SHMD 239 Kinesiology Unit 1 Introduction to Kinesiology & Biomechanics 1.
Career Readiness in Young Adult Brain Tumor Survivors David R. Strauser, Ph.D. Department of...
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![Page 1: 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.](https://reader035.fdocuments.us/reader035/viewer/2022081514/56649eca5503460f94bd8435/html5/thumbnails/1.jpg)
Career Readiness in Young Adult Brain Tumor Survivors
David R. Strauser, Ph.D.Department of Kinesiology and Community
Health October 19, 20091:00-2:30 p.m.
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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
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The Broad Problem
As the number of individuals surviving cancer continues to increase, career developmentcareer development and employmentemployment are becoming central factors that impact the individual’s community integration community integration and well- well-beingbeing.
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Cancer and Employment: AdultsCancer 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13% of all survivors had withdrawn from work for cancer related reasons within four years (Short et al, 2005)
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Cancer and Employment: AdultCancer and Employment: Adult
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
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Cancer and Employment: Young Cancer and Employment: Young AdultsAdults
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)
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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
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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
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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
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Information Processing DomainsInformation Processing Domains
Executive Processing Domain
Knowledge Domains
Decision-Making Skills Domain
SelfKnowledge
Environmental Knowledge
CASVE Cycle
Meta-cognitions
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Self-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
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Self-Knowledge Stored in episodic memory
Perceptions rather than facts
Influenced by interpretation of past events
Influenced by present emotions
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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
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Occupational Knowledge
Stored in semantic memory
Verifiable facts rather than perceptions
Not influenced by interpretation of past events
Not influenced by present emotions
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Decision-Making Cycle
Communication
AnalysisExecution
SynthesisValuing
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Meta-Cognitions (Executive Processing Domain)
Thoughts That Influence Decision Making– Self-TalkSelf-Talk
Positive vs. Negative– Self-AwarenessSelf-Awareness
Thoughts, Emotions and Behaviors Reactions of self to significant others
– Monitoring and ControlMonitoring and Control Where they are in the process Purposeful engagement
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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)
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Complexity(High)
Low ReadinessHigh Degree of Support Needed
(Individual Case Managed (Individual Case Managed Services)Services)
Capability
Moderate ReadinessModerate to Low Support Needed
(Brief Staff Assisted Services)(Brief Staff Assisted Services)
Capability
(Low)
Moderate Degree of ReadinessModerate Degree of Support
Needed
(Brief Staff-Assisted Services)(Brief Staff-Assisted Services)
(High)
High ReadinessNo Support Needed
(Self-Help Services)(Self-Help Services)
Complexity(Low)
Two Dimensional Model of Readiness
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Foundational Research
Career Readiness and Disability
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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)
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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)
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Current Research in Career
Readiness and Young Adult CNS
Survivors
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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.
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Aim 1
Aim 1– Examine the relationship between career readiness,
vocational identity, and relevant work and psycho-social outcomes
Ho: There will be a significant and positive relationship between career readiness, vocational identify, and relevant work and psycho-social outcomes
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Complexity
Capability
Identity Community Integration
Employment Outcomes
Individual Well-Being
Conceptual Model Guiding Aim 1
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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
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Complexity(High)
Low ReadinessHigh Degree of Support Needed
(Individual Case Managed (Individual Case Managed Services)Services)
Capability
Moderate ReadinessModerate to Low Support Needed
(Brief Staff Assisted Services)(Brief Staff Assisted Services)
Capability
(Low)
Moderate Degree of ReadinessModerate Degree of Support
Needed
(Brief Staff-Assisted Services)(Brief Staff-Assisted Services)
(High)
High ReadinessNo Support Needed
(Self-Help Services)(Self-Help Services)
Complexity(Low)
Intervention Matrix for Aim 2
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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)
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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
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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)
Study Demographics
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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 β 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.
Results Aim 1
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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
Aim 1 Results
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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).
Multivariate Results Research Aim 1
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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
Multivariate Results Aim 1
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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)
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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).
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Readiness level Group 1(n=15)Moderate
Group 2(n=15)High
Group 3 (n=7)Low
Χ 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%
Table 4. Demographic Characteristics of Participants in Four Cluster Groups (N=37).
Grouping Results Aim 2
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Readiness level Group 1(n=15)Moderate
Group 2(n=15)High
Group 3 (n=7)Low
Χ 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)
Grouping Results Aim 2
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The GLM Multivariate procedure was computed by entering the raw total score, and three raw subscale scores of CTI as dependent variables and 3-cluster 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.
Results Aim 2
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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.
Differences on CTI across 3 Groups
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Complexity
Capability
Identity Community Integration
Employment Outcomes
Individual Well-Being
Conceptual Model
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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)
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Mean scores of total score of Contextual Work Behavior (CWB) across 3 readiness groups.
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Mean scores of total score of Community Integration Scale, across 3 readiness groups.
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Mean scores of total score of Life Scale across 3 readiness groups.
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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)– Education-may emerge as significant (Low Group)
No difference across groups for– CWB-may emerge as significant– CIS-may emerge as significant– SWLS
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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
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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
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Questions?Comments ?
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Research Team