Improving Sexual Health Communication Between Older Women and Their Providers

Abstract

Talking about sexual health can be a challenge for some older women. This project was initiated to identify key factors that improve communication between aging women and their primary care providers. A sample of women (aged 60+) completed an online survey regarding their intent to communicate with a provider about sexual health. Using the integrative model of behavioral prediction as a guide, the survey instrument captured data on attitudes, perceived norms, self-efficacy, and intent to communicate with a provider about sexual health. Data were analyzed using structural equation modeling. Self-efficacy and perceived norms were the most important factors predicting intent to communicate for this sample of women. Intent did not vary with race, but mean scores of the predictors of intent varied for African American and White women. Results can guide practice and intervention with ethnically diverse older women who may be struggling to communicate about their sexual health concerns.

Keywords

medical decision making older adults structural equation modeling

Introduction

The World Health Organization considers sexual health to be an important component of quality of life and overall well-being (World Health Organization, 2006), but it is often overlooked as a concern for older women (Gott, 2005). Aging women experience high rates of some sexual problems (Laumann, Das, & Waite, 2008) and these problems can serve as important indicators of other serious health concerns, such as cardiovascular problems and depression (Basson & Schultz, 2007; Nusbaum, Lenahan, & Sadovsky, 2005). However, barriers to communication with a health care provider can influence whether or not older women get help for sexual health concerns (Lindau, Leitsch, Lundberg, & Jerome, 2006). Communication could be enhanced if the factors that play a role in whether or not older women will communicate with their health providers about sexual health were better understood. The integrative model of behavioral prediction (IMBP; Fishbein, 2000) proposes a model that identifies the factors that predict engagement in a behavior, such as communication. This study aims to increase understanding of how important the main variables of the IMBP are to an older woman’s intent to communicate with a health provider about sexual health.

Literature Review

Sexual Health and Aging

Sexual health is associated positively with life satisfaction (Woloski-Wruble, Oliel, Leefsma, & Hochner-Celnikier, 2010), greater purpose in life (Prairie, Scheier, Matthews, Chang, & Hess, 2011), and well-being (Avis et al., 2005; Davison, Bell, LaChina, Holden, & Davis, 2009; Laumann, Paik, & Rosen, 1999). In a global study of older men and women, subjective sexual well-being was found to be positively correlated with overall happiness (Laumann et al., 2005). Older women identify sexual health as a lifelong need (Woloski-Wruble et al., 2010), and continue to engage in sexual activity well into older age (Jacoby & Revere, 2005; Trompeter, Bettencourt, & Barrett-Connor, 2012). However, aging is also associated with an increased incidence of problems in sexual functioning and associated relationship strain (Hartmann, Philippsohn, Heiser, & Ruffer-Hesse, 2004; Howard, O’Neill, & Travers, 2006; Ling, Wong, & Ho, 2008; Luftey, Link, Rosen, Wiegel, & McKinlay, 2009). With the incidence of some sexual problems as high as 49% among women aged 40–80 (Moreira et al., 2005) inclusion of sexual health in assessments or clinical encounters would provide an opportunity for providers to address this concern (Woloski-Wruble et al., 2010).

Communication About Sexual Health

Because many sexual health concerns (e.g., anorgasmia, low desire, and some sexually transmitted diseases) do not present with physical signs, communication is especially relevant to their identification, treatment, and management (Sobecki, Curlin, Rasinski, & Lindau, 2012). Unfortunately, providers have struggled with communication about sexual health, especially across gender, age, and cultural differences (Burd, Nevadunsky, & Bachmann, 2005; Gott, Galena, Hinchliff, & Elford, 2004; Gott & Hinchliff, 2003). Factors that contribute to communication difficulties are provider discomfort, negative attitudes about sexuality and aging, and patient discomfort (Gott, 2005). Older female patients may be reluctant to talk because of embarrassment or shame or belief in the social stereotype that older women should not be concerned with sexuality beyond reproduction (Gott & Hinchliff, 2003). Younger age of the provider, perceived lack of interest on the provider’s part, and preference that the provider initiate discussions have also been found to impact sexual health communication for older women (Nusbaum, Singh, & Pyles, 2004).

The IMBP

The IMBP proposes that to understand why someone engages in a particular behavior, we must understand that person’s intent to engage in the behavior. Intent is predicted by three primary variables: (1) attitudes toward the behavior, (2) perceived norms regarding the behavior, and (3) self-efficacy to perform the behavior, as well as skills and environmental constraints (Fishbein, 2000; Fishbein & Yzer, 2003). Intent is enhanced if one has a positive attitude toward the behavior, perceives that important people in their life will support the behavior, and has positive self-efficacy to perform the behavior (Fishbein, 2000; Fishbein & Yzer, 2003). Attitudes come from one’s feelings toward the behavior and are based on a person’s beliefs about the positive and negative consequences of engaging in the behavior. Sexual health communication may be associated for some older women with negative outcomes, especially if they have had a negative experience with it in the past. Perceived norms are described as having two components: injunctive norms (e.g., the perception that other people that you are close to would support you adopting the behavior) and descriptive norms (e.g., whether or not those people engage in the behavior themselves). Older women’s intent can be impacted if their friends and family are generally supportive of discussing sexual health with providers and if those friends and family have spoken to a provider about their own sexual health. Self-efficacy refers to one’s belief that she could perform the behavior even under difficult circumstances (Fishbein, 2000; Fishbein & Yzer, 2003). In the area of sexual health communication, an example would be if a woman felt she was able to talk to her physician even if the sexual health topic was very difficult for her, say discussing a sexually transmitted disease or decreased sexual function.

It is important to understand to what degree behavioral intent is under the control of attitudes, perceived norms, or self-efficacy (Fishbein & Yzer, 2003). The IMBP has been used in several studies to understand health behavior, such as predicting participation in cancer prevention activities (Smith-McLallen & Fishbein, 2009), HIV prevention (Rhodes, Stein, Fishbein, Goldstein, & Rotheram-Borus, 2007), and use of decision aids in primary care (Frosch, Legare, & Mangione, 2008). These research studies found that the influential factors in changing health behavior varied with the particular behavior under study as well as the sample population. Fishbein (2000) discusses the primacy of understanding behavior, so that we can implement interventions that most effectively target behavior change.

A previous qualitative study (Hughes, 2011) found that for a convenience sample of 27 women in the Midwest (mean age = 60.96 [SD = 7.95]; 48% African American), perceived norms was the least important IMBP construct when these women considered whether or not to communicate about sexual health with a health care provider. Attitudes and self-efficacy were found to be more salient to this group of women, all of whom had intent to communicate with a provider about their sexual health. The current study was developed to examine whether the trends indicated in the previous qualitative work would be maintained in a larger, more representative sample of older U.S. women. This study was guided by two research questions: (1) How do the IMBP variables—attitudes, perceived norms, and self-efficacy—relate to intention to communicate about sexual health for older U.S. women? and (2) What is the relative strength of these three variables as predictors of an older woman’s intent to communicate with a health care provider about sexual health?

Method

Sample

The sampling frame consisted of members of SurveyMonkey Audience, a diverse group of people who are reflective of the U.S. population that uses the Internet (K. Campbell, SurveyMonkey Audience account representative, personal communication, September 29, 2011). Members of SurveyMonkey Audience participate in the completion of surveys on a voluntary basis and are compensated for their participation with points toward merchandise or donations to a charity of their choice. The principal investigator worked with a representative from SurveyMonkey to determine the sampling frame, which included women, aged 60 and above, one third of whom were non-White. The survey was made available online to this stratified sample. Participants had to be members of SurveyMonkey Audience to receive an invitation to participate in the online survey, and they chose whether or not to complete it.

Procedures

The research protocol was approved by institutional review board of the university. During the fall of 2011, members of the sample were sent an e-mail notification from SurveyMonkey informing them of the study and a link to the online questionnaire, which was available for 1 week. The questionnaire included a cover letter that described the study as well as informed consent. No incentive was given to participants. Analysis was conducted using Mplus version 6.1 (Muthen & Muthen, 1998–2011).

Measures

The questionnaire included demographic items, such as year of birth, race and ethnicity, level of education, income, and marital status. Items measuring the constructs of intent, attitudes, perceived norms, and self-efficacy were created by the principal investigator, and were guided by prior research on development of items to measure IMBP constructs (Busse, Fishbein, Bleakley, & Hennessy, 2010; Francis et al., 2004; Frosch, Legare, Fishbein, & Elwyn, 2009). The questionnaire was piloted with 10 women aged 60 and over from the community. The women provided feedback on the length of time it took to complete, their comprehension of the items, and what they thought the purpose of the study was. Changes based on their feedback were integrated into the final online questionnaire. Table 1 provides details on the individual items that were utilized to measure each of the IMBP constructs. Items were reverse scored when necessary and summed, with higher numbers corresponding to more of the construct (e.g., more positive attitudes, higher self-efficacy). Cronbach’s α coefficients were calculated for the IMBP variables in the model, with the following results: intent (.954), attitudes (.837), perceived norms (.625), and self-efficacy (.689).

Table 1.

IMBP Questionnaire Items.

IMBP construct and response choice options	Item
Attitudes (5 items) –Semantic differential response choices	Talking to my primary care provider about my sexual health is: –likely/not likely to bring results –harmful/helpful^a –will answer my questions/will not answer my questions –is pleasant for me/is unpleasant for me –not the right thing to do/the right thing to do^a
Perceived norms (5 items) –Semantic differential response choices (first item) –5 point Likert-type scale, strongly disagree to strongly agree (second to fifth items)	Most people who are important to me think that I should/I should not talk about my sexual health with my primary care provider^a
	I feel under social pressure to talk about my sexual health with my primary care provider
	People who are important to me want me to talk about my sexual health with my primary care provider
	Most people who are important to me talk about their sexual health with their primary care providers
	My primary care provider is comfortable talking with me about my sexual health
Self-efficacy (4 items) –5 point Likert-type scale, not difficult at all to very difficult (first item), not confident to very confident (second item), strongly disagree to strongly agree (third and fourth items)	How difficult is it for you to talk about your sexual health with your primary care provider?
	How confident are you that you could talk to your primary care provider about your sexual health?^a
	Whether or not I talk about my sexual health with my primary care provider is under my control^a
	My primary care provider’s comfort level impacts my ability to talk about sexual health at my visits
Intent (3 items) –7 point Likert-type scale, strongly disagree to strongly agree	I expect to talk about my sexual health with my primary care provider at my next visit
	I want to talk about my sexual health with my primary care provider at my next visit
	I intend to talk about my sexual health with my primary care provider at my next visit

Note. IMBP = integrative model of behavioral prediction.

^aIndicates reverse scoring of the item in analysis.

Statistical Analysis

Demographic characteristics of the sample were summarized using descriptive statistics. Confirmatory factor analysis and structural equation modeling were used to test the IMBP that examined the antecedents of intent to communicate about sexual health with a health care provider. A measurement model was tested for each of the four constructs (1) attitudes, (2) perceived norms, (3) self-efficacy, and (4) intent. Measurement models were evaluated and respecified before examination of the structural model (Bentler, 1989).

To assess model fit multiple global fit indices were used, namely, the comparative fit index (CFI; Bentler, 1990), the Tucker–Lewis index (TLI; Tucker & Lewis, 1973), and the root mean square error of approximation (RMSEA; Brown & Cudeck, 1993). For the CFI and TLI indices values at or above .90 indicate adequate fit, for the RMSEA a value less than .08 is considered to indicate good fit (Bentler, 1995). Lagrange multiplier indices were used for post hoc model testing in order to identify theoretically relevant paths and enhance overall model fit (Bentler, 1995). We analyzed our models using full information maximum likelihood estimation that takes missingness into account (Enders & Bandalos, 2001; Muthen & Muthen, 1998–2011).

Results

The invitation to participate in this study was sent to a total of 7,225 members of the SurveyMonkey Audience. Nine hundred and ninety-six respondents completed the survey for a response rate of 13.79%. Race of respondents included the following: 4.0% Native American, 2.7% Asian, 18.2% African American, 71% White, and 0.8% Native Hawaiian or Other Pacific Islander. Women of Hispanic ethnicity were 2.2% of the respondents. Because of the relatively large numbers of these races, women who were African American or White were included in the analysis for a sample size of 853 participants. Table 2 provides the demographic details of the sample.

Table 2.

Demographic Characteristics of the Sample (N = 853).

Variable	N	%	M	SD
Age			66.0	5.07
Race
White	679	79.6
African American	174	20.4
Education
Some high school	7	.8
High school graduate/equivalency	67	8.0
Some college	195	23.2
Associate’s degree	71	8.4
Bachelor’s degree	219	26.0
Master’s degree	219	26.0
Professional degree	30	3.6
Doctorate degree	33	3.9
Missing	12
Total household income
Less than US$19,999	67	8.2
US$20,000–US$39,999	174	21.3
US$40,000–US$59,999	185	22.7
US$60,000–US$79,999	159	19.5
US$80,000–US$99,999	97	11.9
US$100,000 or more	134	16.4
Missing	37
Marital/relationship status
Married	405	48.6
Widowed	109	13.1
Divorced	191	22.9
Separated	21	2.5
Never married	77	9.2
Living with a partner	30	3.6
Missing	20

The first measurement model specified fit the data poorly (CFI = .850, TLI = .819, RMSEA = .104). Evaluation of Lagrange multiplier indices identified five error covariances: two within the attitudes subscale, two within the perceived norms subscale, and one between Item 1 on the perceived norms subscale and Item 4 on the attitudes subscale. The error covariance within subscales likely reflects some shared measurement error. Shared error may also reflect the IMBP proposition that there are common background factors affecting behavior through their influence on the proximal predictors of intent (Busse et al., 2010). Prior theory and research has suggested a potential relationship between attitudes and perceived norms, as someone’s attitude or perception of the behavioral outcome can be influenced by powerful others in their lives (Hardeman et al., 2002, p. 150; Makoul & Clayman, 2006, p. 306). Because of this, as well as the supposition that there are other factors related to the behavior that may be accounting for the error covariance (Noar, Chabot, & Zimmerman, 2008), these modifications were deemed to be substantively reasonable.

The addition of these correlated error covariances resulted in a significant improvement in model fit, ▵χ²(1) = 556.50, p < .001 (CFI = .933, TLI = .916, RMSEA = .071). All factor loadings were significant except for the fourth item on the self-efficacy factor. The removal of this item resulted in improved model fit, ▵χ²(1) = 63.745, p < .001 (CFI = .940, TLI = .922, RMSEA = .073), and this model was retained as the final model. Intent was regressed on attitudes, self-efficacy, and perceived norms. Results indicated that intent is positively related to perceived norms (.127, p < .05) and self-efficacy (.43, p < .0001), but the relationship to attitudes is not statistically significant. Self-efficacy is a stronger predictor of intent when compared to perceived norms, while all other relationships among latent factors are not statistically significant (see Figure 1). Finally, race (African American women and White women) was entered into the model as a predictor of all of the latent factors. Scores for African American women were significantly lower on attitudes (−0.14, p < .0001) and self-efficacy (−0.085, p <.05) but higher on perceived norms (.10, p < .05). The relationship between race and intent was nonsignificant, indicating that there is no difference on intent to communicate by race.

Discussion

The final model indicates that of the three main IMBP variables, self-efficacy is the strongest predictor of intent to communicate with a primary care provider about sexual health. Perceived norms is a weaker predictor of intent to communicate about sexual health, and attitudes were unrelated to intent for this sample. Analysis by race indicated that intent was similar for both African American and White women. Some variation by race was found in the mean scores of the predictors of intent. These results can help guide practice with ethnically diverse older women who may be struggling to communicate about their sexual health concerns. This type of formative research also has implications for interventions aimed at improving communication with health care providers about sexual health. Targeting interventions to have the most impact is more plausible when we can identify which factors are most influential to the enactment of a particular behavior (Frosch et al., 2009).

Following the logic of the IMBP, those with intent are more likely to actually carry out the behavior. Self-efficacy, one’s belief that they could perform a behavior even in the face of difficulties, was most important to predicting intent in this sample. Self-efficacy has been found to be important to the management of chronic illness; Holman and Lorig (2004) found that patient self-efficacy was the most important outcome related to improvements in chronic disease self-management. Improving self-efficacy to communicate about sexual health with a provider can be fostered through practice and modeling (Bandura, 1977; Gist & Mitchell, 1992). Supportive counseling to enhance self-efficacy to discuss these issues will likely increase a woman’s intention to do so. This can be especially impactful as sexual health is important to the overall well-being of aging women. An intervention that targets self-efficacy beliefs could help women to identify barriers to communication about sexual health, and work to diminish those barriers and increase her belief that she can communicate.

Women in this sample were sensitive to the opinions and actions of important others in their lives (perceived norms), and this influenced their intent to engage in communication about their sexual health. Although this factor was less important than self-efficacy in predicting intent, it provides an opportunity for providers in the health field. Providers can be powerful models of communication behavior, and through normative pressure increase the likelihood that their clients will follow suit. Women who see this will understand that their provider endorses communication (injunctive norm) and engages in the behavior themselves (descriptive norm). This may be especially important for older African American women, given the findings that intent was more impacted by perceived norms for these women when compared to White women.

Generally, older women prefer if providers initiate a conversation about sexual health (Grant & Ragsdale, 2008; Politi, Clark, Armstrong, McGarry, & Sciamanna, 2009; Woloski-Wruble et al., 2010). Providers in health care have had varied contact with communication training, and such training may be helpful. Studies have found that for nurses and medical doctors the lack of formal communication training is a barrier to discussion of sexual health (Hinchliff & Gott, 2011; Stokes & Mears, 2000). Although not specific to sexual health, a brief training on communication skills for providers yielded improvements in communication about other difficult topics (Helitzer et al., 2011). Within a health care team, discussions should include who is best suited to have these conversations with clients, as these conversations can serve as powerful models for older women.

Limitations

The findings of this study need to be considered in light of some limitations. First, response rate was low at 14%. While web-based response rates are typically lower than surveys sent by the mail (Shih & Fan, 2008), and a previous study using SurveyMonkey Audience also yielded a low (16%) response rate (Morris, 2013), results need to be interpreted with caution regarding generalizability. Response rate may be low because some potential respondents did not care for the topic area, although others have endorsed the use of the Internet to collect data on sensitive topics (Alessi & Martin, 2010). The sample was self-selected and may reflect participation by people who have a particular interest in the topic, and possible selection bias (Couper, 2007). Response rate could have been improved with the use of multiple contacts and greater personalization (Cook, Heath, & Thompson, 2000), or with use of an incentive (Dillman, Smyth, & Christian, 2009). Because a representative sample was not utilized, the sample does not adequately represent the population of older women in the United States. All potential participants were Internet users, and Internet use has been found to be associated with higher income, White race, and more education (Pew, 2012). While this sample had more representation from African Americans as compared to census data from 2010 (Federal Interagency Forum on Aging-Related Statistics, 2012, p. 4), it may be that the African American Internet users in this sample differ significantly from the general population of older African American women on income and education.

In this study, we did not actually measure the behavior communication about sexual health, rather a proxy for this behavior, intent. The IMBP tells us that enactment of the behavior is likely to occur if intent is there, but we do not know if this actually occurred for the women in our sample. It is important to note that within this sample there likely were varying levels of need to discuss sexual health, and that level of need may be an alternate explanation for intent. In addition, we did not ask women about their definition of sexual health concerns, and it is very likely that intent varies as well with the type of sexual health problem. Future research could pursue these avenues to enhance our understanding of this important topic. Despite these limitations, this study enhances our understanding of the potential factors that guide the communication decisions made by older women with regard to their sexual health.

Footnotes

Acknowledgment

The authors would like to thank the reviewers who read and commented on this article.

Authors’ Note

The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health & Human Development or the National Institutes of Health.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The project described was supported by Award Number K12HD065879 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development.

References

Alessi

E. J.

Martin

J. I.

(2010). Conducting an internet-based survey: Benefits, pitalls, and lessons learned. Social Work Research, 34, 122–128.

Avis

N. E.

Zhao

Johannes

C. B.

Ory

Brockwell

Greendale

G. A

. (2005). Correlates of sexual function among multi-ethnic middle-aged women: Results from the study of women’s health across the nation (SWAN). Menopause: The Journal of the North American Menopause Society, 12, 385–398.

Bandura

. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.

Basson

Schultz

W. W

. (2007). Sexual dysfunction 1: Sexual sequelae of general medical disorders. The Lancet, 369, 409–424.

Bentler

P. M

. (1989). EQS structural equations program manual. Los Angeles, CA: BMDP Statistical Software.

Bentler

P. M

. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246.

Bentler

P. M

. (1995). EQS structural equations program manual [Computer software]. Los Angeles, CA: BMDP Statistical Software..

Brown

M. W.

Cudeck

(1993). Alternative ways of assessing model fit. In Bollen

L. J.

. (Ed.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.

Burd

I. D.

Nevadunsky

Bachmann

. (2005). Impact of physician gender on sexual history taking in a multispecialty practice. Journal of Sexual Medicine, 3, 194–200. doi:10.1111/j.1743-6109.2005.00168.x

10.

Busse

Fishbein

Bleakley

Hennessy

(2010). The role of communication with friends in sexual initiation. Communication Research, 37, 239–255. doi:10.1177/0093650209356393

11.

Cook

Heath

Thompson

R. L.

(2000). A meta-analysis of response rates in web- or internet-based surveys. Educational and Psychological Measurement, 60, 821–836. doi:10.1177/00131640021970934

12.

Couper

M. P

. (2007). Issues of representation in eHealth research (with a focus on web surveys). American Journal of Preventive Medicine, 32, S83–S89. doi:10.1016/j.amepre.2007.01.017

13.

Davison

S. L.

Bell

R. J.

LaChina

Holden

S. L.

Davis

S. R

. (2009). The relationship between self-reported sexual satisfaction and general well-being in women. Journal of Sexual Medicine, 6, 2690–2697. doi:10.1111/j.1743-6109.2009.01406.x

14.

Dillman

D. A.

Smyth

J. D.

Christian

L. M.

(2009). Internet, mail, and mixed-mode surveys: The tailored design method (3rd ed.). Hoboken, NJ: John Wiley.

15.

Enders

C. K.

Bandalos

D. L.

(2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling, 8, 430–457.

16.

Federal Interagency Forum on Aging-Related Statistics. (2012). Older Americans 2012: Key indicators of well-being. Washington, DC: U.S. Government Printing Office.

17.

Fishbein

(2000). The role of theory in HIV prevention. AIDS Care, 12, 273–278.

18.

Fishbein

Yzer

M. C

. (2003). Using theory to design effective health behavior interventions. Communication Theory, 13, 164–183.

19.

Francis

J. J.

Eccles

M. P.

Johnston

Walker

Grimshaw

Foy

… Bonetti

. (2004). Constructing questionnaires based on the theory of planned behaviour: A manual for health services researchers. Newcastle upon Tyne, England: Centre for Health Services Research.

20.

Frosch

D. L.

Legare

Fishbein

Elwyn

. (2009). Adjuncts or adversaries to shared decision-making? Applying the integrative model of behavior to the role and design of decision support interventions in healthcare interactions. Implementation Science, 4, 10. Retrieved from <Go to ISI>://000272223500002 doi:10.1186/1748-5908-4-73

21.

Frosch

D. L.

Legare

Mangione

C. M

. (2008). Using decision aids in community-based primary care: A theory-driven evaluation with ethnically diverse patients. Patient Education and Counseling, 73, 490–496. doi:10.1016/j.pec.2008.07.040

22.

Gist

M. E.

Mitchell

T. R.

(1992). Self-Efficacy: A theoretical analysis of its determinants and malleability. The Academy of Management Review, 17, 183–211. doi:10.2307/258770

23.

Gott

(2005). Sexuality, sexual health, and ageing. Maidenhead, England: Open University Press.

24.

Gott

Galena

Hinchliff

Elford

. (2004). “Opening a can of worms”: GP and practice nurse barriers to talking about sexual health in primary care. Family Practice, 21, 528–536. doi:10.1093/fampra/cmh509

25.

Gott

Hinchliff

(2003). Barriers to seeking treatment for sexual problems in primary care: A qualitative study with older people. Family Practice, 20, 690–695. doi:10.1093/fampra/cmg612

26.

Grant

Ragsdale

(2008). Sex and the ‘recently single’: perceptions of sexuality and HIV risk among mature women and primary care physicians. Culture, Health & Sexuality, 10, 495–511. doi:10.1080/13691050801948094

27.

Hardeman

Johnston

D. W.

Bonetti

Wareham

N. J.

Kinmonth

A. L.

(2002). Application of the theory of planned behaviour in behaviour change interventions: A systematic review. Psychology & Health, 17, 123–158.

28.

Hartmann

Philippsohn

Heiser

Ruffer-Hesse

. (2004). Low sexual desire in midlife and older women: Personality factors, psychosocial development, present sexuality. Menopause: The Journal of the North American Menopause Society, 11, 726–740. doi:10.1097/01.GME.0000143705.42486.33

29.

Helitzer

D. L.

LaNoue

Wilson

de Hernandez

B. U.

Warner

Roter

. (2011). A randomized controlled trial of communication training with primary care providers to improve patient-centeredness and health risk communication. Patient Education and Counseling, 82, 21–29. doi:10.1016/j.pec.2010.01.021

30.

Hinchliff

Gott

. (2011). Seeking medical help for sexual concerns in mid- and later life: A review of the literature. Journal of Sex Research, 48, 106–117. doi:10.1080/00224499.2010.548610

31.

Holman

Lorig

K. R.

(2004). Patient self-management: A key to effectiveness and efficiency in care of chronic disease. Public Health Reports, 19, 239–243.

32.

Howard

J. R.

O’Neill

Travers

. (2006). Factors affecting sexulaity in older Australian women: Sexual interest, sexual arousal, relationships and sexual distress in older Australian women. Climacteric, 9, 355–367. doi:10.1080/13697130600961870

33.

Hughes

A. K.

(2011, November). Factors influencing the views that aging women have about sexual health communication with their health care providers. Paper presented at the Eighth Annual Interdisciplinary Women's Health Research Symposium, Washington, DC.

34.

Jacoby

Revere

(2005). Sex in America. AARP The Magazine, 48, 63.

35.

Laumann

E. O.

Das

Waite

L. J

. (2008). Sexual dysfunction among older adults: Prevalence and risk factors from a nationally representative U.S. probability sample of men and women 57-85 years of age. Journal of Sexual Medicine, 5, 2300–2315. doi:10.1111/j.1743-6109.2008.00974.x

36.

Laumann

E. O.

Nicolosi

Glasser

D. B.

Paik

Gingell

Moreira

Wang

. (2005). Sexual problems among women and men aged 40-80y: Prevalence and correlates identified in the global study of sexual attitudes and behaviors. International Journal of Impotence Research, 17, 39–57. doi:10.1038/sj.ijir.3901250

37.

Laumann

E. O.

Paik

Rosen

R. C

. (1999). Sexual dysfunction in the United States: Prevalence and predictors. JAMA: The Journal of the American Medical Association, 281, 537–544. doi:10.1001/jama.281.6.537

38.

Lindau

S. T.

Leitsch

S. A.

Lundberg

K. L.

Jerome

(2006). Older women’s attitudes, behavior, and communication about sex and HIV: A community-based study. Journal of Women’s Health, 15, 747–753.

39.

Ling

D. C. Y.

Wong

W. C. W.

S. C

. (2008). Are post-menopausal women “Half-a-Man”?: Sexual beliefs, attitudes and concerns among midlife Chinese women. Journal of Sex & Marital Therapy, 34, 14–28. doi:10.1080/00926230701620522

40.

Luftey

K. E.

Link

C. L.

Rosen

R. C.

Wiegel

McKinlay

J. B.

(2009). Prevalence and correlates of sexual activity and function in women: Results from the Boston Area Community Health (BACH) survey. Archives of Sexual Behavior, 38, 514–527. doi:10.1007/s10508-007-9290-0

41.

Makoul

Clayman

M. L.

(2006). An integrative model of shared decision making in medical encounters. Patient Education and Counseling, 60, 301–312.

42.

Moreira

E. D.

Brock

Glasser

D. B.

Nicolosi

Laumann

E. O.

Paik

… Gingell

. (2005). Help-seeking behavior for sexual problems: The global study of sexual attitudes and behaviors. Journal of Clinical Practice, 59, 6–16. doi:10.1111/j.1368-5031.2004.00382x

43.

Morris

M. R

. (2013). Collaborative search revisited. Retrieved from http://research.microsoft.com/pubs/175497/morris_cscw2013_collab_search_revisited.pdf

44.

Muthen

L. K.

Muthen

B. O

. (1998–2011). MPlus user’s guide (6th ed.). Los Angeles, CA: Author.

45.

Noar

S. M.

Chabot

Zimmerman

R. S

. (2008). Applying behavior theory to multiple behavior change: Considerations and approaches. Preventive Medicine, 46, 275–280. doi:10.1016/j.ypmed.2007.08.001

46.

Nusbaum

M. R. H.

Lenahan

Sadovsky

(2005). Sexual health in aging men and women: Addressing the physiologic and psychological sexual changes that occur with age. Geriatrics, 60, 18–23.

47.

Nusbaum

M. R. H.

Singh

A. R.

Pyles

A. A

. (2004). Sexual healthcare needs of women aged 65 and older. Journal of the American Geriatrics Society, 52, 117–122.

48.

Pew. (2012). Internet use and home broadband connection. Pew Internet and American Life Project. Retrieved from http://pewinternet.org/Infographics/2012/Internet-Use-and-Home-Broadband-Connections.aspx

49.

Politi

M. C.

Clark

M. A.

Armstrong

McGarry

K. A.

Sciamanna

C. N.

(2009). Patient-provider communication about sexual health among unmarried middle-aged and older women. Journal of General Internal Medicine, 24, 511–516. doi:10.1007/s11606-009-0930-z

50.

Prairie

B. A.

Scheier

M. F.

Matthews

K. A.

Chang

C. H.

Hess

. (2011). A higher sense of purpose in life is associated with sexual enjoyment in midlife women. Menopause: The Journal of the North American Menopause Society, 18, 839–844. doi:10.1097/gme.0b13e31820befca

51.

Rhodes

Stein

J. A.

Fishbein

Goldstein

R. B.

Rotheram-Borus

M. J.

(2007). Using theory to understand how interventions work: Project RESPECT, condom use, and the integrative model. AIDS and Behavior, 11, 393–407. doi:10.1007/s10461-007-9208-9

52.

Shih

Fan

(2008). Comparing response rates from web and mail surveys: A meta-analysis. Field Methods, 20, 249–271. doi:10.1177/1525822X08317085

53.

Smith-McLallen

Fishbein

(2009). Predicting intentions to engage in cancer prevention and detection behaviors: Examining differences between Black and White adults. Psychology Health & Medicine, 14, 180–189. doi:10.1080/13548500802183575

54.

Sobecki

J. N.

Curlin

F. A.

Rasinski

K. A.

Lindau

S. T

. (2012). What we don’t talk about when we don’t talk about sex1: Results of a national survey of U.S. obstetrician/gynecologists. The Journal of Sexual Medicine, 9, 1285–1294. doi:10.1111/j.1743-6109.2012.02702.x

55.

Stokes

Mears

(2000). Sexual health and the practice nurse: A survey of reported practice and attitudes. The British Journal of Family Planning, 26, 89–92.

56.

Trompeter

S. E.

Bettencourt

Barrett-Connor

. (2012). Sexual activity and satisfaction in healthy community-dwelling older women. The American Journal of Medicine, 125, 37–43. doi:10.1016/j.amjmed.2011.07.036

57.

Tucker

L. R.

Lewis

(1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrica, 38, 1–10.

58.

Woloski-Wruble

A. C.

Oliel

Leefsma

Hochner-Celnikier

. (2010). Sexual activities, sexual and life satisfaction, and successful aging in women. Journal of Sexual Medicine, 7, 2401–2410. doi:10.1111/j.1743-6109.2010.01747.x

59.

World Health Organization. (2006). Defining sexual health: Report of a technical consultation on sexual health, 28–31 January 2002, Geneva . Geneva, Switzerland: WHO Press. Retrieved from http://www.who.int/reproductivehealth/publications/sexual_health/defining_sexual_health.pdf