1
Evaluation of Factor Structure and Validity of HIV Knowledge Questionnaire
By
Talwar P1, Ghazalia SR 2, Ahmad R3 & Mohd Fadzil AR4
Dr. Prashanth Talwar1Ph.D
Associate Professor
Universiti Malaysia Sarawak
94300 Kota Samrahan.
Dr. Siti Raudzah Ghazalia 2Ph.D
Associate Professor
Universiti Malaysia Sarawak
94300 Kota Samrahan.
Dr. Rusli Ahmad 3 Ph.D
Dean (PPP) and Associate Professor
Universiti Malaysia Sarawak
94300 Kota Samrahan.
Prof. Mohd Fadzil Abdul Rahman4MA
Deputy Vice Chancellor and Professor
Universiti Malaysia Sarawak
94300 Kota Samrahan.
Corresponding Author
Dr. Prashanth Talwar1Ph.D
Associate Professor
Universiti Malaysia Sarawak
94300 Kota Samrahan.
drpytalwar@yahoo.com
Statistical summary of the manuscript
Total Number of words: 3707.
Number of words in abstract: 155
Number of references: 25
Number of Tables: 2
2
Evaluation of Factor Structure and Validity of HIV Knowledge Questionnaire
Abstract
Background: HIV is a major social problem which can be prevent, unfortunately many young
adults lack comprehensive and adequate knowledge. There are many scales available to measure
knowledge on HIV. The brief HIV Knowledge Questionnaire (HIV-KQ-18) was designed to
provide a more concise and well-established measure of HIV-related knowledge. The objective
of this study is to assess the factor structure and internal consistency of the HIV-KQ-18 among
university students in Malaysia. Method: The study was conducted in one of the Universities in
Malaysia. Questionnaires and the HIV-KQ-18 scale was distributed in the class room and taken
back on completion. 405 students completed the questionnaires and the scale in all respects.
Results: Factor analysis explained 58.35 % of the variance and items clustered together into
subscales. The internal consistency was 0.60. Conclusion: The HIV-KQ-18 scale was easy to
understand with 71% correct answers. The internal consistency of the scale is considered under
lower limit of acceptability.
Key Words: Knowledge. HIV Scale. Factor Analysis. Internal consistency.
3
Factor Analysis of HIV-KQ-18 among a group of Malaysian University Students
Introduction
HIV/AIDS is a major public health problem. Every day, more than 10 Malaysians are tested
positive for HIV infection
[1]
. The continuous increase in number of people living with
HIV/AIDS (PLWHA) represents a serious health and economic burden
[2]
. The increasing trend
of premarital sexual experience and unintended pregnancies in Malaysia warrants sustained and
serious attention
[3]
. HIV is a stigmatizing medical condition. The concept of HIV stigma is
multifaceted, with personalized stigma (perceived stigmatizing consequences of others knowing
of their HIV status), disclosure concerns, negative self-image, and concerns with public attitudes
described as core aspects of stigma for individuals with HIV infection [4].
Knowledge is a crucial factor of HIV risk reduction. Many teenagers are knowledgeable about
the risks and consequences of HIV, yet a large percentage do not perceive that they are
personally at risk. Gaining insight into the perceptions and factors influencing the behavior of
teens is critical in HIV and AIDS prevention
[5]
. The stigma of and discrimination because of
HIV has been described as the most important obstacle to prevention and treatment efforts
Bandura
[7]
[6]
.
emphasized that prevention of infection with the AIDS virus requires people to
exercise influence over their own behavior and their social environment. Societal efforts
designed to control the spread of AIDS have centered mainly on informing the public on how the
human immunodeficiency virus (HIV) is transmitted and how to safeguard against such
infection. It is widely assumed that if people are adequately informed about the AIDS threat they
will take appropriate self-protective action. Bandura [7] maintains that heightened awareness and
knowledge of health risks are important preconditions for self-directed change. Unfortunately,
information alone does not necessarily exert much influence on refractory health-impairing
4
habits. To achieve self-directed change, people need to be given not only reasons to alter risky
habits but also the behavioral means, resources, and social supports to do so. Effective selfregulation of behavior is not achieved by an act of will. It requires certain skills in selfmotivation and self-guidance.
In the context of the evaluation of prevention programs, it is necessary to have valid, reliable and
parsimonious instruments to assess the degree of knowledge in the target population. Few
questionnaires are specifically designed for adolescents. This means that the information content
on HIV/AIDS is not necessarily the most appropriate for this population and the psychometric
properties of the scale are not guaranteed for use with adolescents [8].
The HIV Knowledge Questionnaire originally developed by Carey and Schroder
[9]
consists of
45 items and known as HIV-KQ-45. Although the HIV-KQ-45 is psychometrically strong, it is
impractical for street outreach, field surveys, and intervention evaluation work in settings where
evaluators also wish to assess knowledge as well as other constructs with minimum respondent
burden. Needed is a briefer, but psychometrically well-established measure
[9]
. The brief HIV
Knowledge Questionnaire (HIV-KQ-18) was designed to provide a more concise and wellestablished measure of HIV-related knowledge in street outreach, fieldwork, and intervention
settings. The scale aims to tap into other related constructs, for which the original HIV-KQ 45item scale did not address [9].
One of the factors that influence risk behavior among students is their HIV/AIDS knowledge.
The objective of this study is to assess the factor structure and internal consistency of the HIVKQ-18 among university students in Malaysia.
5
MATERIALS AND METHODS
Participants:
The study was conducted in one of the Universities in Malaysia. The
undergraduate students who volunteered to participate in the study were explained about the
purpose of the study and implications. The students were assured anonymity and were told to
respond honestly. Study was approved by university research committee.
Sample: Questionnaires and the scale was distributed in the class room and taken back on
completion. 405 students completed the questionnaires and the scale in all respects.
Instrumentation:
The HIV Knowledge Questionnaire (HIV-KQ-18) has 18-items. It is a brief self-administered
measure of the individual's HIV-related knowledge. This instrument contains 18 forced-choice
statements ('true', 'false', 'don't know') knowledge related to sexual transmission. A single
summary score is yielded overall, with higher scores significant of greater HIV-related
knowledge. ‘Don’t know’ response are scored incorrect.
Analysis
SPSS version 21 was used to analyze the data. Kaiser-Meyer-Olkin (KMO) measure of sampling
adequacy suggests that pattern of correlation are relatively compact and so factor analysis should
yield distinct and reliable factors. KMO value is 0.617, which is considered mediocre.
Bartlett’s test of sphericity was 2=629.47 (df=153, p<0.000). In this study, the sample inter
correlation matrix did not come from a population in which the inter correlation matrix is an
identical matrix. There was no correlation error among the variables.
6
Exploratory factor analysis, with varimax rotation, was applied to the data. Eigen values above
1.00 were used. The criterion for factor loading was set at ≥ 0.40 to suppress absolute value less
than 0.40.
Principle component analysis was used as extraction method. Factor loadings and screen plot
were examined. One good method of screening for efficient items is to run an exploratory factor
analysis on all the items to eliminate those variables that failed to show high correlation [10].
Cronbach’s alpha [11] was used to find the internal consistency of the scale. Cronbach's alpha is
an index of reliability associated with the variation accounted for by the true score of the
"underlying construct." Construct is the hypothetical variable that is being measured
[12]
. The
higher the score, the more reliable the generated scale is.
Results
The mean age of students was 21 years. 42% were male students while 58% were female
students. 2% were Hindus’, 4% Buddhists’, 33% Christians’ and 61% Muslims’. 42% were male
students while 58% were female students.
Percentage of correct answer.
As seen in Table No. 1, the mean and standard deviation varied from individual items. Frequency
of correct answers differed from one item to another. The total mean score was 12.81. (71 %
correct ).
7
Table No. 1
HIV-KQ-18: Individual item mean and standard deviation
ITEM
1
Mean
Coughing and sneezing DO .74
SD
.43
NOT spread HIV
2
A person can get HIV by .81
.38
sharing a glass of water with
someone who has HIV
3
Pulling out the penis before a .69
.46
man climaxes/cums keeps a
woman from getting HIV
during sex
4
A woman can get HIV if she .79
.40
has anal sex with a man
5
Showering, or washing one’s .81
.38
genitals/private parts, after
sex keeps a person from
getting HIV
6
All pregnant women infected .21
with HIV will have babies
born with AIDS
.41
8
7
People
who
have
been .81
.38
infected with HIV quickly
show serious signs of being
infected
8
There is a vaccine that can .67
.46
stop adults from getting HIV
9
People are likely to get HIV .72
.44
by deep kissing, putting their
tongue in their partner’s
mouth, if their partner has
HIV
10 A woman cannot get HIV if .83
.37
she has sex during her period
11 There is a female condom .61
.48
that can help decrease a
woman’s chance of getting
HIV
12 A
natural
skin
condom .67
works better against HIV
than does a latex condom
.46
9
13 A person will NOT get HIV .71
.45
if she or he is taking
antibiotics
14 Having sex with more than .94
.22
one partner can increase a
person’s chance
of being infected with HIV
15 Taking a test for HIV one .56
.49
week after having sex will
tell a person if she or he has
HIV
16 A person can get HIV by .84
.36
sitting in a hot tub or a
swimming pool with a
person who has HIV
17 A person can get HIV from .56
.49
oral sex
18 Using Vaseline or baby oil .84
with condoms lowers the
chance of getting HIV
Total Score
(71 % correct)
12.81
.36
10
Factor Structure of HIV KQ-18
The overall results from the Exploratory Factor Analysis are presented in Table 2. The HIV-KQ18 was factor analyzed; Principal Component Analysis was used to explore factor structures. The
seven factor solution accounted for 55.79 % of the total variance. Item No. 4 failed to load.
Factor analysis was redone by eliminating item No. 4, the total variance increased to 58.35 %.
It was found that the loadings ranged from 0.43 to 0.83. Majority of the loading was >0.40. Only
one item (7) showed poor loading (0.432). Varimax rotation was applied resulting in 7 subscales
solutions.
The first factor accounted for 13.67 % of the variance and included four items 6,7,12 & 13.
The second factor accounted for 10.21 % of the variance and included three items 9, 16 & 17.
The third factor accounted for 8.00 % of the variance and included two items 3 & 5.
The fourth factor accounted for 7.28 % of the variance and included two items 1&18
The fifth factor accounted for 6.74 % of the variance and included two items representing items
2 &11.
The sixth factor accounted for 6.46 % of the variance and included two items 10 & 14.
The seventh factor accounted for 5.99 % of the variance and included two items 8 &15.
Internal consistency
Cronbach’s α was 0.40. If items with low homogeneity index (HI) were to be deleted it is
presumed that there would be substantial increase in alpha. Item No. 4,6,11,15 & 17 were deleted
and it was found that the Cronbach’s α increased substantially to 0.60.
11
Discussion
HIV/AIDS knowledge is an important component of HIV/AIDS risk prevention strategies that
may influence engagement in high risk behavior
[13]
. One property that may drive this inference
process is the degree to which the content of knowledge on which the attitude is based is directly
relevant to the goal of the behavior [14].
Because knowledge is a key component of HIV risk reduction programs, interventions often use
knowledge assessment guide educational curricula and to provide feedback to enhance risk
awareness [15].
The relationship between risk knowledge, attitude, and behavior among different population
groups is complex and has not been sufficiently explored [16]. HIV scales are useful to determine
the effectiveness of education provided to different groups. There are many scales to measure
HIV knowledge, 11 item HIV risk-taking behavior scale (HRBS)
[17]
, the 14-item human
immunodeficiency virus/acquired immunodeficiency syndrome knowledge scale
[18]
, the
perceived risk of HIV scale (PRHS) [19] and the HIV/AIDS Knowledge and Attitudes Scales for
Teachers [20].
The HIV knowledge questionnaire
[21]
, is a self –administered instrument. It consisted of 45
items. The 45 item scale was reduced to 18 item scale based on empirical item analysis, called as
the HIV-KQ-18 scale. It is easy to understand at 7th grade level and can be used across cultures.
A single summary score is obtained by summing the number of items correctly answered. Carry
reported correlation that ranged from .24 to .57. and found that the internal consistency ranged
from .75 to .89 across samples.
12
The objective of this study is to assess the factor structure internal consistency and of the HIVKQ-18 among university students in Malaysia.
It appears that there was no difficulty in understanding the content of the HIV-KQ-18 scale
among Malaysian students. Only one item ie “All pregnant women infected with HIV will have
babies born with AIDS” had a low percentage of correct answer (22%). This is consistent with a
similar study done by Swenson et al
[22]
among African American Adolescents, who reported 85
% of the students thought that all pregnant women infected with HIV will have babies born with
AIDS. Overall, 71 % correct answers on an 18 item scale in this study is reasonable good
enough.
Factor analysis was done to see whether items clustered together into subscales. Results of this
study found that the HIV-KQ-18 had seven factors which explained 58.35 % of the variance.
Factor I explained 13.67 % variance. Factor II explained 10.21 % variance. Factor III explained
8.00 % variance. Factor IV explained 7.28 % variance. Factor V explained 6.74 % variance.
Factor VI explained 6.46 % variance. Last Factor 7 explained 5.99 % variance.
Cronbach’s alpha is generally used as a measure of the reliability of a set of questions in a survey
instrument. It measures the interrelatedness of a set of items, although a high value for alpha
does not imply uni-dimensionality (where the items measure a single latent construct)
Consider the typical assessment by a researcher who achieves an alpha that
[10]
.
exceeds .70 and
concludes, based on Nunnally’s[23] rule-of-thumb, that the level of reliability is “sufficient”.
What Nunnally[23] actually said is that “in the early stages of predictive or construct validation
research,” it may be “satisfactory” to “have only modest reliability. For other scenarios,
Nunnally
[23]
goes on to state that .80 or even .90 may be required. Further, if one computes an
13
alpha equal to .70, with a confidence interval that ranges from .60 to .80, it is not so obvious that
an “acceptable level of reliability” has been achieved [11].
Carry [9] reported that the stability coefficients varied between .75 to .89, providing evidence for
satisfactory to excellent reliability of the test scores. In this study the internal consistency was
0.60 which is considered lower limit of acceptability. The reason why Cronbach's alpha was low
could be because of the number of items in the scale. If the items in the scale is too short, the
value of alpha is reduced
[24]
. Increasing the number of items can increase the value of alpha to
an acceptable level. This reveals that the scales with a greater number of items are more reliable.
In this study the random error was 0.64. It is a well-known fact that random error can affect the
degree of reliability. Where there is very little random error, the measure is reliable [25].
Conclusion and Future research.
The findings of this study may be interpreted in with its limitations. This study was conducted on
a homogeneous sample of undergraduate student from only one university and the small sample
size was substantially small. The HIV-KQ-18 scale was easy to understand with 71% correct
answers. Factor analysis showed items clustered together into subscales. The internal consistency
was 0.60 which is considered lower limit of acceptability. Replication of this study need to be
done among different group of population to test the internal consistency of the HIV-KQ-18
scale.
14
TABLE No.2
Exploratory Factor Analysis [Malay version of the HIV-KQ-18 with English translation]
ITEM
1
F1
F2
F3
Coughing and sneezing DO
F4
F5
.768
NOT spread HIV
2
A person can get HIV by
.568
sharing a glass of water with
someone who has HIV
3
Pulling out the penis before a
0.784
man climaxes/cums keeps a
woman from getting HIV
during sex
4
A woman can get HIV if she
has anal sex with a man
5
Showering, or washing one’s
genitals/private parts, after
sex keeps a person from
getting HIV
6
All pregnant women infected .698
with HIV will have babies
born with AIDS
0.565
F6
F7
15
7
People
who
have
been .432
infected with HIV quickly
show serious signs of being
infected
8
There is a vaccine that can .510
0.525
stop adults from getting HIV
9
People are likely to get HIV
0.717
by deep kissing, putting their
tongue in their partner’s
mouth, if their partner has
HIV
10 A woman cannot get HIV if
0.451
she has sex during her period
11 There is a female condom
.413
.661
that can help decrease a
woman’s chance of getting
HIV
12 A
natural
skin
condom .433
works better against HIV
than does a latex condom
.529
16
13 A person will NOT get HIV .629
if she or he is taking
antibiotics
14 Having sex with more than
.832
one partner can increase a
person’s chance
of being infected with HIV
15 Taking a test for HIV one
.810
week after having sex will
tell a person if she or he has
HIV
16 A person can get HIV by
0.602
sitting in a hot tub or a
swimming pool with a
person who has HIV
17 A person can get HIV from
0.603
oral sex
18 Using Vaseline or baby oil
with condoms lowers the
chance of getting HIV
0.614
17
REFERENCES
1.
Han N & Htet A. Knowledge and Attitude of HIV/AIDS Infection among Medical
Students. Int. J. of Collaborative Research on Intern. Med. & Public Health
(IJCRIMPH). 2012; 4 (4): 317-326.
2.
Khan SA, Moorthy J, Omar H & Hasan SS. People living with HIV /AIDS (PLWHA)
and HIV/AIDS associated oral lesions; a study in Malaysia. BMC Public Health
[Internet]. 2012; 12:
850.
Available
from:
http://www.biomedcentral.com/1471-
2458/12/850
3.
Wong Li-Ping. An exploration of knowledge, attitudes and behaviours of young multiethnic Muslim-majority society in Malaysia in relation to reproductive and premarital
sexual practices. BMC Public Health [Internet]. 2012; 12: 865. Available from
http://www.biomedcentral.com/1471-2458/12/865
4.
Wiklander
M , Rydström L ,Ygge B , Navér L ,Wettergren L , Eriksson
L.
Psychometric properties of a short version of the HIV stigma scale, adapted for children
with HIV infection. Health & Qual. Life Outcomes. 2013; 11(1): 1-16.
5.
Facente AC. Adolescents and HIV: knowledge, behaviors, influences, and risk
perceptions. J. Sch. Nurs. 2001; 17(4):198-203.
6.
Wang G, Wada K, Hoshi K, Sasaki N, Ezoe S & Satoh T. Association of Knowledge of
HIV and Other Factors with Individuals’ Attitudes toward HIV Infection: A National
Cross-Sectional Survey among the Japanese Non-Medical Working Population. PLOS
ONE [Internet]. 2013; 8(7): e68495. Available from: http://www.plosone.org
18
7.
Bandura A. (1994). Social cognitive theory and exercise of control over HIV infection.
In R. J. Di Clemente and J. L. Peterson (Eds.), Preventing AIDS: Theories and methods
of behavioral interventions. New York: Plenum.
8.
Espada JP, Huedo-Medina TB, Orgilés M, Secades R, Ballester R, & Remor E.
Psychometric properties of the HIV/AIDS Knowledge Scale for Spanish adolescents
(HIV-KS). Health Addict. 2009, 9(2): 149-164.
9.
Carry MP & Schoder K.E.E. Development and Psychometric Evaluation of the Brief
HIV Knowledge Questionnaire. AIDS Edu. Prev. 2002; 14: 174-184.
10. Cortina J M. What is coefficient alpha? An examination of theory and applications. J.
Appl. Psycol. 1993; 78: 98–104.
11. Iacobucci D & Duhachek A. Advancing Alpha: Measuring Reliability. J. Cons.Psycol.
2003; 13(4): 478–487.
12. Balogun JA, Abiona TC, Lukobo-Durrell M, Adefuye A, Amosun S, Frantz J, Yakut Y.
Educ Health (Abingdon). Evaluation of the content validity, internal consistency and
stability of an instrument designed to assess the HIV/AIDS knowledge of university
students.
Epub
2010
[Internet];
23(3):400.
Available
from:
http://www.ncbi.nlm.nih.gov/pubmed/21290359
Kerlinger FN. (1995). Foundations of Behavioral Research. 3rd Edition. Bangalore.
Prism Books Pvt. Ltd.
13. Anderson KG & Beutel MA. HIV/AIDS Prevention Knowledge among Youth in Cape
Town, South Africa. J. Soc. Sci. 2007; 3 (3): 143-151.
19
14. Fabrigar LR, Petty RE, Smith SM & Crites SL. Understanding Knowledge Effects on
Attitude-Behavior Consistency: The Role of Relevance, Complexity, and Amount of
Knowledge. J. Person. and Soc. Psycol. Copyright 2006 by the American Psychological
Association. 2006; 90(4): 556–577.
15. Carry MP, Lewis BP. Motivational strategies can augment HIV-risk reduction
programs. AIDS Behav. 1999;3:269-276.
16. Khachkalyan T, Petrosyan V & Soghikian K. Association Between Health Risk
Knowledge and Risk Behaviour Among Medical Students and Residents In Yerevan. J.
Health Promot. 2006; 4(2): 197-206.
17. Darke S, Hall W, Heather N, Ward J, Wodak A. The reliability and validity of a scale to
measure HIV
risk-taking behavior among intravenous drug users. AIDS.1991;
5(2):181-5.
18. Aaro L, Breivik K, Klepp KI, Kaaya S, Onya HE, Wubs A, Helleve A, Flisher A. An
HIV/AIDS knowledge scale for adolescents: item response theory analyses based on
data from a study in South Africa and Tanzania. Health Educ. Res. 2010. 26(2); 212224.
19. Napper LE, Fisher DG, & Reynolds GL. Development of the perceived risk of HIV
scale. AIDS Behav. 2012; 16(4):1075-83.
20. Fisher, T. D., Davis, C. M., Yarber, W. L, & Davis, S. L. (2010). Handbook of
Sexuality-Related Measures. In New York: Routledge.
21. Carry MP, Morrison-Beedy D, Jphnson BT. The HIV-Knowledge Questionnaire:
Development and evaluation of a reliability, valid, and practical self-administered
questionnaire. AIDS Behav. 1997; 1: 61-74.
20
22
Swenson RR, Rizzo CJ, Brown LK, Vanable PA. Carey MP. HIV Knowledge and its
contribution to Sexual Health Behavior of Low income African American Adolescents.
23. Nunnaly, J. (1978). Psychometric theory. New York: McGraw-Hill.
24. Tavakol M and Dennick R. Making sense of Cronbach’s alpha. Int. J. Med. Educ. 2011;
2: 53-55.
25. Vaus DD (2002). Analyzing Social Science Data. London. Sage.