Stigma and Discrimination versus HIV status
The second issue that the study sought to answer was the extent to which stigma and
discrimination are associated with an individual’s HIV status. In other words, do HIV
victims suffer significantly higher stigma and discrimination? To answer this issue, the
study analysed stigma and discrimination, resulting from distress, stress, anxiety and
depression based on the premise that stigma and discrimination manifest themselves in
significantly higher distress, stress, and anxiety and may lead into depression.
Data for this study revealed that 334 participants answered the items that probed stigma
and discrimination; but, the study was only able to match 311 (85%) of the participants
with their HIV status. Of that number, 66(21%) had tested positive for HIV while
245(79%) tested negative. The study investigated stigma and discrimination by anchoring
the concepts on six out of eight items listed under item eight. The sub-items were derived
from the research instrument numbered 8(a) – 8(f). The items listed were used to probe
depression, anxiety, distress, and stress and were measured as both internalised and enacted
stigma because both stigma and discrimination can occur and manifest themselves through
many physiological reactions. By employing a five-point scale, ranging from one (1) [Not at
all] to five (5) [A lot], the study measured stigma and discrimination and collated it with the
individual's HIV status. The reliability coefficients of the sub-scale measuring stigma and
discrimination consisting of 6 items were estimated to be approximately, α = .74.
To determine whether significant differences in stigma and discrimination were
experienced by individuals based on their HIV status, the study employed a one-way
ANOVA. The study utilised 311 participants, of whom 66 compared with 245 were HIV
positive and negative respectively. Table 4.10 shows the variable of interest, HIV status,
number of participants, the mean score and the standard deviation
Table Variable, HIV status, Mean scores, and Standard deviation among participants
Variable HIV Status N Mean SD
Avoided Positive 66 1.766 1.28
Negative 245 1.836 1.35
Doing Positive 66 1.65 1.16
Negative 245 1.91 1.36
Depression Positive 66 1.82 1.28
Negative 245 1.67 1.26
Lonely Positive 66 1.68 1.22
Negative 245 1.69 1.23
Upset Positive 66 1.74 .14
Negative 245 2.05 1.41
Sleepless Positive 66 1.71 1.12
Negative 245 1.93 1.36
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Table 4.10 shows that HIV negative participants had higher mean scores on all the variables
measured except for depression compared with HIV positive participants. This implies that
HIV infected persons suffer comparable levels of discrimination like that suffered by their
HIV negative colleagues; save that they suffer slightly higher stigmatisation. It is perhaps for
this reason that the WHO cites fear of discriminations and stigmatization as the main factors
that contribute to many people becoming reluctant to test for HIV to disclose their HIV status
and to prevent and treat the disease (WHO, 2011).
The study’s findings support the conclusion arrived at by Sayles in his study. He found that
participants with high levels of stigma have more chances (over four times) of reporting poor
access to care compared to those with low levels of stigma (Sayles, 2009). This AIDS-related
stigma and discrimination can contribute to increased disease incidence resulting in more
AIDS-related deaths globally. For instance, the implications of not testing for HIV is that
majority of the people get diagnosed when it is too late making prevention measures less
effective as the disease progression may have advanced to full-blown AIDS. This leads to
increased chances of not only infecting others but also causing early death. Table 4.11 shows
the results obtained from performing the one-way ANOVA.
Table The ANOVA Output Table
Sum of df Mean F Sig.
Squares Square
Avoided
Between Groups .26 1 .26 .148 .701
With-in Groups 548.92 309 1.78
Doing
Between Groups 3.48 1 3.48 2.002 .158
With-in Groups 537.01 309 1.74
Depression
Between Groups 1.15 1 1.15 .717 .398
Within Groups 496.04 309 1.61
Lonely Between Groups .00 1 .00 .001 .982
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Within Groups 463.12 309 1.50
Between Groups 4.89 1 4.89 2.649 .105
Upset
570.03 309 1.85With-in Groups
Between Groups 2.48 1 2.48 1.433 .232
Sleepless
535.35 309 1.73With-in Groups
From Table 4.11, all variables were positively associated with the HIV status of the
participants except for depression. In addition, the Results clearly indicate that the mean
scores for stigma and discrimination suffered by HIV positive participants compared with
HIV negative participants were not significantly different statistically; in that no variable
had ρ<0.05. Consequently, the study did not need to perform post hoc tests.
The study further investigated the correlation between the participant's HIV status on the
one hand and stigma on the other. Stigma pathways investigated were "being avoided"
(enacted stigma), and, avoid doing something (internalized stigma). These are manifested
through depression, loneliness, upset and sleeplessness. To test the proposed relationships
between enacted stigma and internalised stigma, structural equation modelling was used.
Asymptotic and re-sampling strategies were performed to explore whether relationships
exist between stigma and participants’ HIV status. Table 4.12 displays the results
obtained from the analysis.
Table 4. 12 Correlations between Stigma and participants’ HIV status
Variables Mean (SD) 1 2 3 4 5
1.Being Avoided 1.81 (1.33) 1.00
2. Avoid Doing 1.86 (1.32) 0.41** 1.00
3. Depression 1.70 (1.27) -0.07 0.21** 1.00
4. Lonely 1.68 (1.22) 0.05 0.27** 0.63** 1.00
5. Upset 1.98 (1.36) -0.03 0.23** 0.49** 0.61** 1.00
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Variables Mean (SD) 1 2 3 4 5
6. Sleepless 1.88 (1.32) 0.09 0.28** 0.52** 0.53** 0.60**
** Correlation is significant at the 0.01 level (2—tailed).
From Table 4.12 it can be seen that enacted stigma was positively correlated to internalised
stigma, loneliness and sleepless but not depression and upset. In addition, internalised stigma
was positively correlated to all the variables investigated. Depression was positively
correlated to loneliness, upset and sleeplessness; while loneliness was positively correlated to
upset and sleeplessness; and finally, upset was positively correlated to sleeplessness.
These results show that enacted stigma (that is, stigma experienced by an individual for
being discriminated by others) may lead to internalised stigma, loneliness and
sleeplessness but not to depression and upset. However, internalised stigma is worse in
that it can lead to depression, loneliness, upset, and sleeplessness. Consequently, care
providers should endeavour to create an environment that does not drive a HIV positive
individual to develop internalised stigma.
Further, it was necessary to develop a model in order to explain the amount of variation
in the dependent variable can be explained. Fitting a logistic regression model to the
stigma and discrimination associated with an individual’s HIV status: ln(p/1-p) = β0+
β1x1+ β2x2+ β3x3
Given
β0 , β1, β2, β3 are coefficients
x1- Depression
x2- Avoided
x3- Sleeplessness
Y=exp(β0+ β1x1+ β2x2+ β3x3)/1+ exp(β0+ β1x1+ β2x2+ β3x3)
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Where y is the odds of getting tested for HIV. The results are given in table 4.13
The key variables of interest are:
Dependent variable: Whether the respondent has tested for HIV or not (those tested were
indicated by1).
Explanatory variables: Avoided, depression and sleeplessness which had scores of 1-
5(1-strongly Agree, 2-Agree, 3-Undecided, 4-Disagree, 5- Strongly disagree),
