Career Readiness in Young Adult 
Brain Tumor Survivors 


David R. Strauser, Ph.D. 
Department of Kinesiology and Community 
Health 
October 19, 2009 
1:00-2:30 p.m. 


2
Overview 

• Overview of the problem 
• Overview of Cognitive Information Processing 
• Brief Review of foundational research 
• Initial results of current young adult career 
readiness study findings 
• Applications to service delivery 

3
The Broad Problem 

• As the number of individuals surviving cancer continues to increase, career development and employment are becoming central factors that impact the individual’s community integration and well-being.  

4
Cancer and Employment: Adults
• 
Employment rates of cancer survivors range from 41 to 84% 
– 
Mean rate of 62% (Taskilia &Lindbohm, 2007) 
– 
16.8% of working age cancer survivors (vs. 5% for matched 
controls) are “unable to work because of physical, mental, or 
emotional problems” 
• 
7.4% (vs. 3.2% of matched controls) “were limited in the kind or 
amount of work they could perform” (Hewitt, Rowland, & Yancik, 2003) 
. 
Long term cancer survivors 

. 
One in five survivors reported “cancer related disabilities” 
. 
with 50% continuing to work. 
. 
13% of all survivors had withdrawn from work for cancer related 
reasons within four years (Short et al, 2005) 

5
 
Unequal employment practices are forms of discrimination for 
cancer survivors (Feuerstein, et al., 2007) 
– 
More likely to file claims related to job loss and differential 
treatment 
– 
Cancer combined with another impairment increases 
relationship problems at work 
• 
Duration of sick leave associated with difficulties in returning to 
work in cancer survivors (Amir et al. 2007) 
– 
Males use less sick leave then females 
– 
Males have longer sick leave 
– 
Sick leave used most by those economically deprived 

6
• 
Young adults who are childhood cancer survivors experience 
significant difficulty in obtaining employment 
– 
Adult survivors of childhood cancer are twice as likely to be 
unemployed compared to their healthy controls 
– 
5 times more likely to be unemployed in CNS cancer survivors. 
(deBoer et al, 2006) 

• 
Young adults who are childhood cancer survivors experience 
concerns about obtaining employment 
– 19% with a history of childhood bone marrow transplant reported 
work as a major concern vs. 2% of their age matched controls 
(Bradley,2002) 

– 
Co-Morbid health conditions (depression, anxiety, fatigue, 
cardiovascular disease, visual impairments, and impaired attention 
span) have been linked to difficulty in obtaining employment in 
childhood cancer survivors (deBoer et al, 2006) 

7
Career Development and Cancer Survivorship 
• 
Career counseling has an important role with 
young cancer survivors 
• 
Cognitive Information Processing (CIP) 
provides a theoretical model regarding the 
provision of career services 
– 
Two core constructs 
• 
Information Processing Domains 
• 
Decision-Making Cycle 

8

Theoretical Assumptions (CIP) 

• 
Career decision making involves both 
emotions (affect) and thoughts (cognition) 
– 
Knowledge-content of career choice 
– 
Process-what we need to do 
• 
Knowledge and Emotions are dynamic states 
– 
Impacted by health and disability (i.e. cancer) 
• 
Career problem solving and decision making 
are skills that can be learned 
– 
Can improve with practice 
– 
Career counseling and resources 

9
Dysfunctional Career Thoughts 
• 
Dysfunctional career thoughts lead to… 
– Avoidance of career and other life decisions 
– Decreased life satisfaction 
– Depression and anxiety 
– Decreased job satisfaction 
– Increased job stress 
– Interpersonal relationship problems 
• 
Expressed through… 
– Behavior-poor performance 
– Verbal-negative statements and expressions 
– Emotions-depression and anxiety 

10

Information processing Domains

Executive Processing Domain - Meta Cognitions

Decision-Making Skills Domain to CASVE Cycle

Self Knowledge & Environmental Knowledge to 
Knowledge Domains 

11
Self-Knowledg-Knowledge 

• Values, interests, skills, and employment preferences 
are influenced by 
– 
Personal characteristics 
– 
Life experience 
• 
Values, interests, skills, and employment preferences 
may be influenced by 
– 
Religious or spiritual beliefs 
• 
Cancer Related Issues 
– 
Symptom burden-fatigue, depression, anxiety, decreased 
concentration 
• 
Receptive and Expressive skills 

12
Self-Knowledge 
.Stored in episodic memory 
.Perceptions rather than facts 
.Influenced by interpretation of past events 
.Influenced by present emotions 
Self-Knowledge 
.Stored in episodic memory 
.Perceptions rather than facts 
.Influenced by interpretation of past events 
.Influenced by present emotions 

13
Environmental Knowledge 

• Knowledge of Environmental Demands 
– Direct experience or observing others 
– Expands over time 
• Components of Environmental Knowledge 
– Tasks 
– Tools & Technology 
– Knowledge (i.e. language, interpersonal) 
– Skills & Abilities 
– Work Activities (i.e. communicating, moving objects) 
– Work Context ( i.e. contact with others) 
– Work Styles (i.e. stress tolerance, dependability) 
– Work Values (i.e. relationship, support, achievement) 
– Interests 
• 
Expressive and Receptive demands 

14
Occupational KnowledgKnowledge 

• Stored in semantic memory 
• Verifiable facts rather than perceptions 
• Not influenced by interpretation of past events 
• Not influenced by present emotions 

15
Decision-Making Cycle 
Communication -
Analysis 
Synthesis 
Valuing -
Execution which leads back to communication

16
Meta-Cognitions (Executive Processin-Cognitions (Executive Processing 
Domain) 
Thoughts That Influence Decision Making
Self-Talk
Positive vs. Negative
Self-Awareness
Thoughts, Emotions and Behaviors
Reactions of self to significant others
Monitoring and Control
Where they are in the process
Purposeful engagement

17
Two Dimensions of Career Readiness 

• Capability 
– Cognitive and affective ability to engage in effective 
-career problem solving and decision making 
• Career Thoughts Inventory (CTI) Subscales 
– Decision Making Confusion (DMC) 
– Commitment Anxiety (CA) 
• 
Complexity 
– Contextual factors, originating in the family, society, 
economy, or employing organizations that make it 
(more or less) difficult to solve career problems or 
make decisions 
• CTI Subscale 
– External Conflict (EC) 

18
Two Dimensional Model of Readiness 

Complexity 
(High) 

Low Readiness 
High Degree of Support Needed 

Capability 

(Low) 

Moderate Degree of Readiness 

Moderate Degree of Support 
Needed 

Moderate Readiness 

Moderate to Low Support Needed 
Capability 
(High) 

High Readiness 

No Support Needed 

Complexity 
(Low) 


19
 
Foundational Research Career Readiness and Disability 

20
Key Findings (Disability Specific) 

• People with disabilities have increased levels of 
dysfunctional career thoughts compared to controls 
(Strauser et al, 2002, Strauser et al., 2004) 
• 
The Career Thoughts Inventory (CTI) can be used with 
individuals with disabilities to identify their levels of 
career readiness (Lustig et al., 2003) 
• 
Cognitive and affective states negatively impact career 
readiness (Yanchak et al., 2005; Strauser et al., 2006a; 
Strauser et al., 2006b) 
• 
PWB is positively related to career readiness (Lustig et 
al, 2002; Lustig et al. 2008; Strauser et al, 2008) 


21
Key Findings (Broader Career Literature) 

• Career services are effective in reducing 
negative career thoughts (Dipeolu et al. 2002) 
• 
Completion of higher education is related to 
less dysfunctional career thoughts (Reardon, 
et al., 2000) 
• 
Positive effect of Vocational and Career 
services for individuals with disabilities (Bolton 
& Akridge, 1995; Enright, 1995; Merz & 
Syzmanski, 2002) 

22
Current Research in Career Readiness and Young Adult CNS 
Survivors 

23
Purpose of Current Exploratory Study 

• The overall purpose of this exploratory study is two fold. 
– 
Examine the relationship between career readiness, 
vocational identify and relevant career and psycho-social 
outcomes in young adult brain tumor survivors 
• 
Enhancing career readiness can increase career and 
vocational functioning and career and psycho-social 
outcomes 
– 
Determine if we can classify brain tumor survivors 
according to their level of career readiness 
• 
Classifying survivors according to their level of career 
readiness can guide the implementation of clinical and 
vocational interventions focused on improving career 
and employment outcomes. 

24
Aim 1 

• Aim 1 
– Examine the relationship between career readiness, 
vocational identity, and relevant work and psychosocial 
outcomes 
• Ho: There will be a significant and positive 
relationship between career readiness, vocational 
identify, and relevant work and psycho-social 
outcomes 

25
Conceptual Model Guiding Aim 1
Complexity Capability Identity Community Integration Employment 
Outcomes 
Individual Well- Being 
Conceptual Model Guiding Aim 1 
Complexity 
Capability 
Identity Community 
Integration 
Employment Outcomes Individual Well-Being 
 
26
Aim 2 

• Aim 2 
– Determine if it is feasible to classify brain tumor 
survivors according to their reported level of career 
readiness. 
• Ho: Brain tumor survivors can be classified 
according their reported level of career readiness. 
Specifically, we hypothesize that we will be able 
to classify individuals into three groups (High, 
Moderate, and Low) which then can be used to 
guide the type, level, and implementation of 
career intervention 

27
Intervention Matrix for Aim 2 

Complexity 
(High) 

Low Readiness 
High Degree of Support Needed 

Capability 
(Low) 

Moderate Degree of Readiness 

Moderate Degree of Support 
Needed 


Moderate Readiness 

Moderate to Low Support Needed 

Capability 
(High) 

High Readiness 

No Support Needed 

Complexity 
(Low) 

28
Procedures 

•
Surveys distributed to young adult brain 
tumor survivors 
•Age 18-30 
• IRB approval 
• Research packet contained 
– Demographic Form 
– Career Thoughts Inventory (CTI) 
– Contextual Work Behaviors (CWB) 
– Community Integration Scale (CIS) 
– Satisfaction with Life Scale (SWLS) 

29

Participating Sites 

• Children’s Brain Tumor Foundation 
• 
St. Jude Children’s Hospital 
• Camp-Make-A-Dream 
• Hope Advocate Hospital-Chicago 
• L.A. Children’s Hospital-City of Hope 

30
Study Demographics 

Demographic Characteristics of Participants (N=37). Total (N = 37) 
Gender 
Male 45.9% 
Female 54.1% 
Ethnicity 
Caucasian 76.5% 
African American 8.8% 
Hispanic 5.9% 
Asian/ Pacific Islander 8.8% 
Education 
Grade 12 or below 27.0% 
Community college 24.3% 
Some college 35.1% 
4-year college 10.8% 
Graduate school 2.7% 
Mean Age (years) 21.9 (SD = 3.3) 
Mean age of Onset of Brain Tumor (years) 9.9 (SD = 5.5) 
Mean years off Treatment (years) 7.0 (SD = 6.0) 

31
Results Aim 1 

Multiple linear regression (Stepwise) for total score and 3 subscale 
scores of Career Thoughts Inventory (CTI), predicting total score of 
Vocational Identity (MVS) (N= 37) 

Variables in the equation 
Variables B SEB ί 
t p 
CTI (Total) -.151 .020 -.790 -7.623 <.001 
CTI (DMC) -.152 -.564 .576 
CTI (CA) -.164 -.652 .519 
CTI (EC) -.088 -.599 .553 
Constant 17.385 1.085 16.018 <.001 

Note: R2=.61, Dependent variables: Total score (Vocational Identity) of the My Vocational Situation; Predictor 
variables: CTI (Total) = Total score; CTI (DMC) = Decision Making Confusion; CTI (CA) = Commitment Anxiety; CTI 
(EC) = External Conflict. 

32
Aim 1 Results 

When the four independent variables are entered using 
stepwise method, the total score of CTI alone 
significantly predicted the total score (Vocational 
Identity) of MVS, F= 58.110, p < .001. 

The adjusted R squared value was 0.613, indicating 
that 61.3% of the variance in the total score (Vocational 
Identity) of MVS was explained by this model. 

CTI Subscales (DMC, CA, and EC) did not make a 
unique contribution to the model 

33
Multivariate Results Research Aim 1 

Multivariate analysis procedure for Vocational Identity total score predicting 
the total scores of Contextual Work Behaviors (CWB), Community 
Integration Scale (CIS), and Satisfaction with Life Scale (SWLS) (N=37). 

Variables MS F p Adjusted R2 Power 
CWB (Total) 10919.386 9.293 .004 .186 .842 
CIS (Total) 227.081 5.264 .028 .106 .607 
SWLS (Total) 207.873 4.201 .048 .082 .513 

Note: Dependent variables: CWB (Total) = total score of Contextual Work Behavior (CWB); CIS (Total) = total score of 
Community Integration Scale (CIS); SWLS (Total) = total score of Satisfaction with Life Scale (SWLS). Independent 
variable: VI (Total) = total score (Vocational Identity) of the My Vocational Situation (MVS). 

34
Multivariate Results Aim 1 

Result indicated that the overall model was significant 
(Pillai’s Trace F (3, 33) = 4.131, p = .014) 
Vocational Identify total score significantly predicted: 
CWB (R2 value = .186) 18.6% of the Variance 
CIS (R2 value = .106) 10.6% of the Variance 
SWLS (R2 value = .082) 8.2% of the Variance 

35
Summary Aim 1 Findings 

• Career Thoughts significantly and positively 
related to vocational identity 
• Complexity and capability not a unique 
predictor at this time 
• Vocational identity significantly and positively 
related to: 
– Contextual Work Behaviors (CWB) 
– Community Integration (CIS) 
– Individual Well-being (SWLS) 

36
Grouping Results Aim 2 

Cluster analysis (Ward’s method) was used to 
classify participants into three groups. 
• Results from Chi-square or F-statistics analysis 
indicated that all demographic characteristics, 
except were not significant (p > 0.05). 

37
Grouping Results Aim 2 

Table 4. Demographic Characteristics of Participants in Four 
Cluster Groups (N=37). 

Readiness level Group 1 
(n=15) 
Moderate 
Group 2 
(n=15) 
High 
Group 3 
(n=7) 
Low 
.or F 
Gender 
Male 60.0% 33.3% 42.9% 2.181 
Female 40.0% 66.7% 57.1% (p=.336) 
Ethnicity 
African American 7.1% 7.1% 16.7% 11.603 
Caucasian 78.6% 85.7% 50.0% (p=.071) 
Hispanic 0.0% 0.0% 33.3% 
Asian/ Pacific Islander 14.3% 7.1% 0.0% 

38
Grouping Results Aim 2 

Readiness level Group 1 
(n=15) 
Moderate 
Group 2 
(n=15) 
High 
Group 3 
(n=7) 
Low 
.or F 
Education 
Grade 12 or below 20.0% 26.7% 42.9% 3.726 
Community college 20.0% 26.7% 28.6% (p=.881) 
Some college 40.0% 33.3% 28.6% 
4-year college 13.3% 13.3% 0.0% 
Graduate school 6.7% 0.0% 0.0% 
Mean Age (years) 22.2 (SD = 2.7) 22.3 (SD = 4.1) 20.3 (SD = 2.6) .973 
(p=.389) 
Mean age of Onset of 
Brain Tumor 
(years) 
10.2 (SD = 6.1) 10.0 (SD = 5.3) 9.4 (SD = 5.4) .045 
(p=.956) 
Mean years off 
Treatment (years) 
8.3 (SD = 4.0) 7.4 (SD = 7.9) 3.8 (SD = 3.3) 1.141 
(p = .334) 

Note: Participants were clustered by the total score 
and three subscale scores (DMC, CA, & EA) of Career 
Thoughts Inventory (CTI) 

39
Results Aim 2 

.The GLM Multivariate procedure was computed by entering the raw total 
score, and three raw subscale scores of CTI as dependent variables and 3cluster 
solution as fixed variable. 
.Result indicated that the overall model was significant (Pillai’s Trace F 
(8, 64) = 6.410, p < .001). 
.Test of between-subjects effects further indicated that the CTI Total, DMC, 
CA, and EC are all significant [F (2. 34) = 8.356-98.478, ps < 0.001]. 
• Post-hoc analysis indicated that all pair-wise comparisons of all four 
variables across all three readiness groups are significantly different (ps 
< .05) 
.Except that there is no significant difference on EC score was 
found between Moderate and Low readiness groups (p = .478). 
.Generally speaking, the High readiness group tends to have lower negative 
career thoughts 
.lower DMC,CA, and EC than the other groups. 

40
Differences on CTI across 3 Groups 

Figure 1. T-scores of the total score (CTI Total), and 3 subscale scores (Decision Making Confusion (DMC), Commitment 
Anxiety (CA), and External Conflict (EC) of Career Thoughts Inventory (CTI) across 3 readiness groups. 

Note: T-score conversion was based on the profile for adults as reference. Lower T-score reflected less negative 
career thoughts, less DMC, less CA, & less EC. In other words, lower T-score reflected better readiness. 

41
Conceptual Model (chart)
Complexity & Capability lead to
Identity which leads to 
Employment Outcomes 
Community Integration
and Individual Well-Being 



42
Mean total score of Contextual Work Behavior (CWB Total) across 3 readiness groups.


Readiness level 
Group 1 -
(n=15) Moderate 
Group 2 -
(n=15) High 
Group 3 -
(n=7) Low 
Overall -(N=37) 
CWB Total (Mean) 189.53 205.53 176.85 193.62 
Readiness level 
Group 1 -
(n=15) Moderate 
Group 2 -
(n=15) High 
Group 3 -
(n=7) Low 

Overall (N=37) 
CIS Total (Mean) 21.33 17.87 23.00 20.24 
Readiness level 
Group 1 -
(n=15) Moderate 
Group 2 -
(n=15) High 
Group 3 -
(n=7) Low 

Overall (N=37) 
SWLS Total (Mean) 18.87 22.87 22.14 21.11 

Note: Participants were clustered by the total score 
and three subscale scores (DMC, CA, & EA) of Career 
Thoughts Inventory (CTI) 

43
Mean scores of total score of Contextual Work Behavior (CWB) 
across 3 readiness groups. (Blue Bar Graph)
CWB Total-
Group 1 moderate - 189.5 
Group 2 High- 205.5
Group 3- Low- 176.9
Overall- 193.6

44 (Black Bar Graph)
Mean scores of total score of Community Integration 
Scale, across 3 readiness groups. 
CIS Total:
Group 1 moderate - 21.3
Group 2 High- 17.9
Group 3- Low- 23.0
Overall- 20.2

45 (Red Bar Graph)
Mean scores of total score of Life Scale across 3 readiness 
groups. 
SWLST Total
Group 1 moderate - 18.9
Group 2 High- 22.9
Group 3- Low- 22.1
Overall- 21.1


46
Results Aim 2 

• Able to group cancer survivors according to 
their level of career readiness 
• No differences in demographic variables 
– Ethnicity-may emerge as significant (Low Group) 
– Educatio-may emerge as significant (Low Group) 
• No difference across groups for 
– CWB-may emerge as significant 
– CIS-may emerge as significant 
– SWLS 

47
Implications for Practice 


• Readiness assessment valuable as a means to 
identify level of career and vocational 
intervention 
– High Readiness-Self-help Services 
– Moderate Readiness-Brief Assisted Services 
– Low Readiness-Intensive Services 

48
Implications 

• Improving Readiness may increase CWB 
– Job Maintenance behaviors 
• Handling stress 
• Making adjustments 
• Dealing with co-workers 
• Dealing with supervisors 
• Improving Readiness may increase 
Community Integration 
• Level of community support 
• Level of independence 
• Level of occupational participation 

49
Comments ? Questions ? 

50 (End Slide)
Research Team Research Team:
Logos- 
University of Illinois At Urbana-Champaign
Uniformed Svcs University
Hunter Foundation
St Jude Children's Research Hospital
Children's Brain Tumor Foundation
University of Wisconsin- Madison