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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article"><?properties manuscript?><front><journal-meta><journal-id journal-id-type="nlm-journal-id">8915313</journal-id><journal-id journal-id-type="pubmed-jr-id">1056</journal-id><journal-id journal-id-type="nlm-ta">AIDS Care</journal-id><journal-id journal-id-type="iso-abbrev">AIDS Care</journal-id><journal-title-group><journal-title>AIDS care</journal-title></journal-title-group><issn pub-type="ppub">0954-0121</issn><issn pub-type="epub">1360-0451</issn></journal-meta><article-meta><article-id pub-id-type="pmid">25022287</article-id><article-id pub-id-type="pmc">4329971</article-id><article-id pub-id-type="doi">10.1080/09540121.2014.936814</article-id><article-id pub-id-type="manuscript">NIHMS608076</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Opportunities for technology-based HIV prevention programming among
high school students in Cape Town, South Africa</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Ybarra</surname><given-names>Michele L</given-names></name><degrees>MPH PhD</degrees><email>Michele@InnovativePublicHealth.org</email><aff id="A1">Center for Innovative Public Health Research, 555 El Camino Real
#A347, San Clemente, 92672 United States</aff></contrib><contrib contrib-type="author"><name><surname>Mwaba</surname><given-names>Kelvin</given-names></name><aff id="A2">University of the Western Cape, Pyschology, Cape Town, South
Africa</aff></contrib><contrib contrib-type="author"><name><surname>Prescott</surname><given-names>Tonya L.</given-names></name><aff id="A3">Center for Innovative Public Health Research, 555 N. El Camino Real
#A347, San Clemente, 92672 United States</aff></contrib><contrib contrib-type="author"><name><surname>Roman</surname><given-names>Nicolette V.</given-names></name><aff id="A4">University of Western Cape, Cape Town, South Africa</aff></contrib><contrib contrib-type="author"><name><surname>Rooi</surname><given-names>Bronwyn</given-names></name><aff id="A5">University of Western Cape, Cape Town, South Africa</aff></contrib><contrib contrib-type="author"><name><surname>Bull</surname><given-names>Sheana</given-names></name><aff id="A6">University of Colorado Denver, Colorado School of Public Health,
Mail stop B-119, Aurora, 80045 United States</aff></contrib></contrib-group><pub-date pub-type="nihms-submitted"><day>25</day><month>6</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>15</day><month>7</month><year>2014</year></pub-date><pub-date pub-type="ppub"><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>12</month><year>2015</year></pub-date><volume>26</volume><issue>12</issue><fpage>1562</fpage><lpage>1567</lpage><!--elocation-id from pubmed: 10.1080/09540121.2014.936814--><abstract><p id="P1">One in three new cases of HIV in South Africa is among adolescents. Given
that adolescents are particularly affected, scalable and cost-effective
prevention programs are urgently needed. This study aims to identify
opportunities to integrate technology into youth HIV prevention efforts. In
2012, 1,107 8<sup>th</sup> &#x02013; 11<sup>th</sup> graders completed a
paper-and-pencil survey. Respondents were enrolled in one of three public high
schools in Langa. Because it is the closest black township to Cape Town, Langa
has the highest density of people in the region. Eighty-nine percent of
respondents have used text messaging (SMS) and 86% have gone online. If
an HIV prevention program was offered online, 66% of youth would be
somewhat or extremely likely to access it; slightly fewer (55%) felt the
same about SMS-based programming. In comparison, 85% said they would be
somewhat or extremely likely to access a school-based HIV prevention program.
Interest in Internet-(60%) and SMS-based (54%) HIV prevention
programming was similar for youth who had a self-appraised risk for HIV compared
to youth who appraised their risk to be lower, as it was for youth who were
tired of hearing messages about HIV prevention.</p><p id="P2">Technology use is common &#x02013; even among high school students who
live in lower income communities. At the same time, these data reveal that it is
not uncommon for youth to be tired of hearing messages about HIV prevention, and
many of the typical topics key to HIV prevention have low interest levels among
youth. HIV prevention researchers need to be mindful of the extent of existing
programming that youth are exposed to. Technology-based programming may be
especially amenable to meeting these requirements because of its novelty
especially in developing countries, and because interactive functionality can be
easily integrated into the program design. Given the preference for school- and
Internet-based programming, it seems that a hybrid approach is likely feasible
and acceptable.</p></abstract><kwd-group><kwd>HIV prevention</kwd><kwd>adolescents</kwd><kwd>technology</kwd><kwd>needs assessment</kwd></kwd-group></article-meta></front><body><sec sec-type="intro" id="S1"><title>INTRODUCTION</title><p id="P3">Despite intensive HIV prevention research (<xref rid="R5" ref-type="bibr">Hargreaves et al., 2007</xref>; <xref rid="R14" ref-type="bibr">Rehle et al.,
2007</xref>) and the development of effective prevention programming (<xref rid="R6" ref-type="bibr">Harrison, Newell, Imrie, &#x00026; Hoddinott,
2010</xref>; <xref rid="R9" ref-type="bibr">Jewkes et al., 2008</xref>; <xref rid="R13" ref-type="bibr">Pettifor et al., 2004</xref>), adolescent HIV
preventive behavior change remains elusive (<xref rid="R7" ref-type="bibr">Hartell,
2005</xref>; <xref rid="R15" ref-type="bibr">Shisana et al., 2009</xref>; <xref rid="R18" ref-type="bibr">Van der Linde &#x00026; Human Sciences Research
Council, 2013</xref>). Of great concern, HIV risk behaviors appear to be
increasing among South Africans (<xref rid="R18" ref-type="bibr">Van der Linde
&#x00026; Human Sciences Research Council, 2013</xref>).</p><p id="P4">To promote behavior change, HIV prevention programs need to be efficacious
but also easily implemented. Data suggest explosive technology growth in South
Africa (<xref rid="R1" ref-type="bibr">Central Intelligence Agency, 2013</xref>;
<xref rid="R16" ref-type="bibr">Smith, 2013</xref>). Technology-based
interventions lack many of the structural challenges noted in traditional
interventions and are less costly to scale up (<xref rid="R2" ref-type="bibr">Cole-Lewis &#x00026; Kershaw, 2010</xref>; <xref rid="R3" ref-type="bibr">Free
et al., 2013</xref>; <xref rid="R11" ref-type="bibr">Noar, Black, &#x00026;
Pierce, 2009</xref>; <xref rid="R12" ref-type="bibr">Perry et al., 2012</xref>;
<xref rid="R20" ref-type="bibr">Ybarra &#x00026; Eaton, 2005</xref>).
Nonetheless, technology is under-utilized to promote HIV preventive behavior in
developing countries. To determine whether technology is an appropriate delivery
mechanism for adolescent-focused HIV preventive programming in South Africa, a
better understanding of both how young people use technology and also their interest
in engaging with HIV preventive information through technology, is critical.</p></sec><sec sec-type="methods" id="S2"><title>Methods</title><p id="P5">The research protocol was reviewed and approved by the University of the
Western Cape and the Chesapeake Institutional Review Board. Data were collected
between April-August 2012. All participants provided written informed consent.</p><sec id="S3"><title>Location and Participants</title><p id="P6">Respondents attended one of three partner schools in Langa, a low income
community with the highest density of people in the region because it is the
closest black township to Cape Town. All students in Grade 8 to Grade 11 who
were 16 years of age (the legal age of consent in South Africa) or older were
invited to voluntarily participate in the study.</p></sec><sec id="S4"><title>Procedures</title><p id="P7">Surveys were completed via paper and pencil in the absence of the
teachers and school administrators. To assure anonymity, names were not
collected on the survey instrument.</p><p id="P8">Respondents took an average of one hour to complete the survey. The
survey was written in English, which is the official language of South Africa
and the language of instruction in the high schools. There are multiple living
languages in South Africa, however (<xref rid="R8" ref-type="bibr">Intersol Inc,
2010</xref>). The survey was first piloted among youth in the target age
range to ensure readability and acceptability of sensitive questions.</p></sec><sec id="S5"><title>Measures</title><sec id="S6"><title>Acceptability of information delivery by mode</title><p id="P9">All youth were asked: &#x0201c;If there was a health education
program about HIV/AIDS prevention for teenagers, how likely would you go to
it if it was &#x02026;. a) at school, b) at a religious organization, c)
over e-mail, d) over text (SMS) messages, and e) on the
Internet&#x0201d;.</p></sec><sec id="S7"><title>Interest in HIV prevention programming</title><p id="P10">Topics were chosen to reflect key components of HIV prevention
programs, as well as those that were posited to be salient to youth based
upon our previous work with sub-Saharan adolescents (<xref rid="R19" ref-type="bibr">Ybarra, Biringi, Prescott, &#x00026; Bull, 2012</xref>). Youth
were asked to rate how much they agreed or disagreed with the statement:
&#x0201c;I am tired of hearing about how to prevent HIV / AIDS and other
STDs (sexually transmitted diseases).&#x0201d; They also were presented with
a list of eight different topics related to HIV/AIDS and were asked whether
they would be interested in receiving information about them. Topics
included HIV-specific information (e.g., how to use a condom), family
planning (e.g., birth control), and relationships (e.g., how to start a
relationship).</p></sec><sec id="S8"><title>HIV risk attitudes and behaviors</title><p id="P11">Youth were asked to appraise their personal risk of getting HIV; and
how strongly they agreed or disagreed with the following statement:
&#x0201c;I am <underline>tired</underline> of hearing about how to prevent
HIV/AIDS and other STDs (sexually transmitted diseases).&#x0201d;</p><p id="P12">Vaginal sex was queried: &#x0201c;Have you <bold>ever</bold> had
vaginal sex? We mean when a penis goes into a vagina.&#x0201d; Anal sex was
queried: &#x0201c;Have you <bold>ever</bold> had anal sex? We mean when a
penis goes into an anus.&#x0201d;</p></sec></sec><sec id="S9"><title>Data cleaning</title><p id="P13">All surveys were double entered by project staff to ensure accuracy.
Missing data were imputed using the &#x0201c;impute&#x0201d; command in Stata,
which estimates missing values using best set regression (<xref rid="R17" ref-type="bibr">StataCorp, 2009</xref>). Each respondent was required to have
valid, non-missing data for at least 70% of the variables included in
the analyses. Based on this criterion, 92 respondents were removed and 1,015
were retained.</p></sec></sec><sec sec-type="results" id="S10"><title>Results</title><p id="P14">Of the total 1,460 students who were enrolled in the three partner schools,
1,279 students (88%) were present on the day of the survey. 1,107 of the
1,191 eligible students completed the survey (Response rate = 93%).
Demographic and technology use characteristics are shown in <xref ref-type="table" rid="T1">Table 1</xref>.</p><sec id="S11"><title>Interest in HIV prevention programming</title><p id="P15">As shown in <xref ref-type="table" rid="T2">Table 2</xref>, one in three
youth (38%) somewhat or strongly agreed that they were tired of hearing
about how to prevent HIV/AIDS and other STDs. Few expressed interest in
learning: how to &#x0201c;refuse sex&#x0201d; (43%), how to use a condom
(42%), and about birth control (32%). Even topics posited to be
of interest to adolescents (e.g., how to develop a relationship) were endorsed
by less than half of youth. Males tended to be more fatigued and less
interested than females about HIV prevention programming.</p></sec><sec id="S12"><title>Acceptability of information delivery by mode</title><p id="P16">Of the five access points queried, youth were most likely to indicate
that they would be somewhat or very likely to access an HIV prevention program
if it were delivered at school (85%, <xref ref-type="table" rid="T3">Table 3</xref>).</p></sec><sec id="S13"><title>Reaching youth at greater risk for HIV</title><p id="P17">Sixty percent of youth who appraised their likelihood of getting HIV as
above average chance said they were somewhat or very likely to access an HIV
prevention program if it were online and 54% if it were via SMS. Similar
rates of interest in Internet (60%) and SMS (53%) programming
were noted among youth who agreed they were tired of HIV prevention messaging,
and for youth who reported ever having vaginal or anal sex (67% and
55%, respectively). As shown in <xref ref-type="table" rid="T4">Table
4</xref>, among otherwise similar youth, those who were tired of hearing
about HIV prevention were about 50% less likely to access a program if
it were offered at school or online, with a similar trend noted for email. Youth
who had had vaginal sex were 34% less likely to access it if it were
offered online.</p></sec></sec><sec sec-type="discussion" id="S14"><title>Discussion</title><p id="P18">Technology use is common among adolescents attending our three partner
schools in the lower income community, Langa, South Africa. Yet, these data reveal
that it is not uncommon for youth to be tired of hearing messages about HIV
prevention, and many of the typical key HIV prevention topics key have low interest
levels among youth. HIV prevention researchers need to be mindful of the extent of
existing programming that youth are exposed to. Technology-based programming may be
especially amenable to meeting these requirements because of its novelty especially
in developing countries, and because interactive functionality can be easily
integrated into the program design.</p><p id="P19">According to youth in this study, the likelihood of accessing an HIV
prevention program was greatest if the program were offered at school. Perhaps this
is because currently available programming is predominantly delivered in schools, so
this is the most familiar option for youth. This does not mean that youth were
opposed to technology-based programs, however: Two in three youth said they were at
least somewhat likely to access an Internet-based program, and slightly more than
one in two youth would access an SMS-based program. Given the preference for school-
and Internet-based programming (among the technology-related access points), a
hybrid approach may be feasible and acceptable. For example, perhaps an Internet
program could be offered as an after-school activity on school grounds. By utilizing
the Internet as the program delivery mechanism, one safeguards program fidelity by
ensuring all youth have access to the same, accurate sexual health information,
while simultaneously allowing youth greater privacy to complete the program when and
where they are comfortable. It also takes the onus off the teacher to deliver what
can be uncomfortable or embarrassing information to their students, as well as the
burden of finding classroom time to teach the material.</p><sec id="S15"><title>Limitations</title><p id="P20">The generalizability of these data to greater South Africa, and youth
who do not speak English fluently or are not enrolled in high school is unknown.
Furthermore, it is possible that some youth did not answer honestly.
Additionally, technology use was lower among the 92 respondents excluded from
the analyses. Differences in findings may have been noted if these youth or
those who were absent on the day of the survey had been included in the
analytical sample.</p></sec><sec id="S16" sec-type="conclusions"><title>Conclusions</title><p id="P21">In South Africa, like many countries, people who live in low income households are at
higher risk for HIV (<xref rid="R4" ref-type="bibr">Government of the Republic
of South Africa, 2011</xref>). The access to and interest in technology as a
delivery mechanism for HIV prevention programming among low income students in
the current study suggest this may be an under-utilized opportunity to reach
this vulnerable population. Importantly, too, youth with characteristics that
may further increase their risk for HIV (e.g., vaginal sex) are generally as
likely to be interested in technology-based programming as their peers. The
current data support a greater exploration of applications of technology in
delivering HIV preventive behavior in South Africa.</p></sec></sec></body><back><ack id="S17"><title>Acknowledgement</title><p id="P22">This research was funded by a grant from the National Institute of Mental
Health at the National Institutes of Health (R03MH094238; PI: Ybarra). The content
is solely the responsibility of the authors and does not necessarily represent the
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last the glass is half full"</source><year>2013</year><date-in-citation>Retrieved September 11, 2013</date-in-citation><comment>from <ext-link ext-link-type="uri" xlink:href="http://www.hsrc.ac.za/en/media-briefs/hiv-aids-stis-and-tb/plenary-session-3-20-june-2013-hiv-aids-in-south-africa-at-last-the-glass-is-half-full">http://www.hsrc.ac.za/en/media-briefs/hiv-aids-stis-and-tb/plenary-session-3-20-june-2013-hiv-aids-in-south-africa-at-last-the-glass-is-half-full</ext-link></comment></element-citation></ref><ref id="R19"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ybarra</surname><given-names>ML</given-names></name><name><surname>Biringi</surname><given-names>R</given-names></name><name><surname>Prescott</surname><given-names>T</given-names></name><name><surname>Bull</surname><given-names>SS</given-names></name></person-group><article-title>Usability and navigability of an HIV/AIDS internet intervention
for adolescents in a resource limited setting</article-title><source>Computer Informatics in Nursing</source><year>2012</year><volume>30</volume><fpage>587</fpage><lpage>595</lpage></element-citation></ref><ref id="R20"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ybarra</surname><given-names>ML</given-names></name><name><surname>Eaton</surname><given-names>WW</given-names></name></person-group><article-title>Internet-based mental health interventions</article-title><source>Mental Health Services Research</source><year>2005</year><volume>7</volume><fpage>75</fpage><lpage>87</lpage><pub-id pub-id-type="pmid">15974154</pub-id></element-citation></ref></ref-list></back><floats-group><table-wrap id="T1" position="float" orientation="portrait"><label>Table 1</label><caption><p id="P23">Youth characteristics (n=1,015)</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" colspan="2" rowspan="1">Youth characteristics</th><th align="left" rowspan="1" colspan="1">% (n)</th></tr></thead><tbody><tr><td align="left" colspan="2" rowspan="1">Demographic characteristics</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Female</td><td align="left" rowspan="1" colspan="1">63.7% (647)</td></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Age (Range: 16&#x02013;24;
M:SD)</td><td align="left" rowspan="1" colspan="1">17.5 (1.2)</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;Grade</td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Grade 8</td><td align="left" rowspan="1" colspan="1">0.2% (2)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Grade 9</td><td align="left" rowspan="1" colspan="1">0.1% (1)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Grade 10</td><td align="left" rowspan="1" colspan="1">52.0% (528)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Grade 11</td><td align="left" rowspan="1" colspan="1">47.7% (484)</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;Race</td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">African</td><td align="left" rowspan="1" colspan="1">97.7% (992)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Colored <xref ref-type="table-fn" rid="TFN1">*</xref></td><td align="left" rowspan="1" colspan="1">0.6% (6)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Indian</td><td align="left" rowspan="1" colspan="1">0.1% (1)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">White</td><td align="left" rowspan="1" colspan="1">0.1% (1)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Other</td><td align="left" rowspan="1" colspan="1">1.5% (15)</td></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Father's
education</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">No formal education</td><td align="left" rowspan="1" colspan="1">2.4% (24)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Primary school</td><td align="left" rowspan="1" colspan="1">6.5% (66)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Secondary school</td><td align="left" rowspan="1" colspan="1">36.6% (371)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Tertiary institution / University graduate</td><td align="left" rowspan="1" colspan="1">25.8% (262)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">I am not sure</td><td align="left" rowspan="1" colspan="1">28.8% (292)</td></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Income</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Lower than the average family</td><td align="left" rowspan="1" colspan="1">29.0% (294)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Similar to the average family</td><td align="left" rowspan="1" colspan="1">60.8% (617)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Higher than the average family</td><td align="left" rowspan="1" colspan="1">10.3% (104)</td></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Mother's
education</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">No formal education</td><td align="left" rowspan="1" colspan="1">2.6% (26)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Primary school</td><td align="left" rowspan="1" colspan="1">5.2% (53)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Secondary school</td><td align="left" rowspan="1" colspan="1">39.8% (404)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Tertiary institution / University graduate</td><td align="left" rowspan="1" colspan="1">31.1% (316)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">I am not sure</td><td align="left" rowspan="1" colspan="1">21.3% (216)</td></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Importance of religion on
respondent's life</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Not at all important</td><td align="left" rowspan="1" colspan="1">3.0% (30)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Somewhat unimportant</td><td align="left" rowspan="1" colspan="1">1.4% (14)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Somewhat important</td><td align="left" rowspan="1" colspan="1">11.8% (120)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Very important</td><td align="left" rowspan="1" colspan="1">83.8% (851)</td></tr><tr><td align="left" colspan="2" rowspan="1">Technology use</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Ever used the Internet</td><td align="left" rowspan="1" colspan="1">85.8% (871)</td></tr><tr><td align="left" colspan="2" rowspan="1">&#x000a0;&#x000a0;Ever used SMS (text
messaging)</td><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Do not have a phone</td><td align="left" rowspan="1" colspan="1">9.9% (100)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">Have a phone, do not SMS</td><td align="left" rowspan="1" colspan="1">1.5% (15)</td></tr><tr><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1">SMS</td><td align="left" rowspan="1" colspan="1">88.7% (900)</td></tr><tr><td align="left" colspan="2" rowspan="1">Self-appraised chance of getting HIV is above
average / very strong</td><td align="left" rowspan="1" colspan="1">12.7 (129)</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><label>*</label><p id="P24">Colored refers to youth who are mixed race (White and African)</p></fn></table-wrap-foot></table-wrap><table-wrap id="T2" position="float" orientation="portrait"><label>Table 2</label><caption><p id="P25">Interest in specific HIV prevention programming-related topics
(n=1,015)</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom" rowspan="1" colspan="1">Appraisal of HIV prevention
programming</th><th align="left" rowspan="1" colspan="1">All<break/>(n=1,015)</th><th align="left" rowspan="1" colspan="1">Males<break/>(n=368)</th><th align="left" rowspan="1" colspan="1">Females<break/>(n=647)</th><th align="right" rowspan="1" colspan="1">p-<break/>value</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Somewhat / very tired of hearing about how to prevent
HIV</td><td align="left" rowspan="1" colspan="1">37.5% (381)</td><td align="left" rowspan="1" colspan="1">42.1% (155)</td><td align="left" rowspan="1" colspan="1">34.9% (226)</td><td align="right" rowspan="1" colspan="1">0.02</td></tr><tr><td align="left" rowspan="1" colspan="1">Interested in learning about&#x02026;</td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/><td align="right" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;How to end a relationship</td><td align="left" rowspan="1" colspan="1">43.8% (445)</td><td align="left" rowspan="1" colspan="1">36.7% (135)</td><td align="left" rowspan="1" colspan="1">47.9% (310)</td><td align="right" rowspan="1" colspan="1">0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;How to avoid sex if you don't
want to have sex</td><td align="left" rowspan="1" colspan="1">43.4% (440)</td><td align="left" rowspan="1" colspan="1">28.8% (106)</td><td align="left" rowspan="1" colspan="1">51.6% (334)</td><td align="right" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;How to use a condom</td><td align="left" rowspan="1" colspan="1">42.2% (428)</td><td align="left" rowspan="1" colspan="1">43.5% (160)</td><td align="left" rowspan="1" colspan="1">41.4% (268)</td><td align="right" rowspan="1" colspan="1">0.52</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;How drugs and alcohol affect your
decision making</td><td align="left" rowspan="1" colspan="1">39.1% (397)</td><td align="left" rowspan="1" colspan="1">50.3% (185)</td><td align="left" rowspan="1" colspan="1">32.8% (212)</td><td align="right" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;Birth control / family planning</td><td align="left" rowspan="1" colspan="1">31.5% (320)</td><td align="left" rowspan="1" colspan="1">27.5% (101)</td><td align="left" rowspan="1" colspan="1">33.9% (219)</td><td align="right" rowspan="1" colspan="1">0.04</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;How to refuse sex from a sugar daddy /
mommy</td><td align="left" rowspan="1" colspan="1">22.7% (230)</td><td align="left" rowspan="1" colspan="1">22.3% (82)</td><td align="left" rowspan="1" colspan="1">22.9% (148)</td><td align="right" rowspan="1" colspan="1">0.83</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;Where to get an HIV test</td><td align="left" rowspan="1" colspan="1">21.9% (222)</td><td align="left" rowspan="1" colspan="1">23.9% (88)</td><td align="left" rowspan="1" colspan="1">20.7% (134)</td><td align="right" rowspan="1" colspan="1">0.24</td></tr><tr><td align="left" rowspan="1" colspan="1">&#x000a0;&#x000a0;How to develop and maintain a romantic
relationship</td><td align="left" rowspan="1" colspan="1">16.7% (169)</td><td align="left" rowspan="1" colspan="1">22.0% (81)</td><td align="left" rowspan="1" colspan="1">13.6% (88)</td><td align="right" rowspan="1" colspan="1">0.001</td></tr></tbody></table><table-wrap-foot><fn id="TFN2"><p id="P26">p-value based upon a chi-square testing the relative difference in
endorsement for males versus females</p></fn></table-wrap-foot></table-wrap><table-wrap id="T3" position="float" orientation="landscape"><label>Table 3</label><caption><p id="P27">Likelihood of accessing an HIV prevention program based upon different
access points (n=1,015)</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Likelihood of<break/>accessing an HIV<break/>prevention
program if<break/>it were available<break/>through&#x02026;.</th><th align="left" valign="bottom" rowspan="1" colspan="1">School</th><th align="left" valign="bottom" rowspan="1" colspan="1">Religious<break/>Organization</th><th align="left" valign="bottom" rowspan="1" colspan="1">Email</th><th align="left" valign="bottom" rowspan="1" colspan="1">SMS (text<break/>messaging)</th><th align="left" valign="bottom" rowspan="1" colspan="1">Internet</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Not at all likely</td><td align="left" rowspan="1" colspan="1">10.1% (102)</td><td align="left" rowspan="1" colspan="1">17.8% (181)</td><td align="left" rowspan="1" colspan="1">33.1% (336)</td><td align="left" rowspan="1" colspan="1">27.5% (279)</td><td align="left" rowspan="1" colspan="1">20.9% (212)</td></tr><tr><td align="left" rowspan="1" colspan="1">Somewhat unlikely</td><td align="left" rowspan="1" colspan="1">4.7% (48)</td><td align="left" rowspan="1" colspan="1">12.3% (125)</td><td align="left" rowspan="1" colspan="1">24.6% (250)</td><td align="left" rowspan="1" colspan="1">17.4% (177)</td><td align="left" rowspan="1" colspan="1">13.0% (132)</td></tr><tr><td align="left" rowspan="1" colspan="1">Somewhat likely</td><td align="left" rowspan="1" colspan="1">38.3% (389)</td><td align="left" rowspan="1" colspan="1">46.1% (468)</td><td align="left" rowspan="1" colspan="1">22.2% (225)</td><td align="left" rowspan="1" colspan="1">30.6% (311)</td><td align="left" rowspan="1" colspan="1">31.4% (319)</td></tr><tr><td align="left" rowspan="1" colspan="1">Extremely likely</td><td align="left" rowspan="1" colspan="1">46.9% (476)</td><td align="left" rowspan="1" colspan="1">23.7% (241)</td><td align="left" rowspan="1" colspan="1">20.1% (204)</td><td align="left" rowspan="1" colspan="1">24.4% (248)</td><td align="left" rowspan="1" colspan="1">34.7% (352)</td></tr></tbody></table></table-wrap><table-wrap id="T4" position="float" orientation="landscape"><label>Table 4</label><caption><p id="P28">Relative odds of being somewhat or very likely to access an HIV
prevention program<xref ref-type="table-fn" rid="TFN3">a</xref></p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="3" valign="middle" colspan="1">HIV risk attitudes and
behaviors</th><th align="left" valign="middle" rowspan="1" colspan="1">School (n=1015)</th><th align="left" valign="middle" rowspan="1" colspan="1">Religious<break/>organization<break/>(n=1015)</th><th align="left" valign="middle" rowspan="1" colspan="1">Email (n=1015)</th><th align="left" valign="middle" rowspan="1" colspan="1">SMS
(text<break/>messaging;<break/>n=1015))</th><th align="left" valign="middle" rowspan="1" colspan="1">Internet<break/>(n=1015)</th></tr><tr><th align="left" colspan="5" valign="bottom" rowspan="1"><hr/></th></tr><tr><th align="left" valign="top" rowspan="1" colspan="1">aOR (95% CI)</th><th align="left" valign="top" rowspan="1" colspan="1">aOR (95% CI)</th><th align="left" valign="top" rowspan="1" colspan="1">aOR (95% CI)</th><th align="left" valign="top" rowspan="1" colspan="1">aOR (95% CI)</th><th align="left" valign="top" rowspan="1" colspan="1">aOR (95% CI)</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Above average chance of getting HIV</td><td align="left" rowspan="1" colspan="1">0.97 (0.54, 1.73)</td><td align="left" rowspan="1" colspan="1">1.00 (0.60, 1.66)</td><td align="left" rowspan="1" colspan="1">0.82 (0.55, 1.23)</td><td align="left" rowspan="1" colspan="1">0.86 (0.57, 1.32)</td><td align="left" rowspan="1" colspan="1">1.26 (0.78, 2.04)</td></tr><tr><td align="left" rowspan="1" colspan="1">Tired of hearing about HIV prevention</td><td align="left" rowspan="1" colspan="1"><bold>0.47 (0.31, 0.72)</bold></td><td align="left" rowspan="1" colspan="1">0.79 (0.56, 1.11)</td><td align="left" rowspan="1" colspan="1"><italic>0.78 (0.59, 1.03)</italic></td><td align="left" rowspan="1" colspan="1">0.79 (0.59, 1.06)</td><td align="left" rowspan="1" colspan="1"><bold>0.57 (0.42, 0.80)</bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Ever had vaginal or anal sex</td><td align="left" rowspan="1" colspan="1">0.82 (0.51, 1.33)</td><td align="left" rowspan="1" colspan="1">0.82 (0.56, 1.20)</td><td align="left" rowspan="1" colspan="1">0.89 (0.66, 1.22)</td><td align="left" rowspan="1" colspan="1">0.95 (0.69, 1.32)</td><td align="left" rowspan="1" colspan="1"><bold>0.66 (0.45, 0.95)</bold></td></tr></tbody></table><table-wrap-foot><fn id="TFN3"><label>a</label><p id="P29">Five different multivariate logistic regression models were
estimated, one for each access point (e.g., school). Each model estimates
the relative odds of being somewhat or very likely to access an HIV
prevention program through the access point in question, given the indicator
of HIV risk behavior or attitudes in question. Odds ratios are adjusted for
the other two HIV risk attitudes and behaviors, as well as demographic
characteristics (i.e., biological sex, age, grade, race, paternal and
maternal education, income, i.e., religiosity), technology use (i.e.,
Internet, SMS), self-reported honesty, and the number of variables imputed.
Bold text denotes statistical significance (p&#x0003c;0.05). Italicized text
denotes borderline statistical significance (p&#x0003c;0.10).</p></fn></table-wrap-foot></table-wrap></floats-group></article>