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. Author manuscript; available in PMC: 2023 Jun 1.
Published in final edited form as: AIDS Care. 2021 May 3;34(6):708–716. doi: 10.1080/09540121.2021.1922576

Student Characteristics and Substance Use as Predictors of Self-Reported HIV Testing: The Youth Risk Behavior Survey (YRBS) 2013 – 2015

Angulique Y Outlaw 1, Blair Turner 2, Rachel Marro 2, Monique Green-Jones 1, Gregory Phillips II 2
PMCID: PMC8563506  NIHMSID: NIHMS1701249  PMID: 33938333

Abstract

Many adolescents and young adults (AYAs; ages 13 – 24) are unaware of their HIV status despite participating in behavior that places them at risk for contracting HIV. This study examined possible predictors of self-reported HIV testing for high school students (grades 9 to 12) who completed the Youth Risk Behavior Survey (YRBS). Three sex-stratified, stepwise multivariable logistic models were used to estimate odds of having received a HIV test being associated with student characteristics and substance use. The likelihood of being tested for HIV was associated with students who were a racial/ethnic minority and age 18 and older. HIV testing was also associated with male students who reported same sex partners (males) or same sex partners (males) and different sex partners (females). Female students who reported same sex partners (females) and different sex partners (males) were more likely to have been tested for HIV. Male and female students were more likely to have been tested for HIV if they reported illicit drug and/or marijuana use, while prescription drug use was also associated with HIV testing for female students. Knowledge of the predictors of HIV testing for adolescents can guide efforts for the effective scale up of testing for this vulnerable population.

Keywords: Adolescents, Students Demographics, Sexual Behavior, Substance Use, HIV Testing

Introduction

Adolescents and young adults (AYAs; ages 13 – 24) are the fastest growing group of individuals living with HIV infection (Center for Disease Control and Prevention: CDC, 2018a; CDC, 2018b). In 2018, AYAs made up 21% of all new HIV diagnoses in the United States, with the majority of new HIV infections occurring in sexual minority adolescent and young men of color who have sex with men (MSM) (CDC, 2018b). Routine HIV testing is recommended for individuals ages 13 to 64, yet HIV testing among AYAs remains low (U.S. Preventive Services Task Force, 2013; Branson et al., 2006). Pooled data (2009 – 2011) from the Youth Risk Behavior Survey (YRBS), a national school-based health risk survey conducted biennially among students in grades 9 to 12, indicated that self-reported HIV testing was 22% (Van Handel et al., 2016; CDC, 2018c). This is concerning given HIV testing is a key strategy for addressing HIV infection among AYAs (CDC, 2018b; Coeytaux et al., 2014).

Adolescence and young adulthood are developmental periods where spontaneous and unplanned behavior (e.g., unplanned sexual behavior, experimentation with alcohol and illicit drugs, etc.) are common (Coeytaux et al., 2014; Straub et al., 2011; Gao et al., 2017). Nonetheless, many sexually experienced AYAs engaging in behavior that places them at risk for HIV (e.g., condomless sex, substance use prior to sexual behavior) do not believe that they are at risk for contracting HIV (Adebayo & Gonzalez-Guarda, 2017; Peralta et al., 2007). Concrete thinking and limited emotional processing during these developmental periods can lead to an inability to perform a proper risk appraisal (Henry-Reid & Martinez, 2008; Naswa & Marfatia, 2010). Limited sexual health knowledge can also lead to an underestimation of personal infection risk (Balaji et al., 2012; Martin & Schackman, 2013).

Individual characteristics have been associated with HIV testing for AYAs. HIV testing occurs more frequently in female than male AYAs (Peralta et al., 2007; Decker et al., 2015; Talib et al., 2013). Furthermore, AYAs who identify as sexual minorities (e.g., MSM, lesbian, bisexual, transgender, etc.) are more likely to be tested for HIV than AYAs who identify as heterosexual (Straub et al., 2011; Hall et al., 2012; Moyer et al., 2007) and Black/African American AYAs are more likely to be tested for HIV than other racial/ethnic AYAs (Balaji et al., 2012; Rakhmanina et al., 2014; Whitmore et al., 2013). Finally, the likelihood of testing for HIV increases with age (Decker et al., 2015; Talib et al., 2013; Rakhmanina et al., 2014). Examining the relationship between individual characteristics and HIV testing for AYAs can provide information about predictors of HIV testing and subsequent guidance for effective intervention.

Substance use (e.g., alcohol and illicit drug use) has been associated with HIV testing for AYAs (Adebayo & Gonzalez-Guarda, 2017; Balaji et al., 2012). Pooled data from YRBS (2005 – 2011) suggested that HIV testing was positively associated with substance use ( among sexually experienced high school students (Coeytaux et al., 2014). However, literature also suggests that substance use is not associated with HIV testing for AYAs (Gao et al., 2017; Tolou-Shams et al., 2007). Therefore, the relationship between substance use and HIV testing for AYAs requires additional investigation.

HIV testing for AYAs should be prioritized given HIV infection rates for this population (CDC, 2018b). This is particularly recommended for high school age adolescents given adolescence is a period marked by sexual debut and risk behavior. This study examines high school student characteristics and substance use as predictors of self-reported HIV testing.

Methods

Data Source

The YRBS is a biennial national survey conducted by the CDC since 1991 to collect data on health behaviors (alcohol use, drug use, sexual behaviors, etc.) from students in grades 9 to 12 (Brener et al., 2013; Kann et al., 2016). For this study, data from local versions of the YRBS, which were administered on a state, territorial, tribal, and large urban school district level by the departments of education or health rather than on a national scale was used. In this implementation, jurisdictions use a two-stage cluster sample design to identify a sample of students (CDC, 2016). In the first stage, schools were selected with a probability proportional to their enrollment; in the second stage, classes of a required subject or during a required period were randomly selected, and all students within the classes were eligible to participate. A new sample was selected in this manner each year that the survey was administered.

Analytic Sample

Local YRBS data were pooled across multiple jurisdictions (states and large urban school districts). The entire dataset consisted of 47 jurisdictions across 6 time points, and 541,410 students. There was a total of 98 jurisdiction-years (i.e., distinct surveys administered by a particular jurisdiction in a specific year). The present analysis uses 2013 – 2015 data from 35 jurisdictions which included questions about sexual behavior and HIV testing. Students were excluded if they were missing any of the primary characteristic variables of interest (i.e., race/ethnicity: 3.3%; sex: 0.8%; age: 0.3%; sexual behavior: 12.1%; and HIV testing: 32.7%; not mutually exclusive), resulting in a sample of 105,147 students.

The study was submitted to the Northwestern University IRB and received a designation of exempt. The study was based in secondary data analysis of fully de-identified data, therefore, informed consent was not required or obtained.

Measures

Student Characteristics

Sex.

Students were asked, “What is your sex?” Response options were “Female” and “Male.”

Race/Ethnicity.

Students were asked if they identified as “Hispanic or Latino.” Additionally, they selected their race from “American Indian/Alaska Native,” “Asian,” “Black/African American,” “Native Hawaiian/Other Pacific Islander,” and “White.” These variables were combined into the following categories: (1) “White,” (2) “Black/African American,” (3) “Hispanic/Latino,” (4) “Asian,” and (5) “Other Race/Ethnicity.”

Age.

Students were asked, “How old are you?” The seven response options ranged from “12 years old or younger” to “18 years old or older.” Response options were collapsed based on developmental periods: “14 or younger,” “15 – 17 years old,” and “18 and older.”

Sexual Behavior.

Sexual behavior was measured by the question, “During your life, with whom have you had sexual contact?” Response options included, “I have never had sexual contact,” “Same sex partners,” “Same and different sex partners” and “Different sex partners.” This variable was coded by combining responses with the students’ self-reported sex. Students’ who reported only having sexual contact with individuals of the same sex were coded as “Same sex partners.” Those who indicated having sexual contact with the same and different sex partners were coded as “Same and different sex partners.” Finally, students who reported only having sexual contact with individuals of a different sex were coded as “Different sex partners.”

Alcohol Use

Lifetime use.

Students were asked, “During your life, on how many days have you had at least one drink of alcohol?” Response options ranged from “0 days” to “100 or more days.” Responses were collapsed and dichotomized as “0 days” or “1 or more days.”

Age of first drink.

Students were asked, “How old were you when you had your first drink of alcohol other than a few sips?” The item was coded to reflect those who “Never drank,” drank “Before age 13,” and those who drank “At age 13 or older,” per the CDC dichotomization used in the 2015 YRBS Combined Data Users Guide (SAS Institute, Inc.).

Binge drinking.

Students were asked, “During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?” Response options ranged from “0 days” to “20 or more days.” Endorsement of any number of days was coded as binge drinking.

Drug Use

Illicit drug use.

Students were asked, “During your life, how many times have you used any form of cocaine, including powder, crack, or freebase?” Response options ranged from “0 times” to “40 or more times.” Endorsement of any use was coded as illicit drug use.

Prescription drug use.

Students were asked, “During your life, how many times have you taken a prescription drug (such as OxyContin, Percocet, Vicodin, Codeine, Adderall, Ritalin, or Xanax) without a doctor’s prescription?” Response options ranged from “0 times” to “40 or more times.” Endorsement of any use was coded as prescription drug use.

Marijuana use.

Students were asked, “During your life, how many times have you used marijuana?” Response options ranged from “0 times” to “40 or more times.” Endorsement of any use was coded as marijuana use.

HIV Testing

Students were asked, “Have you ever been tested for HIV, the virus that causes AIDS (Do not count tests done if you donated blood)?” Response options were “Yes,” “No,” or “Not sure.” The selection of “Not Sure” was coded as missing data.

Statistical Analysis

All data cleaning and recoding was conducted in SAS Version 9.4 (SAS Institute, Inc., Cary, NC). Analyses were carried out using SAS-Callable SUDAAN Version 11.0.1 (RTI International Research Triangle, Park, NC) to appropriately weight estimates and to account for the complex sampling design of the YRBS. The YRBS data weights adjusts for student non-response and distribution of students by grade, sex, and race/ethnicity in each jurisdiction (Brener et al., 2013).

First, descriptive statistics were calculated for student characteristics, alcohol use, drug use, and HIV testing by the sample and sex. Next, three sex-stratified, stepwise multivariable logistic models were used to estimate odds of ever having received a HIV test being associated with student characteristics and substance use, starting with student characteristics and sequentially adding blocks of alcohol and drug use variables.

Results

There was an even distribution of female (50.79%) and male (49.21%) students. The majority of students were White (47.47%), followed by Hispanic/Latino (26.39%) and Black/African American (15.30%), and nearly three-quarters were between 15 and 17 years old (74.28%). Over half of the students reported being sexually experienced (54.06%) with 47.12% reporting sexual contact with different sex partners only, 4.5% with the same sex partners, and 2.44% with both the same and different sex partners. However, less than a quarter of students (13.50%) reported being tested for HIV. Over half of students reported alcohol use (58.73%), but fewer reported binge drinking (16.28%). Illicit drug use was low (6.90%), but prescription drug use (14.51%) and marijuana use (38.44%) were higher (see Table 1).

Table 1.

YRBS 2013 – 2015 Student Characteristics, Substance Use, and HIV Testing (N=105,147).

Total Males Females
N % N % N %
Student Characteristics
Sex
Male 49298 49.21 49298 100.00 0 0.00
Female 55849 50.79 0 0.00 55849 100.00
Race/Ethnicity
White 34782 47.47 16762 48.36 18020 46.62
Black/African American 19382 15.30 8655 14.43 10727 16.13
Hispanic/Latino 33474 26.39 15404 26.11 18070 26.67
Asian 8319 6.04 4118 6.27 4201 5.81
Other Race/Ethnicity 9190 4.80 4359 4.83 4831 4.78
Age
14 or younger 13450 11.40 5969 10.75 7481 12.03
15 - 17 79522 74.28 37045 74.14 42477 74.41
18 or older 12175 14.32 6284 15.11 5891 13.56
Sexual Behavior
Never had sexual contact 49871 45.94 21821 44.94 28050 49.23
Same sex partners 3141 4.50 1244 2.19 1897 2.67
Same and different sex partners 5211 2.44 1023 2.05 4188 6.88
Different sex partners 46924 47.12 25210 50.82 21714 41.22
Alcohol Use 87882 86.50 41332 86.80 46550 86.21
Ever Drank Alcohol
Yes 54819 58.73 24467 56.70 30352 60.67
No 41256 41.27 20597 43.30 20659 39.33
Age of First Drink
Never had a drink 41256 41.27 20597 43.30 20659 39.33
Less than 13 10654 15.35 8343 17.16 7711 13.61
13 or older 38765 43.37 16124 39.54 22641 47.06
Binge Drinking
Yes 14601 16.28 6946 17.01 7655 15.58
No 87424 83.72 40549 82.99 46875 84.42
Drug Use
Illicit Drug Use
Yes 7431 6.90 4267 8.32 3164 5.53
No 97716 93.10 45031 91.68 52685 94.47
Prescription Drug Use
Yes 10591 14.51 5240 14.82 5351 14.21
No 67728 85.49 31872 85.18 35856 85.79
Marijuana Use
Yes 38364 38.44 18132 39.18 20232 37.74
No 62770 61.56 29013 60.82 33757 62.26
HIV Testing
Yes 17265 13.50 7966 13.20 9299 13.79
No
Open in a new tab

Binge drinking involved a response of “1 or more days” to the question “During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?” Illicit drug use included cocaine, heroin, methamphetamines, or ecstasy. Prescription drug use involved the use of such drugs as Oxycontin, Percocet, Vicodin, codeine, Adderall, Ritalin, and/or Xanax without a doctor’s prescription

Multivariable logistic regression identified several student and substance use factors associated with HIV testing. For Model 1, Black/African American female (odds ratio [OR] = 2.62; 95% confidence interval [CI] = 2.31, 2.96; p <.0001) and Black/African American male students (OR = 2.27; 95% CI = 1.97, 2.61; p <.0000) had increased odds of having been tested for HIV compared to White female and male students. Hispanic/Latino female (OR = 1.63; 95% CI = 1.41, 1.88; p <.0001) and Hispanic/Latino male students (OR = 1.69; 95% CI = 1.49, 1.93; p < .0001), Asian female (OR = 1.61; 95% CI = 1.19, 2.17; p <.0018) and Asian male students (OR = 1.50; 95% CI = 1.15, 1.96; p = .0028), and female students who identified as Other Race/Ethnicity (OR = 1.72; 95% CI = 1.40, 2.12; p <.0001) all had increased odds of having been tested for HIV compared to White female and male students.

Female students ages 14 or younger (OR = 0.43; 95% CI = 0.34, 0.53; p <.0001) and ages 15 to 17 (OR = 0.60; 95% CI = 0.53, 0.68; p <.0001) had decreased odds of having been tested for HIV test compared to female students ages 18 and older. Similarly, male students ages 14 or younger (OR = 0.83; 95% CI = 0.69, 0.99; p =.0401) and ages 15 to 17 (OR = 0.63; 95% CI = 0.54, 0.74; p < .0001) had decreased odds of being tested for HIV compared with male students ages 18 and older (see Tables 2 and 3).

Table 2.

Multivariate Logistic Regression Models (M1, M2, and M3) Estimating the Odds of HIV Testing Among Female Sexual Behavior.

M1: Characteristics (n=55,849) M2: Characteristics+Alcohol (n=49,854) M3: Characteristics+sAlcohol+Drugs (n=38,903)
β SE p-value OR 95% CI β SE p-value OR 95% CI β SE p-value OR 95% CI
Student Characteristics
Sexual Behavior
Never had sexual contact −1.41 0.06 <0.0001 0.24 (0.22,0.27) −1.33 0.06 <0.0001 0.26 (0.34, 0.30) −1.26 0.07 <0.0001 0.28 (0.25, 0.33)
Same sex partners 0.10 0.13 0.4498 1.10 (0.86,1.42) 0.12 0.14 0.4176 1.12 (0.85, 1.49) 0.04 0.20 0.8237 1.04 (0.71, 1.53)
Same and different sex partners 0.45 0.08 <0.0001 1.56 (1.34,1.82) 0.37 0.09 <0.0001 1.44 (1.22, 1.71) 0.12 0.10 0.2366 1.13 (0.92, 1.38)
Different sex partners 1.00 1.00 1.00
Race/Ethnicity
Black/African American 0.96 0.06 <0.0001 2.62 (2.31,2.96) 1.00 0.07 <0.0001 2.71 (2.38, 3.09) 0.92 0.07 <0.0001 2.50 (2.17, 2.89)
Hispanic/Latino 0.49 0.07 <0.0001 1.63 (1.41,1.88) 0.46 0.07 <0.0001 1.58 (1.37, 1.83) 0.30 0.08 0.0002 1.36 (1.16, 1.59)
Asian 0.48 0.15 0.0018 1.61 (1.19,2.17) 0.54 0.17 0.0021 1.71 (1.21, 2.41) 0.61 0.22 0.0063 1.84 (1.19, 2.84)
Other Race/Ethnicity 0.54 0.11 <0.0001 1.72 (1.40,2.12) 0.58 0.11 <0.0001 1.78 (1.43, 2.22) 0.50 0.13 0.0001 1.64 (1.27, 2.12)
White 1.00 1.00 1.00
Age
14 or younger −0.85 0.11 <0.0001 0.43 (0.34,0.53) −0.83 0.12 <0.0001 0.43 (0.34, 0.55) −0.87 0.15 <0.0001 0.42 (0.31, 0.57)
15 – 17 −0.52 0.06 <0.0001 0.60 (0.53,0.68) −0.53 0.06 <0.0001 0.59 (0.52, 0.67) −0.53 0.07 <0.0001 0.59 (0.51, 0.68)
18 or older 1.00 1.00 1.00
Alcohol Use
Age at First Use
Less than 13 0.14 0.08 0.0742 1.16 (0.99, 1.36) −0.09 0.10 0.3716 0.91 (0.74, 1.12)
13 or older 0.10 0.06 0.0991 1.11 (0.98, 1.26) −0.04 0.07 0.6024 0.96 (0.83, 1.11)
Never drank 1.00 1.00
Binge Drinking
Binge Drinking
Yes		 0.21 0.07 0.0016 1.23 (1.08, 1.41) 0.04 0.08 0.6662 1.04 (0.88, 1.21)
No 1.00 1.00
Drug Use
Illicit Drugs
Yes 0.54 0.14 0.0001 1.72 (1.30, 2.27)
No 1.00
Prescription Drugs
Yes 0.22 0.09 0.0138 1.25 (1.05, 1.49)
No 1.00
Marijuana
Yes 0.41 0.09 <0.0001 1.51 (1.26, 1.80)
No 1.00
Open in a new tab

Note. Binge drinking involved a response of “1 or more days” to the question “During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?” Illicit drug use involved the use of cocaine, heroin, methamphetamines, and ecstasy. Prescription drug use involved the use of such drugs as Oxycontin, Percocet, Vicodin, codeine, Adderall, Ritalin, and/or Xanax without a doctor’s prescription.

Table 3.

Multivariate Logistic Regression Models (M1, M2, and M3) Estimating the Odds of HIV Testing Among Male Sexual Behavior.

M1: Characteristics (n=49,298) M2: Characteristics+Alcohol (n=43,493) M3: Characteristics+Alcohol+Drugs (n=34,219)
β SE p-value OR 95% CI β SE p-value OR 95% CI β SE p-value OR 95% CI
Student Characteristics
Sexual Behavior
Never had sexual contact −0.81 0.06 <0.0001 0.45 (0.39, 0.51) −0.71 0.07 <0.0001 0.49 (0.43, 0.57) −0.67 0.10 <0.0001 0.51 (0.42, 0.62)
Same sex partners 0.63 0.15 <0.0001 1.88 (1.41, 2.50) 0.56 0.15 0.0003 1.75 (1.29, 2.35) 0.51 0.19 0.0078 1.66 (1.14, 2.42)
Same and different sex partners 1.01 0.14 <0.0001 2.75 (2.08, 3.64) 0.96 0.19 <0.0001 2.61 (1.81, 3.76) 0.78 0.21 0.0002 2.18 (1.45, 3.29)
Different sex partners 1.00 1.00 1.00
Race/Ethnicity
Black/African American 0.82 0.07 <0.0000 2.27 (1.97, 2.61) 0.83 0.08 <0.0001 2.30 (1.95, 2.70) 0.83 0.09 <0.0001 2.29 (1.91, 2.75)
Hispanic/Latino 0.53 0.07 <0.0001 1.69 (1.49, 1.93) 0.48 0.07 <0.0001 1.62 (1.41, 1.87) 0.41 0.08 <0.0001 1.50 (1.27, 1.77)
Asian 0.41 0.14 0.0028 1.50 (1.15, 1.96) 0.44 0.15 0.0031 1.55 (1.16, 2.08) 0.25 0.19 0.1813 1.29 (0.89, 1.86)
Other Race/Ethnicity 0.15 0.12 0.2298 1.16 (0.91, 1.47) 0.18 0.13 0.1624 1.20 (0.93, 1.54) 0.16 0.16 0.3138 1.17 (0.86, 1.59)
White 1.00 1.00 1.00
Age
14 or younger −0.19 0.09 0.0401 0.83 (0.69, 0.99) −0.26 0.11 0.0128 0.77 (0.63, 0.95) −0.40 0.16 0.0109 0.67 (0.49, 0.91)
15 – 17 −0.46 0.08 <0.0001 0.63 (0.54, 0.74) −0.50 0.10 <0.0001 0.61 (0.50, 0.74) −0.55 0.13 <0.0001 0.58 (0.45, 0.74)
18 or older 1.00 1.00 1.00
Alcohol Use
Age at First Use
Less than 13 0.30 0.10 0.0035 1.34 (1.10, 1.64) 0.14 0.12 0.2318 1.15 (0.91, 1.45)
13 or older −0.10 0.07 0.1800 0.91 (0.79, 1.05) −0.18 0.09 0.0549 0.84 (0.70, 1.00)
Never drank 1.00 1.00
Binge Drinking
Yes 0.11 0.10 0.2561 1.12 (0.92, 1.37) −0.15 0.10 0.1338 0.86 (0.70, 1.05)
No 1.00 1.00
Drug Use
Illicit Drugs
Yes 0.66 0.10 <0.0001 1.94 (1.58, 2.38)
No 1.00
Prescription Drugs
Yes 0.09 0.08 0.2826 1.09 (0.93, 1.29)
No 1.00
Marijuana
Yes 0.20 0.08 0.0125 1.22 (1.04, 1.42)
No 1.00
Open in a new tab

Note. Binge drinking included a response of “1 or more days” to the item “During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?” Illicit drug use included the use of cocaine, heroin, methamphetamines, or ecstasy. Prescription drug use included the use of such drugs as Oxycontin, Percocet, Vicodin, codeine, Adderall, Ritalin, or Xanax without a doctor’s prescription.

Female students had increased odds of having been tested for HIV if they reported sexual contact with same sex partners (females) and different sex partners (males) (OR = 1.56; 95% CI = 1.34, 1.82; p <.0001) compared to female students who reported same sex partners (females) or different sex partners (males). Male students who reported sexual contact with same sex partners (males) (OR = 1.88; 95% CI = 1.41, 2.50; p <.0001) or same sex partners (males) and different sex partners (females) (OR = 2.75; 95% CI = 2.08, 3.64; p <.0001) had increased odds of having been tested compared to male students who reported sexual contact with different sex partners (females) (see Tables 2 and 3).

Model 1 findings were maintained for Model 2. Once alcohol was introduced into the model, binge drinking was associated with increased odds of having been tested for HIV for female students (OR = 1.23; 95% CI = 1.08, 1.41; p = .0016) compared to female students who did not report binge drinking, while male students whose first alcohol use was before the age of 13 had increased odds of being tested (OR = 1.34; 95% CI = 1.10, 1.64; p = .0035) compared to male students who first alcohol use was after the age 13 or those who never used alcohol (see Tables 2 and 3).

For Model 3, once drug use variables were introduced into the model, increased odds of HIV testing were no longer associated with female students who had sexual contact with same sex partners (females) and different sex partners (males) or for Asian male students who had sexual contact with different sex partners (females). Furthermore, binge drinking for female students and first alcohol use before the age of 13 for male students were also no longer associated with increased odds of HIV testing. However, female students had increased odds of being tested for HIV if they reported illicit drug use (OR = 1.72; 95% CI = 1.30, 2.27; p = .0001), prescription drug use (OR = 1.25; 95% CI = 1.05, 1.49; p = .0138), and/or marijuana use (OR = 1.51; 95% CI = 1.26, 1.80; p <.0001) compared to female students who did not report drug use. Male students who reported illicit drug use (OR = 1.94; 95% CI = 1.58, 2.38; p <.0001) and/or marijuana use (OR = 1.22; 95% CI = 1.04, 1.42; p = .0120) also had increased odds of being tested for HIV compared to male students who did not report drug use (see Tables 2 and 3).

Discussion

Student characteristics and substance use were associated with the increased likelihood of self-reported HIV testing for a sample of high school students. These findings highlight the importance of sexual and/or racial/ethnic minority adolescents and older adolescents knowing their HIV status. Substance use was also associated with HIV testing for adolescents, suggesting the possible impact of drug use (illicit and prescription) on decisions involving sexual health. This is particularly notable for prescription drug use, which is perceived as safer or less harmful than illicit drugs (Wu, 2008; Schepisa et al., 2018; SAMHSA, 2019). Further investigation is needed to understand the impact of polysubstance use on HIV testing. The ability to predict HIV testing for adolescents, especially subpopulations of adolescents, is encouraging and can assist with targeted scale up HIV testing (i.e., self-testing, rapid testing) and biomedical prevention (pre-exposure prophylaxis: PrEP).

The public health implications of current HIV testing rates for AYAs are apparent (i.e., undiagnosed infection, HIV transmission, lack of treatment) and concerning. Scaling up HIV testing for this population must remain a top priority to identify and prevent new infections. School-based health clinics are important in the effort to scale up HIV testing for adolescents. Adolescents are in school during critical developmental stages and significant time periods during the day (National Center for Education Statistics, 2018; Mirzazadeh et al., 2018). The school setting provides the perfect opportunity for concentrated, comprehensive sexual health education and HIV testing.

Community-based HIV testing efforts are also necessary to scale up testing for adolescents. In recent years, funding for community-based testing efforts have decreased substantially. While AYAs are more likely to be tested in a healthcare facility, tests were less likely to yield diagnoses than tests performed in non-healthcare facilities (Stein et al., 2017). This may be due to the most high-risk AYA not accessing health care or not being comfortable testing with healthcare provider. The re-investment in community-based HIV testing (e.g., mobile vans, community drop-in centers, city parks, and bars) is critical to providing access to prevention services in nonclinical settings, and can be a strategy to engage hard to reach adolescents who do not access the health care system for sexual health planning (Straub et al., 2011; Thornton et al., 2012; Weidle et al., 2014). HIV testing efforts in diverse settings can lead the way in increasing testing for adolescents (Boyer et al., 2014; Mdodo et al., 2014).

While this study provides important information regarding predictors of self-reported HIV testing for high school age adolescents, it has limitations. While the cross-sectional study design provides information on factors associated with HIV testing, possible confounding factors were not assessed. Self-report data of HIV testing is subject to social desirability and recall bias which impacts the accuracy of responses. Only students attending high school completed the YRBS, thus, the study findings are not generalizable to other adolescent populations (e.g., those not attending high school). The majority of the study sample were White students (47.47%), although Black/African American students (15.30%) were more likely to have tested for HIV. Predetermined categories of “Male” and “Female” restricted variability with regard to sex. Finally, a range of risk behaviors previously associated with HIV testing for adolescents (e.g., number of sexual partners; condomless sex; STI history, etc.) were not included in this study due to survey limitations. Despite these limitations, this study provides crucial findings for adolescents who are in desperate need of coordinated efforts to scale up HIV testing.

Conclusions

The study findings support scaling up HIV testing for adolescents. HIV testing strategies must involve best practices for reaching and engaging adolescents, especially racial/ethnic and/or sexual minority adolescents, as they are disproportionately impacted by HIV infection. Effectively scaling up HIV testing for adolescents must involve tailored strategies for diverse populations of adolescents within diverse settings.

Acknowledgments

This work was supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA: R01AA024409). We would like to thank the students who provided data for this study.

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