Young women with disabilities face multiple barriers that limit their career pathways. Little research has been conducted to examine how cognitive constructs of career self-efficacy and outcome expectations contribute to their future aspirations. This study examined direct relationships between career self-efficacy and outcome expectations on future aspirations, mediating effects of autonomy and self-realization on these relationships, and moderating effects of mental health on these links for young women with disabilities. Although existing research on social cognitive career theory has focused on career self-efficacy, results from this study indicated that outcome expectations might have an even stronger influence on future aspirations. Mental health barriers negatively impact future aspirations of the study’s sample. Limitations and implications for research and practice were discussed.
AppletonJ. J.ChristensonS. L.KimD.ReschlyA. L. (2006). Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument. Journal of School Psychology, 44(5), 427–445. https://doi.org/10.1016/j.jsp.2006.04.002
3.
AshbyJ. S.SchoonI. (2010). Career success: The role of teenage career aspirations, ambition value and gender in predicting adult social status and earnings. Journal of Vocational Behav-ior, 77(3), 350–360. https://doi.org/10.1016/j.jvb.2010.06.006
4.
BanduraA. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.
5.
BanduraA.BarbaranelliC.CapraraG. V.PastorelliC. (2001). Self-efficacy beliefs as shapers of children’s aspirations and career trajectories. Child Development, 72(1), 187–206. https://doi.org/10.1111/1467-8624.00273
6.
BettsJ. E.AppletonJ. J.ReschlyA. L.ChristensonS. L.HuebnerE. S. (2010). A study of the factorial invariance of the Student Engagement Instrument (SEI): Results from middle and high school students. School Psychology Quarterly, 25(2), 84–93. https://doi.org/10.1037/a0020259
Byars-WinstonA.EstradaY.HowardC.DavisD.ZalapaJ. (2010). Influence of social cognitive and ethnic variables on academic goals of underrepresented students in science and engineering: A multiple-groups analysis. Journal of Counseling Psychology, 57(2), 205–218. https://www.doi.org/10.1037/a0018608
9.
CarrD. (1997). The fulfillment of career dreams at midlife: Does it matter for women’s mental health?Journal of Health and Social Behavior, 38(4), 331–344. https://doi.org/10.2307/2955429
10.
DickinsonJ.AbramsM. D.TokarD. M. (2017). An examination of the applicability of social cognitive career theory for African American college students. Journal of Career Assessment, 25(1), 75–92. https://doi.org/10.1177/1069072716658648
11.
DorenB.KangH. J. (2016). Autonomy, self-realization, and self-advocacy and the school- and career-related adjustment of adolescent girls with disabilities. Career Development and Transition for Exceptional Individuals, 39(3), 132–143. https://doi.org/10.1177/2165143415574875
12.
DorenB.LombardiA. R.ClarkJ.LindstromL. (2013). Addressing career barriers for high risk adolescent girls: The PATHS curriculum intervention. Journal of Adolescence, 36(6), 1083–1092. https://doi.org/10.1016/j.adolescence.2013.08.014
13.
DudovitzR. N.ChungP. J.NelsonB. B.WongM. D. (2017). What do you want to be when you grow up? Career aspirations as a marker for adolescent well-being. Academic Pediatrics, 17(2), 153–160. https://doi.org/10.1016/j.acap.2016.08.006
14.
EmersonE.HattonC. (2007). Mental health of children and adolescents with intellectual disabilities in Britain. British Journal of Psychiatry, 191(6), 493–499. https://doi.org/10.1192/bjp.bp.107.038729
15.
FerriB. A.ConnorD. J. (2010). “I was the special ed. girl”: Urban working-class young women of colour. Gender and Education, 22(1), 105–121. https://doi.org/10.1080/09540250802612688
16.
FouadN. A.SmithP. L. (1996). A test of a social cognitive model for middle school students: Math and science. Journal of Counseling Psychology, 43(3), 338–346. https://doi.org/10.1037/0022-0167.43.3.338
17.
GieddJ. N.KeshavanM.PausT. (2008). Why do many psychiatric disorders emerge during adolescence?Nature Reviews Neuroscience, 9(12), 947–957. https://doi.org/10.1038/nrn2513
18.
HayesA. F.RockwoodN. J. (2017). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behavior Research and Therapy, 98, 39–57. https://doi.org/10.1016/j.brat.2016.11.001
19.
KirshB.Stergiou-KitaM.GewurtzR.DawsonD.KrupaT.LysaghtR.ShawL. (2009). From margins to mainstream: What do we know about work integration for persons with brain injury, mental illness and intellectual disability?Work, 32(4), 391–405. https://doi.org/10.3233/WOR-2009-0851
20.
LaiM. H. C.KwokO.-M. (2015). Examining the rule of thumb of not using multilevel modeling: The “design effect smaller than two” rule. The Journal of Experimental Education, 83(3), 423–438. https://doi.org/10.1080/00220973.2014.907229
21.
LeeH. I.RojewskiJ. W. (2013). Brief report: A growth mixture model of occupational aspirations of individuals with high-incidence disabilities. Journal of Adolescence, 36(1), 233–239. https://doi.org/10.1016/j.adolescence.2012.11.003
22.
LentR. W.BrownS. D. (2017). Social cognitive career theory in a diverse world: Guest editors’ introduction. Journal of Career Assessment, 25(1), 3–5. https://doi.org/10.1177/1069072716657811
23.
LentR. W.BrownS. D.HackettG. (1994). Monograph: Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79–122. https://doi.org/10.1006/jvbe.1994.1027
24.
LentR. W.HackettG.BrownS. D. (1999). A social cognitive view of school-to-work transition. The Career Development Quarterly, 47(1), 297–311. https://doi.org/10.1006/jvbe.1994.1027
25.
LentR. W.MorrisonA.EzeoforI. (2014). The career development of people with disabilities: A social cognitive perspective. In StrauserD. R. (Ed.), Career development, employment, and disability in rehabilitation (pp. 113–124). Springer.
26.
LindstromL.HarwickR.PoppenM.DorenB. (2012). Gender gaps: Career development for young women with disabilities. Career Development and Transition for Exceptional Individuals, 35(2), 108–117. https://doi.org/10.1177/0885728812437737
27.
LindstromL.HiranoK. A.IngramA.DeGarmoD. S.PostC. (2018). “Learning to be myself”: Paths 2 the future career development curriculum for young women with disabilities. Journal of Career Development, 46(4), 469–483. https://doi.org/10.1177/0894845318776795
28.
LuskS. L.CookD. (2009). Enhancing career exploration, decision making, and problem solving of adolescent girls with disabilities. Journal of Vocational Rehabilitation, 31(3), 145–153. https://doi.org/10.3233/jvr-2009-0484
29.
McWhirterE. H.CrothersM.RasheedS. (2000). The effects of high school career education on social–cognitive variables. Journal of Counseling Psychology, 47(3), 330–341. https://doi.org/10.1037/0022-0167.47.3.330
30.
MerikangasK. R.HeJ.-P.BursteinM.SwansonS. A.AvenevoliS.CuiL.BenjetC.GeorgiadesK.SwendsenJ. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication—Adolescent supplement (NCS-A). Journal of American Academy of Child and Adolescent Psychiatry, 49(10), 980–989. https://doi.org/10.1016/j.jaac.2010.05.017
31.
MuthénL. K.MuthénB. O. (1998–2019). Mplus user’s guide (8th ed.).
32.
NalbantogluF. Y.CetinH. G. (2018). Career indecision and career anxiety in high school students: An investigation through structural equation modeling. Eurasian Journal of Educational Research, 78, 23–42. https://doi.org/10.14689/ejer.2018.78.2
33.
NeuhausJ. M.SegalM. R. (1993). Design effects for binary regression models fitted to dependent data. Statistics in Medicine, 12(13), 1259–1268. https://doi.org/10.1002/sim.4780121307
34.
NewmanL.WagnerM.KnokeyA.-M.MarderC.NagleK.ShaverD.WeiX. (2011). The post-high school outcomes of young adults with disabilities up to 8 years after high school: A report from the National Longitudinal Transition Study-2 (NLTS2) (NCSER 2011-3005). SRI International.
35.
NoonanB. M.GallorS. M.Hensler-McGinnisN. F.FassingerR. E.WangS.GoodmanJ. (2004). Challenge and success: A qualitative study of the career development of highly achieving women with physical and sensory disabilities. Journal of Counseling Psychology, 51(1), 68–80. https://doi.org/10.1037/0022-0167.51.1.68
36.
OchsL. A.RoesslerR. T. (2004). Predictors of career exploration intentions: A social cognitive career theory perspective. Rehabilitation Counseling Bulletin, 47(4), 224–233. https://doi.org/10.1177/00343552040470040401
37.
O’SullivanD. O.StrauserD. R.WongA. W. (2012). Five-factor model of personality, work behavior self-efficacy, and length of prior employment for individuals with disabilities: An exploratory analysis. Rehabilitation Counseling Bulletin, 55(3), 156–165. https://doi.org/10.1177/0034355212437046
38.
PreacherK. J.HayesA. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879
39.
SheuH.LentR. W.BrownS. D.MillerM. J.HennessyK. D.DuffyR. D. (2010). Testing the choice model of social cognitive career theory across Holland themes: A meta-analytic path analysis. Journal of Vocational Behavior, 76(2), 252–264. https://doi.org/10.1016/j.jvb.2009.10.015
40.
ShogrenK. A.KennedyW.DowsettC.LittleT. D. (2014). Autonomy, psychological empowerment, and self-realization: Exploring data on self-determination from NLTS2. Exceptional Children, 80(2), 221–235. https://doi.org/10.1177/001440291408000206
41.
ShogrenK. A.WehmeyerM. L.PalmerS. B. (2017). Causal agency theory. In WehmeyerM.ShogrenK. A.LittleT.LopezS. (Eds.), Development of self-determination through the life-course (pp. 55–66). Springer.
42.
ShroutP. E.BolgerN. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7(4), 422–445. https://doi.org/10.1037/1082-989X.7.4.422
43.
SmithD. L. (2007). Employment status of women with disabilities from the behavioral risk factor surveillance survey (1995-2002). Work: A Journal of Prevention, Assessment, and Rehabilitation, 29(2), 127–135.
44.
SungC.ConnorA. (2017). Social-cognitive predictors of vocational outcomes in transition youth with epilepsy: Application of social cognitive career theory. Rehabilitation Psychology, 62(3), 276–289. https://doi.org/10.1037/rep0000161
45.
TaggartL.CousinsW.MilnerS. (2007). Young people with learning disabilities living in state care: Their emotional, behavioral and mental health status. Child Care in Practice, 13(4), 401–416. https://doi.org/10.1080/13575270701488816
46.
TrainorA. A. (2007). Perceptions of adolescent girls with LD regarding self-determination and postsecondary transition planning. Learning Disability Quarterly, 30(1), 31–46. https://doi.org/10.2307/30035514
WehmeyerM. L.KelchnerK. (1995). The Arc’s Self-Determination Scale. The Arc National Headquarters.
51.
WehmeyerM. L.NotaL.SoresiS.ShogrenK. A.MorningstarM. E.FerrariL.SgaramellaT. M.DiMaggioI. (2019). A crisis in career development: Life designing and implications for transition. Career Development and Transition for Exceptional Individuals, 42(3), 179–187. https://doi.org/10.1177/2165143417750092
52.
WehmeyerM. L.PalmerS. B.ShogrenK.Williams-DiehmK.SoukupJ. H. (2013). Establishing a causal relationship between intervention to promote self-determination and enhanced student self-determination. The Journal of Special Education, 46(4), 195–210. https://doi.org/10.1177/0022466910392377
