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Social Support & Youth Suicide
An Intersectional and Socioecological Approach
Corbin J. Standley, M.A.
Michigan State University
Study II Data Report August 6, 2019
Page | 1
Table of Contents
Executive Summary..........................................................................................................................................2
Acknowledgements..........................................................................................................................................3
Data Dashboard................................................................................................................................................4
Introduction.......................................................................................................................................................5
Michigan Profile for Healthy Youth (MiPHY) .............................................................................................6
Suicide-Related Questions .........................................................................................................................6
Missing and Invalid Data..............................................................................................................................6
Methods and Analysis ......................................................................................................................................7
Data Usage and Security.............................................................................................................................7
Research Questions.....................................................................................................................................7
Sample.............................................................................................................................................................8
Missing Data ..................................................................................................................................................8
Analysis...........................................................................................................................................................9
Analytic Procedures................................................................................................................................9
Scales and Measures................................................................................................................................9
Additional Analytics and Statistical Information ...............................................................................9
Findings............................................................................................................................................................. 11
A. Risk for Suicide..................................................................................................................................... 11
B. Social Support as a Protective Factor.............................................................................................. 12
Types of Social Support....................................................................................................................... 13
C. Compounding Social Support ........................................................................................................... 14
D. Social Support as a Moderator......................................................................................................... 14
Modeling the Moderation of Social Support................................................................................... 15
Recommendations......................................................................................................................................... 16
Build a Trusted and Empowered Coalition......................................................................................... 16
Foster Collaboration and Sharing of Resources ................................................................................ 16
Promote Evidence-Based Action........................................................................................................... 16
Future Research.................................................................................................................................... 17
Develop a Sustainability Plan .................................................................................................................. 17
Conclusion ...................................................................................................................................................... 17
References....................................................................................................................................................... 19
Appendix A ..................................................................................................................................................... 20
Page | 2
Executive Summary
In response to rising youth suicide rates in mid-Michigan, the LifeSavers Suicide Prevention
Coalition was established in partnership with Community Mental Health (CEI-CMH) and the
Eaton Regional Education Service Agency (Eaton RESA). As a part of this Coalition, the steering
committee engaged Corbin J. Standley, doctoral student in Ecological-Community Psychology at
Michigan State University, to conduct a series of secondary data analyses studies to determine
the risk and protective factors for youth suicide in Clinton, Eaton, and Ingham counties. This
report follows the Tri-County Youth Suicide Preliminary Data Report produced in May of 2018 and
addresses four major questions:
A. Which youth are most at risk for suicide?
B. To what extent does social support reduced suicide risk?
C. To what extent does compounding support reduce suicide risk?
D. To what extent does social support moderate the impacts of intersectionality on suicide
risk?
Data for the study came from the 2015-2016 wave of the Michigan Profile for Healthy Youth
(MiPHY) survey provided in accordance with a data use agreement with the Michigan Department
of Education. Additional publicly available aggregate data are also presented. The study began in
June of 2018.
Major findings from the study include the following:
1. Youth with marginalized identities (females, non-white, and LGB youth) are at
significantly increased risk for suicide.
2. The more marginalized identities youth have, the more at risk they are for suicide.
3. Social support at the family, school, and community levels is significantly associated with
reduced suicide risk for youth.
4. The combination of social support at all of these levels is significantly associated with
the largest decrease in suicide risk for youth.
5. Social support in families and schools significantly mitigates the impacts of multiple
marginalized identities on suicide risk suggesting that social support is most important
and effective for marginalized youth.
There are five major implications based upon these findings:
1. While per-capita suicide rates for white Americans are higher than most minority
groups, once we account for intersectional disadvantage, such trends become less clear.
2. The way in which social support is applied in each context impacts its protective effects
on suicide risk.
3. To be most effective, social support should be bolstered across every context in which
youth live, learn, and play.
4. More proximal sources of social support (those that most closely impact youth directly)
have greater protective effects than more distal sources.
5. Social support is even more important for youth with intersecting marginalized
identities.
Page | 3
There are three major recommendations based upon these findings:
1. Efforts to expand the LifeSavers should consider these findings by engaging youth,
marginalized communities, and relevant stakeholders in the work.
2. Social support programs should be designed and implemented across all contexts in which
youth live, learn, and play. Such programs should also be tailored to meet the needs of
youth with multiple marginalized identities.
3. Future research should further examine the impacts of intersectionality on youths’
experiences of suicidal ideation and behavior. Qualitative research methods may shed light
on such experiences and aid in the effective design and implementation of programs and
supports for youth.
Acknowledgements
This initiative and the following report would not have been possible without the support of the
following individuals and organizations. Their dedication, passion, and drive helped make this
project successful.
Pennie Foster-Fishman, Ph.D.
Professor, Department of Psychology
Michigan State University
Jody Nelson, LMSW
Urgent Care Clinical Coordinator
Community Mental Health
Kim Thalison, B.B.A.
Prevention Services Supervisor
Eaton RESA
Joel Hoepfner, B.S., CPC
Prevention and Outreach Coordinator
Community Mental Health
Jennifer Cronkite, M.A., LPC
Prevention Specialist
Community Mental Health
Malea Bullock, M.A., M.S., LLPC
Certified Prevention Specialist
Eaton RESA
Annemarie Hodges, M.A.
Temporary Survey Specialist
Michigan Department of Education
Nicole Kramer-Dodge, B.A.
Survey Specialist
Michigan Department of Education
This study was presented to Michigan State University in partial fulfillment of the requirements for the degree of
Master of Arts in Ecological-Community Psychology for Corbin J. Standley.
This report contains citations and references according to the American Psychological Association Publication Manual, 6th
Edition.
This study was approved by the Michigan Department of Education and Michigan State University’s Institutional Review
Board and was conducted in accordance with all ethical guidelines set forth by the American Psychological Association.
Page | 4
Data Dashboard
The following infographics display findings and demographics from Study II of the Youth Suicide Data
Initiative. Data represent a total of 5,058 students across high schools in Clinton, Eaton, and Ingham
counties who participated in the 2015-2016 wave of the MiPHY survey.
Suicide Risk Clusters Social Support
The more marginalized identities a respondent had, the
more likely they were to be classified as “high-risk.”
For those with high intersectionality scores, the
protective effects of social support are stronger.
Social Support and Suicide Risk Social Support Scores
A one-point increase in social support significantly contributed to the noted
reduction in overall suicide risk score for youth. Values are points and not percentages.
Lower social support scores were
associated with higher suicide risk.
.62-point
reduction
in suicide
risk
.50-point
reduction
in suicide
risk
.25-point
reduction
in suicide
risk
22.1%
16.1%
61.8
%
3130 Low-Risk
812 Medium-Risk
1116 High-Risk
3.16
2.88
2.52
2.78
2.59
2.45
2.34
2.11
1.95
High-RiskMedium-RiskLow-Risk
Family support is activities,
opportunities for input,
connectedness, and
attachment within one’s
family.
School support is peer
and teacher interactions,
extracurricular
involvement, and climate
within the school.
Community support is
community activities and
interactions with non-familial
adults and peers within one’s
community.
.66-point
reduction
in suicide
risk
0.79
1.45
0.13
0.57
0
0.25
0.5
0.75
1
1.25
1.5
1.75
SuicideRisk
0.61
1.35
0.23
0.77
Low Intersect. High Intersect.
High Support
Low Support
Page | 5
Introduction
ver the last 15 years, suicide rates in the state of Michigan have increased by more than 33%
and have reached their highest point since the Great
Depression era. Even more alarming, suicide is the second
leading cause of death among 15-29-year-olds globally.1
Moreover, in the U.S., suicide is currently the third leading
cause of death among youth ages 10 to 14, and the second
leading cause of death among youth and young adults ages
15 to 34.4
In 2017, an average of one young person (age 24
or younger) died by suicide every 78 minutes—an average
of 18.5 suicides per day.5
To that end, the LifeSavers Suicide Prevention Coalition (“LifeSavers”) emerged out of a
partnership between Community Mental Health (CEI-CMH) and the Eaton Regional Education
Service Agency (Eaton RESA) in order to investigate and work to stop the rising youth suicide rates
in Clinton, Eaton, and Ingham counties in mid-Michigan. The LifeSavers brings together stakeholders
from across these three counties in order to address the issue of youth suicide. Members of the
LifeSavers include representatives from education, juvenile justice, mental health, policy and local
government, and local non-profit organizations.
Once established, the LifeSavers’ steering committee partnered with Corbin J. Standley of Michigan
State University to establish the Youth Suicide Data Initiative. The purpose of the project is to
examine existing data to better understand the incidence of youth suicide in Clinton, Eaton, and
Ingham counties in order to uncover risk, preventive factors for youth suicide and use that
information to inform prevention and intervention strategies.
The following report outlines the findings from the second study in the initiative and builds on the
Tri-County Youth Suicide Preliminary Data Report produced in May of 2018. The study aimed to
contribute to the existing understanding of youth suicide in two major ways. Firstly, the study goes
beyond the individual level to look at suicide and the role of social support as a protective factor
at multiple levels. Secondly, it uses an intersectional approach to examine how social identities and
their combination impacts suicide risk and prevention for youth. Data from the 2015-2016 wave of
the Michigan Profile for Health Youth (MiPHY) were analyzed over a period of one year to inform
the results. Recommendations for practice and future research for the LifeSavers are also discussed.
The study was approved by the Michigan Department of Education, was reviewed by Michigan State
University’s Institutional Review Board, and was conducted in accordance with all ethical guidelines
set forth by the American Psychological Association. Any questions, concerns, or feedback
regarding the methods or findings in this report should be directed to:
Corbin J. Standley, M.A.
Ph.D. Student, Ecological-Community Psychology
Michigan State University
corbinjs@msu.edu
O
Suicidal ideation and
suicide attempts are the
most commonly
reported mental health
crises among youth.6
Page | 6
Michigan Profile for Healthy Youth (MiPHY)
The Michigan Profile for Healthy Youth (MiPHY) is an online student health survey administered
by the Michigan Department of Education (MDE) and the Michigan Department of Health and
Human Services (MDHHS) to support local and regional needs assessment. The MiPHY provides
student results on health risk behaviors including substance use, violence, physical activity, nutrition,
sexual behavior, and emotional health in middle schools (seventh grade) and high schools (ninth
and eleventh grades) across the state. The survey also measures risk and protective factors most
predictive of alcohol, tobacco, and other drug use and violence.
Suicide-Related Questions
Table 1 below lists the suicide-related questions asked in the MiPHY survey. Analyses for “Suicide
Attempt Injury” are not reported beyond this point as the intent of the study was to assess suicide
risk rather than outcomes for suicide attempts.
Table 1. Suicide-related questions in the MiPHY survey by school level.
Construct Survey Item
Sadness and
Hopelessness
163. During the past 12 months, did you ever feel so sad or hopeless
almost every day for two weeks or more in a row that you stopped doing
some usual activities?
Suicidal Ideation
164. During the past 12 months, did you ever seriously consider
attempting suicide?
Suicide Plan
165. During the past 12 months, did you make a plan about how you
would attempt suicide?
Suicide Attempts
166. During the past 12 months, how many times did you actually attempt
suicide?
Suicide Attempt
Injury
167. If you attempted suicide during the past 12 months, did any attempt
result in an injury, poisoning, or overdose that had to be treated by a
doctor or nurse?
Missing and Invalid Data
Data for the study were included only for high-school students due to survey item differences and
time and resource limitations of the researcher. Of the 8,359 completed high school MiPHY surveys
during the 2015-2016 wave, 3,301 (39.5%) were not included in the analyses. Table 2 below details
the reasoning behind their exclusion. After eliminating invalid surveys, the data reported herein
come from a total valid sample of 5,058 high school students in Clinton, Eaton, and Ingham counties.
Table 2. Count and percentage of excluded surveys by reasoning and school level.
Reasoning n %
Respondent selected a grade level other than 9th
or 11th
797 9.5%
Respondent answered fewer than 20% of the questions in the survey 326 3.9%
Removed in listwise deletion procedures prior to analysis1
2178 26.1%
Total 3,301 39.5%
1
These procedures are discussed in further detail in the Methods and Analysis section of this report.
Page | 7
Methods and Analysis
The findings reported herein emerged from a quantitative study of secondary data from the source
described above. Secondary data analysis can be defined as “second-hand” analysis. It is the analysis
of information that was either gathered by someone else or for some other purpose other than
the one currently being considered. Secondary data analysis is helpful in (1) providing a baseline
with which to compare other data, (2) designing potential subsequent research, and (3) informing
recommendations for policy, practice, and research.
Data Usage and Security
In January of 2018, a data use agreement was made between Eaton RESA (on behalf of the LifeSavers
Suicide Prevention Coalition) and the Michigan Department of Education (see Appendix A). As a
part of this agreement, the complete electronic database of 2015-2016 student-level MiPHY survey
data from all Clinton, Eaton, and Ingham county middle and high schools who participated in the
MiPHY survey during the 2015-2016 academic year were sent to Corbin J. Standley (hereafter
referred to as “the researcher”). These data did not include school building or district identifiers
to maintain data confidentiality. The data from each district and county were combined into two
separate databases (high school and middle school). Data for this study came only from the high
school database.
As a part of this agreement, the researcher employed all data usage protocols set forth by the
Michigan Department of Education in order to maintain the reliability and validity of the results
and, most importantly, the anonymity of students. Data based upon a sample size of fewer than 10
students are suppressed in this and all reports resulting from these data.
Research Questions
In collaboration with the LifeSavers’ steering committee, a list of factors and indicators of interest
were identified including suicidal ideation, suicide attempts, substance and alcohol use, school
climate, social support, and demographic factors such as race and ethnicity, age, sexual identity, and
county. In an effort to determine the risk and preventive factors for youth suicide in the tri-county
area, three primary research questions emerged from these preliminary indicators and guided the
analysis of the data. The Tri-County Youth Suicide Preliminary Data Report answers the first of these
questions. The findings reported herein attempt to answer the second and third primary questions:
1. What are the major demographic risk factors for youth in the tri-county area?
2. Is school climate significantly related to suicidal ideation or suicide risk among youth? In
what ways?
3. What are the major protective factors for youth suicide? To what extent are they
available to youth in the tri-county area?
To answer these latter two research questions, four secondary research questions guided this
study:
A. Who is most at risk for suicide?
B. To what extent does the presence of social support reduce suicide risk among youth?
C. To what extent do compounding sources of social support reduce suicide risk?
D. To what extent does social support moderate the effect of intersectionality on suicide
risk?
Page | 8
Sample
The data in this report represent a total of 5,058 students across high schools in Clinton, Eaton,
and Ingham counties who participated in the 2015-2016 wave of the MiPHY survey. Table 3 below
outlines the demographic characteristics of the sample.
Table 3. Demographic characteristics of high school students who participated in the 2015-2016 wave of the MiPHY
survey.
Demographic n %*
County
Clinton 1004 19.8%
Eaton 1292 25.5%
Ingham 2762 54.6%
Gender
Male 2512 49.7%
Female 2546 50.3%
Sexual Identity
Bisexual 330 6.5%
Gay or Lesbian 82 1.6%
Heterosexual 4366 86.3%
Not Sure 280 5.5%
Race/Ethnicity
American Indian/Alaska Native 47 0.9%
Arab/Chaldean 71 1.4%
Asian 209 4.1%
Black 419 8.3%
Hispanic/Latino 872 17.2%
White 3503 69.3%
TOTAL 5,058
*
Percentages within a category may not add up to 100% given missing data and incomplete survey responses.
Missing Data
The researcher used a complete-case analysis approach to analyze only the cases for which data
on the outcome and predictor variables were available. A total of 2,178 (30.1%) cases were
excluded by the researcher prior to analysis. This resulted in a final subsample of 5,058 for all
subsequent analyses.
The rationale for excluding cases from these analyses was three-fold.
1. The final subsample of provided sufficient statistical power for the analyses conducted.
2. As the demographic variables were being tested in statistical regression models (rather than
simply controlled for), a full set of these data was necessary.
3. The demographic distribution of the final subsample did not significantly shift from the
original full sample and remained representative of the tri-county area.
Cases were excluded in three phases:
1. Respondent missing data on any of the three demographic variables (1,863).
2. Respondent missing data on any of the four items related to suicide risk (190).
3. Responded to less than 51% of the items related to social support in any domain (125).
Page | 9
Analysis
Data were analyzed using version 24 of the Statistical Package for the
Social Sciences (SPSS) with the addition of the PROCESS Macro8
. The
researcher used descriptive statistics, correlational analyses, analyses
of variance (ANOVAs), multiple linear regression, stepwise linear
regression, and hierarchical liner regression analyses to analyze the
data.
Analytic Procedures
Four phases of analysis were used in the study in order to fulfill its aims.
The first phase of analysis used ANOVAs, means comparison, and
cluster analysis to determine risk groups (secondary research question
A). The second and third used linear and stepwise regression analyses
to determine the unique and compounding effects of social support on
suicide risk (secondary research questions B and C, respectively).
Finally, the fourth phase used multiple hierarchical linear regression to
assess the impact of social support as a moderator on the relationship
between intersectionality and suicide risk (secondary research
question D).
Scales and Measures
Three major constructs were of interest in the study including identity and intersectionality, suicide
risk, and social support. The scales and measures used in the study for each of these constructs
are detailed here. Table 4 below lists the survey items used in the study.
• Identity was measured using the gender, race and ethnicity, and sexual identity demographic
items.
o Intersectionality was measured by creating an additive score of the three demographic
variables (1 being minority status, 0 being majority status) resulting in an
intersectionality score ranging from 0 to 3 for each case.
• Suicide risk was measured using an additive score of the sadness and hopelessness, suicidal
ideation, planned suicide attempt, and previous suicide attempts variables resulting in a
composite suicide risk score ranging from 0 to 4 for each case.
• Social support was measured at the family, school, and community levels measuring
opportunities and rewards for pro-social involvement.
Additional Analytics and Statistical Information
For the purposes of this report, findings are presented in an
accessible manner using lay language and graphs to convey the
results. Specifics related to the analyses conducted, particular
statistical findings, and overall methods for this study can be found
in the full Social Support as a Protective Factor for Youth Suicide: An
Intersectional and Socioecological Approach document (Standley,
2019). Please contact the author for more information.
CLICK HERE FOR
ACCESS TO THE FULL
DOCUMENT
Page | 10
Table 4. MiPHY survey items included in the study.
Demographics
Gender: What is your sex?
Race: What is your race?
Ethnicity: Are you Hispanic or Latino?
Sexual Identity: Which of the following best describes you?
Protective Factors – Family Domain
Oa
My parents ask me what I think before most family decisions affecting me are made.
O If I had a personal problem, I could ask my mom or dad for help.
O My parents give me lots of chances to do fun things with them.
R My parents notice when I am doing a good job and let me know about it.
R How often do your parents tell you they're proud of you for something you've done?
R Do you enjoy spending time with your mother?
R Do you enjoy spending time with your father?
Protective Factors – School Domain
O
In my school, students have lots of chances to help decide things like class activities and
rules.
O There are lots of chances for students in my school to talk with a teacher one-on-one.
O Teachers ask me to work on special classroom projects.
O
There are lots of chances for students in my school to get involved in school activities
outside of class.
O I have lots of chances to be part of class discussions or activities.
R My teacher(s) notice when I am doing a good job and let me know about it.
R The school lets my parents know when I have done something well.
R My teachers praise me when I work hard in school.
Protective Factors – Community Domain
O There are adults in my neighborhood I could talk to about something important
R I feel safe at my school.
R My neighbors notice when I am doing a good job and let me know.
R There are people in my neighborhood who encourage me to do my best.
R There are people in my neighborhood who are proud of me when I do something well.
Suicide Risk
During the past 12 months, did you ever feel so sad or hopeless almost every day for
two weeks or more in a row that you stopped doing some usual activities?
During the past 12 months, did you ever seriously consider attempting suicide?
During the past 12 months, did you make a plan about how you would attempt suicide?
During the past 12 months, how many times did you attempt suicide?
Note: A full version of the 2015-2016 high school MiPHY survey is available upon request.
a
“O” scales measure opportunities for prosocial involvement. “R” scales measure rewards for
prosocial involvement as defined by the Communities That Care Youth Survey.
Page | 11
Findings
The findings presented below are organized around the four
secondary research questions that guided the study. The study
examined how social identity influences suicide risk and the role
of social support as a protective factor in that relationship. Overall,
findings highlight the importance of paying attention to protective
factors in every context in which youth live, learn, and play.
Moreover, findings also
suggest that measuring and
reporting social identities as
well as their intersections
adds to our understanding
of both risk and prevention
when it comes to youth
suicide.
A. Risk for Suicide
ANOVAs and cluster analyses indicated that risk group
membership was largely delineated by minority status for gender,
race and ethnicity, and sexual identity. In other words, females;
non-white students; and lesbian, gay, or bisexual (LGB) youth were
found to be at significantly higher risk for suicide. These findings
provide yet more evidence that attending to issues of
marginalization experienced by females and LGB individuals is not
only advisable but necessary in order to prevent suicides. These
findings do not, however, clarify the mixed research regarding race
and ethnicity and suicide risk. Overall, non-white youth were
significantly more likely to be classified as high-risk, however, this
finding revealed a small effect size. Moreover, findings from Study
I9
revealed significant differences between racial and ethnic groups
only for those with multiple racial identities (i.e., those who
identified as multi-racial were significantly more likely to have high
risk scores as compared to their Asian, Black/African American,
and White peers).
Findings also indicate that those with intersecting marginalized
identities were significantly more likely to be classified as high-risk.
This adds to the scarce literature regarding intersectionality and
suicide risk and echoes previous research regarding compounded
suicide risk for youth. Table 5 below illustrates the demographic
breakdown of risk groups. Taken together, these findings suggest
that, while per-capita suicide rates for white Americans are higher
than most minority groups, once we account for intersectional
disadvantage associated with gender and sexual identity, such
trends become less clear.
Key Findings
1. Youth with marginalized
identities (females, non-
white, and LGB youth) are at
significantly increased risk
for suicide.
2. The more marginalized
identities youth have, the
more at risk they are for
suicide.
3. Social support at the
family, school, and
community levels is
significantly associated with
reduced suicide risk for
youth.
4. The combination of social
support at all of these levels
is significantly associated
with the largest decrease
in suicide risk for youth.
5. Social support in families
and schools significantly
mitigates the impacts of
multiple marginalized
identities on suicide risk
suggesting that social
support is most important
and effective for marginalized
youth.
The study examined how
social identity influences
suicide risk and the role of
social support as a
protective factor in that
relationship.
Page | 12
Table 5. Demographic composition of the low-, medium-, and high-risk suicide risk group membership.
Low-Risk
(n = 3130)
Medium-Risk
(n = 812)
High-Risk
(n = 1116)
% % %
Gender
Female 42.2% 61.9% 64.8%
Male 57.8% 38.1% 35.2%
Racial identity
American Indian/Alaska Native 0.9% * 1.0%
Asian 4.5% 3.9% 3.2%
Black/African American 8.2% 8.5% 8.4%
Native Hawaiian/Pacific Islander * * *
White 71.8% 66.3% 64.3%
Multiple-Hispanic 8.3% 12.7% 13.7%
Multiple-Non-Hispanic 6.2% 7.3% 9.2%
Sexual identity
Bisexual 2.5% 6.0% 18.2%
Gay or Lesbian 0.7% 1.7% 4.2%
Heterosexual 92.9% 85.6% 68.5%
Not Sure 4.0% 6.7% 9.1%
Intersectionality score
0 39.0% 23.8% 17.9%
1 46.1% 46.3% 42.6%
2 13.2% 26.0% 29.1%
3 1.7% 3.9% 10.4%
*Suppressed due to small cell size (n < 10).
B. Social Support as a Protective Factor
Linear regression analyses indicated that social support at the family, school, and community levels
each uniquely and significantly contributed to reduced suicide risk in the sample. As Catalano and
Hawkins (1996) purport in their social development theory, three conditions must be present at
various levels of the socioecological model in order for youth to develop well socially: opportunities
for prosocial involvement, skills to be successful in such involvement, and rewards and
reinforcement for such involvement (Toumbourou, 2010). Findings from this study support this
theory and highlight the importance of increasing social support for youth throughout every level
of the socioecological model (see Figure 1 on page 14).
In addition, the regression coefficients and effect sizes for these results suggest that more proximal
sources of social support were more protective than more distal sources (i.e., the magnitude of
the protective effects of family support were greater than those for school support and community
support, respectively).
Page | 13
Types of Social Support
The protective effects of both opportunities and
recognition (see Figure 1) were significant for each
source of support; however, the analyses
demonstrate how these manifestations of
support might best be applied at each ecological
level (see Figure 2). Within the family and
community environments, opportunities were
found to be more protective than rewards. This
suggests that opportunities to have input into
decision-making and develop trusting and
supportive relationships with family members and
neighbors are more protective than positive
feedback within a child’s home and community.
Within the school environment, rewards were
found to be slightly more protective than
opportunities. This suggests that, when youth
receive positive feedback for their successes in
school, they are also more likely to develop strong social bonds and less likely to engage in risky
behaviors. Table 6 below illustrates these differing scores across domains.
Table 6. Regression analysis summary for social support predicting suicide risk composite score.†
B+
SE B β
Family Domain
Family opportunities -.31 .03 -.20**
Family rewards -.26 .03 -.16**
df1 2
df2 5019
R2
.207
Change in R2
.114**
F for change in R2
361.738**
School Domain
School opportunities -.14 .04 -.07**
School rewards -.29 .03 -.16**
df1 2
df2 5047
R2
.137
Change in R2
.044**
F for change in R2
128.549**
Community Domain
Community opportunities -.13 .02 -.11**
Community rewards -.08 .02 -.06*
df1 2
df2 5041
R2
.119
Change in R2
.026**
F for change in R2
73.160**
*p = .001, **p < .001
†
A full, detailed explanation of the statistical models used in the analysis is available in the full thesis document.
+
The unstandardized regression coefficient (B) represents the effect of the variable (opportunities or rewards) on
suicide risk.
Figure 1. Factors leading to healthy behaviors. Adapted
from Communities That Care Social Development Strategy.10
Page | 14
C. Compounding Social Support
Building upon the finding in section B, stepwise linear regression analyses indicated that the
combination of family, school, and community support was significantly more protective than any
unique source of social support, and that the
reduction in risk explained by each domain was
directly related to its proximity to the individual.
This is a relatively novel finding suggesting that
while the combination of all three sources of
social support is most protective, more proximal
sources of social support are more protective
individually. Table 7 below outlines the statistical
significance of these models.
These findings also validate both social
development and socioecological theories
highlighting the importance of social support at
multiple ecological levels. Figure 2 to the right
illustrates this model relative to the individual. In
viewing these environments as both connected
and nested, we see how the interpersonal,
community, and social environments impact
youth outcomes.
Table 7. Summary of stepwise regression analysis for variables predicting suicide risk.
Model 1†
Model 2 Model 3
B+
SE B β B SE B β B SE(B) β
Family -.563 .021 -.340** -.515 .024 -.311** -.501 .024 -.303**
School -.128 .031 -.059** -.110 .032 -.051*
Community -.046 .018 -.035*
R2
.207 .209 .210
F for change
in R2
718.200** 17.182** 6.268*
*p < .05. **p < .001.
†
A full, detailed explanation of the statistical models used in the analysis is available in the full thesis document.
+
The unstandardized regression coefficient (B) represents the effect of the variable (opportunities or rewards) on
suicide risk.
D. Social Support as a Moderator
Finally, hierarchical moderated linear regression analyses indicated that both family and school
support significantly moderated the relationship between intersectionality and suicide risk such
that, for those with high intersectionality scores, the protective effects of social support at the
family and school levels were stronger than for those with low intersectionality scores.
Community-level support was not found to be a significant moderator in this relationship. This
novel moderation finding suggests that the role of social support is particularly important (and
effective) for youth with intersecting marginalized identities.
Interpersonal
Family, School
Community
Social/Structural
Individual
Figure 2. Socioecological mode illustrating the levels of
the environment that impact youth outcomes and well-
being.
Page | 15
Figure 4. Predicting suicide risk as a function of intersectionality and
social support at the family and school levels.
Modeling the Moderation of Social Support
Moreover, these findings contradict the one-size-fits-all approach
that typifies many suicide prevention efforts for youth. Just as suicide
risk itself is different for each child throughout the developmental
process, and based on their social identities, so must our efforts
approach prevention strategies in multifaceted, multi-level, and
individually informed ways. It is only through this combination of
individually tailored supports at multiple ecological levels that we
can make the most difference for marginalized youth struggling with
suicidal ideation and behavior.
As Figure 4 below illustrates, intersectionality is significantly related
to increased suicide risk at each level of social support, meaning that
those with multiple marginalized identities are at increased risk.
Analyses show, however, that the magnitude of the effect is smaller
with higher levels of social support. In other words, the protective
effects of family and school support are stronger for those with high
intersectionality scores.
Intersectionality Suicide Risk
Social Support
Figure 3. Conceptual model illustrating the moderating effects of social
support on the relationship between intersectionality and suicide risk.
Key Implications
1. While per-capita suicide
rates for white Americans
are higher than most
minority groups, once we
account for
intersectional
disadvantage, such
trends become less clear.
2. The way in which social
support is applied in each
context impacts its
protective effects on suicide
risk.
3. To be most effective, social
support should be
bolstered across every
context in which youth
live, learn, and play.
4. More proximal sources
of social support (those
that most closely impact
youth directly) have
greater protective effects
than more distal sources.
5. Social support is even
more important for
youth with intersecting
marginalized identities.
0.79
1.45
0.13
0.57
0
0.25
0.5
0.75
1
1.25
1.5
1.75
SuicideRisk
0.61
1.35
0.23
0.77
High Support
Low Support
Low Intersect. High Intersect.
Page | 16
Recommendations
Based on the findings presented above, the following paragraphs
discuss recommendations informed by the Tri-County LifeSavers
Suicide Prevention Coalition Strategic Plan (See Figure 5 on page 18).
Build a Trusted and Empowered Coalition
The findings above further emphasize the need to engage youth in
the LifeSavers in order to understand their experiences first-hand
and design effective programs to combat youth suicide. The
LifeSavers has already taken steps to engage youth which will
undoubtably inform its efforts moving forward.
These findings also highlight the importance of expanding the
diversity and inclusion of the LifeSavers. Given that youth with
marginalized identities are at increased risk for suicide, engaging
with communities that represent these identities is crucial in order
to design and implement effective programs.
Foster Collaboration and Sharing of Resources
A major finding of this study is that resources and supports across
ecological levels are imperative to reducing youth suicide in the tri-
county area. As such, collaborating with families, schools, and
communities to (1) leverage their expertise and experience, (2)
identify and promote evidence-based strategies, and (3) empower
them to enact change is vital to the success of the Coalition.
Promote Evidence-Based Action
Interventions and programs aimed at suicide prevention should
target multiple ecological levels in order create sustainable
outcomes. In particular, social support programs should be designed
and implemented across all contexts in which youth live, learn, and
play. Programs that prioritize family systems; school personnel, staff,
and peers; and community-level supports are encouraged.
Any intervention or program should also consider the unique and
compounding impacts of minority social identities on both risk and
prevention. In other words, programs should be tailored to meet
the needs of youth with multiple marginalized identities. This should
be done in the design phase of these interventions as research
shows that one-size-fits-all approaches are not sufficient for creating
the change necessary to reduce suicide rates.
Key Recommendations
1. Efforts to expand the
LifeSavers should consider
these findings by engaging
youth, marginalized
communities, and
relevant stakeholders in
the work.
2. Social support programs
should be designed and
implemented across all
contexts in which youth
live, learn, and play. Such
programs should also be
tailored to meet the
needs of youth with
multiple marginalized
identities.
3. Future research should
further examine the
impacts of
intersectionality on
youths’ experiences of
suicidal ideation and
behavior. Qualitative
research methods may shed
light on such experiences and
aid in the effective design and
implementation of programs
and supports for youth.
Page | 17
Future Research
Further quantitative and qualitative research is recommended in order to holistically understand
the nature of suicidality among youth in the tri-county area. In particular, a subsequent qualitative
study is recommended wherein the perspectives and experiences of youth are uncovered
through focus groups and interviewing. In conducting such a study,
experiences at the individual, social, and system levels can be better
understood. Moreover, understanding the individual and collective
perceptions and experiences of suicidality among youth is a useful, often
unexplored approach to investigating the issue. Finally, qualitative research
approaches are uniquely positioned to examine the socioecological factors
that contribute to youth suicide given their emphasis on individual stories
and collective narratives
Develop a Sustainability Plan
Legislative policy change, organizational and agency policy change, and continued funding are
necessary in order to design, implement, and sustain the recommendations outlined above. In
addition to these social and structural changes, continued engagement from youth in the
LifeSavers’ efforts will help to continually cultivate and improve youth-driven initiatives to combat
youth suicide.
Conclusion
As suicide rates among youth continue to rise in the United States, it is
apparent that the conventional approaches to suicide research and
prevention are not entirely effective. Findings from previous research have
undoubtedly shined light on the demographic and social risk factors for
suicide, but few have examined how these factors intersect, how protective
factors can be studied and enhanced, or how these factors are nested within
a socioecological model.
In applying intersectional and socioecological approaches typically underutilized in suicidology,
the overarching aim of this study is to refocus suicidology research and practice more holistically
in order to better capture the individual, social, and ecological factors relevant to youth suicide.
More importantly, in examining each of these areas, we learn more about their interactions and
interdependencies thus illuminating critical intervention and prevention points. Lastly, by
investigating these protective factors, we continue to chip away at the stigma surrounding mental
health and suicide. In doing so, we prevent more deaths and fulfill our moral obligation to ensure
our youth are poised to live safe, happy, and healthy lives.
Page | 18
Figure 5. Tri-County LifeSavers Suicide Prevention Coalition Strategic Plan.
Page | 19
References
Catalano, R. F. & Hawkins, J. D. (1996). The social development model: A theory of antisocial
behavior. In J. D. Hawkins (Ed.), Delinquency and Crime: Current Theories, pp. 149-197.
New York, NY: Cambridge University Press.
7
Centers for Disease Control and Prevention. (2016). 10 leading causes of death by age group,
United States – 2015. From National Vital Statistics System, National Center for Health
Statistics. Retrieved from https://www.cdc.gov/injury/wisqars/LeadingCauses.html
4
Centers for Disease Control and Prevention. (2017). Americans in rural areas more likely to
die by suicide. From National Vital Statistics System, Morbidity and Mortality Report.
Retrieved from: https://www.cdc.gov/media/releases/2017/p1005-rural-suicide-rates.html
2
Curtin, S. C., Warner, M., Hedegaard, H., & others. (2016). Increase in suicide in the United
States, 1999-2014. U.S. Department of Health and Human Services, Centers for Disease
Control and Prevention, National Center for Health Statistics.
1
Drapeau, C. W. & McIntosh, J. L. (for the American Association of Suicidology). (2018). U.S.A.
suicide 2017: Official final data. Washington, DC: American Association of Suicidology.
Retrieved from http://www.suicidology.org.
5
Drapeau, C. W. & McIntosh, J. L. (for the American Association of Suicidology). (2018). U.S.A.
suicide 2017: Official final data. Washington, DC: American Association of Suicidology.
Retrieved from http://www.suicidology.org.
8
Hayes, A. (2013). An Introduction to mediation, moderation, and conditional process analysis: A
regression-based approach. New York, NY: Guildford Press.
Hudnall, G. A. (2018). Hope Squad: The successful suicide prevention program for students.
Springville, UT: Cedar Fort.
6
Miller, A. B., Esposito-Smythers, C., & Leichtweis, R. N. (2015). Role of social support in
adolescent suicidal ideation and suicide attempts. Journal of Adolescent Health, 56(3), 286–
292. https://doi.org/10.1016/j.jadohealth.2014.10.265
Standley, C. J. (2019). Social support as a protective factor for youth suicide: An intersectional and
socioecological approach. Order No. 13895536 Michigan State University, 2019. Ann
Arbor, MI: ProQuest.
9
Standley, C. J. (2018). Tri-county youth suicide preliminary data report. [Technical report]. Lansing,
MI: Tri-County LifeSavers Suicide Prevention Coalition. Retrieved from
www.CorbinJStandley.com/#projects
10
Toumbourou, J. (2010). The Communities That Care Youth Survey. Burwood Australia:
Communities that Care.
3
Twenge, J. M. (2017). Insecure: The new mental health crisis. In J. M. Twenge, iGen. New York,
NY: Atria Books, pp. 93-118.
Page | 20
Appendix A
Page | 21Corbin J. Standley, M.A.
corbinjs@msu.edu
2019

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Social Support and Youth Suicide

  • 1. Page | 0 Social Support & Youth Suicide An Intersectional and Socioecological Approach Corbin J. Standley, M.A. Michigan State University Study II Data Report August 6, 2019
  • 2. Page | 1 Table of Contents Executive Summary..........................................................................................................................................2 Acknowledgements..........................................................................................................................................3 Data Dashboard................................................................................................................................................4 Introduction.......................................................................................................................................................5 Michigan Profile for Healthy Youth (MiPHY) .............................................................................................6 Suicide-Related Questions .........................................................................................................................6 Missing and Invalid Data..............................................................................................................................6 Methods and Analysis ......................................................................................................................................7 Data Usage and Security.............................................................................................................................7 Research Questions.....................................................................................................................................7 Sample.............................................................................................................................................................8 Missing Data ..................................................................................................................................................8 Analysis...........................................................................................................................................................9 Analytic Procedures................................................................................................................................9 Scales and Measures................................................................................................................................9 Additional Analytics and Statistical Information ...............................................................................9 Findings............................................................................................................................................................. 11 A. Risk for Suicide..................................................................................................................................... 11 B. Social Support as a Protective Factor.............................................................................................. 12 Types of Social Support....................................................................................................................... 13 C. Compounding Social Support ........................................................................................................... 14 D. Social Support as a Moderator......................................................................................................... 14 Modeling the Moderation of Social Support................................................................................... 15 Recommendations......................................................................................................................................... 16 Build a Trusted and Empowered Coalition......................................................................................... 16 Foster Collaboration and Sharing of Resources ................................................................................ 16 Promote Evidence-Based Action........................................................................................................... 16 Future Research.................................................................................................................................... 17 Develop a Sustainability Plan .................................................................................................................. 17 Conclusion ...................................................................................................................................................... 17 References....................................................................................................................................................... 19 Appendix A ..................................................................................................................................................... 20
  • 3. Page | 2 Executive Summary In response to rising youth suicide rates in mid-Michigan, the LifeSavers Suicide Prevention Coalition was established in partnership with Community Mental Health (CEI-CMH) and the Eaton Regional Education Service Agency (Eaton RESA). As a part of this Coalition, the steering committee engaged Corbin J. Standley, doctoral student in Ecological-Community Psychology at Michigan State University, to conduct a series of secondary data analyses studies to determine the risk and protective factors for youth suicide in Clinton, Eaton, and Ingham counties. This report follows the Tri-County Youth Suicide Preliminary Data Report produced in May of 2018 and addresses four major questions: A. Which youth are most at risk for suicide? B. To what extent does social support reduced suicide risk? C. To what extent does compounding support reduce suicide risk? D. To what extent does social support moderate the impacts of intersectionality on suicide risk? Data for the study came from the 2015-2016 wave of the Michigan Profile for Healthy Youth (MiPHY) survey provided in accordance with a data use agreement with the Michigan Department of Education. Additional publicly available aggregate data are also presented. The study began in June of 2018. Major findings from the study include the following: 1. Youth with marginalized identities (females, non-white, and LGB youth) are at significantly increased risk for suicide. 2. The more marginalized identities youth have, the more at risk they are for suicide. 3. Social support at the family, school, and community levels is significantly associated with reduced suicide risk for youth. 4. The combination of social support at all of these levels is significantly associated with the largest decrease in suicide risk for youth. 5. Social support in families and schools significantly mitigates the impacts of multiple marginalized identities on suicide risk suggesting that social support is most important and effective for marginalized youth. There are five major implications based upon these findings: 1. While per-capita suicide rates for white Americans are higher than most minority groups, once we account for intersectional disadvantage, such trends become less clear. 2. The way in which social support is applied in each context impacts its protective effects on suicide risk. 3. To be most effective, social support should be bolstered across every context in which youth live, learn, and play. 4. More proximal sources of social support (those that most closely impact youth directly) have greater protective effects than more distal sources. 5. Social support is even more important for youth with intersecting marginalized identities.
  • 4. Page | 3 There are three major recommendations based upon these findings: 1. Efforts to expand the LifeSavers should consider these findings by engaging youth, marginalized communities, and relevant stakeholders in the work. 2. Social support programs should be designed and implemented across all contexts in which youth live, learn, and play. Such programs should also be tailored to meet the needs of youth with multiple marginalized identities. 3. Future research should further examine the impacts of intersectionality on youths’ experiences of suicidal ideation and behavior. Qualitative research methods may shed light on such experiences and aid in the effective design and implementation of programs and supports for youth. Acknowledgements This initiative and the following report would not have been possible without the support of the following individuals and organizations. Their dedication, passion, and drive helped make this project successful. Pennie Foster-Fishman, Ph.D. Professor, Department of Psychology Michigan State University Jody Nelson, LMSW Urgent Care Clinical Coordinator Community Mental Health Kim Thalison, B.B.A. Prevention Services Supervisor Eaton RESA Joel Hoepfner, B.S., CPC Prevention and Outreach Coordinator Community Mental Health Jennifer Cronkite, M.A., LPC Prevention Specialist Community Mental Health Malea Bullock, M.A., M.S., LLPC Certified Prevention Specialist Eaton RESA Annemarie Hodges, M.A. Temporary Survey Specialist Michigan Department of Education Nicole Kramer-Dodge, B.A. Survey Specialist Michigan Department of Education This study was presented to Michigan State University in partial fulfillment of the requirements for the degree of Master of Arts in Ecological-Community Psychology for Corbin J. Standley. This report contains citations and references according to the American Psychological Association Publication Manual, 6th Edition. This study was approved by the Michigan Department of Education and Michigan State University’s Institutional Review Board and was conducted in accordance with all ethical guidelines set forth by the American Psychological Association.
  • 5. Page | 4 Data Dashboard The following infographics display findings and demographics from Study II of the Youth Suicide Data Initiative. Data represent a total of 5,058 students across high schools in Clinton, Eaton, and Ingham counties who participated in the 2015-2016 wave of the MiPHY survey. Suicide Risk Clusters Social Support The more marginalized identities a respondent had, the more likely they were to be classified as “high-risk.” For those with high intersectionality scores, the protective effects of social support are stronger. Social Support and Suicide Risk Social Support Scores A one-point increase in social support significantly contributed to the noted reduction in overall suicide risk score for youth. Values are points and not percentages. Lower social support scores were associated with higher suicide risk. .62-point reduction in suicide risk .50-point reduction in suicide risk .25-point reduction in suicide risk 22.1% 16.1% 61.8 % 3130 Low-Risk 812 Medium-Risk 1116 High-Risk 3.16 2.88 2.52 2.78 2.59 2.45 2.34 2.11 1.95 High-RiskMedium-RiskLow-Risk Family support is activities, opportunities for input, connectedness, and attachment within one’s family. School support is peer and teacher interactions, extracurricular involvement, and climate within the school. Community support is community activities and interactions with non-familial adults and peers within one’s community. .66-point reduction in suicide risk 0.79 1.45 0.13 0.57 0 0.25 0.5 0.75 1 1.25 1.5 1.75 SuicideRisk 0.61 1.35 0.23 0.77 Low Intersect. High Intersect. High Support Low Support
  • 6. Page | 5 Introduction ver the last 15 years, suicide rates in the state of Michigan have increased by more than 33% and have reached their highest point since the Great Depression era. Even more alarming, suicide is the second leading cause of death among 15-29-year-olds globally.1 Moreover, in the U.S., suicide is currently the third leading cause of death among youth ages 10 to 14, and the second leading cause of death among youth and young adults ages 15 to 34.4 In 2017, an average of one young person (age 24 or younger) died by suicide every 78 minutes—an average of 18.5 suicides per day.5 To that end, the LifeSavers Suicide Prevention Coalition (“LifeSavers”) emerged out of a partnership between Community Mental Health (CEI-CMH) and the Eaton Regional Education Service Agency (Eaton RESA) in order to investigate and work to stop the rising youth suicide rates in Clinton, Eaton, and Ingham counties in mid-Michigan. The LifeSavers brings together stakeholders from across these three counties in order to address the issue of youth suicide. Members of the LifeSavers include representatives from education, juvenile justice, mental health, policy and local government, and local non-profit organizations. Once established, the LifeSavers’ steering committee partnered with Corbin J. Standley of Michigan State University to establish the Youth Suicide Data Initiative. The purpose of the project is to examine existing data to better understand the incidence of youth suicide in Clinton, Eaton, and Ingham counties in order to uncover risk, preventive factors for youth suicide and use that information to inform prevention and intervention strategies. The following report outlines the findings from the second study in the initiative and builds on the Tri-County Youth Suicide Preliminary Data Report produced in May of 2018. The study aimed to contribute to the existing understanding of youth suicide in two major ways. Firstly, the study goes beyond the individual level to look at suicide and the role of social support as a protective factor at multiple levels. Secondly, it uses an intersectional approach to examine how social identities and their combination impacts suicide risk and prevention for youth. Data from the 2015-2016 wave of the Michigan Profile for Health Youth (MiPHY) were analyzed over a period of one year to inform the results. Recommendations for practice and future research for the LifeSavers are also discussed. The study was approved by the Michigan Department of Education, was reviewed by Michigan State University’s Institutional Review Board, and was conducted in accordance with all ethical guidelines set forth by the American Psychological Association. Any questions, concerns, or feedback regarding the methods or findings in this report should be directed to: Corbin J. Standley, M.A. Ph.D. Student, Ecological-Community Psychology Michigan State University corbinjs@msu.edu O Suicidal ideation and suicide attempts are the most commonly reported mental health crises among youth.6
  • 7. Page | 6 Michigan Profile for Healthy Youth (MiPHY) The Michigan Profile for Healthy Youth (MiPHY) is an online student health survey administered by the Michigan Department of Education (MDE) and the Michigan Department of Health and Human Services (MDHHS) to support local and regional needs assessment. The MiPHY provides student results on health risk behaviors including substance use, violence, physical activity, nutrition, sexual behavior, and emotional health in middle schools (seventh grade) and high schools (ninth and eleventh grades) across the state. The survey also measures risk and protective factors most predictive of alcohol, tobacco, and other drug use and violence. Suicide-Related Questions Table 1 below lists the suicide-related questions asked in the MiPHY survey. Analyses for “Suicide Attempt Injury” are not reported beyond this point as the intent of the study was to assess suicide risk rather than outcomes for suicide attempts. Table 1. Suicide-related questions in the MiPHY survey by school level. Construct Survey Item Sadness and Hopelessness 163. During the past 12 months, did you ever feel so sad or hopeless almost every day for two weeks or more in a row that you stopped doing some usual activities? Suicidal Ideation 164. During the past 12 months, did you ever seriously consider attempting suicide? Suicide Plan 165. During the past 12 months, did you make a plan about how you would attempt suicide? Suicide Attempts 166. During the past 12 months, how many times did you actually attempt suicide? Suicide Attempt Injury 167. If you attempted suicide during the past 12 months, did any attempt result in an injury, poisoning, or overdose that had to be treated by a doctor or nurse? Missing and Invalid Data Data for the study were included only for high-school students due to survey item differences and time and resource limitations of the researcher. Of the 8,359 completed high school MiPHY surveys during the 2015-2016 wave, 3,301 (39.5%) were not included in the analyses. Table 2 below details the reasoning behind their exclusion. After eliminating invalid surveys, the data reported herein come from a total valid sample of 5,058 high school students in Clinton, Eaton, and Ingham counties. Table 2. Count and percentage of excluded surveys by reasoning and school level. Reasoning n % Respondent selected a grade level other than 9th or 11th 797 9.5% Respondent answered fewer than 20% of the questions in the survey 326 3.9% Removed in listwise deletion procedures prior to analysis1 2178 26.1% Total 3,301 39.5% 1 These procedures are discussed in further detail in the Methods and Analysis section of this report.
  • 8. Page | 7 Methods and Analysis The findings reported herein emerged from a quantitative study of secondary data from the source described above. Secondary data analysis can be defined as “second-hand” analysis. It is the analysis of information that was either gathered by someone else or for some other purpose other than the one currently being considered. Secondary data analysis is helpful in (1) providing a baseline with which to compare other data, (2) designing potential subsequent research, and (3) informing recommendations for policy, practice, and research. Data Usage and Security In January of 2018, a data use agreement was made between Eaton RESA (on behalf of the LifeSavers Suicide Prevention Coalition) and the Michigan Department of Education (see Appendix A). As a part of this agreement, the complete electronic database of 2015-2016 student-level MiPHY survey data from all Clinton, Eaton, and Ingham county middle and high schools who participated in the MiPHY survey during the 2015-2016 academic year were sent to Corbin J. Standley (hereafter referred to as “the researcher”). These data did not include school building or district identifiers to maintain data confidentiality. The data from each district and county were combined into two separate databases (high school and middle school). Data for this study came only from the high school database. As a part of this agreement, the researcher employed all data usage protocols set forth by the Michigan Department of Education in order to maintain the reliability and validity of the results and, most importantly, the anonymity of students. Data based upon a sample size of fewer than 10 students are suppressed in this and all reports resulting from these data. Research Questions In collaboration with the LifeSavers’ steering committee, a list of factors and indicators of interest were identified including suicidal ideation, suicide attempts, substance and alcohol use, school climate, social support, and demographic factors such as race and ethnicity, age, sexual identity, and county. In an effort to determine the risk and preventive factors for youth suicide in the tri-county area, three primary research questions emerged from these preliminary indicators and guided the analysis of the data. The Tri-County Youth Suicide Preliminary Data Report answers the first of these questions. The findings reported herein attempt to answer the second and third primary questions: 1. What are the major demographic risk factors for youth in the tri-county area? 2. Is school climate significantly related to suicidal ideation or suicide risk among youth? In what ways? 3. What are the major protective factors for youth suicide? To what extent are they available to youth in the tri-county area? To answer these latter two research questions, four secondary research questions guided this study: A. Who is most at risk for suicide? B. To what extent does the presence of social support reduce suicide risk among youth? C. To what extent do compounding sources of social support reduce suicide risk? D. To what extent does social support moderate the effect of intersectionality on suicide risk?
  • 9. Page | 8 Sample The data in this report represent a total of 5,058 students across high schools in Clinton, Eaton, and Ingham counties who participated in the 2015-2016 wave of the MiPHY survey. Table 3 below outlines the demographic characteristics of the sample. Table 3. Demographic characteristics of high school students who participated in the 2015-2016 wave of the MiPHY survey. Demographic n %* County Clinton 1004 19.8% Eaton 1292 25.5% Ingham 2762 54.6% Gender Male 2512 49.7% Female 2546 50.3% Sexual Identity Bisexual 330 6.5% Gay or Lesbian 82 1.6% Heterosexual 4366 86.3% Not Sure 280 5.5% Race/Ethnicity American Indian/Alaska Native 47 0.9% Arab/Chaldean 71 1.4% Asian 209 4.1% Black 419 8.3% Hispanic/Latino 872 17.2% White 3503 69.3% TOTAL 5,058 * Percentages within a category may not add up to 100% given missing data and incomplete survey responses. Missing Data The researcher used a complete-case analysis approach to analyze only the cases for which data on the outcome and predictor variables were available. A total of 2,178 (30.1%) cases were excluded by the researcher prior to analysis. This resulted in a final subsample of 5,058 for all subsequent analyses. The rationale for excluding cases from these analyses was three-fold. 1. The final subsample of provided sufficient statistical power for the analyses conducted. 2. As the demographic variables were being tested in statistical regression models (rather than simply controlled for), a full set of these data was necessary. 3. The demographic distribution of the final subsample did not significantly shift from the original full sample and remained representative of the tri-county area. Cases were excluded in three phases: 1. Respondent missing data on any of the three demographic variables (1,863). 2. Respondent missing data on any of the four items related to suicide risk (190). 3. Responded to less than 51% of the items related to social support in any domain (125).
  • 10. Page | 9 Analysis Data were analyzed using version 24 of the Statistical Package for the Social Sciences (SPSS) with the addition of the PROCESS Macro8 . The researcher used descriptive statistics, correlational analyses, analyses of variance (ANOVAs), multiple linear regression, stepwise linear regression, and hierarchical liner regression analyses to analyze the data. Analytic Procedures Four phases of analysis were used in the study in order to fulfill its aims. The first phase of analysis used ANOVAs, means comparison, and cluster analysis to determine risk groups (secondary research question A). The second and third used linear and stepwise regression analyses to determine the unique and compounding effects of social support on suicide risk (secondary research questions B and C, respectively). Finally, the fourth phase used multiple hierarchical linear regression to assess the impact of social support as a moderator on the relationship between intersectionality and suicide risk (secondary research question D). Scales and Measures Three major constructs were of interest in the study including identity and intersectionality, suicide risk, and social support. The scales and measures used in the study for each of these constructs are detailed here. Table 4 below lists the survey items used in the study. • Identity was measured using the gender, race and ethnicity, and sexual identity demographic items. o Intersectionality was measured by creating an additive score of the three demographic variables (1 being minority status, 0 being majority status) resulting in an intersectionality score ranging from 0 to 3 for each case. • Suicide risk was measured using an additive score of the sadness and hopelessness, suicidal ideation, planned suicide attempt, and previous suicide attempts variables resulting in a composite suicide risk score ranging from 0 to 4 for each case. • Social support was measured at the family, school, and community levels measuring opportunities and rewards for pro-social involvement. Additional Analytics and Statistical Information For the purposes of this report, findings are presented in an accessible manner using lay language and graphs to convey the results. Specifics related to the analyses conducted, particular statistical findings, and overall methods for this study can be found in the full Social Support as a Protective Factor for Youth Suicide: An Intersectional and Socioecological Approach document (Standley, 2019). Please contact the author for more information. CLICK HERE FOR ACCESS TO THE FULL DOCUMENT
  • 11. Page | 10 Table 4. MiPHY survey items included in the study. Demographics Gender: What is your sex? Race: What is your race? Ethnicity: Are you Hispanic or Latino? Sexual Identity: Which of the following best describes you? Protective Factors – Family Domain Oa My parents ask me what I think before most family decisions affecting me are made. O If I had a personal problem, I could ask my mom or dad for help. O My parents give me lots of chances to do fun things with them. R My parents notice when I am doing a good job and let me know about it. R How often do your parents tell you they're proud of you for something you've done? R Do you enjoy spending time with your mother? R Do you enjoy spending time with your father? Protective Factors – School Domain O In my school, students have lots of chances to help decide things like class activities and rules. O There are lots of chances for students in my school to talk with a teacher one-on-one. O Teachers ask me to work on special classroom projects. O There are lots of chances for students in my school to get involved in school activities outside of class. O I have lots of chances to be part of class discussions or activities. R My teacher(s) notice when I am doing a good job and let me know about it. R The school lets my parents know when I have done something well. R My teachers praise me when I work hard in school. Protective Factors – Community Domain O There are adults in my neighborhood I could talk to about something important R I feel safe at my school. R My neighbors notice when I am doing a good job and let me know. R There are people in my neighborhood who encourage me to do my best. R There are people in my neighborhood who are proud of me when I do something well. Suicide Risk During the past 12 months, did you ever feel so sad or hopeless almost every day for two weeks or more in a row that you stopped doing some usual activities? During the past 12 months, did you ever seriously consider attempting suicide? During the past 12 months, did you make a plan about how you would attempt suicide? During the past 12 months, how many times did you attempt suicide? Note: A full version of the 2015-2016 high school MiPHY survey is available upon request. a “O” scales measure opportunities for prosocial involvement. “R” scales measure rewards for prosocial involvement as defined by the Communities That Care Youth Survey.
  • 12. Page | 11 Findings The findings presented below are organized around the four secondary research questions that guided the study. The study examined how social identity influences suicide risk and the role of social support as a protective factor in that relationship. Overall, findings highlight the importance of paying attention to protective factors in every context in which youth live, learn, and play. Moreover, findings also suggest that measuring and reporting social identities as well as their intersections adds to our understanding of both risk and prevention when it comes to youth suicide. A. Risk for Suicide ANOVAs and cluster analyses indicated that risk group membership was largely delineated by minority status for gender, race and ethnicity, and sexual identity. In other words, females; non-white students; and lesbian, gay, or bisexual (LGB) youth were found to be at significantly higher risk for suicide. These findings provide yet more evidence that attending to issues of marginalization experienced by females and LGB individuals is not only advisable but necessary in order to prevent suicides. These findings do not, however, clarify the mixed research regarding race and ethnicity and suicide risk. Overall, non-white youth were significantly more likely to be classified as high-risk, however, this finding revealed a small effect size. Moreover, findings from Study I9 revealed significant differences between racial and ethnic groups only for those with multiple racial identities (i.e., those who identified as multi-racial were significantly more likely to have high risk scores as compared to their Asian, Black/African American, and White peers). Findings also indicate that those with intersecting marginalized identities were significantly more likely to be classified as high-risk. This adds to the scarce literature regarding intersectionality and suicide risk and echoes previous research regarding compounded suicide risk for youth. Table 5 below illustrates the demographic breakdown of risk groups. Taken together, these findings suggest that, while per-capita suicide rates for white Americans are higher than most minority groups, once we account for intersectional disadvantage associated with gender and sexual identity, such trends become less clear. Key Findings 1. Youth with marginalized identities (females, non- white, and LGB youth) are at significantly increased risk for suicide. 2. The more marginalized identities youth have, the more at risk they are for suicide. 3. Social support at the family, school, and community levels is significantly associated with reduced suicide risk for youth. 4. The combination of social support at all of these levels is significantly associated with the largest decrease in suicide risk for youth. 5. Social support in families and schools significantly mitigates the impacts of multiple marginalized identities on suicide risk suggesting that social support is most important and effective for marginalized youth. The study examined how social identity influences suicide risk and the role of social support as a protective factor in that relationship.
  • 13. Page | 12 Table 5. Demographic composition of the low-, medium-, and high-risk suicide risk group membership. Low-Risk (n = 3130) Medium-Risk (n = 812) High-Risk (n = 1116) % % % Gender Female 42.2% 61.9% 64.8% Male 57.8% 38.1% 35.2% Racial identity American Indian/Alaska Native 0.9% * 1.0% Asian 4.5% 3.9% 3.2% Black/African American 8.2% 8.5% 8.4% Native Hawaiian/Pacific Islander * * * White 71.8% 66.3% 64.3% Multiple-Hispanic 8.3% 12.7% 13.7% Multiple-Non-Hispanic 6.2% 7.3% 9.2% Sexual identity Bisexual 2.5% 6.0% 18.2% Gay or Lesbian 0.7% 1.7% 4.2% Heterosexual 92.9% 85.6% 68.5% Not Sure 4.0% 6.7% 9.1% Intersectionality score 0 39.0% 23.8% 17.9% 1 46.1% 46.3% 42.6% 2 13.2% 26.0% 29.1% 3 1.7% 3.9% 10.4% *Suppressed due to small cell size (n < 10). B. Social Support as a Protective Factor Linear regression analyses indicated that social support at the family, school, and community levels each uniquely and significantly contributed to reduced suicide risk in the sample. As Catalano and Hawkins (1996) purport in their social development theory, three conditions must be present at various levels of the socioecological model in order for youth to develop well socially: opportunities for prosocial involvement, skills to be successful in such involvement, and rewards and reinforcement for such involvement (Toumbourou, 2010). Findings from this study support this theory and highlight the importance of increasing social support for youth throughout every level of the socioecological model (see Figure 1 on page 14). In addition, the regression coefficients and effect sizes for these results suggest that more proximal sources of social support were more protective than more distal sources (i.e., the magnitude of the protective effects of family support were greater than those for school support and community support, respectively).
  • 14. Page | 13 Types of Social Support The protective effects of both opportunities and recognition (see Figure 1) were significant for each source of support; however, the analyses demonstrate how these manifestations of support might best be applied at each ecological level (see Figure 2). Within the family and community environments, opportunities were found to be more protective than rewards. This suggests that opportunities to have input into decision-making and develop trusting and supportive relationships with family members and neighbors are more protective than positive feedback within a child’s home and community. Within the school environment, rewards were found to be slightly more protective than opportunities. This suggests that, when youth receive positive feedback for their successes in school, they are also more likely to develop strong social bonds and less likely to engage in risky behaviors. Table 6 below illustrates these differing scores across domains. Table 6. Regression analysis summary for social support predicting suicide risk composite score.† B+ SE B β Family Domain Family opportunities -.31 .03 -.20** Family rewards -.26 .03 -.16** df1 2 df2 5019 R2 .207 Change in R2 .114** F for change in R2 361.738** School Domain School opportunities -.14 .04 -.07** School rewards -.29 .03 -.16** df1 2 df2 5047 R2 .137 Change in R2 .044** F for change in R2 128.549** Community Domain Community opportunities -.13 .02 -.11** Community rewards -.08 .02 -.06* df1 2 df2 5041 R2 .119 Change in R2 .026** F for change in R2 73.160** *p = .001, **p < .001 † A full, detailed explanation of the statistical models used in the analysis is available in the full thesis document. + The unstandardized regression coefficient (B) represents the effect of the variable (opportunities or rewards) on suicide risk. Figure 1. Factors leading to healthy behaviors. Adapted from Communities That Care Social Development Strategy.10
  • 15. Page | 14 C. Compounding Social Support Building upon the finding in section B, stepwise linear regression analyses indicated that the combination of family, school, and community support was significantly more protective than any unique source of social support, and that the reduction in risk explained by each domain was directly related to its proximity to the individual. This is a relatively novel finding suggesting that while the combination of all three sources of social support is most protective, more proximal sources of social support are more protective individually. Table 7 below outlines the statistical significance of these models. These findings also validate both social development and socioecological theories highlighting the importance of social support at multiple ecological levels. Figure 2 to the right illustrates this model relative to the individual. In viewing these environments as both connected and nested, we see how the interpersonal, community, and social environments impact youth outcomes. Table 7. Summary of stepwise regression analysis for variables predicting suicide risk. Model 1† Model 2 Model 3 B+ SE B β B SE B β B SE(B) β Family -.563 .021 -.340** -.515 .024 -.311** -.501 .024 -.303** School -.128 .031 -.059** -.110 .032 -.051* Community -.046 .018 -.035* R2 .207 .209 .210 F for change in R2 718.200** 17.182** 6.268* *p < .05. **p < .001. † A full, detailed explanation of the statistical models used in the analysis is available in the full thesis document. + The unstandardized regression coefficient (B) represents the effect of the variable (opportunities or rewards) on suicide risk. D. Social Support as a Moderator Finally, hierarchical moderated linear regression analyses indicated that both family and school support significantly moderated the relationship between intersectionality and suicide risk such that, for those with high intersectionality scores, the protective effects of social support at the family and school levels were stronger than for those with low intersectionality scores. Community-level support was not found to be a significant moderator in this relationship. This novel moderation finding suggests that the role of social support is particularly important (and effective) for youth with intersecting marginalized identities. Interpersonal Family, School Community Social/Structural Individual Figure 2. Socioecological mode illustrating the levels of the environment that impact youth outcomes and well- being.
  • 16. Page | 15 Figure 4. Predicting suicide risk as a function of intersectionality and social support at the family and school levels. Modeling the Moderation of Social Support Moreover, these findings contradict the one-size-fits-all approach that typifies many suicide prevention efforts for youth. Just as suicide risk itself is different for each child throughout the developmental process, and based on their social identities, so must our efforts approach prevention strategies in multifaceted, multi-level, and individually informed ways. It is only through this combination of individually tailored supports at multiple ecological levels that we can make the most difference for marginalized youth struggling with suicidal ideation and behavior. As Figure 4 below illustrates, intersectionality is significantly related to increased suicide risk at each level of social support, meaning that those with multiple marginalized identities are at increased risk. Analyses show, however, that the magnitude of the effect is smaller with higher levels of social support. In other words, the protective effects of family and school support are stronger for those with high intersectionality scores. Intersectionality Suicide Risk Social Support Figure 3. Conceptual model illustrating the moderating effects of social support on the relationship between intersectionality and suicide risk. Key Implications 1. While per-capita suicide rates for white Americans are higher than most minority groups, once we account for intersectional disadvantage, such trends become less clear. 2. The way in which social support is applied in each context impacts its protective effects on suicide risk. 3. To be most effective, social support should be bolstered across every context in which youth live, learn, and play. 4. More proximal sources of social support (those that most closely impact youth directly) have greater protective effects than more distal sources. 5. Social support is even more important for youth with intersecting marginalized identities. 0.79 1.45 0.13 0.57 0 0.25 0.5 0.75 1 1.25 1.5 1.75 SuicideRisk 0.61 1.35 0.23 0.77 High Support Low Support Low Intersect. High Intersect.
  • 17. Page | 16 Recommendations Based on the findings presented above, the following paragraphs discuss recommendations informed by the Tri-County LifeSavers Suicide Prevention Coalition Strategic Plan (See Figure 5 on page 18). Build a Trusted and Empowered Coalition The findings above further emphasize the need to engage youth in the LifeSavers in order to understand their experiences first-hand and design effective programs to combat youth suicide. The LifeSavers has already taken steps to engage youth which will undoubtably inform its efforts moving forward. These findings also highlight the importance of expanding the diversity and inclusion of the LifeSavers. Given that youth with marginalized identities are at increased risk for suicide, engaging with communities that represent these identities is crucial in order to design and implement effective programs. Foster Collaboration and Sharing of Resources A major finding of this study is that resources and supports across ecological levels are imperative to reducing youth suicide in the tri- county area. As such, collaborating with families, schools, and communities to (1) leverage their expertise and experience, (2) identify and promote evidence-based strategies, and (3) empower them to enact change is vital to the success of the Coalition. Promote Evidence-Based Action Interventions and programs aimed at suicide prevention should target multiple ecological levels in order create sustainable outcomes. In particular, social support programs should be designed and implemented across all contexts in which youth live, learn, and play. Programs that prioritize family systems; school personnel, staff, and peers; and community-level supports are encouraged. Any intervention or program should also consider the unique and compounding impacts of minority social identities on both risk and prevention. In other words, programs should be tailored to meet the needs of youth with multiple marginalized identities. This should be done in the design phase of these interventions as research shows that one-size-fits-all approaches are not sufficient for creating the change necessary to reduce suicide rates. Key Recommendations 1. Efforts to expand the LifeSavers should consider these findings by engaging youth, marginalized communities, and relevant stakeholders in the work. 2. Social support programs should be designed and implemented across all contexts in which youth live, learn, and play. Such programs should also be tailored to meet the needs of youth with multiple marginalized identities. 3. Future research should further examine the impacts of intersectionality on youths’ experiences of suicidal ideation and behavior. Qualitative research methods may shed light on such experiences and aid in the effective design and implementation of programs and supports for youth.
  • 18. Page | 17 Future Research Further quantitative and qualitative research is recommended in order to holistically understand the nature of suicidality among youth in the tri-county area. In particular, a subsequent qualitative study is recommended wherein the perspectives and experiences of youth are uncovered through focus groups and interviewing. In conducting such a study, experiences at the individual, social, and system levels can be better understood. Moreover, understanding the individual and collective perceptions and experiences of suicidality among youth is a useful, often unexplored approach to investigating the issue. Finally, qualitative research approaches are uniquely positioned to examine the socioecological factors that contribute to youth suicide given their emphasis on individual stories and collective narratives Develop a Sustainability Plan Legislative policy change, organizational and agency policy change, and continued funding are necessary in order to design, implement, and sustain the recommendations outlined above. In addition to these social and structural changes, continued engagement from youth in the LifeSavers’ efforts will help to continually cultivate and improve youth-driven initiatives to combat youth suicide. Conclusion As suicide rates among youth continue to rise in the United States, it is apparent that the conventional approaches to suicide research and prevention are not entirely effective. Findings from previous research have undoubtedly shined light on the demographic and social risk factors for suicide, but few have examined how these factors intersect, how protective factors can be studied and enhanced, or how these factors are nested within a socioecological model. In applying intersectional and socioecological approaches typically underutilized in suicidology, the overarching aim of this study is to refocus suicidology research and practice more holistically in order to better capture the individual, social, and ecological factors relevant to youth suicide. More importantly, in examining each of these areas, we learn more about their interactions and interdependencies thus illuminating critical intervention and prevention points. Lastly, by investigating these protective factors, we continue to chip away at the stigma surrounding mental health and suicide. In doing so, we prevent more deaths and fulfill our moral obligation to ensure our youth are poised to live safe, happy, and healthy lives.
  • 19. Page | 18 Figure 5. Tri-County LifeSavers Suicide Prevention Coalition Strategic Plan.
  • 20. Page | 19 References Catalano, R. F. & Hawkins, J. D. (1996). The social development model: A theory of antisocial behavior. In J. D. Hawkins (Ed.), Delinquency and Crime: Current Theories, pp. 149-197. New York, NY: Cambridge University Press. 7 Centers for Disease Control and Prevention. (2016). 10 leading causes of death by age group, United States – 2015. From National Vital Statistics System, National Center for Health Statistics. Retrieved from https://www.cdc.gov/injury/wisqars/LeadingCauses.html 4 Centers for Disease Control and Prevention. (2017). Americans in rural areas more likely to die by suicide. From National Vital Statistics System, Morbidity and Mortality Report. Retrieved from: https://www.cdc.gov/media/releases/2017/p1005-rural-suicide-rates.html 2 Curtin, S. C., Warner, M., Hedegaard, H., & others. (2016). Increase in suicide in the United States, 1999-2014. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics. 1 Drapeau, C. W. & McIntosh, J. L. (for the American Association of Suicidology). (2018). U.S.A. suicide 2017: Official final data. Washington, DC: American Association of Suicidology. Retrieved from http://www.suicidology.org. 5 Drapeau, C. W. & McIntosh, J. L. (for the American Association of Suicidology). (2018). U.S.A. suicide 2017: Official final data. Washington, DC: American Association of Suicidology. Retrieved from http://www.suicidology.org. 8 Hayes, A. (2013). An Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: Guildford Press. Hudnall, G. A. (2018). Hope Squad: The successful suicide prevention program for students. Springville, UT: Cedar Fort. 6 Miller, A. B., Esposito-Smythers, C., & Leichtweis, R. N. (2015). Role of social support in adolescent suicidal ideation and suicide attempts. Journal of Adolescent Health, 56(3), 286– 292. https://doi.org/10.1016/j.jadohealth.2014.10.265 Standley, C. J. (2019). Social support as a protective factor for youth suicide: An intersectional and socioecological approach. Order No. 13895536 Michigan State University, 2019. Ann Arbor, MI: ProQuest. 9 Standley, C. J. (2018). Tri-county youth suicide preliminary data report. [Technical report]. Lansing, MI: Tri-County LifeSavers Suicide Prevention Coalition. Retrieved from www.CorbinJStandley.com/#projects 10 Toumbourou, J. (2010). The Communities That Care Youth Survey. Burwood Australia: Communities that Care. 3 Twenge, J. M. (2017). Insecure: The new mental health crisis. In J. M. Twenge, iGen. New York, NY: Atria Books, pp. 93-118.
  • 22. Page | 21Corbin J. Standley, M.A. corbinjs@msu.edu 2019