PeerNaija: A Mobile Health Platform Incentivizing Medication Adherence Among Youth Living With HIV in Nigeria
Phase: NA
Conditions: HIV/AIDS
Sponsor: Vanderbilt University Medical Center

Version 4 
Date: Oct 05, 2025 
1 
 
VANDERBILT UNIVERSITY MEDICAL CENTER 
HUMAN RESEARCH COMMITTEE 
PROTOCOL SUMMARY 
 
 
PeerNaija: A Mobile Health Platform Incentivizing Medication Adherence Among Youth Living with 
HIV in Nigeria 
 
 
VANDERBILT UNIVERSITY MEDICAL CENTER 
Martin Were, MD MS FIAHSI FAMIA FACMI 
Professor of Biomedical Informatics and Medicine 
Vanderbilt Institute for Global Health 
Vanderbilt University Medical Center, Nashville, TN USA 
martin.c.were@vumc.org 
 
 
FUNDING 
NIH/NIAID: 1R21TW011327-01 
 
VERSION DATE 
October 05, 2025

Version 4 
Date: Oct 05, 2025 
2 
 
TABLE OF CONTENTS 
SUMMARY OF STUDY ....................................................................................................................................... 3 
1. 
INTRODUCTION/ BACKGROUND INFORMATION (CITING RELEVANT CRITERIA) .............................. 3 
2. 
RATIONALE/ JUSTIFICATION OF STUDY (CITING RELEVANT CRITERIA) ........................................... 4 
3. 
STUDY OBJECTIVE AND HYPOTHESIS .................................................................................................... 5 
4. 
METHODS (TO INCLUDE STUDY DESIGN, DETERMINATION OF SAMPLE SIZE, EXCLUSION/ 
INCLUSION CRITERIA, ANALYSES OF DATA, ETC.) ..................................................................................... 5 
5. 
ETHICAL CONSIDERATION. CONSENT DOCUMENTATION (TRANSLATION TO LOCAL 
LANGUAGES WHERE APPLICABLE) AND PATIENT INFORMATION LEAFLET (WHERE APPLICABLE) .. 6 
A. Risks to the Subjects .............................................................................................................................. 6 
B. Adequacy of Protection Against Risks .................................................................................................. 7 
6. 
STATISTICAL ANALYSIS PLAN (SAP) ...................................................................................................... 8 
7. 
POTENTIAL VALUE OF RESULTS (OUTCOME OF STUDY) .................................................................... 9 
8. 
LIST OF INVESTIGATORS. INVESTIGATOR SPECIALTY AND COLLABORATORS (ATTACH CVS OF 
INVESTIGATORS NOT MORE THAN 3 PAGES, LETTER OF COLLABORATION/SUPERVISION, ETC.) ... 10 
9. 
TIMEFRAME: ............................................................................................................................................. 10 
10. 
REFERENCES ........................................................................................................................................ 10 
11. 
ATTACHMENTS/ENCLOSURES ........................................................................................................... 13 
 

Version 4 
Date: Oct 05, 2025 
3 
 
 
SUMMARY OF STUDY 
 
The scale-up of global antiretroviral therapy (ART) represents an unparalleled global health success story, 
leading to impressive overall reductions in HIV-related morbidity and mortality. However, adolescents and 
young adults (AYA), especially those in Sub-Saharan Africa, have largely been left out of this story. While 
AIDS-related deaths declined by 30% for adults from 2005-2012, they increased by 50% among AYA over 
the same period, making AIDS the leading cause of death among African youth. AYA living with HIV perform 
poorly across the entire care continuum. ART adherence is central to effective HIV treatment, but AYA have 
high rates of virologic failure, virologic rebound after initial suppression, and attrition from HIV care. Unique 
developmental features of adolescence and young adulthood such as impulsivity, risk-taking, and poor 
concrete thinking make daily medication adherence even more challenging in this population. In addition, the 
attitudes and behaviours of young people are often strongly influenced by their peers. This influence can be 
seen as a powerful incentive for desired behaviours. Much of the literature on incentives for health has 
focused on financial incentives, which have shown success in promoting health behaviours. There are few 
data exploring mobile health (mHealth) technologies to exploit social and financial incentives, yet mHealth 
platforms allow for the delivery of novel behavioural interventions. With the proliferation of mobile phone 
ownership in Sub-Saharan Africa in general and in Nigeria in particular, such interventions can be delivered 
where there is greatest need. More than 75% of HIV-infected AYA live in Sub-Saharan Africa, and fully 10% 
reside in Nigeria. 
In this proposal, we will adapt an mHealth application, PEERNaija, to leverage both social and financial 
incentives to improve medication adherence among AYA living with HIV in Nigeria. We will also work with our 
partners at APIN Public Health Initiatives and NIMR in Nigeria to improve capacity to conduct mHealth 
research. The PEERNaija application will feature daily medication reminders, with individual adherence 
monitoring, individual adherence scores based on daily monitoring, anonymized peer adherence scores (from 
peers attending the same clinic; social incentive), and a monthly lottery-based prize for youth with the highest 
adherence scores (financial incentive). To accomplish these aims, we will build on previous collaborations 
between Vanderbilt and APIN, a multi-site PEPFAR-supported program serving more than 250,000 persons 
living with HIV in Nigeria. We will engage key stakeholders in the community through focus groups and key 
informant interviews to guide iterative adaptation of the app. We will recruit a cohort of 50 HIV-infected AYA 
to pilot the app and assess feasibility, acceptability, adoption, and preliminary efficacy of important clinical 
measures (including adherence and virologic suppression). The proposed study will provide important 
preliminary data for the role of mHealth platforms to harness and deliver social and financial incentives to 
promote adherence efforts, for vulnerable youth, and for a larger intervention trial evaluating this app among 
HIV-infected AYA in Nigeria. 
 
1. INTRODUCTION/ BACKGROUND INFORMATION (CITING RELEVANT CRITERIA) 
 
Eighty-five percent of the world’s adolescents and young adults (AYA) living with HIV reside in Sub- 
Saharan Africa. Sub-Saharan Africa (SSA) is home to 12% of the world’s population but a staggering 71% 
of the 36.7 million HIV-infected persons worldwide.1 Antiretroviral therapy (ART) scale-up has led to 
unprecedented progress in the global AIDS response, but these gains have not fully benefited the four million 
AYA (15-24 years) living with HIV.2 This is especially true in SSA. Over the past decade, while HIV-related 
deaths decreased by 30% overall, HIV-related deaths among adolescents increased by 50%, making HIV 
the leading cause of death among this population.2-4 Nigeria has had the highest annual incidence of 
perinatally infected children for the past seven years.5 Coupled with ongoing behavioral transmission, 10% 
of HIV-infected AYA worldwide now live in Nigeria.6-8 
Adherence and retention remain major challenges to effective HIV care for AYA. Adolescence and 
young adulthood is typically considered a period of optimal physical health but is also a vulnerable 
developmental period for health outcomes.3 Adolescence is characterized by impulsivity, risk-taking, poor 
concrete thinking, nascent autonomy, and variable levels of social support; these factors often conflict with 
behaviour necessary for adherence to chronic medical therapies.5, 9, 10 While excellent adherence 
(approximately >90%) is required to effectively control HIV and suppress the virus in the bloodstream, HIV- 
infected AYA have very poor adherence to life-saving ART.5, 11,9, 12-14 Accordingly, AYA show unacceptably 
high rates of virologic failure (30-50%).5, 9, 11, 12, 15, 16 Such lapses in treatment have likely driven the increase 

Version 4 
Date: Oct 05, 2025 
4 
 
in mortality rates for this age group and also pose a great public health risk for HIV transmission.5, 9, 11, 12 
Peer relationships can be successfully leveraged to promote desirable health behaviors among AYA. 
Attitudes and behaviors of AYA are strongly influenced by peers.17, 18 Early research has primarily focused 
on the link between peer influence and undesirable behaviors, which are sometimes adopted and spread via 
social networks through a process coined social contagion.19, 20 Several studies however, highlight the 
important role of peer relationships on a range of desirable health and social behaviors (e.g.. volunteerism, 
weight loss).21, 22 Peer relationships have also been utilized to support outcomes along the entire HIV care 
continuum, but have not been evaluated extensively among youth in general, and African youth in 
particular.23-27 One way in which peer relationships may influence behaviors is through the exertion of 
descriptive norms (what is most commonly done, or what individuals perceive to be so) and injunctive norms 
(what ought to be done) for certain behaviors.28, 29 As such, peer acceptance and alignment with normative 
behavior may be a powerful social incentive to promote health behaviors in young people. Given limited data 
on the use of social incentives to support ART adherence for youth, the proposed study will address an 
important data gap. 
 
Financial incentives have been recognized as a powerful tool for influencing a wide range of health 
outcomes, including HIV.30-32 Grounded in principles of behavioural economics and contingency 
management, financial or other incentives are provided to reward desired behaviors.33 In the field of HIV, 
much of the evidence for financial incentives to date has focused on HIV prevention, where incentives have 
shown great promise.34-36 Conditional incentives for HIV treatment have been effective in small studies, with 
absolute increases in adherence ranging from 15% to 25%.37-39 Similar data are few in resource-limited 
settings (RLS), but one study from Uganda found small prize incentives resulted in an absolute increase of 
23% in adherence to ART for adults.40 There are no data, however, assessing financial incentives for ART 
adherence for AYA, especially in RLS. Nonetheless, the provision of rewards for desired behaviours may be 
a particularly appealing approach for the adolescent brain, which is primed to seek reward.41 
 
An mHealth application can integrate motivating incentives with daily medication reminders and peer 
support to address substantial barriers to adherence. Studies of AYA living with HIV in SSA have 
identified a range of individual, environmental, structural, and treatment-related factors that impede 
medication adherence.42 At the individual level, “simply forgetting to take the dose” is often identified as a 
barrier to adherence.42 While this may be due to underlying cognitive dysfunction (from HIV infection itself), 
competing priorities, or other factors, medication reminders are well suited to address this barrier.5, 42 Text 
message reminders can result in significant improvement and up to a doubling of the odds of medication 
adherence for chronic diseases, including HIV.43-47 Social support is also an important environmental factor 
for medication adherence in this vulnerable patient group.5, 48-50 Young patients who live outside of the home 
(boarding house, orphanage, etc.) may lack the privacy and support to navigate daily adherence struggles.45- 
47 Even those with more traditional living environments may feel secluded, as many studies describe that fear 
of stigma and disclosure drives patients and families to manage their HIV in isolation.51, 52 Providing a virtual, 
peer-based social support group may address an important need for social support, especially in a region 
where limited clinic-based outreach and largely unavailable adolescent-focused clinical services also threaten 
adherence.42 
2. RATIONALE/ JUSTIFICATION OF STUDY (CITING RELEVANT CRITERIA) 
 
Preliminary work in Nigeria from Dr. Ahonkhai’s (co-PI) Care4Life program demonstrated, in one 
retrospective analysis, that 40% of AYA who remained in care one year after starting ART had virologic failure 
(HIV RNA >1000 copies/mL).12 In a multisite study of adherence as measured by medication possession ratio 
(MPR; proportion of prescribed doses of ART picked up from the pharmacy), AYA with MPR >94% had a 
marked reduction in the risk of virologic failure in the first year on ART compared to those with MPR <80% 
(aRR 0.43, p<0.001).53 Nonetheless, 26% of AYA with optimal adherence by MPR (>94%) still had virologic 
failure, highlighting discordance between ART pick-up from the pharmacy and ART taking behaviour among 
some youth.54 These data underscore need for adherence support measures that help AYA to take 
their medicines, not just get them from the pharmacy. To gain a better understanding of smart phone 
ownership and use in the proposed study setting, 20 AYA attending an adolescent HIV clinic in Lagos, Nigeria 
were surveyed; 95% owned a mobile phone (84% with smart phones) and most were frequent users of 
SMS/text messaging, instant messaging services, and social media platforms. Thus, our proposed mHealth 
intervention, which leverages an existing mHealth application focused on improving medication taking for 
youth with HIV, is well suited to support the adherence needs of AYA in this setting. 

Version 4 
Date: Oct 05, 2025 
5 
 
 
3. STUDY OBJECTIVE AND HYPOTHESIS 
 
SPECIFIC AIM: To establish the feasibility, acceptability, and preliminary efficacy of PEERNaija, an 
mHealth intervention designed to harness peer influence as an incentive to promote medication 
adherence among a pilot cohort of 50 AYA living with HIV in Nigeria. 
 
Hypothesis: PEERNaija will be feasible, acceptable, and show preliminary efficacy in improving ART 
adherence. 
4. METHODS (TO INCLUDE STUDY DESIGN, DETERMINATION OF SAMPLE SIZE, EXCLUSION/ 
INCLUSION CRITERIA, ANALYSES OF DATA, ETC.) 
 
Eligibility and Enrollment: We will conduct a prospective pilot study of the PEERNaija application for 50 AYA 
living with HIV in Nigeria. Patients will be recruited from the APIN HIV clinic and will be eligible for this study 
if they 1) own a smartphone (on which they are willing to download PEERNaija), 2) are 14-29 years of age, 
3) are on ART, and 4) demonstrate the ability read simple text language in English. Patients will provide 
written informed consent for study participation. 
Intervention Description: All participants will receive daily medication reminders, access to the virtual support 
group, and other key features identified in Aim 1. In addition, participants will be randomized to receive the 
social incentive (n=25) or the social plus financial incentive (n=25), PEER+ and be followed for 24 weeks. 
 
For the social incentive, the application will track the participant’s individual adherence score (% of doses 
taken), track the top scorers (leaderboard), and provide a figure highlighting the proportion of their peers with 
poor (<80%), medium (80-94%), or high (>94%) adherence scores. The display of the individual’s adherence 
score relative to peer scores is considered a descriptive norm and is meant to portray “what most people are 
doing,” as young people often inaccurately estimate behaviors for their peer groups. Participants will also 
receive an injunctive norm, or an indication of what they ought to be doing. This will come in the form of an 
emoji or congratulatory vs. motivating text for those with high or low adherence scores, respectively. When 
coupled with descriptive norms, injunctive norms have counteracted regression to the mean for individuals 
who demonstrate desirable behaviors relative to their peers.28 For the financial incentive, the top 5 scorers 
in the PEER+ arm will be eligible win a lottery prize each month of the 24 week pilot of 1000 NGN of “data” 
that can be directly loaded onto the winner’s phone [Figure 1]. Behavioral economics theory tells us that 
individuals are more averse to losses than rewarded by gains, so that even incentives/prizes should be 
framed in terms of losses.40 Accordingly, participants in the financial incentive arm will receive weekly 
motivating messages such as “take your dose today or you lose the chance of winning the lottery.” Potential 
language for these messages will be informed by user-centered feedback in Aim 1. 
 
 
Patients will be seen in clinic at enrollment, 6 weeks, 12 weeks, and 24 weeks. At enrollment, patients will 
complete a comprehensive survey assessing demographics and mobile phone usage patterns. We will also 
collect data on a range of factors known to impact medication adherence including, depression (WHO SQ- 
20 scale), self-efficacy (medication taking self-efficacy scale), stigma (Berger’s HIV stigma scale), symptoms 
(HIV symptom severity scale), and social support (SPS-10 scale).55-58 Adherence will be assessed using from 
the application itself (percentage of doses completed) and from 3 validated measures: 1) self-reported visual 
analog scale (VAS), 2) medication possession ration (MPR), and 3) AIDS Clinical Trials Group (ACTG) 

Version 4 
Date: Oct 05, 2025 
6 
 
adherence questionnaire.59-61 Baseline CD4 count and HIV RNA will be obtained from the clinic record (within 
3 months of enrollment). 
Study Outcomes: The outcomes of interest for this study are feasibility, acceptability, adoption, and 
preliminary efficacy, and will be measured at 24 weeks. Preliminary efficacy will be assessed by comparing 
change in HIV viral load, and adherence from baseline to 12 weeks, and baseline to 24 weeks. We 
hypothesize that the PEERNaija mHealth application will be feasible and acceptable, and show preliminary 
efficacy in improving HIV virologic control. The study outcomes will be assessed through a combination of a) 
questionnaires administered to study participants b) clinical measures or correlates of adherence measured 
at baseline and at each study visit, and (c) analysis of usage data collected during routine use of the 
application. Chat feature use will be measured by monitoring the monthly frequency of posts per participant 
in addition to the thematic content. 
Data analysis: Study feasibility and acceptability will be measured by analyzing the content of the feedback 
surveys at each study visit, and the FGDs at study end. Adoption will be assessed by analyzing usage data. 
Preliminary efficacy will be assessed by conducting a pre–post comparison of adherence measures, HIV viral 
load, and adoption measures at baseline, 12, and at 24 weeks in the two study groups (PEER and PEER+). 
De-identified chatroom the chat posts will be downloaded from the coordinator application, and reviewed from 
weeks 0-12 and 12-24. 
5. ETHICAL CONSIDERATION. CONSENT DOCUMENTATION (TRANSLATION TO LOCAL 
LANGUAGES WHERE APPLICABLE) AND PATIENT INFORMATION LEAFLET (WHERE 
APPLICABLE) 
 
A. Risks to the Subjects 
 
A.1. Human Subjects Involvement and Characteristics. This study will involve several participants, namely: 
• 
Patients (Aims 1 & 2) Adolescents and young adults (AYA) aged 14-29 years will be recruited from 
the APIN-managed HIV clinic at the Nigerian Institute for Medical Research. Patients are legally 
emancipated for HIV care at the age of 15 in Nigeria and can provide consent for clinical care and 
research participation. For the pilot proposed in Aims 2, Patients will be eligible for this study if they 
1) own a smart phone (on which they are willing to download PEERNaija 2) are 14-29 years of age, 
3) on ART, 4) demonstrate the ability read simple text language in English “My phone will remind me 
to take my drugs”, and 5) have a documented history of poor adherence defined as history of virologic 
failure in the preceding 3 months, medication possession ratio (MPR) <80%, or referral to clinic 
counselor for adherence counseling). 
• 
Providers (Aim 1) Providers eligible to participate in this study include physicians, nurses, and 
counselors whose primary responsibility is for the care of patients living with HIV, and who have 
focused responsibility for AYA. They will be recruited from the NIMR HIV clinic. 
• 
Other key stakeholders (Aim 1) Important stakeholders who will also participate in this study include 
parents (of AYA living with HIV), HIV program leaders from NIMR and representatives from the 
primary public health organization focused on HIV outcomes in the country, Nigeria’s National Agency 
for the Control of AIDS (NACA). 
A.2. Sources of material. Data will be obtained through several modalities. A set of data will be obtained 
through focus group discussions and study questionnaires. We will also collect and use several forms of 
electronic data, including: (a) data collected as part of routine patient care that is contained within NIMR’s 
electronic health record system, (b) data entered by patients as part of their use of the mHealth application, 
and (c) logging, activity and location utilized by the mHealth application. 
 
A.3. Potential risks. Overall, potential risks associated with participation in the study are unlikely and of low 
risk. 
• 
Physical. There is a very low likelihood of any physical risk to participants in this project. Patients will be 
recruited during their routine clinic visits, while non-patient participants will be recruited from within their 
work location. No participant will be asked to perform any physical activity during the interviews or focus 
group discussions. Use of the mHealth application will only entail standard activity involving smartphone 
use, such as typing and swiping fingers on the screen. These have no risk of physical injury. 
• 
Psychological. There is a small risk of participants being upset or embarrassed by questions or discussion 

Version 4 
Date: Oct 05, 2025 
7 
 
items during focus groups or interviews. There might also be a concern that participation or lack of 
participation in the study would impact the patient-provider relationship, or affect the quality of care 
received by the participant or offered by the provider. 
• 
Confidentiality. mHealth applications to support HIV adherence may force unintended disclosure if 
provisions are not taken to ensure confidentiality. Examples include the use of non-discreet language 
identifying the patient as HIV+, displaying medication names, or using symbols or logos associated with 
HIV if the mobile phone is shared, or the messages received from the application are viewed by others. 
Unintended disclosure may also occur when researchers “check in” on research participants when 
applications detect non-adherence. Confidentiality concerns are heightened in the context of HIV because 
of high rates of stigma in Nigeria and other communities in Sub-Saharan Africa. 
• 
Privacy. mHealth applications that exert “continuous surveillance” of participants may be perceived as 
intrusive or embarrassing and threatening to a participant’s privacy. The collection and use of electronic 
data can raise the concern for loss of privacy and inadvertent access of data by others. Some individuals 
might also be concerned about privacy of information shared during focus group discussions and 
interviews. 
• 
Autonomy. Adherence monitoring may limit a patient’s liberty to be non-adherent. In this way, adherence 
monitoring or reminders through an mHealth application may limit a patient’s autonomy. 
 
B. Adequacy of Protection Against Risks 
 
B.1. Recruitment and informed consent. 
• 
Informed Consent: Patient recruitment will be done by trained study staff in a private setting (conference 
room) in the clinic. The informed consent process begins at pre-study enrollment when study staff explains 
to the potential participant all the pertinent study information, including: the nature of the study, its 
purpose, the procedures involved, the expected duration, the potential risks and benefits involved, and any 
discomfort it may entail. Patients will be asked to explicitly consent to installing the application on their 
smart phones. Written informed consent, available in both English and three major dialects in the country 
(Igbo, Yoruba, Hausa), will be obtained from all participants in this study. Based on prior experience 
enrolling a 700-patient cohort in this setting where fully 100% spoke English and no translation was needed, 
we anticipate that most participants will be able to write and read in English. As part of the consent 
process, participants will have the opportunity to request information and pose questions related to the 
study. As per Nigerian guidelines, "persons aged 13 and above and emancipated minors can consent for 
themselves without parental consent" in the case on non-therapeutic research (as defined as research 
that does not involve physical contact through examination, treatment or collection of bodily samples). As 
such, parent consent will not be required for either focus group or usability testing participation. However, 
in the case on therapeutic research, defined as physical contact with and taking of bodily fluid from youth, 
"persons aged 16 and above and emancipated minors can consent for themselves without parental 
consent". Therefore, in Aim 2, both parental consent and assent from the minor will be required for persons 
aged 10-15. For children 14-15 years of age, the parent will be required to provide consent. 
Note: For patients consented prior to the amendment on May 20, 2021, the Nigeria-based study 
coordinator will reach out the currently enrolled study participants and inform them that we will additionally 
begin monitoring the chatroom for frequency of posts and will download content without participant 
identification. The participant will be allowed to withdraw from the study if preferred or will be provided 
with a new consent document that contains a description of the changes. 
• 
Study Information document: A detailed informational document will be provided during enrollment. This 
document will explain the purpose of the study, including: its goals, the procedures associated with 
enrollment, the risks and benefits of participation, the voluntary nature of this study, and how the findings 
from this study will be disseminated/published (including details on patient confidentiality), as well as 
contact information for study participants if they have concerns or questions about their rights as a 
research participant and/or if they have questions for the study Principal Investigator. 
• 
Withdrawal of Consent: Each potential participant will be informed that participation in the study is 
completely voluntary, that s/he may withdraw from the study at any time, and that refusal to consent or 
withdrawal of consent at any time will not affect their subsequent care or treatment. 
• 
Minimizing physical, psychological, and social risks. Participants will have the freedom not to respond to 
questions should they be uncomfortable with them. Confidentiality will be discussed and reinforced again 
at the beginning of each focus group discussion, and all participants will be asked to sign a pledge to not 
reveal information (including participants' names) from the focus group discussions. Focus group and 
interview information will be analyzed without including any identifying information, and research data will 

Version 4 
Date: Oct 05, 2025 
8 
 
not be linked to any other data or record source. 
• 
Minimizing risks to confidentiality & privacy. Recognizing that loss of privacy is a serious issue, we have 
put strong methods in place to protect identifiable data. First, all investigators and research personnel will 
receive training on protection of human subjects. Second, identifiable information will only be made 
available to a few specific research personnel who will need access to the data purely for study purposes. 
All paper records will be stored in secure locked cabinets only accessible to study personnel. Third, the 
mHealth application will be developed with security as top priority. The security features include storage 
of data in an encrypted format within a password-protected smartphone, secure https-based data 
transmission between the mHealth application and the server based at VUMC, robust user-level 
authentication to access data, and automatic log out after a period of inactivity. Other features that 
minimize risk to confidentiality and privacy by utilizing neutral signifiers on the application, that would not 
be readily linked to HIV status (for example using the text “it’s time” or another chosen text to pop up on 
the phone screen when it is time to take an ART dose, not including any symbols or logos readily linked 
to HIV, and not using the name of the clinic or of antiretroviral medications on the application screen). 
The choice of text and formatting will be informed by user-centered design. Fourth, patients will provide 
specific consent for the provision of phone or home-based outreach if the mHealth app signals non- 
adherence for 5 days or more. This is a practice that patients at NIMR are accustomed to, as phone 
and/or home-based outreach was standard for patients who defaulted from care before cutbacks in clinic 
funding. Concerted efforts will be made to minimize the use of any paraphernalia (labeled vehicles, 
clothing on clinic staff) that might identify participants as HIV patients, and no communication will be 
initiated in the presence of individuals who are not authorized by the patient to be present. Nonetheless, 
this risk will be explicitly discussed with participants at the time of enrollment and consent for study 
participation. Fifth, youth will be counseled on the low risk of data breach with these safeguards, but also 
on how to further minimize data breach when phones are shared. These safeguards will be present in the 
demonstration session introducing the participants to the application, and additional steps may be taken 
to prioritize safety and privacy, as guided by the focus group discussions. Sixth, we will work with the 
IRBs at Vanderbilt and NIMR to apply for a certificate of confidentiality, to ensure that the information 
collected through the mHealth application remains secure by preventing the academic institutions 
conducting the research from disclosing data collected in the course of the study to outside organizations 
or agencies. This will be an important step to mitigate the potential risk of abuse of data for unforeseen 
or unanticipated use. Finally, only NIMR staff will have access to data in the electronic health record. 
Requested clinical data will be shared with the study team and linked to patients in the pilot cohort (Aim 
2) using a unique identifier. Identifiable data will be removed and not shared where feasible and also will 
be removed from servers as soon as is consistent with completing project tasks. 
• 
Minimizing risks to autonomy. While the above procedures will address potential risks to autonomy 
(especially the informed consent procedure and explicitly offering the option to withdrawal consent), it is 
important to note that studies of SMS reminders for people living with HIV in SSA have suggested that 
loss of autonomy was not a major concern.60 On the contrary, patients had a very positive response to 
electronic adherence reminders which gave patients the sense that their providers really cared for them, 
and provided the patients with the opportunity to be seen demonstrating their commitment to care 
[Haberer personal communication].61 
• 
Vulnerable subjects. While patients may become pregnant during the study, we do not foresee any 
increased risk for this important population. Rather, we anticipate that women who become pregnant 
during the course of the study may have greater benefit (than those not in the study) because of the 
potential adherence benefit, and possible earlier referral and linkage to prevention of mother-to-child 
transmission services, given their close follow-up in the context of the study. Self-reported pregnancy 
status will therefore be assessed at each study visit (enrollment, week 6, week 12, and week 24) with 
prompt referral to prevention of mother to child clinic. 
 
6. STATISTICAL ANALYSIS PLAN (SAP) 
 
Primary Outcomes 
Primary outcomes are feasibility, acceptability, and appropriateness of the PEERNaija app. These will be 
assessed through Weiner’s validated feasibility of intervention measure (FIM), acceptability of intervention 
measure (AIM), and appropriateness of intervention measure (IAM) at six months. The FIM, AIM, and IAM 
surveys each contain four statements and participants are asked to rate their level of agreement to each 
statement on a Likert scale of 1-5, with 1 being “completely disagree” and 5 being “completely agree.” 

Version 4 
Date: Oct 05, 2025 
9 
 
Participants will answer study team-generated questions assessing the acceptability and appropriateness of 
individual app features and the app overall via feedback questionnaires administered at 12 and 24 weeks. 
 
Secondary Outcomes 
Secondary outcome is preliminary efficacy on vial load. This will be assessed by comparing change in HIV viral 
load (from baseline to 24 weeks), and self-reported adherence from baseline to 12 weeks, and baseline to 24 
weeks. ART adherence will also be assessed at baseline and six months using a visual analogue scale where 
participants indicated the percentage of prescribed ART doses taken over the past 30 days. 
 
Additional covariates are assessed at baseline, and include depression, digital health care literacy, self-reported 
ART self-efficacy and adherence, HIV stigma, social support, and alcohol and substance use. Depression was 
assessed through the Patient Health Questionnaire, version 9 (PHQ-9). The PHQ-9 contains 9 items on the 
frequency of depressive symptoms in the past two weeks; total scores range from 0-27 and higher scores 
indicate a higher severity of depressive symptoms. Digital health care literacy will be assessed through the 
Digital Health Care literacy scale. The Digital Health Care Literacy Scale contains 3 items on comfort and ability 
with using technology; total scores range from 0-12 and higher scores indicate higher literacy. ART self-efficacy 
will be assessed through the HIV Medication Taking Self-efficacy Scale (MT SES). The MT SES contains 16 
items on confidence in managing HIV treatment; total scores range from 1-10 and higher scores indicate higher 
self-efficacy. HIV stigma was assessed through Berger’s HIV Stigma Scale. Berger’s stigma scale contains 40 
items on perceived stigma, fears related to disclosure, negative self-image due to HIV status, and perceived 
community stigma; total scores range from 40-160 and higher scores indicate higher HIV stigma. Social support 
will be assessed through the Social Provisions Scale. The Social Provisions Scale contains 24 items on support 
individuals receive from their social networks; total scores range from 24-96 and higher scores indicate higher 
social provisions. Alcohol and substance use was assessed through the CRAFFT screening tool. CRAFFT 
contains 3 items on substance use in the past twelve months; total scores range from 0-3 and higher scores 
indicate a need for further assessment.  
 
Analysis Plan 
Descriptive analyses will be performed to describe the distributional statistics of interested variables, including 
demographic variables, clinical, and psychosocial characteristics, at baseline and during follow-up assessments. 
For continuous variables, the mean and standard error will be reported; for categorical variables, frequencies 
and percentages will be presented. 
 
Comparisons of primary outcomes (feasibility, acceptability and appropriateness) will be performed by 
comparing mean FIM, AIM, and IAM scores respectively between PEERNaija and PEERNaija+ at 24 weeks 
using two-sample t-tests. These constructs will additionally be addressed by comparing questions from feedback 
questionnaires, specifically assessing percentage of reminders received and whether or not reminders or chat 
messaged were intrusive, whether it was helpful to see their peers’ adherence scores, whether they would use 
the app after the study, and whether they would recommend the app to a peer.  
 
Comparisons between secondary outcomes (viral load and self-reported adherence) will be assessed by 
conducting a pre–post comparison of adherence measures at baseline, 12, and at 24 weeks, and pre-post 
comparison of viral load measures at baseline and 24 weeks in the two study groups (PEERNaija and 
PEERNaija+), using paired tests (e.g., paired t-tests, signed rank tests, or McNemar’s tests, as appropriate), 
with a significance level set at p ≤ .05 (2-tailed test). Further, self-reported preliminary efficacy will be assessed 
via response to feedback questionnaire question asking whether the app helped them to miss fewer medication 
doses and responses across study groups using Chi-square tests.  
 
To further explore associations between outcomes and variables of interest, univariate regression analyses will 
be performed. Linear regression will be applied to continuous outcomes, including the primary outcomes (FIM, 
AIM, and IAM score) and self-reported adherence; while logistic regression will be used for binary outcomes 
such as viral suppression status at the study end.  
7. POTENTIAL VALUE OF RESULTS (OUTCOME OF STUDY) 
 
This proposal will provide important data for the potential role for smartphones in delivering incentive-based 
medication adherence interventions along with essential peer support for vulnerable youth living with HIV. The 
project will serve as the basis for a larger R01-supported intervention trial evaluating this mHealth application in 
a critically important region of the world for AYA with HIV, while building capacity for a large programmatic 

Version 4 
Date: Oct 05, 2025 
10 
 
network to conduct future mHealth research in this setting. The proposed intervention has the potential to 
improve medication adherence, and therefore virological control and survival in a very high-risk patient 
population. 
8. LIST OF INVESTIGATORS. INVESTIGATOR SPECIALTY AND COLLABORATORS (ATTACH CVS 
OF INVESTIGATORS NOT MORE THAN 3 PAGES, LETTER OF COLLABORATION/SUPERVISION, 
ETC.) 
 
Our multidisciplinary team will be led by PI Dr. Aima Ahonkhai (Assistant Professor, Medicine, Vanderbilt 
University Medical Center, VUMC), an HIV specialist, epidemiologist, outcomes researcher, and founder of 
the Care4Life Research Program in Nigeria. She will oversee all aspects of this project and coordinate 
between the study teams in the U.S. and Nigeria. Dr. Martin Were (Associate Professor, Biomedical 
Informatics and Medicine, VUMC; Director, Institute for Bioinformatics, Moi University, Kenya) will lead the 
informatics team in adapting and customizing the proposed application. Drs. Ahonkhai and Were will lead the 
mHealth research course. Dr. Carolyn Audet (Assistant Professor, Health Policy and Preventive Medicine, 
VUMC), a medical anthropologist with expertise in adapting, implementing, and evaluating behavioral 
interventions, will guide qualitative analysis informing application adaptation and development. Dr. Bryan 
Shepard (Associate Professor, Biostatistics, VUMC) is a senior biostatistician who will ensure sound study 
design and guide the quantitative analysis. Dr. Prosper Okonkwo, CEO of APIN, has extensive experience 
in service delivery and program management and will serve as the in-country lead investigator. Dr. Nadia 
Dowshen (Assistant Professor, Pediatrics, Adolescent HIV Program Director, Children’s Hospital of 
Philadelphia) is the developer of the prototype application, TreatYourSelf. She will share code an expertise 
particularly in the adaptation phase. Dr. Sandra Amaral (Assistant Professor, Pediatrics, Children’s Hospital 
of Philadelphia) will provide guidance on the design and delivery of social and financial incentives for AYA. 
Drs Oliver Ezechi, Director of Research, and Dr. Agatha David, Head of Clinical Sciences Department, 
both of the Nigerian Institute for Medical Research, will serve as advisors, meeting biannually with the PIs 
and key investigators. Dr. Zaidat Musa (Biostatistician, Monitoring and Evaluation Unit Head, NIMR) and 
Ifeoma Idigbe (Medical Sociologist/Clinical Counselor, Head of HIV Testing Services and Counseling, NIMR) 
will provide oversight onsite and serve as liaisons between NIMR and VUMC, meeting biweekly with the PIs 
and key investigators. 
9. TIMEFRAME: 
 
TIMELINE & DELIVERABLES 
 
 
 
 
 
10- 
13- 
16-  
22- 
Month 
1-3 
4-6 
7-9 
12 
15 
18 
19-21 
24 
Recruit and consent cohort 
 
 
 
 
 
 
 
 
Pilot mHealth app 
 
 
 
 
 
 
 
 
Data analysis 
 
 
 
 
 
 
 
 
Manuscripts (M) and R01 preparation 
 
 
 
 
M 
 
M R01 
 M 
 
10. REFERENCES 
 
1. 
Lightfoot M. HIV prevention for adolescents: where do we go from here? . The American 
psychologist 2012;67(8):661-71. 
2. 
Idele P, Gillespie A, Porth T, Suzuki C, Mahy M, Kasedde S, et al. Epidemiology of HIV and AIDS 
among adolescents: current status, inequities, and data gaps. J Acquir Immune Defic Syndr. 2014;66 Suppl 
2:S144-53. 
3. 
WHO. Health for the world's adolescents: a second chance in the second decade 2014. 
4. 
WHO. Adolescents: health risks and solutions fact sheet. 
5. 
Lowenthal ED, Bakeera-Kitaka S, Marukutira T, Chapman J, Goldrath K, Ferrand RA. Perinatally 
acquired HIV infection in adolescents from sub-Saharan Africa: a review of emerging challenges. Lancet 
Infect Dis. 2014;14(7):627-39. 
6. 
UNAIDS. 2015 Progress report on the global plan toward the elimination of new HIV infections 
among children and keepint their mothers alive. 2015. 
7. 
UNAIDS. All In to #EndAdolescentAIDS. 2015. 

Version 4 
Date: Oct 05, 2025 
11 
 
8. 
UN. Resources for speakers on global issues. 
9. 
Agwu AL, Fairlie L. Antiretroviral treatment, management challenges and outcomes in perinatally 
HIV-infected adolescents. Journal of the International AIDS Society. 2013;16:18579. 
10. 
Murphy DA, Wilson CM, Durako SJ, Muenz LR, Belzer M. Antiretroviral medication adherence 
among the REACH HIV-infected adolescent cohort in the USA. AIDS Care. 2001;13(1):27-40. 
11. 
Auld AF, Agolory SG, Shiraishi RW, Wabwire-Mangen F, Kwesigabo G, Mulenga M, et al. 
Antiretroviral therapy enrollment characteristics and outcomes among HIV-infected adolescents and young 
adults compared with older adults--seven African countries, 2004-2013. MMWR Morb Mortal Wkly Rep. 
2014;63(47):1097-103. 
12. 
Ahonkhai AA BB, Adeola J, Adegoke AB, Regan S, Bassett IV, et al. Age matters: Increased risk of 
inconsistent HIV care and viremia among adolescents and young adults on antiretroviral therapy in Nigeria. 
The Journal of adolescent health : official publication of the Society for Adolescent Medicine. 
13. 
Parienti J-J, Ragland K, Lucht F, de la Blanchardière A, Dargère S, Yazdanpanah Y, et al. Average 
adherence to boosted protease inhibitor therapy, rather than the pattern of missed doses, as a predictor of 
HIV RNA replication. Clinical infectious diseases : an official publication of the Infectious Diseases Society 
of America. 2010;50(8):1192-7. 
14. 
Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al. Adherence to protease 
inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133(1):21-30. 
15. 
Nachega JB, Hislop M, Nguyen H, Dowdy DW, Chaisson RE, Regensberg L, et al. Antiretroviral 
therapy adherence, virologic and immunologic outcomes in adolescents compared with adults in southern 
Africa. J Acquir Immune Defic Syndr. 2009;51(1):65-71. 
16. 
Wood SM, Lowenthal E, Lee S, Ratcliffe SJ, Dowshen N. Longitudinal Viral Suppression Among a 
Cohort of Adolescents and Young Adults with Behaviorally Acquired Human Immunodeficiency Virus. AIDS 
patient care and STDs. 2017;31(9):377-83. 
17. 
Brechwald WA, Prinstein MJ. Beyond Homophily: A Decade of Advances in Understanding Peer 
Influence Processes. J Res Adolesc. 2011;21(1):166-79. 
18. 
Prinstein MJ, Brechwald WA, Cohen GL. Susceptibility to peer influence: using a performance- 
based measure to identify adolescent males at heightened risk for deviant peer socialization. Dev Psychol. 
2011;47(4):1167-72. 
19. 
Hill EM, Griffiths FE, House T. Spreading of healthy mood in adolescent social networks. Proc Biol 
Sci. 2015;282(1813):20151180-. 
20. 
Kramer ADI, Guillory JE, Hancock JT. Experimental evidence of massive-scale emotional contagion 
through social networks. Proceedings of the National Academy of Sciences. 2014;111(24):8788-90. 
21. 
Umberson D, Montez JK. Social relationships and health: a flashpoint for health policy. J Health Soc 
Behav. 2010;51 Suppl(Suppl):S54-S66. 
22. 
Choukas-Bradley S, Giletta M, Cohen GL, Prinstein MJ. Peer Influence, Peer Status, and Prosocial 
Behavior: An Experimental Investigation of Peer Socialization of Adolescents' Intentions to Volunteer. J 
Youth Adolesc. 2015;44(12):2197-210. 
23. 
Tanner AE, Philbin MM, Duval A, Ellen J, Kapogiannis B, Fortenberry JD, et al. "Youth friendly" 
clinics: considerations for linking and engaging HIV-infected adolescents into care. AIDS care. 
2014;26(2):199-205. 
24. 
Philbin MM, Tanner AE, Duval A, Ellen J, Kapogiannis B, Fortenberry JD. Linking HIV-positive 
adolescents to care in 15 different clinics across the United States: creating solutions to address structural 
barriers for linkage to care. AIDS care. 2014;26(1):12-9. 
25. 
Govindasamy D, Meghij J, Kebede Negussi E, Clare Baggaley R, Ford N, Kranzer K. Interventions 
to improve or facilitate linkage to or retention in pre-ART (HIV) care and initiation of ART in low- and middle- 
income settings--a systematic review. Journal of the International AIDS Society. 2014;17:19032. 
26. 
Chang LW, Nakigozi G, Billioux VG, Gray RH, Serwadda D, Quinn TC, et al. Effectiveness of peer 
support on care engagement and preventive care intervention utilization among pre-antiretroviral therapy, 
HIV-infected adults in Rakai, Uganda: a randomized trial. AIDS Behav. 2015;19(10):1742-51. 
27. 
Kanters S, Park JJ, Chan K, Ford N, Forrest J, Thorlund K, et al. Use of peers to improve 
adherence to antiretroviral therapy: a global network meta-analysis. Journal of the International AIDS 
Society. 2016;19(1):21141. 
28. 
Schultz PW, Nolan JM, Cialdini RB, Goldstein NJ, Griskevicius V. The constructive, destructive, and 
reconstructive power of social norms. Psychol Sci. 2007;18(5):429-34. 
29. 
Borsari B, Carey KB. Descriptive and injunctive norms in college drinking: a meta-analytic 
integration. J Stud Alcohol. 2003;64(3):331-41. 
30. 
Volpp KG, Troxel AB, Pauly MV, Glick HA, Puig A, Asch DA, et al. A randomized, controlled trial of 
financial incentives for smoking cessation. N Engl J Med. 2009;360(7):699-709. 

Version 4 
Date: Oct 05, 2025 
12 
 
31. 
Wong WC, Yuen WW, Tang CS, Holroyd E, Fong DY. Evaluation and mechanism analysis of HIV 
prevention programme using resilience framework among female sex workers: A randomised controlled 
trial. Preventive medicine reports. 2019;13:229-37. 
32. 
de Walque D GP, Bautista-Arredondo S, Kwan A, Vermeersch C, de Dieu Bizimana J, et al. Using 
provider performance incentives to increase HIV testing and counseling services in Rwanda. Journal of 
health economics. 2014;40C:1-9. 
33. 
Volpp KG, John LK, Troxel AB, Norton L, Fassbender J, Loewenstein G. Financial incentive-based 
approaches for weight loss: a randomized trial. Jama. 2008;300(22):2631-7. 
34. 
Björkman Nyqvist M, Corno L, de Walque D, Svensson J. Incentivizing Safer Sexual Behavior: 
Evidence from a Lottery Experiment on HIV Prevention. American Economic Journal: Applied Economics. 
2018;10(3):287-314. 
35. 
Heise L, Lutz B, Ranganathan M, Watts C. Cash transfers for HIV prevention: considering their 
potential. Journal of the International AIDS Society. 2013;16:18615. 
36. 
Pettifor A, MacPhail C, Nguyen N, Rosenberg M. Can money prevent the spread of HIV? A review 
of cash payments for HIV prevention. AIDS Behav. 2012;16(7):1729-38. 
37. 
Galarraga O, Genberg BL, Martin RA, Barton Laws M, Wilson IB. Conditional economic incentives 
to improve HIV treatment adherence: literature review and theoretical considerations. AIDS Behav. 
2013;17(7):2283-92. 
38. 
Sorensen JL, Haug NA, Delucchi KL, Gruber V, Kletter E, Batki SL, et al. Voucher reinforcement 
improves medication adherence in HIV-positive methadone patients: a randomized trial. Drug Alcohol 
Depend. 2007;88(1):54-63. 
39. 
Javanbakht M, Prosser P, Grimes T, Weinstein M, Farthing C. Efficacy of an individualized 
adherence support program with contingent reinforcement among nonadherent HIV-positive patients: 
results from a randomized trial. J Int Assoc Physicians AIDS Care (Chic). 2006;5(4):143-50. 
40. 
Linnemayr S, Rice T. Insights From behavioral economics to design more effective incentives for 
improving chronic health behaviors, with an application to adherence to antiretrovirals. J Acquir Immune 
Defic Syndr. 2016;72(2):e50-2. 
41. 
Steinberg L. A Social Neuroscience Perspective on Adolescent Risk-Taking. Dev Rev. 
2008;28(1):78-106. 
42. 
Adejumo OA, Malee KM, Ryscavage P, Hunter SJ, Taiwo BO. Contemporary issues on the 
epidemiology and antiretroviral adherence of HIV-infected adolescents in sub-Saharan Africa: a narrative 
review. Journal of the International AIDS Society. 2015;18:20049. 
43. 
Simoni JM, Pearson CR, Pantalone DW, Marks G, Crepaz N. Efficacy of interventions in improving 
highly active antiretroviral therapy adherence and HIV-1 RNA viral load. A meta-analytic review of 
randomized controlled trials. J Acquir Immune Defic Syndr. 2006;43 Suppl 1:S23-35. 
44. 
Chaiyachati KH, Ogbuoji O, Price M, Suthar AB, Negussie EK, Barnighausen T. Interventions to 
improve adherence to antiretroviral therapy: a rapid systematic review. AIDS (London, England). 2014;28 
Suppl 2:S187-204. 
45. 
Thakkar J, Kurup R, Laba TL, Santo K, Thiagalingam A, Rodgers A, et al. Mobile Telephone Text 
Messaging for Medication Adherence in Chronic Disease: A Meta-analysis. JAMA Intern Med. 
2016;176(3):340-9. 
46. 
Mbuagbaw L, Thabane L, Ongolo-Zogo P, Lester RT, Mills EJ, Smieja M, et al. The Cameroon 
Mobile Phone SMS (CAMPS) Trial: A Randomized Trial of Text Messaging versus Usual Care for 
Adherence to Antiretroviral Therapy. PLOS ONE. 2012;7(12):e46909. 
47. 
Pop-Eleches C, Thirumurthy H, Habyarimana JP, Zivin JG, Goldstein MP, de Walque D, et al. 
Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a 
randomized controlled trial of text message reminders. AIDS (London, England). 2011;25(6):825-34. 
48. 
Bakanda C, Birungi J, Mwesigwa R, Nachega JB, Chan K, Palmer A, et al. Survival of HIV-Infected 
Adolescents on Antiretroviral Therapy in Uganda: Findings from a Nationally Representative Cohort in 
Uganda. PLOS ONE. 2011;6(4):e19261. 
49. 
Haberer JE, Cook A, Walker AS, Ngambi M, Ferrier A, Mulenga V, et al. Excellent adherence to 
antiretrovirals in HIV+ Zambian children is compromised by disrupted routine, HIV nondisclosure, and 
paradoxical income effects. PLoS One. 2011;6(4):e18505. 
50. 
Biadgilign S, Deribew A, Amberbir A, Deribe K. Barriers and facilitators to antiretroviral medication 
adherence among HIV-infected paediatric patients in Ethiopia: A qualitative study. Sahara j. 2009;6(4):148- 
54. 
51. 
Inzaule SC, Hamers RL, Kityo C, Rinke de Wit TF, Roura M. Long-Term Antiretroviral Treatment 
Adherence in HIV-Infected Adolescents and Adults in Uganda: A Qualitative Study. PLOS ONE. 
2016;11(11):e0167492. 

Version 4 
Date: Oct 05, 2025 
13 
 
52. 
Nabukeera-Barungi N, Elyanu P, Asire B, Katureebe C, Lukabwe I, Namusoke E, et al. Adherence 
to antiretroviral therapy and retention in care for adolescents living with HIV from 10 districts in Uganda. 
BMC Infect Dis. 2015;15:520-. 
53. 
Ahonkhai AA, Banigbe B, Adeola J, Bassett IV, Idigbe I, Okonkwo P, et al. High medication 
possession ratios predict greater reductions in the risk of virologic failure for adults compared to youth in a 
Nigerian cohort. 11th International Conference on HIV Treatment and Prevention Adherence; Fort 
Lauderdale, FL2016. 
54. 
Ahonkhai AA, Banigbe B, Adeola J, Bassett IV, Idigbe I, Okonkwo P, et al. High medication 
possession ratios associated with greater risk of virologic failure among youth compared with adults in a 
Nigerian cohort. Journal of acquired immune deficiency syndromes (1999). 2018;78(3):322-8. 
55. 
Berger BE, Ferrans CE, Lashley FR. Measuring stigma in people with HIV: psychometric 
assessment of the HIV stigma scale. Res Nurs Health. 2001;24(6):518-29. 
56. 
Erlen JA, Cha ES, Kim KH, Caruthers D, Sereika SM. The HIV Medication Taking Self-efficacy 
Scale: psychometric evaluation. J Adv Nurs. 2010;66(11):2560-72. 
57. 
Organization WH. A User's Guide to the Self Reporting Questionnaire (SRQ). In: Health DoM, 
editor. 1994. 
58. 
Marc LG, Wang MM, Testa MA. Psychometric evaluation of the HIV symptom distress scale. AIDS 
Care. 2012;24(11):1432-41. 
59. 
ACTG Adherence Baseline Questionnaire. 
60. 
Finitsis DJ, Pellowski JA, Huedo-Medina TB, Fox MC, Kalichman SC. Visual analogue scale (VAS) 
measurement of antiretroviral adherence in people living with HIV (PLWH): a meta-analysis. J Behav Med. 
2016;39(6):1043-55. 
61. 
Berg KM, Arnsten JH. Practical and conceptual challenges in measuring antiretroviral adherence. J 
Acquir Immune Defic Syndr. 2006;43 Suppl 1:S79-87. 
 
11. ATTACHMENTS/ENCLOSURES 
 
APPENDIX A. QUESTIONNAIRE AND FGD GUIDE 
A.1 PeerNaija Pilot AYA Questionnaire 
A.2 PeerNaija Pilot Close Out Focus Group Guide 
APPENDIX B. CONSENT DOCUMENTS 
B.1 Pilot Testing Self Consent Form 
B.2 Pilot Testing Parent Consent Form 
APPENDIX C. LETTERS OF SUPPORT 
C.1 APIN Public Health Initiatives 
C.2 Children’s Hospital of Philadelphia 
 
APPENDIX E. RECRUITMENT FLYERS 
E.1 Participant Recruitment Flyer 
 
APPENDIX F. GRANT 
F.1 Notice of Award