Development and Pilot Testing of a Combination Intervention to Reduce Heavy Drinking and Improve HIV Care Engagement Among Fisherfolk in Uganda
Phase: NA
Conditions: Alcohol Use Disorder, HIV-infection/Aids
Sponsor: San Diego State University

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Protocol 
 
Development and Pilot Testing of a Combination Intervention to Reduce Heavy 
Drinking and Improve HIV Care Engagement among Fisherfolk in Uganda 
 
 
ClinicalTrial.gov study number: NCT03919695 
 
 
Funding: National Institute on Alcohol Abuse and Alcoholism (NIH), grant number: 
R34AA025891 
 
 
Protocol date: January 17, 2023 
 
Clinical trial study period: January 2021-October 2022 
 
Institutional Review Board (IRB) approval numbers: 
Makerere University School of Public Health (MakSPH) Higher Degrees Research and 
Ethics Committee (HDREC): Protocol number: 647 
San Diego State University Institutional Review Board: Protocol number: HS-2018-0136 
 
Uganda National Council for Science and Technology approval registration reference 
number: SS 4908 
 
  
Principal Investigator:  
Susan M. Kiene, PhD, Professor of Global Health, Department of Epidemiology & 
Biostatistics, San Diego State University, USA 
Co-Investigators: 
Nazarius Mbona Tumwesigye, PhD, Associate Professor and Chair, Department of 
Epidemiology and Biostatistics, Makerere University School of Public Health, 
Kampala, Uganda 
Rhoda K. Wanyenze, MBChB, MPH, PhD, Associate Professor and Dean, 
Department of Disease Control and Environmental Health, Makerere University 
School of Public Health, Kampala, Uganda 
Barbara Mukasa, MBChB, MPH, Executive Director, Mildmay Uganda, Kampala, 
Uganda 
Judith Hahn, PhD, Professor, Department of Medicine, The University of California 
San Francisco, CA, USA 
Chii-Dean Lin, PhD, Associate Professor of Statistics, San Diego State University, 
USA 
Elizabeth Reed, ScD, MPH, PhD Associate Professor of Global Health, Division of 
Health Promotion and Behavioral Science, San Diego State University, USA 
Katelyn Sileo, PhD, MPH, Assistant Professor, University of Texas San Antonio, USA 
 
  
  
 

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1. Background and rationale 
Alcohol use is inextricably linked to the HIV epidemic in fishing communities on Lake Victoria 
in Uganda, where HIV incidence among regular drinkers is 5 times higher than among non-
drinkers.1  Fishing communities are an HIV “hotspot;” HIV prevalence in fishing communities 
is estimated at >25%2-4 compared to the national prevalence of 7.3%.5 Prevalent alcohol 
consumption is also consistently reported across a range of studies with fisherfolk in 
Uganda3, 4, 6-8 and hazardous and harmful alcohol use, especially among fisherfolk men, is 
dramatically more prevalent (37%)6 than in the general population (5.8%).9 In our preliminary 
research Among the 61% of men who reported alcohol use, 60.2% had AUDIT scores (>7) 
indicative of hazardous/harmful alcohol use and 16% had AUDIT scores (>16) indicative of  
a high level of alcohol problems.6  Heavy alcohol use is especially problematic among 
individuals living with HIV as it leads to poor treatment outcomes10 and is associated with 
suboptimal antiretroviral (ART) adherence and engagement in care.11-13 
 
Like much of Uganda’s economy, fishing villages operate on a cash economy; workers get 
daily cash payments for their work but have limited mechanisms for savings due to a lack of 
access to traditional banking infrastructure. Poverty and stressful work conditions paired with 
easy access to alcohol and cash with no means of savings (i.e., access to banks, savings 
accounts) may be drivers of alcohol consumption among fisherfolk men.14 Moreover, 
frequent mobility and work responsibilities, a lack of social support, HIV stigma, and distance 
to the clinic have been shown to impede access to HIV care services among fisherfolk.15, 16 
Given the unique context of heavy alcohol use and challenges with engaging fisherfolk men 
in HIV care, a combination intervention, which addresses structural as well as behavioral 
factors may be needed for this population. 
 
We propose to develop and pilot a brief combination intervention called Kisoboka which 
addresses the key drivers of alcohol use and barriers to HIV care engagement and ART 
adherence in this population. We address these multi-level factors in an intervention which 
combines behavioral components to promote behavior change with a structural component 
which changes the mode of work payments from cash to mobile money, to reduce “cash in 
the pocket,” and increase the accessibility of savings through mobile phone-based banking 
services. For the behavioral components, we will combine and adapt two efficacious alcohol 
interventions to the cultural and situational context of this population: a brief Motivational 
Interviewing (MI)-based intervention tested in Kenya17 and an intervention rooted in 
behavioral economics.18 The latter intervention focuses on increasing the extent to which 
individuals’ behavior is motivated by and consistent with their long-term goals such as saving 
money for the future—in which we will interweave the structural component of the 
intervention. 
 
2. Specific objectives 
Objective 1. Use formative research with fisherfolk men living with HIV and community 
stakeholders to adapt and develop a behavioral intervention Kisoboka (“It is possible!”)  to 
reduce heavy alcohol use and promote engagement in HIV care and ART adherence among 
fisherfolk men living with HIV. 
Objective 1b. Further refine the intervention through an initial pilot test with 15  
participants examining feasibility and acceptability. 
 
Objective 2. Pilot the Kisoboka intervention, randomizing to the Kisoboka intervention arm 
(n=80) or to the control arm (n=80, alcohol screening and referral). We will assess feasibility, 
acceptability, and preliminary estimates of the potential for the intervention, as compared to 
control, to decrease heavy drinking frequency and improve HIV care engagement and ART 
adherence through 6-month follow-up among this key population.  

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3. Methodology 
3.1 Setting and population. 
Research setting. The study will be conducted in Wakiso District, Uganda which is on the 
northern side of Lake Victoria. Our team has conducted several studies in fishing 
communities in this district. Majority of residents of fishing villages work in the fishing 
industry and individuals receive daily cash payments for their work. The study will take place 
at 5 HIV clinics in Wakiso District which serve large populations of fisherfolk. Fisherfolk 
include fishermen, fish traders, fish processors, fish loaders, boat/fishing equipment 
repairmen, and other workers who engage in work supporting the fishing industry within the 
fishing communities. As of May 2018, there were over 1,700 adult male patients on ART at 
these clinics. 
 
Study population. The study population is fisherfolk men aged 18-50 who engage in heavy 
alcohol use. The age range focuses on men who are the most high risk group for HIV and 
unhealthy alcohol use.5, 9 
 
 
Inclusion criteria: men aged 18-50; work as a fisherman, fish trader, fish processor, fish 
loader, related occupation supporting the fishing industry; living with HIV; on antiretroviral 
treatment for at least 1 month, report missing 1 or more dose of ART in the prior 2 weeks;  
Alcohol use criteria: consumed 5 or more drinks per occasion 2 or more times in the prior 
month or have an AUDIT-C (Alcohol Use Disorder Identification Test-Concise) score of ≥419; 
not planning to move from the area within the next 6 weeks; have their own mobile phone 
and can be reached via phone (nearly all (>97%) fisherfolk men have their own mobile 
phones and receive incoming calls is free).  
 
Consuming ≥ 5 drinks per occasion is the definition of heavy episodic drinking or binge 
drinking, as defined the National Institutes of Alcohol Abuse and Alcoholism (NIAAA). This 
type of drinking is the most concerning type of alcohol use for individuals who are HIV 
positive. Recent longitudinal data has shown that greater frequency of heavy alcohol use is 
directly associated with poor ART adherence and an important clinical outcome (lower CD4 
count) and is indirectly associated with higher HIV viral load (via lower adherence).10 Based 
on this evidence, we focus on heavy alcohol use for this intervention, and restrict our sample 
to those reporting recent heavy/binge alcohol use.   
 
Exclusion criteria: visibly intoxicated at the time of enrollment (eligible to enroll when 
sober); does not speak Luganda or English; unable to read basic Luganda or English; 
currently receiving work payments via mobile money or currently uses mobile money savings 
services; occupation is a boat owner or engine owner.  
 
 
3.2 Study design and procedures 
Intervention 
Recruitment, eligibility screening, and informed consent. 
We will recruit men who are patients at Mildmay’s HIV clinics in Wakiso District using two 
methods.  
1) After a male patient checks in for his appointment and his HIV clinic record is pulled, a 
clinic staff member will review the patient’s records to determine if they may be potentially 
eligible (male, aged 18-50, on ART for at least 6 months, work in the fishing industry, can be 
reached by phone). After the patient has completed his clinic appointment, clinic staff will 
refer male patients who are potentially eligible to a research assistant for eligibility screening. 
2) Clinic staff will also review clinic records to identify potentially eligible patients and will call 
the patient to tell him about the study. If the patient is interested, they will seek permission to 
share his phone number and name with the researchers, provide the contact number for the 
research assistant, and offer that the patient can come to the clinic to meet the research 

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assistant to learn more about the study. Study staff will briefly describe the study and seek 
informed consent to conduct eligibility screening.  
Those determined eligible will be offered participation in the study and study staff will obtain 
written informed consent.  
 
Intervention content and structure 
After participants complete the baseline structured interview, the research assistant will refer 
them to the appropriate counselor who will provide intervention participants with the 
KISOBOKA (“It is possible!”). Our proposed brief intervention consists of 4 sessions: 2 
individual, 2 group over 6 weeks, plus 2 times weekly text message reminders of life/savings 
(family prosperity, opportunities for children) and healthy living goals. Through these 
sessions the combination intervention will address environmental, interpersonal, and 
individual level factors which are key drivers of alcohol use and key barriers to HIV care 
engagement and adherence in this population.  
 
Session 1, at enrollment, In-person individual session combining MI-based counseling and 
goal setting and setting up the structural component of the intervention. During session 1 the 
counselor will: (1) Set-up the participant to receive payments for work via mobile and (if 
necessary) helping the participant set up a free mobile money account; (2) discuss short and 
long term life and healthy living goals, financial planning and savings goal setting (e.g., % of 
income to reach target savings amount in X time), set goal to transfer X% of daily earnings 
to a savings account, establish a separate healthcare savings; (3) feedback about AUDIT-C 
score and assess barriers to HIV care engagement and adherence; (4) MI-based counseling 
about alcohol use and HIV care engagement and adherence to develop discrepancy 
between their behavior and savings/life and health goals, engage client in change talk 
including setting specific goals, discussing barriers, and ways to overcome barriers; (5) 
discuss alcohol-free leisure activities; (6) provide a diary for participant to track spending and 
savings and time and money spent drinking.  
 
Session 2, 2 weeks after enrollment, MI-based individual session via phone. Counselors 
will call participants and will: (1) review progress on alcohol and HIV care engagement and 
adherence goals, additional counseling as needed to set new goals, overcome barriers or 
reinforce positive behaviors; (2) review spending and saving diary and progress on savings; 
(3) review participant’s receipt of work payments via mobile money, progress on savings 
goals, and help troubleshoot any problems. 
 
Sessions 3 and 4, approximately 4 and 6 weeks after enrollment, Group sessions with 4-
8 participants per group. Each session will consist of a counselor-led group discussion: (1) 
encouraging participants to share with the group their life and savings goals, experience with 
savings, motivations to save, benefits to saving, and long term planning for healthy living; (2) 
discussing alcohol-free leisure activities and generate motivation to engage in alcohol-free 
leisure activities; (3) reinforce discrepancy between risky alcohol use and not being engaged 
in care, not adhering to ART, and long term goals; (4) group “problem solving” about 
overcoming challenges to reducing alcohol use, including participating in alcohol-free leisure 
activities, HIV care engagement, and ARV adherence including HIV stigma. 
 
Text message reminders. Intervention arm participants will receive 2 times weekly text 
message reminders of their goals to increase the salience of delayed rewards of saving 
money and healthy living. Timing will be approximately 1 hour prior to when the participant 
reports usually drinking. For confidentiality reasons the text message reminders will not 
address alcohol, HIV care engagement, or adherence specifically but more broadly focus on 
“healthy living”. We chose the frequency of 2 times weekly based on data showing this 
frequency is the most acceptable and effective in adherence studies.20, 21 
 

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Intervention participation incentives. Based on San Diego State University IRB guidance 
we will compensate participants specifically for the time involved in participation since 
participation may require them to take time away from work. The intervention arm involves 
significantly more time commitment (approximately 563 minutes) than the control arm 
(approximately 195 minutes) and participants will be compensated accordingly. The per hour 
rate (18,000 Shillings, ~ $5) will be equivalent between study arms. We detail participant 
incentives below: 
 
Control group: Alcohol screening and referral. Control condition participants will 
complete the baseline questionnaire, which includes the AUDIT-C screening for risky alcohol 
use. After completing their baseline assessment, enhanced control condition participants will 
receive very brief feedback on their AUDIT-C score according to the feedback suggested in 
the AUDIT brief intervention manual,22 be provided a referral for alcohol counseling, and 
briefly engaged in discussion of the importance of HIV care engagement and adherence 
according to the MOH protocol.23 The control session will last approximately 20 minutes. The 
control is an enhanced treatment as usual arm which is recommended for feasibility and 
preliminary efficacy studies.24 
 
Sample size for randomized pilot intervention trial 
We will conduct a stage 1b pilot randomized controlled trial of the intervention. As a pilot 
study, this study is not powered to detect differences in outcomes, but rather to obtain 
reliable estimates of effect sizes for a subsequent efficacy trial. However, for illustrative 
purposes we explore power assuming a small effect size (d= 0.2) which is consistent with 
most brief MI-based alcohol intervention study effect sizes 17, 25-27 as well as care 
engagement interventions.28-32 We plan to enroll 160 participants in the pilot intervention 
trial with 80 in each arm i.e., randomizing to the KISOBOKA intervention arm (n=80) or to 
the control arm (n=80, alcohol screening and referral). To be conservative we anticipate 25% 
attrition. This will provide 72% power to detect an intervention effect and 85% power to 
detect a study arm x time effect. 
 
Sampling procedure for the randomized pilot intervention trial (n=160).  
The participants recruited (based on the inclusion and exclusion criteria) from the Mildmay 
HIV clinics in Wakiso District will be requested to share the research assistant’s contact 
details (phone numbers) with their potentially eligible friends. This snowball-sampling 
procedure will enable us to reach more participants in this hard-to-reach population. Those 
interested in participating in the study will contact the research assistant who will then take 
them through subsequent eligibility screening and recruitment procedures. This process will 
be repeated until the required sample is attained. 
Randomization for stage 1b randomized pilot intervention trial.  
Individual-level randomization with permuted block assignment balancing 1:1 will be used to 
create equal size groups for the two study arms. Blocks of 8 or 10 study-generated ID 
numbers will be created and randomly assigned to intervention or control. Once a participant 
is screened as eligible and attends an enrollment/baseline visit they will be assigned a study-
generated ID number from the pre-randomized list which determined their study arm 
assignment.  
 
Study variables 
Dependent variables 
Primary outcomes: 
• 
Phosphatidylethanol (PEth) (alcohol biomarker, blood sample) 
• 
AUDIT-C score19 
• 
ART adherence33 
Secondary outcomes:  

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• 
HIV care engagement 
• 
HIV viral load obtained from clinic records 
 
• 
Frequency of heavy/binge drinking 
 
  Potential covariates 
• 
Receipt of instrumental and emotional social support34  
• 
Dimensions of HIV stigma:35 (a) anticipated stigma36; (b) enacted stigma36; and (c) 
internalized stigma37  
• 
Delay discounting38  
• 
Motivation for HIV care engagement39  
• 
Income and food insecurity40  
• 
HIV status disclosure28, 34  
• 
Depressive symptoms41  
• 
Subjective health status using the MOS-HIV short form42  
• 
Distance/time to the clinic43  
 
  
3.3 Data collection  
Stage 1b randomized pilot intervention trial (n=160): 
Baseline data collection. After the informed consent process in a one-on-one interview 
(~60 minutes) using a computerized structured questionnaire, the interviewer will collect 
demographic information and detailed contact information (e.g., phone numbers, contact 
details of individuals who would know how to find the participant) to facilitate participant 
retention, and a venous blood sample for the alcohol biomarker measure (PEth). 
Interviewers will set the appointments for the 3- and 6-month follow-up.  
 
3 and 6-month follow-up data collection. For participants’ convenience the 3-month 
follow-up interview may be conducted by phone whereas the 6-month follow-up interview 
must be in person since it involves obtaining a venous blood sample. For the 6-month follow-
up, study interviewers will conduct follow-up data collection either at the study office at the 
clinic or, if requested by the participant, by meeting at a location of the participant’s 
choosing. In our prior work in Uganda, we have found that participants who may have 
challenges in coming to the study office prefer to have the interviewer come to them. At 3- 
and 6-month follow-up the interviewers will conduct an individual structured interviewer-
administered computer-based interview (~45 minutes duration). At the 6-month follow-up 
they will also collect 2mls of venous blood for PEth testing. If participants cannot be reached 
for the blood sample, we will still conduct the interview over the phone. This will allow us to 
still obtain some 6-month follow-up data from all participants. However, we will continue to 
follow up with these participants to obtain the venous blood sample even after the phone 
interview. Follow-up interviewers will be blinded to study arm assignment.  
 
Dried blood spot (DBS) collection and testing. During the baseline and 6-month follow-up 
interviews, 2mls of venous blood will be collected using sterile EDTA tubes and transported 
to a laboratory within 6-10 hours from the time of sample collection. At the laboratory, 50µl 
drops of blood will be placed onto Whatman 903 filter paper (DBS cards), allowed to dry for 
≥3 hours, and then stored packaged with a desiccant in a -80C freezer at Mildmay 
laboratory.44 Since no laboratories in Africa conduct PEth testing, PEth testing will be done 
at the United States Drug Testing Laboratories using liquid chromatography-tandem mass 
spectrometry (LC/MS/MS).45 We will obtain a Materials Transfer Agreement to ship the DBS 
to the U.S. 
 
Monitoring intervention fidelity. We will audio record all intervention sessions and 
randomly select 20% of them to code for fidelity to the intervention protocol.  
 

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Training of research assistants and interviewers 
To collect baseline and follow-up interview data for the intervention, experienced research 
assistants/interviewers will be hired for the purposes of the study. These individuals will be 
trained in the study procedures by one or more of the investigators. Interviewers will be 
individuals qualified and experienced in performing phlebotomy because they will be 
responsible for the blood draws and venous blood collection for PEth testing. Clinic staff will 
also be oriented to the study and the study procedures by the investigators. 
  
Training of counselors in the intervention protocol 
Counselors will be trained to deliver either screening and referral (enhanced control) or the 
KISOBOKA intervention. Counselors will have an advanced high school (college 
preparatory) or college education and have training in general counseling skills. The 
counselors who will deliver the intervention will undergo a 4-day criterion-based training. In 
our prior MI-based intervention in Uganda we successfully trained laboratory technicians in 
MI principles46 thus we are confident that counselors will be able to learn and become 
proficient in MI counseling skills through our training. Using highly trained clinical 
psychologists is not generalizable nor sustainable in this setting since very few of such 
professionals exist in Uganda. 
 
3.4 Measures  
Unless otherwise noted all variables will be assessed at baseline and at follow-up, 3 and 6 
months from baseline.  
  
Primary alcohol outcome. We will use an alcohol biomarker: phosphatidylethanol (PEth) 
as the primary alcohol outcomes assessed at baseline and 6-month follow-up. PEth is a 
phospholipid which is formed only in the presence of alcohol and thus is highly specific.47 
PEth has shown good performance as a medium-term biomarker 48 and in controlled 
laboratory studies, correlated well with level of consumption (Spearman’s r= 0.6-0.8).49-52  
 
We will also use the AUDIT-C19 as another measure of hazardous alcohol use. 
 
ART adherence: We will assess adherence to ART using the AIDS Clinical Trials Group 
Adherence measures (AACTG),53 which includes recall questions about ARVs missed for 
the previous 4 days prior to the interview. It has demonstrated construct validity in Uganda 
and similar settings54 and shows strong correlations with HIV VL55 and moderate correlations 
with electronic adherence monitoring.56  
 
 
Measures and analysis for assessment of feasibility: 
To inform a future larger randomized trial of the KISOBOKA intervention we follow Bowen et 
al.’s suggestions for conducting feasibility studies in preparation for larger RCTs24 which 
includes assessing feasibility on the following dimensions: acceptability, demand/use, 
implementation, and practicality. We will document the number of intervention sessions 
participants attended which will speak to demand for/use of the intervention. To monitor 
implementation for the individual and group intervention sessions the we will audio record 
intervention sessions and transcribe and code 20% of sessions to monitor intervention 
fidelity. Related to the practicality of the procedures, we will assess our retention rate 
through the 6-month follow-up to determine if we will need to develop additional retention 
procedures to maximize retention in a larger trial with a longer follow-up. 
 
3.5 Data management and analysis 
Data management 
Pre-testing: We have used many of these measures in our prior research and already have 
English and Luganda versions finalized. The remaining measures will be pre-tested with staff 

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and patients at the participating clinics before the stage 1a pilot intervention. At this stage, 
we will also pretest the entire follow-up questionnaire to assess the duration of the interview 
and if necessary, remove measures to reduce the interview length. The stage 1ab pilot 
intervention will then be used for further pretesting and subsequent revisions to ensure the 
comprehensibility of each item before the stage 1b trial.   
 
Field editing of data: Except for PEth and Viral load data all data will be entered into the 
CAPI (computer assisted personal interview) program as it is collected during the 
assessment interviews. A research assistant will double enter PEth viral load test results into 
the data file identified only by study ID number.  
   
          
Qualitative data: Audio recordings of all qualitative data will be transferred to an encrypted 
and password protected computer. Electronic audio recordings of individual and group 
counselling sessions will be transcribed within 6 months of the session and the audio 
recordings will be destroyed once the information from the recordings is written down and 
double-checked for accuracy.  
  
Quantitative data: Data for the baseline, 3 and 6-month follow-up questionnaires will be 
entered in real-time using KoboCollect software (A CAPI program). Using the KoboCollect 
system also eliminates the possibility of any out-of-range responses and therefore, data 
cleaning is not necessary. Data collected using Kobo is easily exported into SAS and other 
statistical programs for analysis. A research assistant will double enter PEth test results and 
viral load test results extracted from clinic records, into the data file identified only by study 
ID number. Clinical record data will be double entered by the research assistant into this 
same data file upon receipt. The double entered data will be checked and any discrepancies 
will be corrected by double checking the clinic records, and by comparisons with the 
laboratory report.  
 
Data security: Data directly entered from the questionnaire interviews will be automatically 
encrypted and then uploaded onto a secure server. Only the PIs and data manager will have 
access to the server. No participant names will be stored in the database. All participants will 
be identified by a unique identifier, a random number assigned to them at the time of 
recruitment. In the event of loss of data or theft, all data files will be encrypted, and no 
outside user would be able to access the data. To ensure that no data that is collected is 
lost, encrypted data will be backed up on several sources: a separate server and copied to a 
secondary encrypted database used by the PI and biostatistician for additional processing. 
 
Statistical Analysis Plan 
A key objective of this study is to explore the effectiveness of the intervention vs. control and 
obtain effect size estimates to be used to design a future trial of this intervention. The 
primary outcomes are PEth scores, AUDIT-C score, and ARV adherence. Different statistical 
methods will be utilized depending on the type of outcome variable and whether minimum 
conditions for use of the methods are met. For example, log Gamma models may be used to 
analyze the difference in PEth scores between intervention and control groups given the 
expected distribution of PEth scores. An intent to treat approach will be utilized to determine 
analytic sample. Variables (except PEth which is measured at 2) will be measured at three 
time points (baseline, 3 and 6 months) so the dependency from the repeated measures must 
be considered. Information criterion such as AIC and BIC will be used to select the most 
appropriate covariance structure to address dependance. Generalized estimating equations 
(GEE) will be built to examine the intervention effect on our outcomes of interest across time 
points (baseline, 3 and 6 months), adjusting for repeated measurement, using a 
time*condition interaction term. Potential covariates for each adjusted model will be identified 
a priori from the literature and added to the model. Correlation matrices will be determined 
based on model fit. Statistically significant covariates will be retained in final fitted models 
using an alpha of 0.05.  

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4 Ethical considerations 
Prior to the beginning of the study period, all protocols will be approved by the IRB at San 
Diego State University (FWA00003782) and the IRB at the Makerere University School of 
Public Health (FWA00011353), after receiving IRB approvals, Mildmay Uganda will grant 
administrative clearance. The study will be registered with and granted clearance by the 
Uganda National Council for Science and Technology.  
 
 
 
 
 

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5. References 
1. 
Kiwanuka N, Ssetaala A, Nalutaaya A, et al. High incidence of HIV-1 infection in a 
general population of fishing communities around Lake Victoria, Uganda. PloS one. 
2014;9(5):e94932. doi:10.1371/journal.pone.0094932 
2. 
Opio A, Muyonga M, Mulumba N. HIV sero behavioral survey in fishing communities 
of the Lake Victoria basin of Uganda. SIDA, MOH, AMREF; 2011. 
3. 
Seeley J, Nakiyingi-Miiro J, Kamali A, et al. High HIV incidence and socio-behavioral 
risk patterns in fishing communities on the shores of Lake Victoria, Uganda. Sex Transm 
Dis. 2012;39(6):433-439.  
4. 
Asiki G, Mpendo J, Abaasa A, et al. HIV and syphilis prevalence and associated risk 
factors among fishing communities of Lake Victoria, Uganda. Sex Transm Dis. 20110915 
DCOM- 20111110 2011;87(6):511-515.  
5. 
Uganda MOH, ICF International. Uganda AIDS Indicator Survey (AIS) 2011. 
Kampala, Uganda; Calverton, Maryland, USA: MOH and ICF International; 2012. 
6. 
Tumwesigye NM, Atuyambe L, Wanyenze RK, et al. Alcohol consumption and risky 
sexual behaviour in the fishing communities: evidence from two fish landing sites on Lake 
Victoria in Uganda. BMC Public Health. 20130101 2012;12:12.  
7. 
Smolak A. A meta-analysis and systematic review of HIV risk behavior among 
fishermen. AIDS Care. 2014/03/04 2013;26(3):282-291. doi:10.1080/09540121.2013.824541 
8. 
Seeley JA, Allison EH. HIV/AIDS in fishing communities: Challenges to delivering 
antiretroviral therapy to vulnerable groups. AIDS Care. 2005/08/01 2005;17(6):688-697. 
doi:10.1080/09540120412331336698 
9. 
World Health Organization (WHO). Global status report on alcohol and health. 
Geneva, Switzerland: WHO; 2014. 
10. 
Kahler CW, Liu T, Cioe PA, et al. Direct and Indirect Effects of Heavy Alcohol Use on 
Clinical Outcomes in a Longitudinal Study of HIV Patients on ART. AIDS and behavior. Jul 8 
2016;doi:10.1007/s10461-016-1474-y 
11. 
Vagenas P, Azar MM, Copenhaver MM, Springer SA, Molina PE, Altice FL. The 
Impact of Alcohol Use and Related Disorders on the HIV Continuum of Care: a Systematic 
Review : Alcohol and the HIV Continuum of Care. Curr HIV/AIDS Rep. Dec 2015;12(4):421-
36. doi:10.1007/s11904-015-0285-5 
12. 
Hendershot CS, Stoner SA, Pantalone DW, Simoni JM. Alcohol use and antiretroviral 
adherence: review and meta-analysis. Journal of acquired immune deficiency syndromes 
(1999). Oct 1 2009;52(2):180-202. doi:10.1097/QAI.0b013e3181b18b6e 
13. 
Braithwaite RS, McGinnis KA, Conigliaro J, et al. A temporal and dose-response 
association between alcohol consumption and medication adherence among veterans in 
care. Alcoholism, clinical and experimental research. Jul 2005;29(7):1190-7.  
14. 
Kissling E, Allison EH, Seeley JA, et al. Fisherfolk are among groups most at risk of 
HIV: cross-country analysis of prevalence and numbers infected. Aids. 2005;19(17):1939-
1946.  
15. 
Sileo K, Kintu M, Chanes-Mora P, Kiene S. “Such Behaviors Are Not in My Home 
Village, I Got Them Here”: A Qualitative Study of the Influence of Contextual Factors on 
Alcohol and HIV Risk Behaviors in a Fishing Community on Lake Victoria, Uganda. AIDS 
and behavior. 2015/04/29 2015;doi:10.1007/s10461-015-1077-z 
16. 
Bogart LM, Naigino R, Maistrellis E, et al. Barriers to Linkage to HIV Care in 
Ugandan Fisherfolk Communities: A Qualitative Analysis. AIDS and behavior. Mar 9 
2016;doi:10.1007/s10461-016-1331-z 
17. 
L'Engle KL, Mwarogo P, Kingola N, Sinkele W, Weiner DH. A randomized controlled 
trial of a brief intervention to reduce alcohol use among female sex workers in Mombasa, 
Kenya. Journal of acquired immune deficiency syndromes (1999). Dec 1 2014;67(4):446-53. 
doi:10.1097/QAI.0000000000000335 
18. 
Murphy JG, Dennhardt AA, Skidmore JR, et al. A randomized controlled trial of a 
behavioral economic supplement to brief motivational interventions for college drinking. 
Journal of consulting and clinical psychology. Oct 2012;80(5):876-86. doi:10.1037/a0028763 

11 
 
19. 
Bradley KA, Bush KR, Epler AJ, et al. Two brief alcohol-screening tests From the 
Alcohol Use Disorders Identification Test (AUDIT): validation in a female Veterans Affairs 
patient population. Arch Intern Med. Apr 14 2003;163(7):821-9. 
doi:10.1001/archinte.163.7.821 
20. 
Lester RT, Ritvo P, Mills EJ, et al. Effects of a mobile phone short message service 
on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial. Lancet 
(London, England). Nov 27 2010;376(9755):1838-45. doi:10.1016/s0140-6736(10)61997-6 
21. 
Pop-Eleches C, Thirumurthy H, Habyarimana JP, et al. Mobile phone technologies 
improve adherence to antiretroviral treatment in a resource-limited setting: a randomized 
controlled trial of text message reminders. Aids. Mar 27 2011;25(6):825-34. 
doi:10.1097/QAD.0b013e32834380c1 
22. 
TF B, JC H-B. Brief Intervention for Hazardous and Harmful Drinking. A Manual for 
Use in Primary Care. 2001.  
23. 
Uganda MOH. Addendum to the National Antiretroviral Treatment Guidelines. 
Kampala, Uganda: Uganda Ministry of Health; 2013. 
24. 
Bowen DJ, Kreuter M, Spring B, et al. How we design feasibility studies. American 
journal of preventive medicine. May 2009;36(5):452-7. doi:10.1016/j.amepre.2009.02.002 
25. 
Chander G, Hutton HE, Lau B, Xu X, McCaul ME. Brief Intervention Decreases 
Drinking Frequency in HIV-Infected, Heavy Drinking Women: Results of a Randomized 
Controlled Trial. Journal of acquired immune deficiency syndromes (1999). Oct 1 
2015;70(2):137-45. doi:10.1097/qai.0000000000000679 
26. 
Wandera B, Tumwesigye NM, Nankabirwa JI, et al. Efficacy of a Single, Brief Alcohol 
Reduction Intervention among Men and Women Living with HIV/AIDS and Using Alcohol in 
Kampala, Uganda: A Randomized Trial. Journal of the International Association of Providers 
of AIDS Care. May 23 2016;doi:10.1177/2325957416649669 
27. 
Lundahl BW, Kunz C, Brownell C, Tollefson D, Burke BL. A Meta-Analysis of 
Motivational Interviewing: Twenty-Five Years of Empirical Studies. Res Social Work Prac. 
Mar 2010;20(2):137-160. doi:Doi 10.1177/1049731509347850 
28. 
Wanyenze RK, Kamya MR, Fatch R, et al. Abbreviated HIV counselling and testing 
and enhanced referral to care in Uganda: a factorial randomised controlled trial. The Lancet 
Global Health. 2013;1(3):e137-e145.  
29. 
Gwadz M, Cleland CM, Applegate E, et al. Behavioral Intervention Improves 
Treatment Outcomes Among HIV-Infected Individuals Who Have Delayed, Declined, or 
Discontinued Antiretroviral Therapy: A Randomized Controlled Trial of a Novel Intervention. 
journal article. AIDS and behavior. 2015;19(10):1801-1817. doi:10.1007/s10461-015-1054-6 
30. 
Golin CE, Earp J, Tien H-C, Stewart P, Porter C, Howie L. A 2-Arm, Randomized, 
Controlled Trial of a Motivational Interviewing–Based Intervention to Improve Adherence to 
Antiretroviral Therapy (ART) Among Patients Failing or Initiating ART. Journal of acquired 
immune deficiency syndromes (1999). 2006;42(1):42-51. 
doi:10.1097/01.qai.0000219771.97303.0a 
31. 
Holstad MM, DiIorio C, Kelley ME, Resnicow K, Sharma S. Group Motivational 
Interviewing to Promote Adherence to Antiretroviral Medications and Risk Reduction 
Behaviors in HIV Infected Women. AIDS and behavior. 2011;15(5):885-896. 
doi:10.1007/s10461-010-9865-y 
32. 
DiIorio C, McCarty F, Resnicow K, et al. Using motivational interviewing to promote 
adherence to antiretroviral medications: a randomized controlled study. AIDS Care. Mar 
2008;20(3):273-83. doi:10.1080/09540120701593489 
33. 
Fisher JD, Fisher WA, Amico KR, Harman JJ. An information-motivation-behavioral 
skills model of adherence to antiretroviral therapy. Health Psychol. 2006;25(4):462-473. 
doi:10.1037/0278-6133.25.4.462 
10.1037/0278-6133.25.4.462.supp (Supplemental) 
34. 
Antelman G, Smith Fawzi MC, Kaaya S, et al. Predictors of HIV-1 serostatus 
disclosure: a prospective study among HIV-infected pregnant women in Dar es Salaam, 
Tanzania. AIDS. 2001;15(14):1865-1874.  

12 
 
35. 
Earnshaw V, Chaudoir S. From Conceptualizing to Measuring HIV Stigma: A Review 
of HIV Stigma Mechanism Measures. AIDS and Behavior. 2009;13(6):1160-1177. 
doi:10.1007/s10461-009-9593-3 
36. 
Berger BE, Ferrans CE, Lashley FR. Measuring stigma in people with HIV: 
Psychometric assessment of the HIV stigma scale. Research in Nursing & Health. 
2001;24:518-529.  
37. 
Kalichman SC, Simbayi LC, Cloete A, Mthembu PP, Mkhonta RN, Ginindza T. 
Measuring AIDS stigmas in people living with HIV/AIDS: the Internalized AIDS-Related 
Stigma Scale. AIDS Care. 2009;21(1):87-93. doi:10.1080/09540120802032627 
38. 
Kirby KN, Petry NM, Bickel WK. Heroin addicts have higher discount rates for 
delayed rewards than non-drug-using controls. Journal of experimental psychology General. 
Mar 1999;128(1):78-87.  
39. 
Smith LR, Amico KR, Shuper PA, et al. Information, motivation, and behavioral skills 
for early pre-ART engagement in HIV care among patients entering clinical care in KwaZulu-
Natal, South Africa. AIDS Care. 2013:1-6. doi:10.1080/09540121.2013.775398 
40. 
Coates J, Swindale A, Bilinsky P. Household Food Insecurity Access Scale (HFIAS) 
for Measurement of Food Access: Indicator Guide. Project FaNTA; 2007. 
http://www.fao.org/fileadmin/user_upload/eufao-fsi4dm/doc-training/hfias.pdf 
41. 
Eaton WW, Muntaner C, Smith C, Tien A, Ybarra M. Center for Epidemiologic 
Studies Depression Scale: Review and revision (CESD and CESD-R). In: Maurish ME, ed. 
The Use of Psychological Testing for Treatment Planning and Outcomes Assessment. 
Lawrence Erlbaum; 2004:363-377. 
42. 
Sherbourne CD, Stewart AL. The MOS social support survey. 19910624 DCOM- 
19910624 (0277-9536 (Print)) 
43. 
Peltzer K, Friend-du Preez N, Ramlagan S, Anderson J. Antiretroviral treatment 
adherence among HIV patients in KwaZulu-Natal, South Africa. BMC Public Health. 
2010;10:111.  
44. 
Bakhireva LN, Shrestha S, Gutierrez HL, Berry M, Schmitt C, Sarangarm D. Stability 
of Phosphatidylethanol in Dry Blood Spot Cards. Alcohol and alcoholism (Oxford, 
Oxfordshire). May 2016;51(3):275-80. doi:10.1093/alcalc/agv120 
45. 
Jones J, Jones M, Plate C, Lewis D. The detection of 1-palmitoyl-2-oleoyl-sn-glycero-
3-phosphoethanol in human dried blood spots. Analytical Methods. 2011;3(5):1101. 
doi:10.1039/c0ay00636j 
46. 
Kiene SM, Bateganya MH, Lule H, Wanyenze RK. The Effect of Motivational 
Interviewing-Based Counseling During Outpatient Provider Initiated HIV Testing on High-
Risk Sexual Behavior in Rural Uganda. AIDS and behavior. Apr 1 2016;doi:10.1007/s10461-
016-1377-y 
47. 
Kummer N, Ingels AS, Wille SM, et al. Quantification of phosphatidylethanol 
16:0/18:1, 18:1/18:1, and 16:0/16:0 in venous blood and venous and capillary dried blood 
spots from patients in alcohol withdrawal and control volunteers. Analytical and bioanalytical 
chemistry. Jan 2016;408(3):825-38. doi:10.1007/s00216-015-9169-1 
48. 
Walther L, de Bejczy A, Lof E, et al. Phosphatidylethanol is superior to carbohydrate-
deficient transferrin and gamma-glutamyltransferase as an alcohol marker and is a reliable 
estimate of alcohol consumption level. Alcoholism, clinical and experimental research. Nov 
2015;39(11):2200-8. doi:10.1111/acer.12883 
49. 
Kechagias S, Dernroth DN, Blomgren A, et al. Phosphatidylethanol Compared with 
Other Blood Tests as a Biomarker of Moderate Alcohol Consumption in Healthy Volunteers: 
A Prospective Randomized Study. Alcohol and alcoholism (Oxford, Oxfordshire). Jul 
2015;50(4):399-406. doi:10.1093/alcalc/agv038 
50. 
Aradottir S, Asanovska G, Gjerss S, Hansson P, Alling C. PHosphatidylethanol 
(PEth) concentrations in blood are correlated to reported alcohol intake in alcohol-dependent 
patients. Alcohol and alcoholism (Oxford, Oxfordshire). Jul-Aug 2006;41(4):431-7. 
doi:10.1093/alcalc/agl027 
51. 
Hartmann S, Aradottir S, Graf M, et al. Phosphatidylethanol as a sensitive and 
specific biomarker: comparison with gamma-glutamyl transpeptidase, mean corpuscular 

13 
 
volume and carbohydrate-deficient transferrin. Addiction biology. Mar 2007;12(1):81-4. 
doi:10.1111/j.1369-1600.2006.00040.x 
52. 
Hahn JA, Dobkin LM, Mayanja B, et al. Phosphatidylethanol (PEth) as a biomarker of 
alcohol consumption in HIV-positive patients in sub-Saharan Africa. Alcoholism, clinical and 
experimental research. May 2012;36(5):854-62. doi:10.1111/j.1530-0277.2011.01669.x 
53. 
Chesney MA, Ickovics JR, Chambers DB, et al. Self-reported adherence to 
antiretroviral medications among participants in HIV clinical trials: The AACTG adherence 
instruments. AIDS Care. 2000/06/01 2000;12(3):255-266. doi:10.1080/09540120050042891 
54. 
Oyugi JH, Byakika-Tusiime J, Charlebois ED, et al. Multiple Validated Measures of 
Adherence Indicate High Levels of Adherence to Generic HIV Antiretroviral Therapy in a 
Resource-Limited Setting. JAIDS Journal of Acquired Immune Deficiency Syndromes. 
2004;36(5) 
55. 
Reynolds NR, Sun J, Nagaraja HN, Gifford AL, Wu AW, Chesney MA. Optimizing 
measurement of self-reported adherence with the ACTG Adherence Questionnaire: a cross-
protocol analysis. Journal of acquired immune deficiency syndromes (1999). Dec 1 
2007;46(4):402-9.  
56. 
Buscher A, Hartman C, Kallen MA, Giordano TP. Validity of self-report measures in 
assessing antiretroviral adherence of newly diagnosed, HAART-naive, HIV patients. HIV 
clinical trials. Sep-Oct 2011;12(5):244-54. doi:10.1310/hct1205-244