9. Money for upkeep on campus: 1 for “Not enough”, 2 for “Just enough”, 3 for
5.10 Risk assessment of students (Section F)
The means of scores for respondents’ risk assessment of students are presented in Table 5.13, Appendix C). A similar trend, putting UNIZULU ahead of UNAD as in the previous discussion, is also observed in this section. UNIZULU was rated high in all variables and sub-variables except for divorcees, those from capital cities, those with more than enough for family resources and for stipend where they rated medium. UNAD was rated lower in all variables and sub-variables but higher in faculty, biochemistry, educational psychology, female, age groups covering 15-24 y, levels 1 and 2 of studies, single respondents, respondents with no child, Christianity, where grown up (excluding ‘villages/rural areas’), family resources (excluding ‘not enough’), and stipend (excluding ‘not enough’). In all other cases UNAD scored medium.
A good assessment of risk should translate to better attitude to adopting preventive measures;
thus one would then expect that UNIZULU students should be able to avoid risk taking better than UNAD. However, studies have shown that such is usually not the case as students and youths are known to have so much knowledge about HIV and AIDS which they do not translate to positive use in the sexual activities (Ijadunola, Abiona, Odu & Ijadunola, 2007).
Aim 1.8.5
To establish factors that may account for any differences in the responses from the selected institutions about knowledge and perceptions of preventive strategies.
From the discussion of information drawn from data generated for Sections A and B, certain fundamental factors could be easily identified. Some of these factors are common to both institutions and some are unique.
From the socio-demographic data it is obvious that there were distinct areas of difference between UNAD and UNIZULU that could be hidden from the history that both institutions are located in relatively rural areas. Some of these include about two years mean age difference between UNAD (mean age: 20.1 years) and UNIZULU (mean age: 22.3 years). It was also mentioned earlier that sex debut for a small percentage of UNAD respondents was from elementary school while a substantial percentage of UNIZULU respondent were already sexually active from high school. Most UNAD respondents only became sexually active in the university. It was also observed that some socio-economic factors like family resources,
stipends, where they grew up as children that set both institutions at the opposite end of the scale. UNAD had a good number of respondents from middle and high income families with unemployment at the barest minimum for both parents, many of them from big towns and capital cities. At the other end we have predominant number of UNIZULU respondents brought up in villages and rural areas and by low income or no income parents (or without parents).
However, certain factors appeared to define a bottom line of sexual activities for both institutions: multiple concurrent sexual relationships by both gender, not undergoing HIV testing and counselling, not knowing the HIV status of partners, inconsistent condom use and sex under the influence of alcohol or drugs. A small percentage of respondents from both institutions owned up to being involved in sex-for-money/favour, thus implying the concept of
‘undercover prostitution’ mentioned earlier in this thesis as well as inter-generational sexual relationships. It was also observed that the institutional support structures are different, with UNIZULU having a much better and effective support facilities than UNAD. Awareness, knowledge (of transmission and infection) and perception of preventive strategies are good for both campuses but the scale of risky sexual behaviours observed from their responses did not reveal that they translate their good knowledge to good use for their personal protection.
In addition to the above highlight, the Mann-Whitney non-parametric test on equality of means for all items in Sections C to I was carried out, in anticipation that the trend in statistical significance would make it possible to identify some key variables that promote safe sex (from Section C and D) and those that contribute to risk.
For those variable where P<0.05, the null hypothesis fails and such factor is taken as not contributing significantly to either positive or negative factors. Where P>0.05, the null hypothesis is accepted and such factors would contribute to the sexual risk promotion or risk aversion of each institution differently. The data is presented in Table 5.14. Since the items cover the entire spectrum of activities, attempts would be made to group them appropriately.
Three groups could be drawn from Table 5.14: Those that promote positive lifestyles, those that promote negative lifestyles and those that are built on misconceptions.
Table 5.14: Mann-Whitney non-parametric test on equality of means
Item No. SECTION
C D E F G H I
1 0.000 0.263 0.000 0.000 0.421 0.000 0.000
2 0.000 0.843 0.000 0.002 0.000 0.000 0.000
3 0.000 0.000 0.443 0.960 0.000 0.000 0.247
4 0.000 0.000 0.000 0.000 0.006 0.002 0.000
5 0.000 0.032 0.253 0.622 0.173 0.008 0.000
6 0.824 0.000 0.000 0.000 0.000 0.000 0.000
7 0.038 0.188 - 0.032 0.000 0.000 0.000
8 0.000 0.000 0.004 0.000 0.000 0.000 0.000
9 0.000 0.000 0.398 0.000 0.000 0.041 0.000
10 0.003 0.000 0.018 0.000 0.000 0.000 0.000
11 0.204 0.103 0.000 0.000 0.591 0.000
12 0.011 0.000 0.000 0.000 0.000 0.000
13 0.051 0.002 0.000 0.000 0.003 0.000
14 0.928 0.000 0.000 0.057 0.014 0.032
15 0.000 0.000 0.000 0.000 0.049 0.584
16 0.000 0.000 0.888 0.002 0.000
17 0.000 0.000 0.234 0.002
18 0.009 0.000 0.619 0.073
19 0.000 0.000 0.001 0.403
20 0.000 0.564 0.000 0.580
21 0.000
22 0.269
23 0.083
24 0.000
25 0.000
TOTAL 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Note: The first column should be read as sequence of items in each Section, e.g., for Section C, 1 should be read as corresponding to item C1, etc. Those items that contribute are in red.
Those that promote positive sexual lifestyles:
D1: Sexuality education in the high/secondary school
D2: During orientation in the university D7: Non-Governmental Organization activities on campus
D11: Television/radio advertisements D13: Friends
D14: Government programme F3: I stick to only one faithful partner F5: I use condom every time I have sex H11: By knowing the HIV status of partners before marriage
H18: By keeping the cultural value of remaing a virgin until marriage
H19: By not engaging in sex-for-money trade under any circumstance
H20: By avoiding friends who can influence you into undertaking risky sex
I3: Undertaking HIV test before marriage I15: Avoid sharing injection needles/blades
The six awareness items (D1, D2, D7, D11, D13 and D14) could be taken as those that would impact on each institution positively but not necessarily to the same extent. F3, F5, H11, H18, H19, H20, I3 and I15 are factors that measure the level of recognition of risk that they could be exposed to on their campuses and recognising them is good if doing so they keep to the positive and avoid occasions that could expose them to risk (e.g., F22). I3 and I15 are items ranked first and second by UNAD but ranked third and sixth by UNIZULU on perception of preventive strategies. The rejection of the null hypothesis showing that these items do not play equally to both campuses is therefore justified. They are, however, positive attributes to safe sex.
Those that reflect negative lifestyles
C6: Everyone is left to live independent lifestyle on campus E3: Freedom to have many sexual partners
E5: Many students have sugar daddies E9: Sex for money and material things E11: Difficulties to buy condoms
F16: I have had a few sexually transmitted infections in the past F20: Having several sexual partners is normal in our society F22: I can be raped
G1: Unprotected sex with infected partner(s) G17: A healthy looking person
G18: People with previous record of sexually transmitted infections (STIs)
Many of the items above are taken as core drivers of risky sexual activities on the campuses.
As mentioned earlier, E5 and E9 are more common in Nigeria than is obvious in South Africa.
One would also imagine that E11 may be more of a problem at UNAD than at UNIZULU, since UNIZULU had sponsors for free distribution of condoms. The positive response in
recognising that HIV could be transmitted through a healthy looking person (and through G1 and G18) is also important in averting risk.
Those that reflect misconceptions G5: Insect bites or domestic animal bites G14: Body sweats from an HIV-positive person
Obviously one would readily notice some evidence for misconception of transmission (G5, and G14). The type of misconception inherent from items G5 and G14 often leads to discrimination against those known to be HIV+ among students. This makes openness about one’s status difficult particularly if one is HIV+.
5.11 Discussion of results from inferential statistical analyses