Persistent Link:
http://hdl.handle.net/10150/290223
Title:
Perceived risk of inherited susceptibility to cancer
Author:
Loescher, Lois Jane
Issue Date:
2001
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Perceived risk of inherited susceptibility to cancer (ISC) historically has been determined by objective measures, which neither emphasize how people with ISC perceive their risk of cancer, nor address the meaning of being at risk. The few studies of perceived risk of ISC provide sparse data regarding the process of perceived risk. Knowledge of this process is important because perceived risk may affect how people act to reduce their cancer risk. This study tested the investigator-developed perceived risk of ISC (PRISC) model to learn about this process. The PRISC model, a latent variable (LV) model, is based on existing literature and a preliminary phenomenological study of women at high risk for breast cancer. LVs (Awareness, Perceived Risk, Fear, Support, and Action) in the PRISC model cannot be measured directly, rather, the score of the LVs is inferred through measurements of associated indicator variables. The purpose of this cross-sectional study was to: (a) estimate psychometric properties of instruments used to measure PRISC model indicator variables; (b) test the fit of the PRISC model with instrument-generated data; and (c) examine relationships among the LVs. The sample of 200 women had no cancer history and met established criteria for hereditary predisposition to breast cancer. Participants completed 12 self-report instruments. Analysis of instruments included descriptive statistics, estimates of internal consistency, and confirmatory factor analysis. Testing of the PRISC model used structural equation modeling (SEM) techniques. Psychometric analysis indicated eight instruments had acceptable standardized alpha coefficients of at least .70. Items in most scales loaded on one factor. SEM resulted in two models: one fit acceptably with the data but did not support relationships between LVs Awareness and Perceived Risk and Perceived Risk and Support. Respecification of the model (deleting Perceived Risk) resulted in poor fit with the data, but significant correlations between Awareness and Fear, Fear and Action, and Support and Action. Instability of the PRISC model indicated the need for theory-driven respecification and reconsideration of some instruments for future analysis. Although instability precludes generalization of findings, the model suggests that fear and support may positively predict action to reduce cancer risk.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Health Sciences, Nursing.; Psychology, Psychometrics.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Nursing
Degree Grantor:
University of Arizona
Advisor:
Haase, Joan

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titlePerceived risk of inherited susceptibility to canceren_US
dc.creatorLoescher, Lois Janeen_US
dc.contributor.authorLoescher, Lois Janeen_US
dc.date.issued2001en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractPerceived risk of inherited susceptibility to cancer (ISC) historically has been determined by objective measures, which neither emphasize how people with ISC perceive their risk of cancer, nor address the meaning of being at risk. The few studies of perceived risk of ISC provide sparse data regarding the process of perceived risk. Knowledge of this process is important because perceived risk may affect how people act to reduce their cancer risk. This study tested the investigator-developed perceived risk of ISC (PRISC) model to learn about this process. The PRISC model, a latent variable (LV) model, is based on existing literature and a preliminary phenomenological study of women at high risk for breast cancer. LVs (Awareness, Perceived Risk, Fear, Support, and Action) in the PRISC model cannot be measured directly, rather, the score of the LVs is inferred through measurements of associated indicator variables. The purpose of this cross-sectional study was to: (a) estimate psychometric properties of instruments used to measure PRISC model indicator variables; (b) test the fit of the PRISC model with instrument-generated data; and (c) examine relationships among the LVs. The sample of 200 women had no cancer history and met established criteria for hereditary predisposition to breast cancer. Participants completed 12 self-report instruments. Analysis of instruments included descriptive statistics, estimates of internal consistency, and confirmatory factor analysis. Testing of the PRISC model used structural equation modeling (SEM) techniques. Psychometric analysis indicated eight instruments had acceptable standardized alpha coefficients of at least .70. Items in most scales loaded on one factor. SEM resulted in two models: one fit acceptably with the data but did not support relationships between LVs Awareness and Perceived Risk and Perceived Risk and Support. Respecification of the model (deleting Perceived Risk) resulted in poor fit with the data, but significant correlations between Awareness and Fear, Fear and Action, and Support and Action. Instability of the PRISC model indicated the need for theory-driven respecification and reconsideration of some instruments for future analysis. Although instability precludes generalization of findings, the model suggests that fear and support may positively predict action to reduce cancer risk.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectHealth Sciences, Nursing.en_US
dc.subjectPsychology, Psychometrics.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineNursingen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorHaase, Joanen_US
dc.identifier.proquest3016490en_US
dc.identifier.bibrecord.b41936851en_US
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