Literature DB >> 8004604

Relationship of age to mammography compliance.

V Champion1.   

Abstract

Mammography use varies by age, with older women showing decreased use. The purpose of this research was to identify variables that affect screening use within two different age groups of women, those younger than 50 and those 50 and older. Predictor variables were identified using the Health Belief Model and Theory of Reasoned Action and included susceptibility, seriousness, benefits, barriers, health motivation, control, social influence, and experiential/demographic variables. A probability sample of 581 women aged 35 and older was included for analyses. Two measures of mammography compliance were tested: compliance with American Cancer Society (ACS) guidelines for the 5 years before the study and compliance with the ACS guidelines for the year before the study. An in-home interview was conducted by graduate research assistants. Compliance rates were significantly lower for women 50 and older than they were for younger women for both the 5-year compliance and the single year of compliance. Barriers were more significant for older women. Having a mammography suggested by a health care professional was most important in the older group, indicating that less weight may be given to personal decision making by this population. Higher socioeconomic status was significant with older but not younger women. For older women, interventions need to be directed toward both the physician and the individual woman. Programs that provide knowledge and address cost issues may be the most important primary components for younger women.

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Year:  1994        PMID: 8004604     DOI: 10.1002/cncr.2820741318

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  10 in total

1.  Do social network characteristics predict mammography screening practices?

Authors:  Jennifer D Allen; Anne M Stoddard; Glorian Sorensen
Journal:  Health Educ Behav       Date:  2007-07-09

2.  An examination of differential follow-up rates in breast cancer screening.

Authors:  P A Webber; P Fox; X Zhang; M Pond
Journal:  J Community Health       Date:  1996-04

3.  It's the amount of thought that counts: when ambivalence contributes to mammography screening delay.

Authors:  Suzanne C O'Neill; Isaac M Lipkus; Jennifer M Gierisch; Barbara K Rimer; J Michael Bowling
Journal:  Womens Health Issues       Date:  2011-11-03

4.  Barriers Against Mammographic Screening in a Socioeconomically Underdeveloped Population: A Population-based, Cross-sectional Study.

Authors:  Tolga Özmen; Salih Yüce; Tekin Güler; Canan Ulun; Nilufer Özaydın; Sandhya Pruthi; Nezih Akkapulu; Koray Karabulut; Atilla Soran; Vahit Özmen
Journal:  J Breast Health       Date:  2016-04-01

5.  Factors associated with annual-interval mammography for women in their 40s.

Authors:  Jennifer M Gierisch; Suzanne C O'Neill; Barbara K Rimer; Jessica T DeFrank; J Michael Bowling; Celette Sugg Skinner
Journal:  Cancer Epidemiol       Date:  2009-05-29       Impact factor: 2.984

6.  Health status and mammography use among older women.

Authors:  R C Burack; J G Gurney; A M McDaniel
Journal:  J Gen Intern Med       Date:  1998-06       Impact factor: 5.128

7.  Effect of interventions on stage of mammography adoption.

Authors:  V Champion; G Huster
Journal:  J Behav Med       Date:  1995-04

8.  Sociodemographic determinants of nonattendance in a population-based mammography screening program in the city of Manisa, Turkey.

Authors:  Pınar Erbay Dundar; Beyhan Cengiz Ozyurt; Koray Erdurak
Journal:  ScientificWorldJournal       Date:  2012-03-12

9.  Comparison of Barriers Against Mammography Screening in Socioeconomically Very Low and Very High Populations.

Authors:  Tolga Ozmen; Atilla Soran; Vahit Ozmen
Journal:  Cureus       Date:  2016-07-14

10.  Determinants of non attendance to mammography program in a region with high voluntary health insurance coverage.

Authors:  Magdalena Esteva; Joana Ripoll; Alfonso Leiva; Carmen Sánchez-Contador; Francisca Collado
Journal:  BMC Public Health       Date:  2008-11-13       Impact factor: 3.295

  10 in total

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