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Psychooncology. 2012 May;21(5):469-78. doi: 10.1002/pon.1935. Epub 2011 Mar 6.

Survivor profiles predict health behavior intent: the Childhood Cancer Survivor Study.

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Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN 38105-2794, USA.



To determine whether unique groups of adult childhood cancer survivors could be defined on the basis of modifiable cognitive, affective, and motivation indicators. Secondary objectives were to examine to what extent group membership co-varied with more static variables (e.g. demographics, disease, and treatment) and predicted intent for subsequent medical follow-up.


Using latent class analysis of data from 978 participants (ages, 18-52 years; mean, 31; and SD, 8) in the Childhood Cancer Survivor Study, we classified survivors according to their worries about health, perceived need for follow-up care, health motivation, and background variables. Intent to participate in medical follow-up, as a function of class membership, was tested using equality of proportions.


The best-fitting model (BIC = 18 540.67, BLMRT = <0.001) was characterized by three distinctive survivor classes (worried, 19%; self-controlling, 26%; and collaborative, 55%) and three significant class covariates (gender, perceptions of health, and severity of late effects). A smaller proportion of survivors in the self-controlling group (81%) than in the worried (90%) (P = 0.015) and collaborative (88%) (P = 0.015) groups intended to obtain a routine medical checkup. A smaller proportion of survivors in the self-controlling group (32%) than in the collaborative (65%) (P = <0.001) and worried (86%) (P = <0.001) groups planned a cancer-related check-up. A smaller proportion of survivors in the collaborative group (65%) than in the worried group (86%) (P = <0.001) were likely to obtain a cancer-related check-up.


Childhood cancer survivors can be classified according to the modifiable indicators. The classification is distinctive, predicts intent for future medical follow-up, and can inform tailored interventions.

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