HIV prevention continues to be a significant public health problem in the United States. Despite advances in HIV prevention and care, 6,465 people living in the United States died in 2015 from HIV-related illness, making it the ninth leading cause of death among those between 25 and 44 years of age (Centers for Disease Control and Prevention, 2018). Efforts to slow the spread of HIV have demonstrated mixed but overall positive results, with the incidence of HIV diagnoses declining 10% between 2010 and 2014 among specific populations (Centers for Disease Control and Prevention, 2017). Researchers from the Centers for Disease Control and Prevention (2017) have attributed the decline to (a) interventions promoting safer sex practices, (b) knowledge of individual and partner HIV status, and (c) viral-load suppression.
A recently approved pharmacological intervention, pre-exposure prophylaxis (PrEP), may be the most effective prevention tool to date. Pre-exposure prophylaxis is a once-daily pill composed of emtricitabine/tenofovir disoproxil fumarate (Truvada; Gilead Sciences, Foster City, CA). When taken as directed, PrEP can reduce the risk of HIV transmission by more than 90% (Baeten & Celum, 2012). Pre-exposure prophylaxis was approved by the U.S. Food and Drug Administration in 2012, with the Centers for Disease Control and Prevention releasing practice guidelines in 2014 (U.S. Public Health Service, 2017). The release of PrEP provided a significant step toward addressing the HIV epidemic. However, PrEP's success as an intervention tool is predicated on implementation, which can be drastically affected by either patient use/access or by health care providers being knowledgeable about PrEP and willing to prescribe it. Indeed, one barrier to PrEP efficacy has been providers not prescribing it as often as was expected (Calabrese, Krakower, & Mayer, 2017).
Studies examining the influence of clinical practice behaviors on PrEP prescription and referral within the health care setting have primarily focused on the role of the physician as the primary care provider (Hakre et al., 2016), effectively ignoring nursing practice in the clinical setting. This is a notable oversight because health system cost shifting has placed advanced practice nurses (APNs) at the forefront of clinical care in many settings, including HIV care (Institute of Medicine, 2011). Advanced practice nurses, as compared with their registered nurse counterparts, have prescriptive authority and increasingly work with underserved urban and rural populations (National Governors Association, 2012; Wishner & Burton, 2017), the very populations disproportionately affected by HIV (Reif, Safley, McAllaster, Wilson, & Whetten, 2017). Examining APN knowledge, attitudes, and practices related to PrEP would advance our understanding of opportunities to extend access to PrEP as an important biobehavioral intervention in the fight to prevent transmission of HIV.
Studies of PrEP clinical practice have examined barriers and facilitators to health care provider adoption and indicated that preliminary studies were needed to investigate how clinicians integrated clinical expertise, patient values, and current scientific evidence into the decision-making process for patients at the risk of HIV (Melnyk, Fineout-Overholt, Gallagher-Ford, & Kaplan, 2012). The PrEP protocol, as an evidence-based clinical practice, is generally expected to reduce patient morbidity and mortality, clinical site practice variation, and medical errors (Melnyk et al., 2012). Studies have identified numerous clinical practice barriers to PrEP implementation, including identification of the optimal setting for PrEP prescribing, lack of provider knowledge about PrEP, concerns about patient adherence, and sexual risk compensation (Tellalian, Maznavi, Bredeek, & Hardy, 2013). Although these studies were informative, they broadly defined health care providers, with a minority of the samples including APNs (Calabrese, Magnus, et al., 2017; Gafos, Dolling, McCormack, Desai, & Nardone, 2016). This limits the ability of researchers and public health practitioners to effectively identify and thus intervene on the specific role of nursing practice in fostering PrEP use for HIV prevention. To be effective, interventions to integrate PrEP into nursing practice require a specific understanding of factors associated with knowledge of and readiness to prescribe PrEP, specifically because it pertains to APNs.
We aimed to further advance the understanding of clinical opportunities for PrEP prescription and referral. We specifically sought to identify factors that predicted APN willingness to learn about the PrEP protocol and readiness to prescribe PrEP to patients. These findings were used to develop a short measure to assess APN readiness to prescribe PrEP, with the goal of informing and promoting future work to increase the efficacy of nursing health care providers in HIV prevention.
An exploratory, cross-sectional, study design measured knowledge, attitudes, and practice behaviors related to PrEP in APNs in Indiana. Indiana, a moderately rural midwestern U.S. state, ranks 38th of 50 states in health outcomes and determinants (United Health Foundation, 2018). Indiana has mitigated the lack of physician access with an increased number of APNs because there are only 213 physicians per 100,000 population. The number of Indiana residents per APN ranges from 839 to 26,295 per full-time APN (Sheff et al., 2014).
An online questionnaire was fielded from March 2017 to May 2017 to a random sample of 1,358 APNs drawn from the total state population of 4,733 licensed APNs with prescriptive authority; potential participants were identified through the Indiana licensure database. A power analysis identified the need for approximately 357 respondents.
A hybrid paper/online survey method was used. This included a mailed survey invitation directly addressed to each APN with a hyperlink and QR code for survey access, and a $5 USD cash preincentive. These methods mirror those described elsewhere (Agley et al., 2017). The survey link was randomly assigned to each participant to guide follow-up among nonresponders. A total of 435 participants initiated the study by the close date, representing a 32.3% contact rate. Surveys were included in the final sample used for analysis if they were at least 80% complete, yielding a final sample of 369 participants. The Institutional Review Board at the Indiana University approved all study protocols, and all participants consented to participate.
The questionnaire collected information about participant sociodemographics (age, ethnicity, gender, sexual orientation, highest degree, years of practice, and zip code), HIV knowledge, PrEP knowledge and beliefs, attitudes about evidence-based practice (EBP), readiness for EBP implementation, patient sexual risk assessment, and religiosity. A summary of survey tools and measures can be found in Table 1.
As shown in Table 1, 15 Likert-scaled items from the EBP Attitudes Scale (Melnyk, Fineout-Overholt, & Mays, 2008) measured attitudes toward adoption of EBPs; 23 items from the Survey to Assess Readiness for EBP Implementation (Stamatakis et al., 2012) measured individual stages of readiness for EBP implementation; 8 questions from the HIV Knowledge Questionnaire (Carey & Schroder, 2002) measured HIV prevention knowledge; and 5 items from the Duke University Religion Index (Hafizi et al., 2013) measured religiosity. Eleven questions were adapted from a tool to measure PrEP knowledge and awareness (Kwong, Treston, & Farley, 2015). Finally, five items from the Sexual Risk Assessment, developed by Tellalian et al. (2013), measured how frequently nurses conduct sexual health assessments with their patients.
Discriminant Function Analysis (DFA) is used to classify individuals into predetermined groups and is a multivariate analogue of analysis of variance. In addition to use in research, it has been used in a wide range of practice settings. For example, the Internal Revenue Service uses DFA to identify people they want to audit (Internal Revenue Service, 2006). Discriminant Function Analysis assumes that data represent a sample from a multivariate normal distribution, absence of multicollinearity, absence of multivariate outliers, and within-group variance-covariance matrices are equal across groups. Accordingly, three variables (Perceived Responsibility, Perceived Risk, and Metropolitan Area) were subjected to square-root transformation to reduce skewness. Log transformation was initially applied to all HIV Knowledge variables to make highly skewed distributions less skewed, but this was not effective. The eight questions were collapsed into a single variable and then dichotomized. Two multivariate outliers were deleted, but otherwise multicollinearity was not detected.
Discriminant Function Analysis was used to reveal demographic, attitudinal, community, organizational, knowledge-related, and skill-related dimensions on which the levels of readiness to prescribe PrEP differed. There were 27 independent variables (IVs) in the preliminary DFA model: 12 variables measured personal characteristics and 15 composite variables, each covering a group of unidimensional items in the questionnaire.
Discriminant Function Analysis involved two dependent or classification variables (DVs). The DV of the Model-1, Willingness to Learn PrEP, was created by integrating two survey variables with yes/no answers: (a) Before taking this survey were you aware of PrEP? and (b) Would you be interested in more information or education on PrEP focused on APNs? Consequently, the Model-1 DV consisted of three levels: (a) was aware of PrEP, (b) was not aware of PrEP but wants to learn, and (c) was not aware of PrEP and does not want to learn. Dependent or classification variable of the Model-2, Readiness to Prescribe PrEP, also consisted of three levels: (a) ready now, (b) ready within next 6 months, and (c) never be ready. Discriminant Function Analysis aimed to reveal the dimensions of 27 IVs on which the three groups of each DV differed. Unadjusted group means for IVs were compared. Wilks Lambda, eigenvalues, structure matrix loadings, classification accuracy, and group centroid plots for canonical discriminant functions were used to determine the best combination of IVs in each model.
Of the 1,358 APNs randomly selected to participate, we analyzed a final sample of 369 respondents who completed at least 80% of the survey instrument for an overall response rate of 28%. Compared with the 2015 Indiana Nursing Licensure Survey Data Report (Bowen Center for Health Workforce Research and Policy, 2016), our sample suggested that the sample closely reflected the population of APNs in Indiana (largely female Caucasian) at the time of survey administration. Descriptive results are reported in Table 2.
Of the 369 participants, only 39 (11%) had prescribed PrEP. Results of the DFA identified three groups of APNs: APNs willing to prescribe PrEP now, APNs ready to prescribe PrEP in 6 months, and APNs never ready to prescribe PrEP. Ten of the 24 original (survey) variables in the APN Readiness to Prescribe model contributed to the separation of groups of Readiness to Prescribe and also had sufficient loadings on discriminant functions. The remaining 14 variables, which did not contribute significantly to group separation, were removed from further analysis. In the final model with 10 variables, all three PrEP-related knowledge variables had weak intercorrelations (r = .328–0.457). Although most of the intercorrelations among PrEP-prescribing skills variables were weak to strong (r = .338–0.774), other intercorrelations were very weak (r < .30).
The following were loaded on the first function: sufficient knowledge about adverse effects (r = .923), sufficient knowledge about adherence (r = .639), and sufficient knowledge about PrEP clinical trials (r = .511). Loaded on the second function were frequency of asking patients about safe sexual practices (r = .547) and skills to prescribe PrEP to the following candidates: heterosexual couple in a monogamous relationship with a partner living with HIV (r = .677), injection drug user in a monogamous relationship (r = .590), gay male in a monogamous relationship with a partner living with HIV (r = .554), injection drug user who does not indicate relationship status (r = .438), gay or bisexual individual who does not indicate relationship status (r = .414), and heterosexual person who does not indicate relationship status (r = .398).
In Figure 1, group centroids for unstandardized canonical discriminant functions were used to plot Groups 1 to 3 against two discriminant functions. The first function (rc = .689) maximally separated those who were ready to prescribe now (Group 1) from the rest; whereas the second (rc = 0.494) equally separated all three groups from each other. Advanced practice nurses who were ready to prescribe PrEP now had the highest unadjusted mean for three knowledge variables: Adverse Effects (mean [M] [standard deviation (SD)] = 0.77 [0.43]); Adherence (M [SD] = 0.77 [0.43]), and PrEP Clinical Trials (M [SD] = 0.37 [0.49]). Those who would never be ready to prescribe PrEP had a mean of zero for each variable. For the remaining variables, APNs ready to prescribe in 6 months and those who were never ready had the highest and lowest means, respectively, for the frequency of asking patients about safe sexual practices (M [SD]Gr-2 = 2.85 [0.87]; M [SD]Gr-3 = 2.07 [0.96]); skills to prescribe PrEP to a heterosexual couple in a monogamous relationship with a partner living with HIV(Gr-2 = 0.95 [0.23]; Gr-3 = 0.62 [0.49]); skills to prescribe PrEP to a gay male in a monogamous relationship with a partner living with HIV (Gr-2 = 0.93 [0.25]; Gr-3 = 0.66 [0.48]); skills to prescribe PrEP to a heterosexual person who does not indicate relationship status (Gr-2 = 0.56 [0.50]; Gr-3 = 0.28 [0.46]); skills to prescribe PrEP to a gay or bisexual individual who does not indicate relationship status (Gr-2 = 0.69 [0.46]; Gr-3 = 0.38 [0.49]); skills to prescribe PrEP to an injection drug user in a monogamous relationship (Gr-2 = 0.84 [0.37]; Gr-3 = 0.48 [0.51]); and skills to prescribe PrEP to an injection drug user who does not indicate relationship status (Gr-2 = 0.81 [0.39]; Gr-3 = 0.55 [0.51]).
Using classification function coefficients, an equation was developed for each of the Readiness to Prescribe groups to assist the assignment of APNs based on their scores for 10 survey variables (Table 3). Advanced practice nurses were assigned to the group for which they obtained the highest classification score. This classification function led to 75.4% correct classification based on the discriminant variables, compared with 41% classified by chance alone (34.4% improvement). The stability of the classification procedure was checked by cross-validation in which 69.4% correct classification was revealed (28.4% improvement).
Of the APNs surveyed, 24.3% (n = 33) reported sufficient knowledge to counsel patients on the adverse effects of PrEP. A smaller fraction, 11% (n = 15), believed that they had sufficient knowledge of the PrEP clinical trials. During the previous year, 19.8% (n = 73) of APNs surveyed reported never asking their patients about safe sexual practices, compared with 13.9% (n = 51) of APNs who reported always asking patients about safe sexual practices. Although 80% (n = 312) of the survey respondents reported that they were comfortable discussing PrEP with a heterosexual couple in a monogamous relationship with a partner living with HIV, only 47.4% (n = 185) indicated that they were comfortable prescribing or discussing PrEP with a heterosexual person who did not indicate relationship status.
We focused on the identification of constructs associated with the readiness of APN to prescribe PrEP. Findings from a sample of APNs based in Indiana, USA, suggest that it is possible to predict how willing an APN is to prescribe PrEP using a 10-item questionnaire (Table 3). This measure will have application for larger samples of APNs in other geographic jurisdictions with continued validation.
We found that APNs in Indiana lacked sufficient knowledge about PrEP clinical trials, adverse effects of PrEP, and PrEP adherence. These knowledge gaps, which can influence health care delivery, may be indicative of a more global U.S. health care problem. Despite the Institute of Medicine and the American Nurses Association recognizing the importance of EBP to improve patient outcomes, 30–40% of patients not receiving services who match the appropriate standard of care, and as many as 20–25% of patients receiving harmful or unnecessary care (Maaskant, Knops, Ubbink, & Vermeulen, 2013), there remains a concerning gap in health care delivery efficacy. Barriers to EBP implementation within health care organizations include the lack of EBP knowledge and skills among clinicians and the perception that EBP is burdensome (Hauck, Winsett, & Kuric, 2013).
Advanced practice nurses who were ready to prescribe PrEP differed from their counterparts in several ways: They reported sufficient knowledge about adverse effects of PrEP, did not view patient adherence to medication regimens as a significant barrier, and already knew about the Centers for Disease Control and Prevention PrEP guidelines/clinical trials. The differences between APNs who indicated that they would be ready to prescribe in 6 months and those who indicated that they would never be ready concerned integration of sexual health assessments into clinical practice and adequate skills to prescribe PrEP to individuals who were at most significant risk of acquiring HIV. These findings were in line with research identifying that lack of clinical knowledge and concerns about patient adherence were significant barriers to PrEP uptake in the clinical setting (Bacon et al., 2017; Hakre et al., 2016), reinforcing the importance of educating clinicians about PrEP clinical guidelines and dissemination of data throughout clinical settings.
Notably, our findings revealed that APNs with prior knowledge of PrEP were more likely to be ready to prescribe it, suggesting that knowledge related to current practice standards was essential. This agreed with the literature examining the impact of continuing education on clinical practice outcomes (Su & Osisek, 2011). Our findings that lack of PrEP knowledge and discomfort conducting sexual health screenings negatively impacted PrEP prescription reflected the findings of a study by Carabez et al. (2015), who found that nurses' lack of knowledge and uneasiness regarding diverse populations, such as men who have sex with men (MSM), ultimately impacted patient care. As discussed in a study by Stewart and O'Reilly (2017), nurses possessed a wide range of attitudes toward MSM patients, and lack of education about MSM culture could ultimately lead to health disparities perpetrated by those charged with their care.
A potential pathway to engage and educate APNs about PrEP is the development of continuing nursing education (CNE) modules focused on PrEP, sexual health assessments, and HIV screening, as recommended by Kelley (2017). While CNE refers to education courses or activities that practitioners must complete to maintain registration status, not all states require annual CNE for nursing licensure. The Indiana Professional Licensing Agency requires APNs with prescriptive authority to obtain 30 CNEs annually, at least 8 of whom must focus on pharmacology (Indiana Professional Licensing Agency, 2017). However, as with CNE and other professional certification curricula, content is largely a matter of self-choice, and the mechanisms by which APNs access ongoing training and CNEs, and associated learning efficacy, are not well reported.
Identifying patients most likely to benefit from PrEP is a commonly reported concern among clinicians (Krakower et al., 2014). Men who have sex with men account for the preponderance of HIV cases in the United States, accounting for 70% of new HIV cases (Centers for Disease Control and Prevention, 2016). Our findings revealed that a large number of APNs felt comfortable discussing and prescribing PrEP for heterosexual and gay couples in serodiscordant monogamous relationships, but they reported feeling less comfortable discussing or prescribing PrEP to MSM who did not indicate a relationship status. One explanation for this finding may be a general lack of comfort integrating sexual health conversations into clinical practice. Because only 13.9% of the APNs surveyed reported always asking their patients about safe sexual practices, many patients who could benefit from a PrEP intervention might not be identified. Therefore, we suggest that providing care for MSM may not be an underlying barrier; instead, it may be discomfort providing care related to sexual health in general. Yet, many global health organizations recognize and encourage the necessary integration of sexuality into the successful promotion of health and well-being (World Health Organization, 2017). Improving knowledge about sexual health and HIV, and plans of care for those most at risk of acquiring HIV through sexual behavior (in addition to other risk factors), is an important area for further exploration.
Our study had a few limitations. First, the sample was restricted to APNs practicing in the U.S. state of Indiana. It is possible that reported practice behaviors and beliefs would be different for providers living in other states or regions. Second, we used a hybrid paper/online self-report survey method to measure our variables. Despite this limitation, studies have reported this approach to yield reliable results (Hedberg, Ceasar, & Wallace, 2013). However, participants with previous knowledge of PrEP may have been more inclined to complete the survey compared with those providers with no previous knowledge. One way to mitigate this problem in future studies would be to engage nurses in the clinical setting, using organization or department educators to disseminate surveys, or to assess PrEP knowledge, attitudes, and practices in a more global nursing assessment questionnaire. Another limitation was that only APNs were included in this sample, potentially leaving out other levels of nurses who might affect screening and assessment of at-risk patients. Finally, the preponderance of White female APNs precluded generalization of our results to other groups, including APNs of other genders and various races and ethnic groups. Despite the majority of APNs—both in Indiana and nationwide—being female, the lack of gender diversity in our sample did not allow for the exploration of an equal sample of male and female participants.
Our results suggest that the willingness of APNs to learn and their knowledge about PrEP ultimately influenced implementation of PrEP as an HIV prevention intervention. Findings demonstrated that readiness to prescribe PrEP among APNs in Indiana could be predicted with a high level of certainty using identified variables, resulting in the 10-item measure identified here. Because sexual health assessment appears to be inversely related to PrEP knowledge and prescription, gaining a better understanding of the frequency and quality of provider sexual health screening is essential. Researchers should examine the impact of sexual health screenings and provider practices related to HIV and sexually transmitted infection prevention. Furthermore, additional studies of the nursing role in PrEP uptake are needed and should include all levels of nursing preparation, such as APNs, registered nurses, and licensed practical nurses.
- Undergraduate and graduate nursing school courses should be frequently updated to reflect the rapid changes in both patient populations and advances in health care, including sexual health screening and PrEP.
- As more APNs move into the primary care setting, it is important to consider the availability and development of continuing education opportunities that reflect practices that may not be related to the provider's speciality, potentially resulting in enhanced patient care.
- More research is needed to examine how APNs network with other members of the health care team to disseminate information related to EBP; better understanding how nurses use their peers to advance individual practice could accelerate the uptake of new interventions such as PrEP.
The authors report no real or perceived vested interests related to this article that could be construed as a conflict of interest.
We would like to acknowledge the Kinsey Institute for their input, support, and collaboration.
Agley J., Meyerson B. E., Shannon D. J., Ryder P. T., Ritchie K., Gassman R. A. (2017). Using the hybrid method to survey U.S. pharmacists: Applying lessons learned to leverage technology. Research in Social and Administrative Pharmacy, 13(1), 250–252. doi:
Bacon O., Gonzalez R., Andrew E., Potter M. B., Iniguez J. R., Cohen S. E., Fuchs J. D. (2017). Brief report: Informing strategies to build PrEP capacity among San Francisco Bay Area clinicians. Journal of Acquired Immune Deficiency Syndromes, 74(2), 175–179. doi:
Baeten J., Celum C. (2012). Oral antiretroviral chemoprophylaxis: Current status. Current Opinion in HIV and AIDS, 7(6), 514–519. doi:
Bowen Center for Health Workforce Research and Policy. (2016). Data report: 2015 Indiana Nursing Licensure Survey. Retrieved from http://hdl.handle.net/1805/9688
Calabrese S. K., Krakower D. S., Mayer K. H. (2017). Integrating HIV preexposure prophylaxis (PrEP) into routine preventive health care to avoid exacerbating disparities. American Journal of Public Health, 107(12), 1883–1889. doi:
Calabrese S. K., Magnus M., Mayer K. H., Krakower D. S., Eldahan A. I., Hawkins L. A. G., Dovidio J. F. (2017). Support your client at the space that they're in: HIV pre-exposure prophylaxis
(PrEP) prescribers' perspectives on PrEP-related risk compensation. AIDS Patient Care and STDS, 31(4), 196–204. doi:
Carabez R., Pellegrini M., Mankovitz A., Eliason M., Ciano M., Scott M. (2015). Never in all my years…: Nurses' education about LGBT health. Journal of Professional Nursing, 31(4), 323–329. doi:
Carey M. P., Schroder K. E. (2002). Development and psychometric evaluation of the brief HIV Knowledge Questionnaire. AIDS Education and Prevention, 14(2), 172–182. doi:
Gafos M., Dolling D., McCormack S., Desai M., Nardone A. (2016). Healthcare providers' knowledge of, attitudes to and practice of pre-exposure prophylaxis
for HIV infection. HIV Medicine, 17(2), 133–142. doi:
Hafizi S., Memari A. H., Pakrah M., Mohebi F., Saghazadeh A., Koenig H. G. (2013). The Duke University Religion Index (DUREL): Validation and reliability of the Farsi version. Psychological Reports, 112(1), 151–159. doi:
Hakre S., Blaylock J. M., Dawson P., Beckett C., Garges E. C., Michael N. L., Okulicz J. F. (2016). Knowledge, attitudes, and beliefs about HIV pre-exposure prophylaxis
among US Air Force Health care providers. Medicine, 95(32), e4511. doi:
Hauck S., Winsett R. P., Kuric J. (2013). Leadership facilitation strategies to establish evidence-based practice in an acute care hospital. Journal of Advanced Nursing, 69(3), 664–674. doi:
Hedberg E., Ceasar G., Wallace D. (2013). The effect of survey mode on socially undesirable responses to open ended questions: Online vs. paper instruments. Paper presented at the The American Association for Public Opinion Research 68th Annual Conference in Chicago, Illinois United States.
Indiana Professional Licensing Agency. (2017). Information and application pertaining to prescriptive authority for advanced practice nurses
. Retrieved from https://www.in.gov/pla/2503.htm
Krakower D., Ware N., Mitty J., Maloney K., Mayer K. (2014). HIV providers' perceived barriers and facilitators to implementing pre-exposure prophylaxis
in care settings: A qualitative study. AIDS and Behavior, 18(9), 1712–1721 1710p. doi:
Maaskant J. M., Knops A. M., Ubbink D. T., Vermeulen H. (2013). Evidence-based practice: A survey among pediatric nurses and pediatricians. Journal of Pediatric Nursing, 28(2), 150–157. doi:
Melnyk B. M., Fineout-Overholt E., Gallagher-Ford L., Kaplan L. (2012). The state of evidence-based practice in US nurses: Critical implications for nurse leaders and educators. Journal of Nursing Administration, 42(9), 410–417. doi:
Melnyk B. M., Fineout-Overholt E., Mays M. Z. (2008). The evidence-based practice beliefs and implementation scales: Psychometric properties of two new instruments. Worldviews on Evidence Based Nursing, 5(4), 208–216. doi:
Reif S., Safley D., McAllaster C., Wilson E., Whetten K. (2017). State of HIV in the US Deep South. Journal of Community Health, 42(5), 844–853. doi:
Stamatakis K. A., McQueen A., Filler C., Boland E., Dreisinger M., Brownson R. C., Luke D. A. (2012). Measurement properties of a novel survey to assess stages of organizational readiness for evidence-based interventions in community chronic disease prevention settings. Implementation Science, 7, 65. doi:
Stewart K., O'Reilly P. (2017). Exploring the attitudes, knowledge and beliefs of nurses and midwives of the healthcare needs of the LGBTQ population: An integrative review. Nurse Education Today, 53, 67–77. doi:
Su W. M., Osisek P. J. (2011). The Revised Bloom's Taxonomy: Implications for educating nurses. Journal of Continuning Education in Nursing, 42(7), 321–327. doi:
Tellalian D., Maznavi K., Bredeek U. F., Hardy W. D. (2013). Pre-Exposure Prophylaxis
(PrEP) for HIV infection: Results of a survey of HIV healthcare providers evaluating their knowledge, attitudes, and prescribing practices. AIDS Patient Care and STDs, 27(10), 553–559. doi:
Keywords:© 2019 Association of Nurses in AIDS Care
advanced practice nurses; HIV prevention; pre-exposure prophylaxis