Transcript Zichire Project Overview - Resource Library Home Page

Partner Concurrency and
Implications for Behavior
Change Strategy in Zimbabwe
Danuta Kasprzyk, PhD, Susan Cassels, PhD,
Daniel E. Montaño, PhD, April Greek, PhD, Steven
Goodreau, PhD, Mufuta Tshimanga, MD, MPH,
Martina Morris, PhD
Centers for Public Health Research
and Evaluation
Department of Community Medicine
Context
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Data collected in conjunction with an
NIMH Trial to test an HIV/STD
prevention intervention
Behavioral and biological measures
Three data collection points:
– Baseline,12- and 24-month follow-up
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Add-on funding by NIAAA to examine
mediators of HIV risk behaviors
Results from the Baseline measures
Study Goals and Measures
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To collect data on mediators and to link
them to HIV-risk behavior
Survey measured:
– Demographics
– Overall sexual history; partner-by-partner
sexual history, including concurrency
– Condom use with different partners
– Behavioral mediators
• Attitudes, i.e., beliefs about monogamy
• Social support for monogamy
• Personal agency i.e, self-efficacy and
perceived control
• Intention to commit to monogamy
Integrated Behavioral Model (2008)
Experiential
Attitude
Knowledge and
skills to
perform the
behavior
Attitude
O
t
h
e
r
F
a
c
t
o
r
s
Instrumental
Attitude
Injunctive
Norm
Perceived Norm
Descriptive
Norm
Perceived
Control
Salience of
the Behavior
Intention or
Motivation to
Perform the
Behavior
Environmental/
cultural
Constraints
Personal Agency
SelfEfficacy
Habit
Behavior =
Monogamy
Final IBM Survey
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Measured mediators for each behavior
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5 point scales
Behavioral intention/motivation
Direct attitude: 3 semantic differential items
Indirect attitude: 9-14 behavioral beliefs
Perceived norm: 4-6 normative beliefs
Perceived Control direct: 1 semantic differential
item
– Self-efficacy direct: 1 item
– Self-efficacy indirect: 6-11 self-efficacy beliefs
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Monogamy Attitude Scale
– Direct attitude: 3 items
– Beliefs – 11 items
Methods
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Accrued cohort through purposive selection
of approximately 185 individuals in each of
30 Growth Points
Individuals recruited from venues where
individuals socialize
Conducted Baseline
Personal Interview Assessment:
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–
–
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Demographic, Behavioral risks, Sexual history
IBM mediators
Health Assessment, including STD symptoms
Biologic samples (Bacterial and Viral STDs)
People shopping at Gokwe Growth Point
Shops at Dema Growth Point
Growth Point Recruitment Sites
Local women selling vegetables outside a
store at Nedziwa Growth Point
Men drinking Chibuku at a bottle store in Mamina
Growth Point
.
Prevalence of STIs (n = 4,197)
STI
Chlamydia
Gonorrhea
Syphilis
Trichomoniasis
Herpes Simplex 2(1.1)
Herpes Simplex 2(3.5)
HIV
N positive
197
132
51
350
1698
1272
1034
Co-Infection with 2 or more STIs = 23%
Percent
4.8
3.3
1.2
17.4
40.8
32.4
24.8
Participants who ‘ever had sex’
N = 4,148
Males
(51.4%)
Age at first sex
18.3
16.8
3
Females
(48.6%)
18.0
22.8
2
Ever had
transactional sex
11%
5%
Know how to use
condom
87%
58%
Age of first partner
Median lifetime
partners
16% had concurrent partners in the past year
Participants who ‘ever had sex’
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Overall: 25% drank in the past 30 days
– 11% get drunk 5 or more times a month
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Overall: 16% had concurrent partners in past
12 months
– 25% men; 7% women
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Individuals with concurrent relationships
were:
– Younger at first sex (17 vs. 18)
– Had more total number of partners on average
– Drank for a greater number of days per month;
7 days compared to 2 days
– More likely to get drunk; 42% compared to 13%
Participants with concurrent relationships:
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Were significantly more likely to have
trichamonasis gonorrhea, syphilis, and HIV
Had higher HIV prevalence 30% compared to
24% in those who did not have concurrent
partners
Not more likely to have HSV2, chlamydia
Overall, condom use rates with main or steady
partners are low (only 5-8% used consistently)
Overall, condom use motivations with main or
steady partners are also low
But, individuals with concurrent partners are
significantly more likely to say if they don’t use
condoms with main partners that they are at
risk for STD and HIV acquisition
Sub-sample Analysis
All sexually active men
IBM Comparisons made between:
- those with concurrent partners
- to those without concurrent partners
Participant Characteristics
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2169 men total
540 men had concurrent partnerships
Mean age: 22.76 years
Had the same number of years of schooling
Significantly younger at first sex (17 vs. 18)
Significantly higher median number partners:
– Lifetime: 7 partners (vs. 3)
Individual Indicator Analysis
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Identify key beliefs underlying each IBM
construct to compare men with concurrent
relationships to those not having them
– Behavioral beliefs underlying attitude
– Normative beliefs underlying perceived norm
– Self-efficacy beliefs underlying self-efficacy
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Analytic procedure
– Separate analysis for each construct with each
behavior (especially monogamy)
– Correlations of beliefs with monogamy behavior
– Comparisons of mediators between men
Monogamy Behavioral Expectations/Intentions
Monogamy
Expectations
% strongly agree
Non
r
Concurrent
Concurrent
Motivation to stick to one partner
95%
76%
Expectation main partner is monogamous
65%*
66%*
Spouse expects monogamy
98%*
96%*
Your self standard re: monogamy w spouse
98%
85%
Your spouse has other partners besides you
23%
13%
Steady partner (SP) expects monogamy
96%
90%
Your self standard re: monogamy w SP
96%
79%
Your SP has other partners besides you
18%
22%
* Non Significant
Behavioral Beliefs with Monogamy Behavior
Monogamy
Behavioral Beliefs
% strongly agree
Non
concurrent
Concurrent
13%
22%
Not be sexually satisfied
3%
9%
Does not fit into our culture
6%
10%
Difficult because you have high sex drive
3%
10%
Difficult since traditional for multiple partners
9%
14%
Makes men less manly
6%
10%
You will not get HIV
61%*
63%*
Something you cannot commit to
9%
22%
Would get sick
4%
7%
Would lose prestige or standing in community
4%
7%
Not get variety in sex partners you need
* Non Significant
Normative Beliefs with Monogamy Behavior
Monogamy
Normative Influence Beliefs
% strongly agree
Non
concurrent
Concurrent
Your family
96%
92%
Your closest friends
95%
88%
Your church
97%
86%
Your culture
97%
94%
Radio shows or dramas
96%*
94%*
Spouse
98%*
96%*
* Non Significant
Self-Efficacy with Monogamy Behavior
Monogamy
Self-Efficacy Beliefs
% strongly agree
Non
concurrency
Concurrency
Talking about it with partner
90%
76%
Trust partner is also monogamous
88%
77%
You and partner being apart a lot
80%
63%
Partner did not want sex as often as you
82%
61%
You spot a beautiful girl
81%
66%
CSWs entice you
86%
79%
Wife or steady partner being pregnant
85%
74%
Implications for Interventions
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These types of analyses allow one to
identify specific beliefs/mediators most
highly associated with motivations or
behaviors
Intervention messages can be designed
to focus on these beliefs using
communication media most appropriate
to the target audience
In addition, other mediators that
differentiate those with concurrency
versus none, can also be targets of
interventions (alcohol use)
Summary: Intervention Targets
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Attitudinal beliefs that differentiate men who
do not have concurrent partnerships, from
those who do:
– Are important to target in intervention messages
– May be most important to target first
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Interventions should include additional beliefs
differentiating these men such as,
– Normative beliefs
– Convince men their spouse, families, friends,
churches all support behavioral strategies to avoid
concurrency
– Self-efficacy beliefs can also be targeted
Implications for Interventions
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Broader applications using communication
techniques can be used to change beliefs most
highly associated with motivations or behaviors
Intervention messages using mass media, small
print media, the internet, interpersonal,
provider/patient, etc. (any communication
medium) can be designed to focus on these
beliefs
Beliefs more universally held lend themselves to
mass media approaches
Beliefs held by specific audience segments
should lead to tailored intervention messages
implemented using a more personal
communications strategy, i.e. counselors,
providers, among others
Zimbabwe
Zimbabwe
ACKNOWLEDGEMENTS
Funded by: NIAAA, NIMH
Battelle Team:
Lisa Cubbins, PhD (PI – NIAAA grant: Alcohol Study)
Terry Johnson, VP, CPHRE
William Grady, Seattle site manager
ZiCHIRe Team:
Mufuta Tshimanga, MD, MPH, director Zichire
Godfrey Woelk, PhD (Co-PI POL intervention)
Philani Moyo and Ethnography Team
Reggie Mutsindiri and Nurses Team
Patrick Mateta and Lab Team
Walter Chikanya and Intervention Team
Pesenai Chatikobo and Process Evaluation Team
Rachel Gatsi and Transcription Team
Gay Hendrikse and Admin Staff
Gift Mutepfe and Driving Team
POL and Alcohol Study Participants