First-degree relatives (FDRs) of prostate cancer patients are known to be at increased risk for the disease, yet relatively little is known about their screening behaviors. The current lack of consensus about the value of prostate cancer screening underscores the importance of examining why some men at increased risk participate in screening and others do not. In this study, variables from Protection Motivation Theory were used to identify predictors of prostate specific antigen (PSA) testing in this at-risk population. Toward this end, scales assessing perceived vulnerability, perceived severity, response efficacy, and self-efficacy for prostate cancer screening were administered to 82 unaffected male FDRs aged 40 and older. When recontacted approximately 14 months later, 50% of FDRs were found to have undergone PSA testing in the interim. Older age, prior prostate cancer screening, and a greater sense of personal efficacy about being able to undergo prostate cancer screening were found to be significant (P < 0.05) predictors of subsequently undergoing PSA testing. These findings provide partial support for the predictive validity of Protection Motivation Theory variables and suggest the importance of considering efficacy beliefs in attempting to understand decision-making about PSA testing in at-risk individuals.

Prostate cancer (PC) is a leading cause of cancer specific morbidity and mortality among men in the United States. In the year 2003, there are expected to be 220,900 new cases of PC and 28,900 deaths from the disease (1). Despite the large number of men affected by the disease, there is currently a lack of consensus by leading health agencies on appropriate screening measures for PC. The National Cancer Institute, the United States Preventive Services Task Force, and the American College of Preventive Medicine do not endorse screening for PC in the general population or high-risk groups (2, 3). In contrast, the American Cancer Society and the American Urological Association recommend annual screening for all men age 50 and older who have a life expectancy of at least 10 years and commencing at an earlier age (40–45) for men in high-risk groups such as African Americans and those with affected first-degree relatives (FDRs) (1, 4, 5).

Several studies have examined the relation of family history to use of the prostate specific antigen (PSA) test, the principal method used to screen for PC. Some studies suggests that men with a family history of PC are more likely to get PSA testing (6, 7), while other studies found no association between family history and use of PSA testing (8, 9). In studies of men with a family history of PC, having more affected relatives with PC, higher levels of education, greater knowledge about PSA testing, lower levels of cancer specific distress, and a physician recommendation were associated with higher levels of PSA testing (10–12).

Although providing important information, most of these studies are characterized by a number of methodological limitations. These include a focus on intentions to obtain a PSA test rather than actual behavior as the primary outcome, cross-sectional measurement of health beliefs and PSA testing behavior, and no or partial application of a theoretical framework or model.

Our study sought to address these limitations by prospectively evaluating the potential usefulness of Protection Motivation Theory (PMT) variables, assessed at the time of a baseline interview, in predicting subsequent PSA test use over a 14-month follow up period among men with a family history of PC. PMT has not commonly been used in studies of cancer screening. However, this model has provided insight into prevention and early detection behaviors including consumption of low-fat diets, alcohol use, high-risk sexual behaviors, and smoking cessation to prevent long-term chronic conditions (13–19), and thus may be useful in understanding PSA testing. The theory seeks to explain health behavior change in terms of threat and coping appraisal. The threat appraisal aspect of the model reflects the individual's: (a) perceived vulnerability to a particular disease or condition, in our case PC; and (b) the perceived severity of having the disease or condition. Coping appraisal reflects the individual's: (a) response efficacy or the expectancy that carrying out recommendations can remove the threat; and (b) self-efficacy or believing oneself to be able to carry out the coping response such as PSA testing (20–22). We hypothesized that the PMT variables of perceived vulnerability, response efficacy, and self-efficacy would all be positively associated with use of PSA testing. Previous cancer-related studies have shown little variability in perceived severity among respondents, who overwhelmingly agree that cancer is a serious disease (23–26). Therefore, we hypothesized that the PMT construct of perceived severity would not be associated with PSA testing in our model.

### Subject Recruitment and Data Collection

Patients (index cases) with a confirmed diagnosis of PC being followed at the H. Lee Moffitt Cancer Center (Tampa, FL) or the James A. Haley Veterans Hospital (Tampa, FL) were approached either in person or by telephone by trained research assistants and asked to nominate FDRs (i.e., brothers or sons) for study participation. Eligibility criteria for FDRs were that they must: (a) be males between the ages of 40 and 75; (b) not have been diagnosed with any form of cancer, excluding non-melanoma skin cancer; (c) be able to read questionnaires in English; and (d) be able to provide informed consent.

Using the information provided by the index cases, FDRs were initially contacted by telephone and screened for eligibility. If more than one FDR per index case was nominated, a randomization process was used to determine the order of contact. If the first FDR was ineligible or unwilling to participate, additional FDRs were contacted in the predetermined order until one FDR from the list was successfully recruited. This procedure insured that the participants were unrelated to each other. Individuals who met eligibility criteria 1–3 and verbally agreed to participate were mailed an informed consent form and a study questionnaire. Approximately 2 weeks later, participants were contacted by telephone to confirm that they had received the study materials, answer any questions, and encourage return of the completed questionnaire and signed consent form. If the participants did not return the questionnaire within 2 weeks of the follow-up call, a reminder notice was mailed requesting that the questionnaire be returned by a specified deadline. Those individuals who completed the questionnaire were recontacted by telephone approximately 14 months later, at which time a brief interview was conducted.

### Measures

Sociodemographic and Medical Characteristics. The following sociodemographic and medical characteristics were assessed via a self-report questionnaire at the time of recruitment: age (<50 or ≥50); marital status (Currently married/Living with someone as married or Single/Never Married/Separated/Divorced/Widowed); education (≥College education or <College education); income (≤US$39,999 or >US$40,000); employment status (Full time or Part-time/Retired/Disabled/Unemployed); health insurance status (Currently have health insurance: yes or no); prior PSA test (PSA test at any time before baseline interview: yes or no); number of FDRs with PC (1 FDR or ≥1 FDR); relationship to the index case (Father with PC or Brother with PC); time since PC diagnosis in FDR (<1 year or ≥1year); diagnosis of benign prostatic hypertrophy (BPH) (Ever been told by a doctor that you have BPH: yes or no).

Health Belief Variables. The PMT constructs of vulnerability, severity, response efficacy, and self-efficacy were assessed at the time of recruitment via scales that were developed specifically for this study. Items on each scale were rated using a four-point response format (4 = Strongly agree, 3 = Agree, 2 = Disagree, 1 = Strongly Disagree). Vulnerability was measured with four items (e.g., “Prostate cancer is more common among men like me”), with possible scores ranging from 4 to 16 (Cronbach's α = 0.70). Severity was measured with eight items (e.g., “Developing prostate cancer would be one of the worst things that could happen to me”), with possible scores ranging from 8 to 32 (Cronbach's α = 0.70). Self-efficacy was measured using four items (e.g., “I could follow a doctor's advice to go for prostate cancer screening”), with possible scores ranging from 4 to 16 (Cronbach's α = 0.67). Response efficacy was measured with eight items (e.g., “I believe that prostate cancer screening is the best way of finding prostate cancer early”), with possible scores ranging from 8 to 32 (Cronbach's α = 0.81). The items assessing vulnerability and severity were derived primarily from scales used previously to study women's perceptions of breast cancer (26, 27). The items assessing self-efficacy and response efficacy were derived primarily from scales used previously to measure attitudes regarding PC screening (28), breast cancer screening (29–31), and testicular self-examination (32).

Interval PSA Testing. Occurrence of PSA testing in the 14 months following recruitment was assessed by yes/no response to the following question: “Have you had a PSA test since (interviewer reads date of last contact)?” We selected an interval of 14 months to ensure that at least a year had elapsed since any participant could have undergone prior PSA testing and thus able to examine how health beliefs predicted subsequent PSA testing.

### Data Analysis

All analyses were performed using a standard statistical software package; SAS, version 6.12 (33), and all P values are two-sided with a statistical significance level set at P = 0.05. Analyses comparing men who did and did not receive a PSA test in the 14-month follow-up period were carried out using χ2 tests of heterogeneity for categorical variables and independent samples t tests for continuous variables. Calculations indicated that power was adequate (0.80) to detect medium effect sizes for both t tests (continuous variables) and χ2 tests (dichotomous variables) that compared men who did and did not undergo PSA testing during the follow-up interval. Effect sizes of this magnitude correspond to 0.6 SD unit differences between group means (t tests) or a 30% difference in the proportion of individuals in each group displaying a characteristic (χ2 test). A multiple logistic regression model was then built by using variables that demonstrated significant (P ≤ 0.05) relationships with receipt of PSA testing in univariate analyses.

Of the 693 index cases contacted to obtain information about their FDRs, 370 (53%) responded with 455 nominations. There were no differences based on age or marital status for those who gave contact information versus those who did not. However, those who gave nominations were more likely to be White (P < 0.05). Of those nominated, 236 were randomly selected from lists of more than one FDR per index case. Those who met initial study entry criteria, and were mailed a letter introducing them to the study. Of those individuals, 146 (62%) verbally agreed to participate in the study and 107 (45%) completed and returned the initial baseline questionnaire. At the time the current analyses were planned, 85 of the 107 men were eligible to complete the 14-month follow-up assessment. Of these men, 2 were lost to follow-up and 1 was deceased at the time of follow-up. Thus, a total of 82 (96%) men completed the 14-month follow-up interview. All men were included in the descriptive analyses; however, only 79 men were included in the multivariate analysis due to missing data on the income variable.

The characteristics of the men who completed the 14-month follow-up assessment are reported in Table 1. The majority were Caucasian (92%), currently married (77%), and employed (73%), with annual incomes of least US$40,000 per year (77%). Mean age was 50.5 years (SD = ±8.8), (range = 39.0–77.0), with more than half the sample (57%) under age 50. Less than one third (28%) had a college education. Most (94%) had health insurance and 50% reported having PSA testing before entry into the study. Most (95%) had only one FDR with PC, usually a father (76%). During the 14-month follow-up period, 41 men (50%) received a PSA test and 41 (50%) did not. Table 1. Demographic characteristics, medical characteristics, and health beliefs of first-degree relatives of prostate cancer patients*(n= 82) Total n = 82 (%)PSA Test in Follow-Up Period n = 41 (%)No PSA test in follow-up period N = 41 (%)P value†,§ Age ≥50 35 (43) 25 (61) 10 (24) 0.001 Married 63 (77) 35 (85) 28 (68) 0.07 ≥College education 23 (28) 11 (26) 12 (29) 0.81 Income ≥US$40,000 62 (77) 35 (85) 27 (66) 0.03§
Caucasian 75 (92) 36 (88) 39 (95) 0.43
Employed 60 (73) 33 (80) 27 (66) 0.14
No current health insurance 4 (6) 1 (3) 3 (8) 0.30
Prior PSA test 41 (50) 26 (63) 15 (37) 0.02§
One FDR with prostate cancer 78 (95) 39 (95) 39 (95) 1.00
Father with prostate cancer 62 (76) 29 (71) 33 (80) 0.30
Brother with prostate cancer 17 (21) 10 (24) 7 (17) 0.41
≥1 year since relative diagnosed with prostate cancer 23 (28) 31 (76) 10 (24) 0.06
Personal history of BPH 11 (13) 8 (20) 3 (7) 0.19
Perceived vulnerability (
$${\bar{x}}$$
± SD)
10.89 (1.95) 11.15 (1.98) 10.60 (1.91) 0.22
Perceived severity (
$${\bar{x}}$$
± SD)
20.84 (3.33) 21.02 (2.92) 20.66 (3.73) 0.62
Self-efficacy (
$${\bar{x}}$$
± SD)
13.28 (1.88) 13.85 (1.78) 12.71 (1.82) 0.01§
Response efficacy (
$${\bar{x}}$$
± SD)
26.59 (3.24) 27.24 (3.20) 25.83 (3.13) 0.03§
Total n = 82 (%)PSA Test in Follow-Up Period n = 41 (%)No PSA test in follow-up period N = 41 (%)P value†,§
Age ≥50 35 (43) 25 (61) 10 (24) 0.001
Married 63 (77) 35 (85) 28 (68) 0.07
≥College education 23 (28) 11 (26) 12 (29) 0.81
Income ≥US$40,000 62 (77) 35 (85) 27 (66) 0.03§ Caucasian 75 (92) 36 (88) 39 (95) 0.43 Employed 60 (73) 33 (80) 27 (66) 0.14 No current health insurance 4 (6) 1 (3) 3 (8) 0.30 Prior PSA test 41 (50) 26 (63) 15 (37) 0.02§ One FDR with prostate cancer 78 (95) 39 (95) 39 (95) 1.00 Father with prostate cancer 62 (76) 29 (71) 33 (80) 0.30 Brother with prostate cancer 17 (21) 10 (24) 7 (17) 0.41 ≥1 year since relative diagnosed with prostate cancer 23 (28) 31 (76) 10 (24) 0.06 Personal history of BPH 11 (13) 8 (20) 3 (7) 0.19 Perceived vulnerability ( $${\bar{x}}$$ ± SD) 10.89 (1.95) 11.15 (1.98) 10.60 (1.91) 0.22 Perceived severity ( $${\bar{x}}$$ ± SD) 20.84 (3.33) 21.02 (2.92) 20.66 (3.73) 0.62 Self-efficacy ( $${\bar{x}}$$ ± SD) 13.28 (1.88) 13.85 (1.78) 12.71 (1.82) 0.01§ Response efficacy ( $${\bar{x}}$$ ± SD) 26.59 (3.24) 27.24 (3.20) 25.83 (3.13) 0.03§ * For dichotomous variables, χ2 test of heterogeneity was used to compare groups; for continuous variables, independent samples t test was used to compare groups. Fisher's Exact Test used in variables with <5 in each cell. § Significant at P < 0.05. Significant at P < 0.001. Results of unadjusted analyses comparing men who did and did not receive a PSA test in the 14-month follow-up period are also shown in Table 1. With regard to demographic and clinical variables, results indicated that men who had PSA test during the follow-up interval were more likely to be age 50 or above (P = 0.001), have annual incomes greater than or equal to US$40,000 (P = 0.03), and have had a PSA test before recruitment (P = 0.02). With regard to PMT variables, findings supported predictions. As predicted, men who had a PSA test during the follow-up interval had higher levels of both self-efficacy (P = 0.01) and response efficacy (P = 0.03) for undergoing PC screening. Also as expected, perceived severity was unrelated to undergoing PSA testing in the follow-up interval. However, contrary to the prediction, men who had a PSA test during the follow-up interval did not have evidence of a higher level of perceived vulnerability (P = .22). These results remained stable in the multivariate analysis with the exception of having a PSA test before recruitment and response efficacy, which were no longer significant after adjusting for other covariates.

A multivariate analysis incorporating those variables that demonstrated significant (P < 0.05) univariate relationships revealed that age [odds ratio (OR) = 6.67, 95% confidence interval (CI) 1.95–22.90], income (OR = 5.32, 95% CI 1.32–21.36), and self-efficacy (OR = 1.53, 95% CI 1.01–2.31) were all significant independent predictors of receiving PSA testing in the 14-month follow-up interval (Table 2). The two other variables found to be significant in the univariate analyses (i.e., prior PSA testing and response efficacy) were not found to be significant independent predictors when entered into the multivariate model. Additional analyses were conducted to test for possible interactions among the constructs of PMT (perceived vulnerability, perceived severity, response efficacy, and self-efficacy) with respect to PSA testing, all of which were statistically not significant.

Table 2.

Logistic regression model of predictors of prostate specific antigen testing (n = 79)

OR (95% CI)*
Age ≥50 6.67 (1.95, 22.90)*
Income ≥US$40,000 5.32 (1.32, 21.36)* Prior PSA test 1.72 (0.58, 5.10) Self-efficacy 1.53 (1.01, 2.31)* Response efficacy 0.92 (0.72, 1.16) OR (95% CI)* Age ≥50 6.67 (1.95, 22.90)* Income ≥US$40,000 5.32 (1.32, 21.36)*
Prior PSA test 1.72 (0.58, 5.10)
Self-efficacy 1.53 (1.01, 2.31)*
Response efficacy 0.92 (0.72, 1.16)
*

Significant at P < 0.05.

Our study found that both demographic factors such as age and income, as well as health beliefs, are important predictors of PSA testing behavior among FDRs of men with a family history of PC. It is noteworthy that even among men with another significant risk factor for PC (i.e., family history), age continues to be a strong predictor of PSA testing. Our findings are consistent with the results of the study by Miller et al. (8) which showed that age was a significant predictor of PSA testing among men with a family history of PC. This finding may be explained by recent reports showing that 70–90% of men recognize age as a risk factor for PC compared to 10–75% of men who recognize family history as a risk factor for PC (12, 34, 35). As shown in previous research, income was associated with increased likelihood of PSA testing (6, 36, 37). It is likely that income is representative of factors related to access to the health care system. In a national study of cancer screening trends in the U.S., having a usual source of health care and health insurance were associated with higher levels of PSA testing among U.S. men (38). Similarly, having talked with a health care provider about or been recommended by a health care provider to have PSA testing (which implies having access to a health care provider) was associated with increased PSA testing (7, 12).

With regard to our theoretical model, perceived vulnerability and perceived severity were not significantly associated with PSA testing in unadjusted or multivariate analyses. In studies of women at increased risk for breast cancer due to family history, those women with higher levels of perceived vulnerability were found to be more likely to engage in mammography (39–42). We hypothesized that there would be a similar relationship between perceived vulnerability and PSA testing in men with a family history of PC. As previously stated, perceived vulnerability did not predict PSA testing. Three other studies of men with family history of PC have also found no association between perceived vulnerability or risk and PSA testing (8, 11, 12). A possible explanation may be a fatalistic attitude toward developing cancer. This characteristic has been shown to be associated with reduced levels of participation in mammography and colon cancer screening (43–46). As expected, perceived severity of PC was not a significant predictor of PSA testing. In previous cancer screening research, this factor has been of little predictive value, possibly due the almost universally held belief that cancer is a severe disease (23–26).

In unadjusted analyses, response efficacy and self-efficacy were associated with increased levels of PSA testing. However, in our multivariate model, response efficacy was no longer significant. To our knowledge, PMT has not been used to predict PSA testing behavior; however, response efficacy and self-efficacy have been found to be important components of this theory in predicting other health-related behaviors among men. For example, in a study of risk reduction behavior among gay men, response efficacy and self-efficacy were associated with the belief that an individual is personally capable of limiting one's number of sexual partners (18). Similar to our results, a study of 281 male industrial workers based on PMT found that self-efficacy was predictive of using a hearing protection device (47).

In the case of PSA testing, where the clinical utility of this test is controversial, the role of efficacy is an important issue to consider. Both response and self-efficacy are centered on the belief that coping with a threat in a specific manner will reduce the threat (22). However, with PSA testing, there is a lack of consensus in the medical and scientific community about whether using this test will result in earlier detection and, therefore, reduced morbidity or mortality. The influence of response efficacy or self-efficacy on behavior may be indicative of a lack of understanding of the current limitations of this test. A recent article discussed the potentially biased positive feedback system that can occur with PSA testing for both patients and physicians (48). A patient receives positive feedback if the test is negative because of a reduction in worry about PC, but also for a positive test result due to a feeling that the cancer was caught early. For physicians, recommending PSA testing is a no-lose strategy because performing a simple blood-based PSA test requires less time than discussing with patients the pros and cons of having such a test. Additionally, performing PSA testing may decrease the chances of medical malpractice suits if patients are later discovered to have PC. This feedback system fosters an environment that reinforces minimal discussion of the limitations of PSA testing (48). Therefore, it is worth considering that the beliefs about response efficacy among FDRs who subsequently underwent PSA testing may be based on a lack of understanding of the limited clinical utility of this test in the early detection of PC.

Among a sample of 304 men who received PSA testing at two clinics in Texas, less than half the sample (40%) reported that their doctor discussed advantages and disadvantages of PSA testing with them (49). Interventions targeted an informed decision making for PSA testing show that men are less likely to have or be interested in having a PSA test if they are part of an intervention that discusses both the benefits and limitations of this test (50, 51). It is important to continue to foster men's feelings of efficacy related to cancer screening modalities based on a true understanding of personal health benefits of PSA testing.

Although our study provides some insights into PSA testing among FDRs of men with PC, the results should be considered in light of the following study limitations. Our response rate for index patients who gave contact information was 53%. Whites were more likely to give contact information about their FDRs compared to other minority groups, as reflected by the predominantly White respondents in our survey. Therefore, our findings may not be generalizable to minority men with a family history of PC. Of the 236 FDRs approached about the study, 45% returned the baseline questionnaire. It is possible that men who are more interested in PSA testing and/or family history of PC were more likely to respond to this survey than those who were not. A goal of our study was to evaluate the utility of PMT in understanding PSA testing. Ideally, use of an analytic technique such as structural equation modeling would allow us to definitively test the utility of PMT in predicting PSA testing. However, our study was designed to be a preliminary evaluation of the utility of PMT and did not have a sample size sufficient to conduct this analysis. Another limitation related to PMT is the lack of data about beliefs toward PC among men without a family history of PC. This information would provide insight into whether these beliefs and their impact on PSA testing are specific to men with a family history of PC or are more generally held among men. Additionally, our study sample was comprised primarily of Caucasian men who tended to be of higher socioeconomic status (SES), limiting generalizability to those in lower SES and other racial/ethnic groups. Finally, our assessment of the primary outcome variable of PSA testing was based on self-report. A study of patient self-report of PSA found that self-report of test results was discordant with medical records 29% of the time with patients tending to overreport having a PSA test in the previous 2 years when compared with medical records (52).

As molecular genetic diagnosis improves, family history of PC will become an increasingly important risk factor on which to base decisions for management of PC risk. The present study showed that both demographic and health belief variables are important factors associated with PSA testing among men with a family history of PC. Similar to other studies of PSA testing, age and income were important predictors of PSA test use. The use of a theoretical model in our study allowed us to gain additional insight into other factors that can impact PSA testing in this group. Our findings provide partial support for the predictive utility of PMT variables. Perceived vulnerability and perceived severity were not associated with PSA test use. However, beliefs in the efficacy of PSA testing as a means of detecting PC early and personal confidence that one can carry out this behavior were associated with PSA test use. This finding suggests that efforts to enhance informed decision making about PSA testing or increase PSA test use among men with a family history of PC are likely to be more effective if issues related to efficacy are addressed. Future studies using analytic techniques such as structural equation modeling may allow for more definitive statements about the utility of PMT. Additionally, comparative studies using PMT to understand differences in PSA testing among men with and without a family history of PC may help guide interventions aimed at helping at-risk individuals making informed decisions about PSA testing.

Grant support: National Cancer Institute Grant R01 CA86826.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: During preparation of portions of this manuscript, Dr. Thomas Vadaparampil was supported by the Cancer Prevention Fellowship of the National Cancer Institute.

1
ACS, Cancer facts and figures—2003. (ACS Publication No. 5008.03). Atlanta, GA: American Cancer Society; 2003.
2
Ferrini R, Woolf SH. American College of Preventive Medicine practice policy. Screening for prostate cancer in American men.
Am J Prev Med
1998
;
15(1)
:
81
-4.
3
Harris R, Lohr KN. Screening for prostate cancer: an update of the evidence for the U.S. Preventive Services Task Force.
Ann Intern Med
2002
;
137(11)
:
917
-29.
4
Prostate-specific antigen (PSA) best practice policy. American Urological Association (AUA).
Oncology (Huntingt)
2000
;
14(2)
:
267
-72, 277-8, 280 passim.
5
Smith RA, Cokkinides V, Eyre HJ. American Cancer Society guidelines for the early detection of cancer, 2003.
CA Cancer J Clin
2003
;
53(1)
:
27
-43.
6
Close DR, Kristal AR, Li S, Patterson RE, White E. Associations of demographic and health-related characteristics with prostate cancer screening in Washington State.
Cancer Epidemiol Biomark Prev
1998
;
7(7)
:
627
-30.
7
McDavid K, Melnik TA, Derderian H. Prostate cancer screening trends of New York State men at least 50 years of age, 1994 to 1997.
Prev Med
2000
;
31(3)
:
195
-202.
8
Miller SM, Diefenbach MA, Kruus LK, et al. Psychological and screening profiles of first-degree relatives of prostate cancer patients.
J Behav Med
2001
;
24(3)
:
247
-58.
9
Taylor KL, Di Placido J, Redd WH, et al. Demographics, family histories, and psychological characteristics of prostate carcinoma screening participants.
Cancer
1999
;
85(6)
:
1305
-12.
10
Bratt O, Kristoffersson U, Lundgren R, Olsson H. Sons of men with prostate cancer: their attitudes regarding possible inheritance of prostate cancer, screening, and genetic testing.
Urology
1997
;
50(3)
:
360
-5.
11
Bratt O, Damber JE, Emanuelsson M, et al. Risk perception, screening practice and interest in genetic testing among unaffected men in families with hereditary prostate cancer.
Eur J Cancer
2000
;
36(2)
:
235
-41.
12
Cormier L, Reid K, Kwan L, Litwin MS. Screening behavior in brothers and sons of men with prostate cancer.
J Urol
2003
;
169(5)
:
1715
-9.
13
Van der Velde FW, Van der Pligt J. AIDS-related health behavior: coping, protection motivation, and previous behavior.
J Behav Med
1991
;
14(5)
:
429
-51.
14
Rippetoe PA, Rogers RW. Effects of components of protection-motivation theory on adaptive and maladaptive coping with a health threat.
J Pers Soc Psychol
1987
;
52(3)
:
596
-604.
15
Runge C, Prentice-Dunn S, Scogin F. Protection motivation theory and alcohol use attitudes among older adults.
Psychol Rep
1993
;
73(1)
:
96
-8.
16
Plotnikoff R, Higginbotham N. Predicting low-fat diet intentions and behaviors for the prevention of coronary heart disease: an application of Protection Motivation Theory among an Australian population.
Psychol Health
1995
;
10(5)
:
397
-408.
17
Eppright D, Tanner J, Hunt J. Knowledge of the Ordered Protection Motivation Model: tools for preventing AIDS.
J Bus Res
1994
;
30
:
13
-24.
18
Aspinwall LG, Kemeny ME, Taylor SE, Schneider SG, Dudley JP. Psychosocial predictors of gay men's AIDS risk-reduction behavior.
Health Psychol
1991
;
10(6)
:
432
-44.
19
Brouwers M, Sorrentino R. Uncertainty orientation and Protection Motivation Theory: the role of individual differences in health compliance.
J Pers Soc Psychol
1993
;
65(1)
:
102
-112.
20
Rogers RW. A protection motivation theory of fear appeals and attitude change.
J Psych
1975
;
91
:
93
-114.
21
Maddux J, Rogers RW. Protection motivation theory and self-efficacy: a revised theory of fear appeals and attitude change.
J Exp Soc Psychol
1983
;
19
:
469
-79.
22
Prentice-Dunn S, Rogers RW. Protection Motivation Theory and preventive health: beyond the Health Belief Model.
Health Educ Res
1986
;
1(3)
:
153
-61.
23
Champion VL, Scott CR. Reliability and validity of breast cancer screening belief scales in African American women.
Nurs Res
1997
;
46
:
331
-7.
24
Stein JA, Fox SA, Murata PJ, Morisky DE. Mammography usage and the health belief model.
Health Educ Q
1992
;
19(4)
:
447
-62.
25
Holm CJ, Frank DI, Curtin J. Health beliefs, health locus of control, and women's mammography behavior.
Cancer Nurs
1999
;
22(2)
:
149
-56.
26
Aiken LS, West SG, Woodward CK, Reno RR. Health beliefs and compliance with mammography-screening recommendations in asymptomatic women.
Health Psychol
1994
;
13(2)
:
122
-9.
27
Champion VL. Instrument development for health belief model constructs.
1984
;
6(3)
:
73
-85.
28
Myers RE, Wolf TA, McKee L, et al. Factors associated with intention to undergo annual prostate cancer screening among African American men in Philadelphia.
Cancer
1996
;
78(3)
:
471
-9.
29
Kurtz ME, Given B, Given CW, Kurtz JC. Relationships of barriers and facilitators to breast self-examination, mammography, and clinical breast examination in a worksite population.
Cancer Nurs
1993
;
16
:
251
-9.
30
Champion V. The relationship of selected variables to breast cancer detection behaviors in women 35 and older.
Oncol Nurs Forum
1991
;
18
:
733
-9.
31
Curry SJ, Emmons KM. Theoretical models for predicting and improving compliance with breast cancer screening.
Ann Behav Med
1994
;
16
:
302
-16.
32
Steffen VJ. Men's motivation to perform the testicular self-exam: effects of prior knowledge and an educational brochure.
J Appl Soc Psychol
1990
;
20
:
681
-702.
33
Little RC, Milliken GA, Stroup WW, et al. Sas Systems for Mixed Models. Cary, NC: Sas Institute; 1996.
34
Miesfeldt S, Jones SM, Cohn W, et al. Men's attitudes regarding genetic testing for hereditary prostate cancer risk.
Urology
2000
;
55(1)
:
46
-50.
35
Arar N, Thompsen I, Sarosdy M, et al. Risk perceptions among patients and their relatives regarding prostate cancer and its heredity.
Prostate Cancer Prostatic Dis
2000
;
3(3)
:
176
-85.
36
Steele CB, Mille DS, Maylahn C, Uhler RJ, Baker CT. Knowledge, attitudes, and screening practices among older men regarding prostate cancer.
Am J Public Health
2000
;
90(10)
:
1595
-600.
37
Eisen SA, Waterman B, Skinner CS, et al. Sociodemographic and health status characteristics with prostate cancer screening in a national cohort of middle-aged male veterans.
Urology
1999
;
53(3)
:
516
-22.
38
Swan J, Breen N, Coates RJ, Rimer BK, Lee NC. Progress in cancer screening practices in the United States: results from the 2000 National Health Interview Survey.
Cancer
2003
;
97(6)
:
1528
-40.
39
Drossaert CC, Boer H, Seydel ER. Perceived risk, anxiety, mammogram uptake, and breast self-examination of women with a family history of breast cancer: the role of knowing to be at increased risk.
Cancer Detect Prev
1996
;
20(1)
:
76
-85.
40
Hailey BJ, Carter CL, Burnett DR. Breast cancer attitudes, knowledge, and screening behavior in women with and without a family history of breast cancer.
Health Care Women Int
2000
;
21(8)
:
701
-15.
41
Lerman C, Kash K, Stefanek M. Younger women at increased risk for breast cancer: perceived risk, psychological well-being, and surveillance behavior.
J Natl Cancer Inst Monogr
1994
;(
16
):
171
-6.
42
Royak-Schaler R, Klabunde CN, Greene WF, et al. Communicating breast cancer risk: patient perceptions of provider discussions.
Medscape Women's Health
2002
;
7(2)
:
2.
43
Myers RE, Hyslop T, Jennings-Dozier K, et al. Intention to be tested for prostate cancer risk among African-American men.
Cancer Epidemiol Biomark Prev
2000
;
9(12)
:
1323
-8.
44
Lerman C, Rimer B, Trock B, Balshem A, Engstrom PF. Factors associated with repeat adherence to breast cancer screening.
Prev Med
1990
;
19(3)
:
279
-90.
45
Kash KM, Holland JC, Halper MS, Miller DG. Psychological distress and surveillance behaviors of women with a family history of breast cancer.
J Natl Cancer Inst
1992
;
84(1)
:
24
-30.
46
Powe BD. Fatalism among elderly African Americans. Effects on colorectal cancer screening.
Cancer Nurs
1995
;
18(5)
:
385
-92.
47
Melamed S, Rabinowitz S, Feiner M, Weisberg E, Ribak J. Usefulness of the protection motivation theory in explaining hearing protection device use among male industrial workers.
Health Psychol
1996
;
15(3)
:
209
-15.
48
Ransohoff DF, McNaughton Collins M, Fowler FJ. Why is prostate cancer screening so common when the evidence is so uncertain? A system without negative feedback.
Am J Med
2002
;
113(8)
:
663
-7.
49
Chan EC, Vernon SW, O'Donnell FT, et al. Informed consent for cancer screening with prostate-specific antigen: how well are men getting the message?
Am J Public Health
2003
;
93(5)
:
779
-85.
50
Flood AB, Wennberg JE, Nease RF, et al. The importance of patient preference in the decision to screen for prostate cancer. Prostate Patient Outcomes Research Team.
J Gen Intern Med
1996
;
11(6)
:
342
-9.
51
Wolf AM, Nasser JF, Schorling JB. The impact of informed consent on patient interest in prostate-specific antigen screening.
Arch Intern Med
1996
;
156(12)
:
1333
-6.
52
Jordan TR, Price JH, King KA, Masyk T, Bedell AW. The validity of male patients' self-reports regarding prostate cancer screening.
Prev Med
1999
;
28(3)
:
297
-303.