk behavior in adolescence: A psychosocial framework for understanding and action. Journal of Adolescent Health, 12, 597–605. Jessor, R., Turbin, M. S., & Costa, F. M. (2003). Adolescent problem behavior in China and the United States: A cross-national study of psychosocial protective factors. Journal of Research on Adolescence, 13, 329–360. King, K. A. (2006). Practical strategies for preventing adolescent suicide. The Prevention Researcher, 13, 8–11. Kleinbaum, D. G., & Klein, M. (2002). 2. Important special cases of the logistic model. Logistic regression: A self-learning text (2nd ed., pp. 39–72). New York, NY: Springer. Kramer, C., & Chmura, H. (1987). How many subjects? Statistical power analysis in research. Newbury Park, CA: Sage. Makhija, N. J., & Sher, L. (2007). Preventing suicide in adolescents with alcohol use disorders. International Journal of Adolescent Medicine & Health, 19, 53–59. Menard, S. (Ed.). (2002). Applied logistic regression analysis (2nd ed.). Thousand Oaks. CA: Sage. Mental and Behavioural Disorders Department of Mental Health, World Health Organization. (2000). Preventing suicide: A resource for teachers and other school staff. Retrieved from http://csmh.umaryland.edu/Resources/ClinicianTools/suicidepreventionresources7.pdf National Center for Injury Prevention and Control, Centers for Disease Control and Prevention. (2010). WISQARS fatal injury reports, national and regions, 1999-2010. Retrieved from http://webappa.cdc.gov/sasweb/ncipc/mortrate10_us.html Newman, L., Henry, P. B., DiRenzo, P., & Stecher, T. (1988). Intervention and student assistance: The Pennsylvania model. Practical Approaches in Treating Adolescent Chemical Dependency, 2, 145–162. North Allegheny School District. (2013). Student assistance program. Retrieved from http://www.northallegheny.org/Page/376 Pennsylvania Department of Education. (1997). Safe school online. Historial reports. State. 1996–1997. Statistical breakdown of questions for SAP form (PDE 4092). Retrieved from https:// www.safeschools.state.pa.us/Main.aspx?App¼330ed3ce-9c2f45ba-b12b-6bf97a2019bc&Menu¼dbd39a1f-3319-4a75-8f69d1166dba5d70&res¼


186


Pennsylvania Department of Health. (2013). Tools of the trade. Data analysis: Measuring premature mortality using Years of potential life lost (YPLL). Retrieved from http://www.portal.state.pa.us/ portal/server.pt?open¼514&objID¼556449&mode¼2 Pennsylvania Department of Health. (n.d.). EpiQMS. Retrieved from https://apps.health.pa.gov/EpiQMS/asp/SelectParams_ Tbl.asp Perkins, D. F., & Hartless, G. (2002). An ecological risk-factor examination of suicide ideation and behavior of adolescents. Journal of Adolescent Research, 17, 3–26. Posner, K., Oquendo, M. A., Gould, M., Stanley, B., & Davies, M. (2007). Columbia classification algorithm of suicide assessment (C-CASA): Classification of suicidal events in the FDA’s pediatric suicidal risk analysis of antidepressants American Journal of Psychiatry, 164, 1035–1043. Sean, J., & Marcus, S. C. (2003). Trends by race and gender in suicide attempts among U.S. adolescents, 1991-2001. Psychiatric Services, 54, 454. Retrieved from http://www.ncbi.nlm.nih. gov/pmc/articles/PMC2701687/#!po¼25.0000 Substance Abuse and Mental Health Services Administration. (2012). Preventing suicide: A toolkit for high schools (HHS Publication No. SMA-12-4669). Rockville, MD: Center for Mental Health Services, Substance Abuse and Mental Health Services Administration, 2012. Retrieved from http://store. samhsa.gov/shin/content/SMA12-4669/SMA12-4669.pdf Suicide Prevention Resource Center. (n.d.). The role of high school teachers in preventing suicide. Retrieved from http://www.sprc. org/sites/sprc.org/files/Teachers.pdf Swahn, M. H., & Bossarte, R. M. (2007). Gender, early alcohol use, and suicidal ideation and attempts: Findings from the 2005 Youth Risk Behavior Survey. Journal of Adolescent Health, 41, 175–181. Swahn, M. H., Bossarte, R. M., Choquet, M., Hassler, C., Falissard, B., & Chau, N. (2012). Early substance use initiation and suicide ideation and attempts among students in France and the United States. International Journal of Public Health, 57, 95–105. Tarter, R. E., Kirisci, L., Reynolds, M., & Mezzich, A. (2004). Neurobehavior disinhibition in childhood predicts suicide potential and substance use disorder by young adulthood. Drug and Alcohol Dependence, 76, S45–S52. Taylor-Mearhoff, C. (1990). Suicide prevention: The student assistance model. West Chester, PA: ERIC Document Reproduction Service No. ED322410. Thompson, E. A., Eggert, L. L., Randell, B. P., & Pike, K. C. (2001). Evaluation of indicated suicide risk prevention

approaches for potential high school dropouts. American Journal of Public Health, 91, 742–752. U.S. Department of Health and Human Services. (2012). Healthy people 2020. Topics & objectives. Retrieved from http://www. healthypeople.gov/2020/topicsobjectives2020/default.aspx U.S. Department of Health and Human Services Office of the Surgeon General and National Action Alliance for Suicide Prevention. (2012). National strategy for suicide prevention: Goals and objectives for action. Retrieved from www. samhsa.gov/nssp U.S. Public Health Service. (2000). Report of the surgeon general’s conference on children’s mental health: A national action agenda. Retrieved from http://www.ncbi.nlm.nih.gov/books/ NBK44233/ Walsh, E., & Eggert, L. L. (2007). Suicide risk and protective factors among youth experiencing school difficulties. International Journal of Mental Health Nursing, 16, 349–359. Windle, M. (2004). Suicidal behaviors and alcohol use among adolescents: A developmental psychopathology perspective. Alcoholism: Clinical and Experimental Research, 28, 29S–37S.

Author Biographies Virginia Sue Biddle, PhD, RN, CPNP, PMHNP-BC, is a family psychiatric/mental health and pediatric nurse practitioner at the Department of Psychiatry and Human Behavior at Thomas Jefferson University, Philadelphia, PA, USA. John Kern III, PhD, is an associate professor at the Department of Mathematics and Computer Science at Duquesne University, Pittsburgh, PA, USA. David A. Brent, MD, endowed chair in suicide studies and professor of psychiatry, pediatrics, epidemiology, and clinical and translational science at the Department of Psychiatry, University of Pittsburgh at Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA. Mary Ann Thurkettle, PhD, RN, is an associate professor at the Department of Nursing at Slippery Rock University, Slippery Rock, PA, USA. Kathryn R. Puskar, DrPH, RN, CS, FAAN, is a professor and an associate dean for undergraduate education at Health and Community Systems, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA. L. Kathleen Sekula, PhD, APRN, FAAN, is a professor at the School of Nursing, Duquesne University, Pittsburgh, PA, USA.


From data to program decisions: developing a student assistance program.

Implementing an early intervention program for residential students who present with suicide risk: a case study.

Adapting interpersonal psychotherapy for older adults at risk for suicide.

Academic Responding During Instruction and Reading Outcomes for Kindergarten Students At-risk for Reading Difficulties.

Implementation of a study skills program for entering at-risk medical students.

AIDS Program Assistance and HIV Treatment Outcomes.

How we launched a developmental student-as-teacher (SAT) program for all medical students.

Disabled student program at Cal State Hayward.

Piloting a stress management and mindfulness program for undergraduate nursing students: student feedback and lessons learned.

Student evaluation of a dental health program for third- and fourth-grade students.

The summer premedical program for matriculating medical students: a student-led initiative.

Training for suicide risk assessment and suicide risk formulation.

Psycho-social resilience, vulnerability and suicide prevention: impact evaluation of a mentoring approach to modify suicide risk for remote Indigenous Australian students at boarding school.

Adolescent suicide attempts: outcomes at follow-up.

Depression, self-esteem, suicide ideation, and GPAs of high school students at risk.

The FRIENDS emotional health program for minority groups at risk.

An enrichment program for minority students.

A premedical summer program for disadvantaged students.

A special program for counseling medical students.

A mentorship program for minority students.

Risk factors for suicide attempts in a human immunodeficiency virus screening program.

Genetic risk factors in two Utah pedigrees at high risk for suicide.

Google searches for suicide and risk of suicide.

Patients at risk of suicide and overdose.