Seroconversion Risk Perception Among Jail Populations

Abstract

The prevalence of HIV/AIDS infection among prisoners is 3 to 4 times higher than in the U.S. population. Given that one in seven HIV-positive Americans pass through a correctional facility every year, the criminal justice system is in an ideal position to aggressively implement effective HIV education, treatment, and prevention. This study examines barriers to the effective delivery of these services and evaluates differences in risk perception among nearly 600 female and male inmates. The results underscore gender differences in Perceived Risk of Seroconversion and Exposure to HIV Education, suggesting that jails should implement gender-specific HIV prevention programming.

Keywords

HIV/AIDS HIV education HIV prevention inmates gender-specific

More than three decades have passed since HIV/AIDS cases were first documented among incarcerated populations in the United States. National data suggest that HIV/AIDS prevalence rates among prisoners remain disproportionately higher than rates among the general U.S. population—1.9% of female prisoners and 1.5% of male prisoners were either HIV positive or had confirmed AIDS at year-end 2008 (Maruschak, 2009). Experts believe that most HIV-positive individuals enter the corrections system already with HIV and do not acquire it during incarceration. Instead, individuals entering correctional facilities frequently come to the attention of the criminal justice system for drug addiction, particularly for intravenous drug use (IDU). At the same time, inmates also self-reported high levels of High-Risk Sexual Behaviors, which manifest differently by gender (Abiona, Balogun, Adefuye, & Sloan, 2009). For example, incarcerated women exhibit a higher prevalence of inconsistent condom use and sex with multiple partners, including other IDUs (Collica, 2002; Mullings, Marquart, & Brewer, 2000). Research with women suggests that many of the pathways to female incarceration, such as drug use, prostitution, and multiple incidents of sexual and physical abuse, also contribute to increased HIV seroprevalence rates for women (DeGroot, 2001; Lanier & Paoline, 2005). Sexual encounters with other IDUs and being an intravenous drug user were found to be the most common route of HIV acquisition among female inmates (Magura, Kang, Shapiro, & O’Day, 1993; Mullings, Marquart, Carr, & Hartley, 2004), who are more likely to contract HIV than they are to transmit the virus to others (Shilling et al., 1994).

While researchers have established that most people acquire HIV on the streets outside of prison (Macalino et al., 2004), one study examined a group of men who were thought to have acquired HIV during incarceration and compared these men to a small number of matched controls in the community (Krebs & Simmons, 2002). Men who acquired HIV while incarcerated usually contracted the virus through male-to-male sex behaviors, which is the same primary way that men in the community acquired HIV.

Reducing HIV Among Targeted Populations

About 14% of the total HIV-positive population in the United States is estimated to pass through correctional facilities every year (Spaulding et al., 2009). IDUs are also arrested and imprisoned at a high rate, and may spend up to 70% of their drug-using years incarcerated. There are more IDUs in the criminal justice system than in drug treatment, health care, or social service facilities combined (Swartz, Lurigio, & Weiner, 2004). Correctional facilities thus offer a prime opportunity for HIV intervention. Correctional administrators have improved their response over time by making HIV testing more accessible (Hammett, Kennedy, & Kuck, 2007), offering preventive vaccinations and prophylactic medication regimens to prevent opportunistic infections, providing more programming and education about how HIV is transmitted, and conducting prerelease planning for inmates (DeGroot, Dilorenzo, Sylla, & Bick, 2006). Offering HIV prevention while incarcerated would potentially save US$3 million for every US$1 million spent (Kahn, 1996), yet only 5% of city and county jails and 10% of federal correctional facilities have implemented comprehensive programs to reduce HIV transmission among inmates (Swartz et al., 2004).

Drug treatment has been proposed as one way to reduce the rate of HIV acquisition among female inmates; however, the research on the efficacy of this intervention strategy is divided. Mullings, Marquart, Carr, and Hartley (2004) found that IDUs who received drug treatment were less likely to share needles or inject drugs, and engaged in less high-risk sexual behaviors including multiple sexual partners, sex under the influence of drugs, and trading sex for money or drugs. Alternatively, Latka (2003) and Semann, Des Jarlais, and Marlow (2006) found that such intervention tactics have been fruitful in reducing drug behaviors, but did not reduce high-risk sexual behaviors.

HIV/AIDS education programming in jail settings has become an important part of HIV prevention and harm reduction, but the issue is complex. Researchers expressed concern that early HIV/AIDS education programs merely dispersed HIV/AIDS information or used fear to attain behavioral change, despite empirical evidence that HIV/AIDS knowledge among incarcerated populations was already quite high (Alarid & Marquart, 1999). Hogan (1994) emphasized that using fear is ineffective among inmates who have already displaced fear of repercussions in order to commit crime. In fact, early HIV/AIDS education curriculums were not significantly correlated to reducing high-risk behaviors among those incarcerated (Alarid & Marquart, 1999; Dolan, Woodak, & Penny, 1995; Nyamathi, Bennett, Leake, Lewis, & Flaskerud, 1993; Swartz et al., 2004). Since that time, correctional programs have been retooled. For example, Project START is the only education intervention program specific to correctional facility settings that has been approved by the Centers for Disease Control and Prevention (CDC). However, Project START targets men between 18 and 29 years old who are reentering the community from prison (CDC, 2004).

Perceptions of Risk

Gender, along with impulsive decision making, condom usage, and number of sexual partners, is significantly correlated with risk perception of HIV (Mehrotra, Noar, Zimmerman, & Palmgreen, 2009). On one hand, men’s perceptions of risk of HIV seroconversion is tied more to IDU and sharing drug paraphernalia (Mitchell & Latimer, 2009). Women, on the other hand, are significantly more likely to perceive risk of HIV seroconversion and pregnancy in casual relationships, and risk perception decreases as relationships transition from casual to monogamous. Among adolescent and young adults, this transition takes approximately 3 weeks and leads to a shift from barrier method safer sex practices to hormonal contraception reliance (Fortenberry, Tu, Harezlak, Katz, & Orr, 2002), leaving these women vulnerable to disease. This suggests that women may engage in risky behaviors, yet perceive themselves to be at a low risk for acquiring HIV/AIDS (Brown, Outlaw, & Simpson, 2000; Collica, 2002; Mullings et al., 2004). HIV/AIDS misconceptions seem to play an integral part in behavior modification. If one believes that HIV/AIDS may be transmitted through casual contact, they may be less willing to make difficult behavior changes to reduce their risk for acquiring HIV (Nyamathi et al., 1993).

Based on prior empirical studies regarding seroconversion differences among male and female incarcerated populations, this article seeks to examine how inmates perceive HIV/AIDS risk by gender, as well as factors associated with risk perception, including (1) transmission misconceptions, (2) Transmission Knowledge, (3) HIV/AIDS awareness, (4) past or current IDU, (5) high-risk sexual behaviors, and (6) Health Condition at the time of arrest.

Method

Survey data were collected from 608 male and female inmates in a county jail complex in a large urban area of Texas. Respondents for this study were selected in a two-step process. First, living area pods, each containing 40 to 50 inmates, were selected at random. All inmates within each randomly selected pod were given the opportunity to voluntarily participate. Obtaining a list of individuals was not possible due to constant location changes and unanticipated appointments that were common to daily jail operations.

After consent was obtained, questionnaires and pencils were distributed to participants and self-administered within their cells. Researchers were available as needed to provide question clarification, or to read survey questions aloud to illiterate participants in a private room out of hearing of officers and other inmates. Thirteen surveys were not used due to too many incomplete responses (defined as 40% or more of the survey left blank), so the final sample size yielded 595 surveys. Surveys were aggregated and did not contain individual identifying data.

Table 1.

Sociodemographic Characteristics.

Characteristic	Female (n = 260)	Male (n = 335)
Age
17–24	15.2%	24.2%
25–32	34.6%	31.5%
33–40	37.7%	27.3%
41 and over	12.5%	17.0%
M	32.8	32.0
Median	33	31
Race/ethnicity
African American	59.3%	45.5%
Mexican American	22.5%	20.9%
Caucasian	17.1%	28.5%
Other	1.2%	5.2%
Education
8th and below	12.6%	9.6%
9th–11th grade	33.6%	39.2%
12th grade	26.9%	24.7%
Some college	26.9%	26.5%
GED	32.6%	44.0%
Marital status
Never married	38.7%	44.8%
Married	23.8%	29.0%
Separated	15.6%	9.6%
Divorced	19.1%	14.2%
Widowed	2.7%	2.5%
Children
None	15.2%	29.2%
1–3 children	66.1%	59.3%
4 or more children	18.7%	11.5%
M	2.19	1.59
Median	2	1
Legal monthly income
Less than $1,000	34.6%	33.1%
$1,001–$2,000	24.6%	24.6%
$2,001–$3,000	13.3%	13.4%
$3,001–$4,000	7.9%	10.8%
$4,001 and more	19.6%	18.0%

Note. GED = general equivalency diploma.

Table 2.

Criminal Background.

Characteristic	Female (n = 260)	Male (n = 335)
Prior adult confinement
Jail	76.0%	82.9%
Prison	18.3%	45.7%**
Total misdemeanor convictions
None	30.0%	17.0%**
1–3	52.2%	53.1%**
4 or more	17.9%	29.9%**
Total felony convictions
None	7.9%	4.9%
1	53.5%	39.5%
2 or more	38.6%	55.6%
Current offense type
Narcotics/drugs	39.4%	20.5%
Theft/burglary/fraud	26.0%	26.4%
Assault/robbery/murder	12.3%	26.5%
Driving while intoxicated	5.5%	10.5%
Prostitution	8.1%	1.1%
Sexual offense	.5%	7.1%
Other	7.2%	7.9%

Note. **p < .01.

Measures

The dependent variable for the study was an individual’s perceived risk of seroconversion, which was created by combining two ordinal-level questions: (1) “Based on your past behavior, what are your chances of having the AIDS virus?” and (2) “Based on what you know about AIDS and your current lifestyle, what are your chances of ever getting the AIDS virus?” The four possible responses to each of these questions were the same and coded as follows: 0 = no chance, 1 = low chance, 2 = medium chance, and 3 = high chance. When the responses to the two questions were summed, they ranged from 0 to 6, where a score of “0” indicated no chance and “6” indicated a high likelihood of seroconversion risk. Perceived risk of seroconversion yielded a Cronbach’s reliability coefficient of .83.

Six independent variables examined the effect of HIV/AIDS transmission myths, HIV/AIDS transmission knowledge, IDU, sexual risk behaviors, HIV/AIDS education from a health professional, and health condition at time of arrest.

Seroconversion myths

An individual’s misconceptions regarding HIV/AIDS seroconversion were measured using the following two questions: (1) “What is the likelihood that you could get AIDS by living in the same tank with someone else who has AIDS?” and (2) “What is the likelihood that you could get AIDS by kissing (exchanging saliva) someone else with AIDS?” For each of these questions, there was either an incorrect response (coded as “0”) or a correct response (coded as “1”). The summated score ranged from 0 to 2, such that a score of “0” indicated two incorrect answers, “1” meant that one answer was correct and one incorrect, and “2” indicated that both responses were correct. The Cronbach’s reliability coefficient for this scale was .66.

Seroconversion knowledge

The accuracy of an individual’s knowledge about HIV/AIDS transmission was coded so that (like the previous variable) a score of “0” indicated an incorrect answer and a score of “1” indicated a correct answer. This 3-item summated scale combined the following three nominal-level variables: (1) “HIV can be passed by having sex,” (2) “A pregnant woman can pass AIDS on to her baby,” and (3) “AIDS can lead to death.” The Cronbach’s reliability coefficient for the transmission knowledge scale was .66.

Exposure to HIV education

The degree to which HIV education made a difference for at-risk individuals was made into an index from the following two variables: (1) “Have you ever taken an AIDS/HIV awareness class?” and (2) “Have you ever talked to a doctor or counselor about the transmission of AIDS?” The Cronbach’s reliability coefficient was .60.

IDU behaviors

This index was comprised of two nominal-level questions that asked the respondent to report IDU behaviors exhibited within the last 12 months: (1) “Shared needles with friends?” and (2) “Used drugs intravenously?” This 2-item scale was summated so that a score of 0 indicates very low drug use and a score of 2 indicates very high drug use. The index created from these variables yielded a Cronbach’s coefficient of .60.

High-risk sexual behaviors

Four questions asked about potentially risky sexual behaviors in which the respondent reported engaging in within the last 12 months: (1) “Paid someone to have sex with you?” (2) “Been paid to have sex?” (3) “Had more than one sexual partner?” and (4) “Had unprotected sex?” While recognizing that the level of risk was not necessarily the same for each of these behaviors individually and that we did not ask for the number of times the individual engaged in each behavior, we obtained proxy measures of risk based on engagement in high-risk behaviors at least once over the last year. Each question was coded as 0 indicated no and “1” indicated yes with the summed score ranging from 0 to 4. The Cronbach’s coefficient for this scale was .62.

Health condition

Three ordinal-level items were combined to assess the individual’s self-reported health at the time of most recent arrest. The first question asked the individual to rate his or her overall health: (1) “How would you rate your health at the time when you were arrested?” Possible responses and accompanying codes were 1 = excellent, 2 = very good, 3 = good, 4 = fair, and 5 = poor. The next two questions were based on the correlation between health condition and number of sick days, as well as health and number of doctor visits, on the premise that a healthy person will generally have fewer sick days and doctor visits than a person in fair or poor health. Since socioeconomic status and lack of health insurance may affect ability to visit a doctor, we also asked about number of sick days in which the individual was so physically ill he or she was unable to leave the house or bed. Whether that reason was drug use, allergies, or a virus, we considered them all simultaneously with the following questions: “In the last 12 months before you got to jail, how many ‘sick days’ have you had when you were confined to your house or bed because of illness?” (1 = none; 2 = 1 to 7 days; 3 = 8 to 30 days; 4 = 31 days and over) and “In the last 12 months before you got to jail, how many times have you been to see a doctor for a physical illness?” (1 = none; 2 = 1 to 5 times; 3 = 6 to 10 times; 4 = more than once per month). Summed scores ranged between 3 and 13, with higher scores indicating poorer overall health. The Cronbach’s coefficient for this scale was .63.

Sample

Sociodemographics

According to Table 1, of the 595 inmates who participated in this survey, 44% were female and 56% were male. The mean age was 33 years old among female respondents and 32 among male respondents. With respect to income, one third of women and men respondents earned less than US$1,000 per month, while one fourth earned between US$1,001 and US$2,000 per month. Most men (59%) and women (66%) inmates claimed to have one to three children under the age of 18. The race/ethnic composition of the women was 59% African American, 23% Latino/Mexican American, 17% Caucasian, and 1% identified as member of other racial categories. Among male participants, 45.5% were African American, 21% were Mexican American, 28.5% were Caucasian, and 5% were of other racial categories. Looking at marital status, 39% of women and 45% of men had never married, while 24% of female and 29% of male respondents were married at the time of survey completion. In terms of educational attainment, 46% of female and 49% of male respondents did not earn a high school degree, while 33% of female and 44% of male respondents reported earning a general equivalency diploma (GED). An examination of national data of the jail population suggests that the sample data are comparable with respect to age, race/ethnicity, educational attainment, and earnings prior to arrest. The sample included more women than in the larger jail population, and more sample respondents were married than you might find nationally.

Criminal background

According to Table 2, the male and female samples differed significantly from each other with respect to type of pending charges, with female inmates significantly more likely to be arrested on drug charges. The female inmates who participated in this study also were less likely to report prior adult confinement and to have a lower quantity of felony and misdemeanor convictions than male participants.

To effectively assess the effect of gender on Perceived Risk, this study employed bivariate analysis and multiple linear regression, which separated the population by sex into three distinct models that can be found in Table 3. The collective model included both male and female inmates for a broad view of how Seroconversion Myths, transmission knowledge, IDU, health condition, exposure to HIV education, high-risk sexual behaviors, and gender affect perceived risk of seroconversion. The next two regression models separate the sample by gender.

Table 3.

Linear Regression: Predictors of Risk Perception of HIV.

	Unstandardized b (SE) Standardized β
Variable	Collective Model	Female Model	Male Model
Seroconversion myths	.558 (.087) .024	.200 (.120) −.077	.092 (.126) 093
Transmission knowledge	.305 (.093) .071	.154 (.152) .084	.623 (.120) .027
IV drug use	.000 (.136)** .171	.001 (.193)** .209	.009 (.192)** .148
Health condition	.001 (.142)** .129	.511 (.045) .039	.001 (.044)** .179
HIV education exposure	.008 (.086)** .108	.006 (.126)* .170	.154 (.117) .078
High-risk sexual behaviors	.000 (.063)** .337	.000 (.089)** .349	.000 (.088)** .339
Gender	.013 (.142)** .100	—	—
Constant	−.194 (.591)	−.021 (.526)	−.081 (.454)
Adjusted R²	.224	.260	.200

Note. IV = intravenous.

*p < .05. **p < .01.

Findings

According to Table 3, for both men and women inmates in jail, perceived risk of seroconversion shared a significant, positive relationship with exposure to HIV education. This finding suggests that inmates who were exposed to more formal HIV/AIDS education were more likely to rate themselves as being at a higher risk based on past and current behavior than were individuals who received little or no HIV education. While exposure to HIV education was significant for both genders, it dropped out when men were examined separately, thus reducing its importance for men. Exposing women to HIV education seemed to make a greater difference in self-reflection that her behavior influences the likelihood that she has HIV. The study results also suggest that health condition is a significant predictor of perceived risk of seroconversion for the men in this study, but not for the women.

In all three models, high-risk sexual behaviors and IDU both share positive, statistically significant relationships with an individual’s perceived risk of seroconversion. According to this finding, men and women inmates who have engaged in these behaviors that are most often linked with seroconversion are most likely to perceive themselves as having a greater chance of HIV. Further, the β weights associated with each model suggests that the effect of high-risk sexual behaviors on Perceived Risk does not vary greatly for men and women. With respect to IDU, the relationship with perceived risk is slightly stronger for women than for men inmates.

Finally, Table 3 showed that neither transmission knowledge nor Seroconversion Myths had a relationship with perceived risk of seroconversion for men or women. While female inmates possessed a more accurate understanding of HIV/AIDS and seroconversion myths than their male counterparts, this knowledge did not seem to affect their perceived risk of seroconversion. About one fourth of the total variance in female inmate’s perceived risk of seroconversion was explained by the independent variables, while for men the explained variance was just under 20%.

Discussion

Over the last decade, worldwide public health campaigns have been more effective in reaching populations most at risk with prevention, outreach, and treatment advances. However, most corrections-based HIV/AIDS education in the United States implements a “one-size-fits-all” approach (Keeton, 2004; Swartz et al., 2004). Results of the current study underscore gender differences in perception that persist among inmates with respect to perceived risk of seroconversion and access to HIV education. One of the main findings was that HIV education made a greater difference in women’s self-reflection of their behavior than it did with men. These findings, coupled with how women become HIV positive, indicate a need to devise gender-specific programming (Abiona et al., 2009).

Merely presenting HIV/AIDS information and recommendations for behavior change is an ineffective teaching strategy, irrespective of gender, age, and criminal background (Hogan, 1994; Magura, Sung-Yeon, Shapiro, & O’Day, 1995; Nyamathi et al., 1993). Early attempts to craft a more effective educational model different by gender have been met with mixed results. Magura, Sung-Yeon, Shapiro, and O’Day (1995) implemented an educational model for female IDUs that was steeped in problem-solving theory and divided into four distinct group sessions. These women participated in discussions and role-play activities that not only emphasized the dangers of HIV/AIDS but also taught strategies designed for real-world situations. Postintervention follow-up suggested the female participants exhibited no behavior change as a result of this intervention, despite having positively evaluated the program upon completion. An intervention targeting nonincarcerated adolescent girls aged 11 to 14 years old reported similarly positive results with respect to HIV/AIDS knowledge, enjoyment of abstinence and condoms, and sexual assertiveness (Di Noia & Schinke, 2007).

The correct and consistent use of condoms during intercourse and clean needles for IDU has long defined HIV/AIDS education and public health policy. Though women may implicitly understand the health benefits of condom use, they may find themselves powerless to implement this safer sex practice without the support of their partner. Due to the high variability of enforcing condom use, inmates require more than a simple cause-and-effect understanding of HIV prevention through condom use. Swartz, Lurigio, and Weiner (2004) recommended that female participants receive instruction in condom negotiation strategies to aid in successful behavior modification. Yet for drug-using women, instruction in condom negotiation strategies may be an inefficient use of resources. These women, along with female sex workers, often report a lack of decision-making power in sexual relationships. IDUs and female sex workers engage in high-risk sexual behaviors and are in need of alternatives to the traditional prescription of condom use. For these women, information regarding potentially clandestine barrier methods (e.g., female condom, cervical cap, microbicides) could not only reduce the rate of HIV seroconversion but also prevent a number of unwanted pregnancies in drug-using women (Gollub, 2008).

Another successful intervention known as Project Wall Talk led to a marked increase in both HIV/AIDS knowledge and in HIV testing. Using just 590 peer educators, this intervention successfully diffused HIV/AIDS education to 2,506 students housed within 36 Texas state prison units. Based on projected calculations, the 243 peer educators who participated in the follow-up would have between 84,000 and 154,000 annual opportunities to discuss HIV with students. Further, peer educators reported sharing similar information with nonincarcerated family and friends via telephone at a projected rate of 398 annual opportunities of knowledge diffusion among individuals at risk for incarceration (Ross, Harzke, Scott, McCann, & Kelley, 2006). In 2000, Planned Parenthood of New Mexico implemented Woman to Woman: Coming Together for Positive Change, which focused on empowering women living in low-income areas. A unique feature of this project was the recognition of how gender inequality in low-income populations put women at risk for contracting HIV/AIDS. Posttest results showed participants gained confidence and skills (Romero et al., 2006).

Motivational interviewing has been shown to be another successful way to give women confidence, particularly to address the gender inequality expressed through intimate partner violence. Violent victimization may limit women’s power to negotiate safe-sex practices (El-Bassel et al., 1998) and increase their high-risk drug use (Harvey et al., 1998; Rhodes, Singer, Bourgois, Friedman, & Strathdee, 2005). A recent study tested the efficacy of motivational interviewing in HIV interventions and found that motivational interviewing decreased high-risk sexual behaviors, but had a lesser effect on high-risk drug use (Weir et al., 2009). This may be due to the unstandardized definition of “needle sharing.” Some injection drug users do not classify sharing needles with family and friends as “needle sharing,” a label reserved for high-risk drug use (Hogan, 1994). Because of this, IDUs may be receptive to instruction and score well on a knowledge assessment, only to share needles with a friend or family member at their next opportunity. Curricula not designed with this limitation in mind may not only ineffectively communicate the dangers of needle sharing to an at-risk group most in need of such information but may also increase the false security felt from sharing needles with relatives and friends.

The notion that HIV/AIDS transmission among incarcerated populations poses no risk to the greater community is yet another misconception perpetuated despite evidence to the contrary. Once HIV-infected inmates are released, they return to their communities and often engage in high-risk drug use and sexual behaviors with their nonincarcerated counterparts (Spaulding et al., 2002). HIV interventions can be effectively used in jail just before community reentry to interrupt the return to old behaviors during the transition from a behavior-restricted environment to the freedom of the outside world. A multisite, randomized trial found that a DVD-based intervention was significantly correlated with a decrease in high-risk sexual behaviors among reentry offenders within 90 days of release (Martin, O’Connell, Inciardi, Suratt, & Maiden, 2008).

The findings of the current study may be difficult to generalize to other regions of the United States or to other countries where public health policies are very different. Within the United States, Texas, Florida, and New York together hold approximately 46% of the HIV-positive or AIDS-confirmed state custody population (Maruschak, 2009), so a change in policy in just one of these three states could be significant. On the other hand, perhaps the HIV knowledge and risky behaviors exhibited by inmates housed in these three states are accordingly disproportionate. Future studies should examine the gender difference of HIV education among jail and prison populations on a national level. This might allow more localized studies to more accurately generalize findings to a greater population. Some of the questions could have been more specific, such as the general question, “What is the likelihood that you could get AIDS by living in the same tank with someone else who has AIDS?” The number of sick days should have specified between drug use/withdrawal and viruses/allergies. Our research might also have benefited from detailed information regarding the structure and quality of those HIV education programs that the inmates in this sample received.

In conclusion, an evidence-based approach should be taken to evaluate the current state of HIV programs and to assess the impact of small modifications to programs that are already in place (DeGroot et al., 2006). In the United States, primary funding for HIV intervention and prevention comes from the Ryan White Care Act. This act allows funding to be used for reentry preparation of incarcerated populations (DeGroot et al., 2006). Behavioral intervention and HIV prevention programs in U.S. jails and prisons may wish to examine alternative funding streams from the CDC, or link HIV programs to the government’s obligation to provide safer prison environments while incarcerated as well as safer practices upon community reentry.

Footnotes

Declaration of Conflicting Interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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