Impact of Functioning on the Career Development of Young Adult CNS Survivors David R. Strauser, Ph.D.

Study Partners Fong Chan-University of Wisconsin-Madison Stacia Wagner-Children’s Brain Tumor Foundation Timothy Tansey-University of Wisconsin-Madison Kanako Iwanaga-University of Wisconsin-Madison

Importance of the Problem Within cancer survivorship populations, survivors of central nervous system (CNS) tumors have been identified to be at greater risk for significant impairment in functioning, levels of independence, employment, and social competence when compared to survivors of non-CNS disease. Difficulty transitioning to adulthood via education and work 5x more likely to be unemployed than their non-CNS counter parts

Career Development Perspective Utilizing a vocational counseling framework, researchers have begun to identify potential areas in which survivors of young adult brain tumors can be categorized to better explain the challenges experienced around finding and maintaining employment.

Illinois Work and Well-Being Model Recent work has suggested that the Illinois Work and Well-Being Model can be used to conceptualize how cancer related factors can impact the career development process and ultimately employment Based on the ICF Links career development to employment and overall participation in society Three key Career Development Phases Awareness Acquisition Maintenance

Illinois Work and Well-Being Model

Purpose of the Study RQ1 Examine how physical and mental health self-management impacts the three phases of career development RQ2 Examine how physical and mental functioning impacts the three phases of career development RQ3 Does mental and physical functioning mediate the relationship between physical and mental health self-management and the three phases of career development We should use terms in a consistent way

Methods

Procedures Survey first year college students who are CNS survivors On-line survey IRB approved-University of Illinois at Urbana-Champaign Survey Packet- Demographics & Questionnaire

Instruments Questionnaire developed specifically for this study ICF and Illinois Work and Disability Model Based Areas Career Development-3 domains Physical/Mental Functioning Physical/Mental health self-management

Career Development-3 domains Awareness I know how to obtain information that would assist me in making effective education and career decisions I feel confident that I can make effective education and career decisions People close to me (parents) provide me with the support and resources necessary to make effective education and career decisions. People close to me (parents) believe it is important for me to work as an adult Acquisition I know how to go about looking for a job that meets my personal needs, skills, and abilities Maintenance I feel confident that I would have the ability to maintain employment if I would able to secure a job?

Physical/Mental Functioning Physical functioning Q: In the past 30 days how would you rate your physical health? Excellent=4, Good=3, Fair=2, Poor=1 Mental functioning Q: In the past 30 days how would you rate your emotional health?

Physical/Mental health self-management Physical health self-management Q: In the education and work environment I am confident that I can manage my physical related brain tumor symptoms (pain, fatigue, vision etc..) Agree=4, Somewhat Agree=3, Somewhat Disagree=2, Disagree=1 Mental health self-management Q: In the education and work environment I am confident about my ability to mange my emotional related brain tumor symptoms (depression, anxiety)

Data Analysis RQ1 Multiple linear regression RQ2 RQ3 Examine how physical and mental health self-management impacts the three phases of career development RQ2 Examine how physical and mental functioning impacts the three phases of career development RQ3 Does mental and physical functioning mediate the relationship between physical and mental health self-management and the three phases of career development Multiple linear regression We should use terms in a consistent way Hierarchical regression analysis

Results

Participants 81 young adult survivors of childhood cancer Age: Between 18 and 24 years old (M = 18.90, SD = .97) Diagnosis Astrocytoma 21% Medulloblastoma brain tumor 17% Craninopharyngioma 9% Ependymoma The age at diagnosis of the participants was between 0 and 17 years old (M = 9.23, SD =4.72)

Participants Treatment Recurrence of cancer The age at recurrence of cancer: Between 4 and 23 years old (M = 11.79, SD =6.38)

Job Awareness: RQ1 & 2 RQ1 RQ2 B SE B β .065 .070 .097 .309 .077 Examine how physical and mental health self-management impacts Job Awareness B SE B β Physical health self-management .065 .070 .097 Mental health self-management .309 .077 .421** Note: R2=.211, p < .001. F(2, 78) = 10.422, p < .001 R2 = 21%; BETA for mental health self-management is .421; if controlling for mental health functioning the R2 for mental health self-management becomes smaller (delta R2 and the mental health self-management beta becomes smaller or not significant, then mental health functioning is a partial mediator for the relationship between mental health self-management and job awareness. Mental health self-management  better mental health functioning better mental health functioning leads to better job awareness. Mental health functioning is a mediator. RQ2 Examine how physical and mental functioning impacts Job Awareness B SE B β Physical functioning .092 .057 .172 Mental functioning .234 .055 .448** Note: R2=.299, p < .001. F(2, 78) = 16.627, p < .001

Job Awareness: RQ3 Physical and mental functioning as mediators for the relationship between physical and mental health self-management and job awareness   At entry into model Final model R2 ΔR2 B SE B β Step 1 .299 .299** Physical functioning .092 .057 .172 .093 .063 .173 Mental functioning .234 .055 .448* * .164 .065 .315* Step 2 .342 .043 Physical health self-management .017 .073 .025 Mental health self-management .175 .085 .238* After controlling for the effect of physical and mental health functioning, physical and mental health self-management added 4.3% of the variance; beta for mental health self-management reduced from .421 to .238. Mental health functioning is definitely a mediator for the relationship between mental health self-management and job awareness. Better mental health self-management led to better mental health functioning, better mental health functioning led to better job awareness. F(4, 76) = 9.872, p < .001 for the full model Δ F(2, 78) = 16.627, p < .001 for Step 1; ΔF(2, 76) = 2.484, n.s. for Step 2.

Job Acquisition: RQ1 & 2 RQ1 RQ2 B SE B β .292 .121 .248* .478 .133 Physical health self-management .292 .121 .248* Mental health self-management .478 .133 .368** Note: R2=.251, p < .001. F(2, 78) = 13.088, p < .001 RQ2 R2 = 25%; BETA for mental health self-management is .368; if controlling for mental health functioning the R2 for mental health self-management becomes smaller (delta R2 and the mental health self-management beta becomes smaller or not significant, then mental health functioning is a partial mediator for the relationship between mental health self-management and job acquisition. Mental health self-management  better mental health functioning better mental health functioning leads to better job acquisition. Mental health functioning is a mediator. B SE B β Physical functioning .207 .104 .218* Mental functioning .339 .101 .367** Note: R2=.254, p < .001. F(2, 78) = 13.295, p < .001

Job Acquisition: RQ3 Physical and mental functioning as mediators for the relationship between physical and mental health self-management and Job Acquisition   At entry into model Final model R2 ΔR2 B SE B β Step 1 .254 .254** Physical functioning .207 .104 .218 .135 .111 .143 Mental functioning .339 .101 .367** .232 .115 .251* Step 2 . 337 .082* Physical health self-management .222 .129 .189 Mental health self-management .288 .152 After controlling for the effect of physical and mental health functioning, physical and mental health self-management added 8.2% of the variance in job acquisition (vs. 36.8% without controlling for the effect of physical and mental health functioning; beta for mental health self-management reduced from .368 to .222 and not significant. Mental health functioning is definitely a mediator for the relationship between mental health self-management and job acquisition. F(4, 76) = 9.640, p < .001 for the full model Δ F(2, 78) = 13.295, p < .001 for Step 1; ΔF(2, 76) = 4.717, p < .05 for Step 2.

Job Maintenance : RQ1 & 2 RQ1 RQ2 B SE B β .550 .101 .545** -.041 .111 Physical health self-management .550 .101 .545** Mental health self-management -.041 .111 -.037 Note: R2=.286, p < .001. F(2, 78) = 15.654, p < .001 RQ2 R2 = 29%; BETA for physical health self-management is .550; if controlling for physical health functioning, the R2 for physical health self-management becomes smaller (delta R2 and the physical health self-management beta becomes smaller or not significant, then physical health functioning is a partial mediator for the relationship between physical health self-management and job maintenance. Physical health self-management  better physical health functioning better physical health functioning leads to better job awareness. Physical health functioning is a mediator. B SE B β Physical functioning .395 .090 .486** Mental functioning -.011 .088 -.013 Note: R2=.230, p < .001. F(2, 78) = 11.659, p < .001

Job Maintenance: RQ3 Physical and mental functioning as mediators for the relationship between physical and mental health self-management and Job Maintenance   At entry into model Final model R2 ΔR2 B SE B β Step 1 .230 .230** Physical functioning .395 .090 .486** .093 .283* Mental functioning -.011 .088 -.013 .047 .097 .059 Step 2 .364 .134** Physical health self-management .431 .108 .426** .426* * Mental health self- management -.101 .127 -.090 After controlling for the effect of physical and mental health functioning, physical and mental health self-management added 13.4% of the variance; beta for physicl health self-management reduced from .550 to .426. Physical health functioning is definitely a partial mediator for the relationship between physical health self-management and job awareness. Better physical health self-management led to better physical health functioning, better physicL health functioning led to better job maintenance.   F(4, 76) = 10.886, p < .001 for the full model Δ F(2, 78) = 11.659, p < .001 for Step 1; ΔF(2, 76) = 8.016, p < .001 for Step 2.

Discussion

Limitations Cross-sectional study Well educated sample Limited psychometrics regarding the instruments Predominately female and Caucasian sample

Discussion Facilitating education and employment via career development, it is important to address perceived physical and mental functioning Improving management of functioning may also be warranted Target functioning based on phase of career development

Discussion Improving perception of functioning appears to strengthen ability to manage late effects in the education and work environment Incorporating career development into young adult CNS psychosocial treatment appears to be important. Interventions should be targeted based on career development activities

Contact Information David R. Strauser, Ph.D. Work and Disability Lab Department of Kinesiology and Community Health 213A Huff Hall, MC-588 1206 South Fourth Street Champaign, IL 61820 strauser@illinois.edu